User login
Fecal microbiota transplantation by capsule effective in preventing recurrent C. difficile
Clinical question: Is fecal microbiota transplantation (FMT) by oral capsule noninferior to administration via colonoscopy in preventing recurrent Clostridium difficile infection (RCDI)?
Background: Approximately 20% of patients with an initial episode of C. difficile develop recurrent disease. FMT is the most effective treatment for RCDI. Currently, it is believed that there is a higher rate of success with FMT by colonoscopy, but this is based on studies lacking a control group. The cost of administering FMT by colonoscopy is more than double the cost via oral capsule, and efficacy between the two routes has not been studied in a randomized fashion. If oral capsule delivery is noninferior, then wait times, cost, and procedure risk would be reduced.
Study design: Randomized, unblinded, noninferiority trial.
Setting: Three academic medical centers in Alberta, Ca.
Synopsis: Patients with at least three documented episodes of C. difficile infection were randomized to receive FMT by either oral capsule or colonoscopy. Exclusion criteria included complicated C. difficile infections, cancer undergoing therapy, and conditions requiring antibiotics. The primary outcome was RCDI within 12 weeks after FMT. A total of 105 patients completed the trial, with 96.2% (51/53) of patients in the capsule group and 96.2% (50/52) of patients in the colonoscopy group remaining free of RCDI at the 12-week follow-up. This met the –15% noninferiority margin and suggests that oral capsule may be an effective route of delivery for FMT. Limitations of the study are exclusion of complicated RCDI patients, lack of blinding, and no placebo control (which would have been helpful since the prevention rates were so high and recurrent diarrhea was self-reported among participants, leading to a subjective outcome).
Bottom line: FMT by oral capsule may be noninferior to FMT by colonoscopy in preventing RCDI at 12 weeks.
Citation: Kao D et al. Effect of oral capsule- vs. colonoscopy-delivered fecal microbiota transplantation on recurrent Clostridium difficile infection: A randomized clinical trial. JAMA. 2017 Nov 28;318(20):1985-93.
Dr. Mehra is assistant professor of medicine, division of hospital medicine, University of Virginia.
Clinical question: Is fecal microbiota transplantation (FMT) by oral capsule noninferior to administration via colonoscopy in preventing recurrent Clostridium difficile infection (RCDI)?
Background: Approximately 20% of patients with an initial episode of C. difficile develop recurrent disease. FMT is the most effective treatment for RCDI. Currently, it is believed that there is a higher rate of success with FMT by colonoscopy, but this is based on studies lacking a control group. The cost of administering FMT by colonoscopy is more than double the cost via oral capsule, and efficacy between the two routes has not been studied in a randomized fashion. If oral capsule delivery is noninferior, then wait times, cost, and procedure risk would be reduced.
Study design: Randomized, unblinded, noninferiority trial.
Setting: Three academic medical centers in Alberta, Ca.
Synopsis: Patients with at least three documented episodes of C. difficile infection were randomized to receive FMT by either oral capsule or colonoscopy. Exclusion criteria included complicated C. difficile infections, cancer undergoing therapy, and conditions requiring antibiotics. The primary outcome was RCDI within 12 weeks after FMT. A total of 105 patients completed the trial, with 96.2% (51/53) of patients in the capsule group and 96.2% (50/52) of patients in the colonoscopy group remaining free of RCDI at the 12-week follow-up. This met the –15% noninferiority margin and suggests that oral capsule may be an effective route of delivery for FMT. Limitations of the study are exclusion of complicated RCDI patients, lack of blinding, and no placebo control (which would have been helpful since the prevention rates were so high and recurrent diarrhea was self-reported among participants, leading to a subjective outcome).
Bottom line: FMT by oral capsule may be noninferior to FMT by colonoscopy in preventing RCDI at 12 weeks.
Citation: Kao D et al. Effect of oral capsule- vs. colonoscopy-delivered fecal microbiota transplantation on recurrent Clostridium difficile infection: A randomized clinical trial. JAMA. 2017 Nov 28;318(20):1985-93.
Dr. Mehra is assistant professor of medicine, division of hospital medicine, University of Virginia.
Clinical question: Is fecal microbiota transplantation (FMT) by oral capsule noninferior to administration via colonoscopy in preventing recurrent Clostridium difficile infection (RCDI)?
Background: Approximately 20% of patients with an initial episode of C. difficile develop recurrent disease. FMT is the most effective treatment for RCDI. Currently, it is believed that there is a higher rate of success with FMT by colonoscopy, but this is based on studies lacking a control group. The cost of administering FMT by colonoscopy is more than double the cost via oral capsule, and efficacy between the two routes has not been studied in a randomized fashion. If oral capsule delivery is noninferior, then wait times, cost, and procedure risk would be reduced.
Study design: Randomized, unblinded, noninferiority trial.
Setting: Three academic medical centers in Alberta, Ca.
Synopsis: Patients with at least three documented episodes of C. difficile infection were randomized to receive FMT by either oral capsule or colonoscopy. Exclusion criteria included complicated C. difficile infections, cancer undergoing therapy, and conditions requiring antibiotics. The primary outcome was RCDI within 12 weeks after FMT. A total of 105 patients completed the trial, with 96.2% (51/53) of patients in the capsule group and 96.2% (50/52) of patients in the colonoscopy group remaining free of RCDI at the 12-week follow-up. This met the –15% noninferiority margin and suggests that oral capsule may be an effective route of delivery for FMT. Limitations of the study are exclusion of complicated RCDI patients, lack of blinding, and no placebo control (which would have been helpful since the prevention rates were so high and recurrent diarrhea was self-reported among participants, leading to a subjective outcome).
Bottom line: FMT by oral capsule may be noninferior to FMT by colonoscopy in preventing RCDI at 12 weeks.
Citation: Kao D et al. Effect of oral capsule- vs. colonoscopy-delivered fecal microbiota transplantation on recurrent Clostridium difficile infection: A randomized clinical trial. JAMA. 2017 Nov 28;318(20):1985-93.
Dr. Mehra is assistant professor of medicine, division of hospital medicine, University of Virginia.
DAAs open up organ donation from HCV patients
BOSTON – There was no sign of HCV infection more than a year after 10 patients at Johns Hopkins University, Baltimore, received kidneys from HCV-infected donors.
The patients were treated with prophylactic direct-acting antivirals (DAAs) before and after the procedure. Low levels of hepatitis C RNA were detected shortly after transplant in five patients, but it became undetectable within a week. None of the patients developed any clinical signs of chronic hepatitis C infection, and the transplanted kidneys functioned well.
The number of organs from HCV–infected people is on the rise because of the opioid epidemic. Organ donations from drug overdoses used to be rare, but about 10% of transplanted organs are now from an overdose death, and about 30% of people who overdose have HCV. “These are young people who could donate hearts, lungs, and kidneys, and their parents and families want them to be able to make that gift of life,” said lead investigator Christine Durand, MD, of Johns Hopkins University, Baltimore.
DAAs make that possible because they cure HCV. “If the success of these transplants continues, it could pave the way for other hepatitis C–positive organs, including hearts and livers, to be transplanted as well,” Dr. Durand and her colleagues said in a press release from Johns Hopkins.
The 10 patients were over age 50 years, with a mean age of 71 years, and had been on the kidney transplant list for an average of 4 months. The HCV-positive donors were 13-50 years old with no evidence of kidney disease (Ann Intern Med. 2018 Mar 6. doi: 10.7326/M17-2871)..
Each recipient received a dose of grazoprevir/elbasvir (Zepatier) before transplant and stayed on the medication daily for 12 weeks postop. Three patients also took a daily dose of sofosbuvir (Sovaldi) because of the strain of HCV in the donor kidney. Maybe 8 weeks of treatment, or even 4, is enough, Dr. Durand said at the Conference on Retroviruses and Opportunistic Infections.
“I am thrilled to report that at 1 year post transplant 10 out of 10 of these recipients are HCV free, and they are doing very well. Prophylactic treatment may mean that more individuals can receive transplants from hepatitis C–infected donors without transmission of infection. The use of organs from infected donors can help everyone on the transplant list by shortening wait times and shortening the wait list,” she said.
“I’m not surprised by the results of the study because these DAAs are highly effective, but I was surprised by how willing patients were to sign up for the study. They said it was a no-brainer. In our region, if you need a kidney, you are going to wait for up to 5 years, and you may die while you are waiting. If you can accept a hepatitis C–positive donor organ, you will get transplanted in a matter of weeks,” she said.
“I hope providers tell their patients with HCV that they can register as organ donors,” she said.
The work is being supported primarily by Merck Sharp & Dohme. Dr. Durand is an advisor to Bristol-Meyers Squibb, Gilead Sciences, and Merck Pharmaceuticals and has research funding from the companies.
SOURCE: Durand CM et al. Ann Intern Med. 2018 Mar 6. doi: 10.7326/M17-2871.
BOSTON – There was no sign of HCV infection more than a year after 10 patients at Johns Hopkins University, Baltimore, received kidneys from HCV-infected donors.
The patients were treated with prophylactic direct-acting antivirals (DAAs) before and after the procedure. Low levels of hepatitis C RNA were detected shortly after transplant in five patients, but it became undetectable within a week. None of the patients developed any clinical signs of chronic hepatitis C infection, and the transplanted kidneys functioned well.
The number of organs from HCV–infected people is on the rise because of the opioid epidemic. Organ donations from drug overdoses used to be rare, but about 10% of transplanted organs are now from an overdose death, and about 30% of people who overdose have HCV. “These are young people who could donate hearts, lungs, and kidneys, and their parents and families want them to be able to make that gift of life,” said lead investigator Christine Durand, MD, of Johns Hopkins University, Baltimore.
DAAs make that possible because they cure HCV. “If the success of these transplants continues, it could pave the way for other hepatitis C–positive organs, including hearts and livers, to be transplanted as well,” Dr. Durand and her colleagues said in a press release from Johns Hopkins.
The 10 patients were over age 50 years, with a mean age of 71 years, and had been on the kidney transplant list for an average of 4 months. The HCV-positive donors were 13-50 years old with no evidence of kidney disease (Ann Intern Med. 2018 Mar 6. doi: 10.7326/M17-2871)..
Each recipient received a dose of grazoprevir/elbasvir (Zepatier) before transplant and stayed on the medication daily for 12 weeks postop. Three patients also took a daily dose of sofosbuvir (Sovaldi) because of the strain of HCV in the donor kidney. Maybe 8 weeks of treatment, or even 4, is enough, Dr. Durand said at the Conference on Retroviruses and Opportunistic Infections.
“I am thrilled to report that at 1 year post transplant 10 out of 10 of these recipients are HCV free, and they are doing very well. Prophylactic treatment may mean that more individuals can receive transplants from hepatitis C–infected donors without transmission of infection. The use of organs from infected donors can help everyone on the transplant list by shortening wait times and shortening the wait list,” she said.
“I’m not surprised by the results of the study because these DAAs are highly effective, but I was surprised by how willing patients were to sign up for the study. They said it was a no-brainer. In our region, if you need a kidney, you are going to wait for up to 5 years, and you may die while you are waiting. If you can accept a hepatitis C–positive donor organ, you will get transplanted in a matter of weeks,” she said.
“I hope providers tell their patients with HCV that they can register as organ donors,” she said.
The work is being supported primarily by Merck Sharp & Dohme. Dr. Durand is an advisor to Bristol-Meyers Squibb, Gilead Sciences, and Merck Pharmaceuticals and has research funding from the companies.
SOURCE: Durand CM et al. Ann Intern Med. 2018 Mar 6. doi: 10.7326/M17-2871.
BOSTON – There was no sign of HCV infection more than a year after 10 patients at Johns Hopkins University, Baltimore, received kidneys from HCV-infected donors.
The patients were treated with prophylactic direct-acting antivirals (DAAs) before and after the procedure. Low levels of hepatitis C RNA were detected shortly after transplant in five patients, but it became undetectable within a week. None of the patients developed any clinical signs of chronic hepatitis C infection, and the transplanted kidneys functioned well.
The number of organs from HCV–infected people is on the rise because of the opioid epidemic. Organ donations from drug overdoses used to be rare, but about 10% of transplanted organs are now from an overdose death, and about 30% of people who overdose have HCV. “These are young people who could donate hearts, lungs, and kidneys, and their parents and families want them to be able to make that gift of life,” said lead investigator Christine Durand, MD, of Johns Hopkins University, Baltimore.
DAAs make that possible because they cure HCV. “If the success of these transplants continues, it could pave the way for other hepatitis C–positive organs, including hearts and livers, to be transplanted as well,” Dr. Durand and her colleagues said in a press release from Johns Hopkins.
The 10 patients were over age 50 years, with a mean age of 71 years, and had been on the kidney transplant list for an average of 4 months. The HCV-positive donors were 13-50 years old with no evidence of kidney disease (Ann Intern Med. 2018 Mar 6. doi: 10.7326/M17-2871)..
Each recipient received a dose of grazoprevir/elbasvir (Zepatier) before transplant and stayed on the medication daily for 12 weeks postop. Three patients also took a daily dose of sofosbuvir (Sovaldi) because of the strain of HCV in the donor kidney. Maybe 8 weeks of treatment, or even 4, is enough, Dr. Durand said at the Conference on Retroviruses and Opportunistic Infections.
“I am thrilled to report that at 1 year post transplant 10 out of 10 of these recipients are HCV free, and they are doing very well. Prophylactic treatment may mean that more individuals can receive transplants from hepatitis C–infected donors without transmission of infection. The use of organs from infected donors can help everyone on the transplant list by shortening wait times and shortening the wait list,” she said.
“I’m not surprised by the results of the study because these DAAs are highly effective, but I was surprised by how willing patients were to sign up for the study. They said it was a no-brainer. In our region, if you need a kidney, you are going to wait for up to 5 years, and you may die while you are waiting. If you can accept a hepatitis C–positive donor organ, you will get transplanted in a matter of weeks,” she said.
“I hope providers tell their patients with HCV that they can register as organ donors,” she said.
The work is being supported primarily by Merck Sharp & Dohme. Dr. Durand is an advisor to Bristol-Meyers Squibb, Gilead Sciences, and Merck Pharmaceuticals and has research funding from the companies.
SOURCE: Durand CM et al. Ann Intern Med. 2018 Mar 6. doi: 10.7326/M17-2871.
REPORTING FROM CROI
Key clinical point: HCV may soon no longer bar organ donation.
Major finding: There was no sign of HCV infection more than a year after 10 patients at Johns Hopkins University, Baltimore, received kidneys from HCV-infected donors.
Study details: Open-label nonrandomized trial.
Disclosures: The work is being supported primarily by Merck Sharp & Dohme. The study lead is an advisor to Bristol-Meyers Squibb, Gilead Sciences, and Merck Pharmaceuticals, and has research funding from the companies.
Source: Durand CM et al. Ann Intern Med. 2018 Mar 6. doi: 10.7326/M17-2871.
Migraine and Elevated Vascular Biomarkers Linked
Elevated vascular biomarkers were associated with migraine, a recent study found, particularly migraine with aura (MA), as well as with years of aura and number of aura attacks. Participants (300 women, 117 men) were aged 30–60 (mean 48) years, 155 MA, 128 migraine without aura (MO), and 134 were controls with no severe headaches. Plasma concentrations of fibrinogen, Factor II, D-dimer, high sensitivity C-reactive protein (hs-CRP), and von Willebrand factor antigen were compared between groups, also stratifying by sex. Researchers found:
- Fibrinogen and hs-CRP were elevated in migraineurs compared to controls.
- In logistic regression analyses, MO and MA had increased likelihood of elevated fibrinogen, and MA had increased likelihood of elevated Factor II and hs-CRP.
- Fibrinogen and Factor II were associated with MA in women but not men.
- In the migraine subgroup, the total number of years of aura, but not headache, predicted elevated hs-CRP, and the average number of aura, but not headache, attacks predicted all biomarkers but Factor II.
Migraine and vascular disease biomarkers: A population-based case-control study. Cephalalgia. 2018;38(3):511-518. doi:10.1177/0333102417698936.
Elevated vascular biomarkers were associated with migraine, a recent study found, particularly migraine with aura (MA), as well as with years of aura and number of aura attacks. Participants (300 women, 117 men) were aged 30–60 (mean 48) years, 155 MA, 128 migraine without aura (MO), and 134 were controls with no severe headaches. Plasma concentrations of fibrinogen, Factor II, D-dimer, high sensitivity C-reactive protein (hs-CRP), and von Willebrand factor antigen were compared between groups, also stratifying by sex. Researchers found:
- Fibrinogen and hs-CRP were elevated in migraineurs compared to controls.
- In logistic regression analyses, MO and MA had increased likelihood of elevated fibrinogen, and MA had increased likelihood of elevated Factor II and hs-CRP.
- Fibrinogen and Factor II were associated with MA in women but not men.
- In the migraine subgroup, the total number of years of aura, but not headache, predicted elevated hs-CRP, and the average number of aura, but not headache, attacks predicted all biomarkers but Factor II.
Migraine and vascular disease biomarkers: A population-based case-control study. Cephalalgia. 2018;38(3):511-518. doi:10.1177/0333102417698936.
Elevated vascular biomarkers were associated with migraine, a recent study found, particularly migraine with aura (MA), as well as with years of aura and number of aura attacks. Participants (300 women, 117 men) were aged 30–60 (mean 48) years, 155 MA, 128 migraine without aura (MO), and 134 were controls with no severe headaches. Plasma concentrations of fibrinogen, Factor II, D-dimer, high sensitivity C-reactive protein (hs-CRP), and von Willebrand factor antigen were compared between groups, also stratifying by sex. Researchers found:
- Fibrinogen and hs-CRP were elevated in migraineurs compared to controls.
- In logistic regression analyses, MO and MA had increased likelihood of elevated fibrinogen, and MA had increased likelihood of elevated Factor II and hs-CRP.
- Fibrinogen and Factor II were associated with MA in women but not men.
- In the migraine subgroup, the total number of years of aura, but not headache, predicted elevated hs-CRP, and the average number of aura, but not headache, attacks predicted all biomarkers but Factor II.
Migraine and vascular disease biomarkers: A population-based case-control study. Cephalalgia. 2018;38(3):511-518. doi:10.1177/0333102417698936.
Migraine Linked with Increased Risk of Stroke, MI
Migraine headache was associated with an increased long-term risk of cardiovascular and cerebrovascular events, a recent study found. This effect was due to an increased risk of stroke (both ischemic and hemorrhagic) and myocardial infarction (MI). There was a moderate to severe degree of heterogeneity for the outcomes, which was partly explained by the presence of aura. A total of 16 cohort studies (18 study records) with 394,942 migraineurs and 757,465 non-migraineurs were analyzed. Researchers found:
- Migraine was associated with a higher risk of a major adverse cardiovascular and cerebrovascular event driven by a higher risk of stroke and MI.
- There was no difference in the risk of all-cause mortality, with a considerable degree of statistical heterogeneity between the studies.
- The presence of aura was an effect modifier for stroke and all-cause mortality.
Migraine and the risk of cardiovascular and cerebrovascular events: A meta-analysis of 16 cohort studies including 1,152,407 subjects. [Published online ahead of print March 27, 2018]. BMJ Open. doi:10.1136/bmjopen-2017-020498.
Migraine headache was associated with an increased long-term risk of cardiovascular and cerebrovascular events, a recent study found. This effect was due to an increased risk of stroke (both ischemic and hemorrhagic) and myocardial infarction (MI). There was a moderate to severe degree of heterogeneity for the outcomes, which was partly explained by the presence of aura. A total of 16 cohort studies (18 study records) with 394,942 migraineurs and 757,465 non-migraineurs were analyzed. Researchers found:
- Migraine was associated with a higher risk of a major adverse cardiovascular and cerebrovascular event driven by a higher risk of stroke and MI.
- There was no difference in the risk of all-cause mortality, with a considerable degree of statistical heterogeneity between the studies.
- The presence of aura was an effect modifier for stroke and all-cause mortality.
Migraine and the risk of cardiovascular and cerebrovascular events: A meta-analysis of 16 cohort studies including 1,152,407 subjects. [Published online ahead of print March 27, 2018]. BMJ Open. doi:10.1136/bmjopen-2017-020498.
Migraine headache was associated with an increased long-term risk of cardiovascular and cerebrovascular events, a recent study found. This effect was due to an increased risk of stroke (both ischemic and hemorrhagic) and myocardial infarction (MI). There was a moderate to severe degree of heterogeneity for the outcomes, which was partly explained by the presence of aura. A total of 16 cohort studies (18 study records) with 394,942 migraineurs and 757,465 non-migraineurs were analyzed. Researchers found:
- Migraine was associated with a higher risk of a major adverse cardiovascular and cerebrovascular event driven by a higher risk of stroke and MI.
- There was no difference in the risk of all-cause mortality, with a considerable degree of statistical heterogeneity between the studies.
- The presence of aura was an effect modifier for stroke and all-cause mortality.
Migraine and the risk of cardiovascular and cerebrovascular events: A meta-analysis of 16 cohort studies including 1,152,407 subjects. [Published online ahead of print March 27, 2018]. BMJ Open. doi:10.1136/bmjopen-2017-020498.
Migraine Common in Patients with Sarcoidosis
Migraine is a common comorbidity in patients with sarcoidosis, according to a recent study. As such, better recognition and targeted treatment of migraine has the potential to improve quality of life as part of a comprehensive care plan for those with sarcoidosis. The ID Migraine questionnaire was administered to a well-phenotyped observational cohort of patients with sarcoidosis (most of whom were seeking specialty care) and healthy controls. Predictors of migraine status were examined using univariate and multivariable logistic regression. Researchers found:
- Migraine was seen in 29% of 96 patients with sarcoidosis and 13% of 39 healthy controls.
- Among those with sarcoidosis, in univariate regression analysis only female sex was predictive of having migraine, and in a multivariable regression female sex remained significant.
There was no association between migraine and age, depression, dyspnea, immunosuppression use, or erythrocyte sedimentation rate.
Migraine is common in patients with sarcoidosis. [Published online ahead of print March 26, 2018]. Cephalalgia. doi:10.1177/0333102418768037.
Migraine is a common comorbidity in patients with sarcoidosis, according to a recent study. As such, better recognition and targeted treatment of migraine has the potential to improve quality of life as part of a comprehensive care plan for those with sarcoidosis. The ID Migraine questionnaire was administered to a well-phenotyped observational cohort of patients with sarcoidosis (most of whom were seeking specialty care) and healthy controls. Predictors of migraine status were examined using univariate and multivariable logistic regression. Researchers found:
- Migraine was seen in 29% of 96 patients with sarcoidosis and 13% of 39 healthy controls.
- Among those with sarcoidosis, in univariate regression analysis only female sex was predictive of having migraine, and in a multivariable regression female sex remained significant.
There was no association between migraine and age, depression, dyspnea, immunosuppression use, or erythrocyte sedimentation rate.
Migraine is common in patients with sarcoidosis. [Published online ahead of print March 26, 2018]. Cephalalgia. doi:10.1177/0333102418768037.
Migraine is a common comorbidity in patients with sarcoidosis, according to a recent study. As such, better recognition and targeted treatment of migraine has the potential to improve quality of life as part of a comprehensive care plan for those with sarcoidosis. The ID Migraine questionnaire was administered to a well-phenotyped observational cohort of patients with sarcoidosis (most of whom were seeking specialty care) and healthy controls. Predictors of migraine status were examined using univariate and multivariable logistic regression. Researchers found:
- Migraine was seen in 29% of 96 patients with sarcoidosis and 13% of 39 healthy controls.
- Among those with sarcoidosis, in univariate regression analysis only female sex was predictive of having migraine, and in a multivariable regression female sex remained significant.
There was no association between migraine and age, depression, dyspnea, immunosuppression use, or erythrocyte sedimentation rate.
Migraine is common in patients with sarcoidosis. [Published online ahead of print March 26, 2018]. Cephalalgia. doi:10.1177/0333102418768037.
Fibrosis-related genes are dysregulated in HCV-induced liver disease
Two major pathways exhibited high dysregulation in early liver fibrosis compared with controls or compared with late liver fibrosis – the transforming growth factor beta (TGF-beta)–related pathway genes and Matrix deposition–associated genes, according to an online report in the journal Gene.
The study examined 105 treatment naive HCV genotype 4–infected patients and 16 healthy subjects. The gene-regulation assays were done via PCR arrays on 84 fibrosis-related genes followed by customization of a smaller array consisting of 11 genes that were designed on the bases of results obtained from the larger array. Genes that displayed significant dysregulation at mRNA levels were validated at protein levels, according to the authors.
The researchers found that the expression at protein levels confirmed the RNA data, thereby excluding dysregulation at posttranscriptional levels.
“We assume that the overall expression pattern of ECM molecules described in the present study may be utilized for a prognostic transcriptomic or proteomic signatures for staging of liver fibrosis,” the authors concluded.
SOURCE: Dawood RM et al. Gene 2018 Apr 21. doi: 10.1016/j.gene.2018.04.032.
Two major pathways exhibited high dysregulation in early liver fibrosis compared with controls or compared with late liver fibrosis – the transforming growth factor beta (TGF-beta)–related pathway genes and Matrix deposition–associated genes, according to an online report in the journal Gene.
The study examined 105 treatment naive HCV genotype 4–infected patients and 16 healthy subjects. The gene-regulation assays were done via PCR arrays on 84 fibrosis-related genes followed by customization of a smaller array consisting of 11 genes that were designed on the bases of results obtained from the larger array. Genes that displayed significant dysregulation at mRNA levels were validated at protein levels, according to the authors.
The researchers found that the expression at protein levels confirmed the RNA data, thereby excluding dysregulation at posttranscriptional levels.
“We assume that the overall expression pattern of ECM molecules described in the present study may be utilized for a prognostic transcriptomic or proteomic signatures for staging of liver fibrosis,” the authors concluded.
SOURCE: Dawood RM et al. Gene 2018 Apr 21. doi: 10.1016/j.gene.2018.04.032.
Two major pathways exhibited high dysregulation in early liver fibrosis compared with controls or compared with late liver fibrosis – the transforming growth factor beta (TGF-beta)–related pathway genes and Matrix deposition–associated genes, according to an online report in the journal Gene.
The study examined 105 treatment naive HCV genotype 4–infected patients and 16 healthy subjects. The gene-regulation assays were done via PCR arrays on 84 fibrosis-related genes followed by customization of a smaller array consisting of 11 genes that were designed on the bases of results obtained from the larger array. Genes that displayed significant dysregulation at mRNA levels were validated at protein levels, according to the authors.
The researchers found that the expression at protein levels confirmed the RNA data, thereby excluding dysregulation at posttranscriptional levels.
“We assume that the overall expression pattern of ECM molecules described in the present study may be utilized for a prognostic transcriptomic or proteomic signatures for staging of liver fibrosis,” the authors concluded.
SOURCE: Dawood RM et al. Gene 2018 Apr 21. doi: 10.1016/j.gene.2018.04.032.
FROM GENE
New point-of-care HCV assay shows promise for developing world
Researchers have developed a new portable point-of-care (PoC) molecular test for hepatitis C virus (HCV), with sensitivity and specificity that fulfills the recent FIND/WHO Target Product Profile for HCV decentralized testing in low- and middle-income countries, according to an online report in the journal Gut.
The new assay identified all major HCV genotypes, with a limit of detection of 2,362 IU/mL. In the PoC-HCV Genedrive Viral Detection Assay Validation Study (NCT02992184), 422 patients chronically infected with HCV and 503 controls negative for anti-HCV and HCV RNA were assayed with the device. The Genedrive HCV assay showed 98.6% sensitivity and 100% specificity to detect HCV, the researchers reported. The test was further validated in a small clinical setting in a resource-limited country, they added.
“The next step with the Genedrive HCV assay requires prospective validation in real-life decentralized settings in low-income and middle-income countries,” the authors concluded.
SOURCE: Llibre A et al. Gut 2018 Apr 3. doi: 10.1136/gutjnl-2017-315783.
Researchers have developed a new portable point-of-care (PoC) molecular test for hepatitis C virus (HCV), with sensitivity and specificity that fulfills the recent FIND/WHO Target Product Profile for HCV decentralized testing in low- and middle-income countries, according to an online report in the journal Gut.
The new assay identified all major HCV genotypes, with a limit of detection of 2,362 IU/mL. In the PoC-HCV Genedrive Viral Detection Assay Validation Study (NCT02992184), 422 patients chronically infected with HCV and 503 controls negative for anti-HCV and HCV RNA were assayed with the device. The Genedrive HCV assay showed 98.6% sensitivity and 100% specificity to detect HCV, the researchers reported. The test was further validated in a small clinical setting in a resource-limited country, they added.
“The next step with the Genedrive HCV assay requires prospective validation in real-life decentralized settings in low-income and middle-income countries,” the authors concluded.
SOURCE: Llibre A et al. Gut 2018 Apr 3. doi: 10.1136/gutjnl-2017-315783.
Researchers have developed a new portable point-of-care (PoC) molecular test for hepatitis C virus (HCV), with sensitivity and specificity that fulfills the recent FIND/WHO Target Product Profile for HCV decentralized testing in low- and middle-income countries, according to an online report in the journal Gut.
The new assay identified all major HCV genotypes, with a limit of detection of 2,362 IU/mL. In the PoC-HCV Genedrive Viral Detection Assay Validation Study (NCT02992184), 422 patients chronically infected with HCV and 503 controls negative for anti-HCV and HCV RNA were assayed with the device. The Genedrive HCV assay showed 98.6% sensitivity and 100% specificity to detect HCV, the researchers reported. The test was further validated in a small clinical setting in a resource-limited country, they added.
“The next step with the Genedrive HCV assay requires prospective validation in real-life decentralized settings in low-income and middle-income countries,” the authors concluded.
SOURCE: Llibre A et al. Gut 2018 Apr 3. doi: 10.1136/gutjnl-2017-315783.
FROM GUT
MDedge Daily News: Which nonopioids are ripe for abuse?
There’s new clarity on multiple sclerosis therapy. How infections boost Sjogren’s syndrome risk. And bum kidneys shouldn’t stop dabigatran reversal.
Listen to the MDedge Daily News podcast for all the details on today’s top news.
There’s new clarity on multiple sclerosis therapy. How infections boost Sjogren’s syndrome risk. And bum kidneys shouldn’t stop dabigatran reversal.
Listen to the MDedge Daily News podcast for all the details on today’s top news.
There’s new clarity on multiple sclerosis therapy. How infections boost Sjogren’s syndrome risk. And bum kidneys shouldn’t stop dabigatran reversal.
Listen to the MDedge Daily News podcast for all the details on today’s top news.
Value-Based Purchasing for Hospital-Acquired Venous Thromboembolism: Too Much, Too Soon
As a hospital-acquired condition responsible for a significant share of preventable deaths in the United States,1 venous thromboembolism (VTE) prevention should remain a high priority for healthcare organizations. Pursuant to the goal of reducing the frequency of this and other hospital-acquired conditions, several performance measures have been developed by third-party payers in the United States to provide incentives for inpatients to receive prophylaxis measures appropriate to their specific level of risk. Perhaps the best known of these is the Hospital Value-Based Purchasing Program, initiated by the Center for Medicare and Medicaid Studies (CMS) in 2013 as a provision of the Affordable Care Act.2 The Joint Commission, as steward of the 6 VTE-related measures,3 dictates the criteria for assessing performance. However, recent adjustments to one of these measures have been performed in such a way that neglects real-world considerations faced by providers and threatens to delegitimize the important role that value-based purchasing should have in reimbursement.
Effective in 2017, the guidelines pertaining to abstraction-based reporting added a new component to the VTE-6 measure, which applies to those inpatients not ordered to receive mechanical or pharmacologic prophylaxis who go on to suffer VTE. Specifically, it is concerned with how accurately hospitals stratify such patients as low risk before the decision is made to not order either method of prophylaxis. With the update, to satisfy the measure, a formal assessment confirming a patient’s low-risk status must have been documented between arrival and the time the VTE diagnostic test was performed. The guidelines explicitly note that only 3 risk assessment models (RAMs) are accepted, including the Caprini DVT Prediction Score, Padua Prediction Score, and IMPROVE VTE Risk Score.4 The rationale for this addition to the measure clearly is to protect patients from being incorrectly designated as low risk and subsequently receiving inadequate prophylaxis that could increase their likelihood of developing preventable VTE. Unfortunately, in its current form, it imposes a substantial burden on providers and healthcare organizations, without much promise of significantly reducing rates of this pervasive threat to patient safety.
LIMITATIONS
Although the aim of reducing the incidence of VTE is laudable, this updated requirement for VTE-6 is problematic on several levels. First, there is considerable uncertainty regarding how to implement the RAMs clinically in a user-friendly way that is conducive to their intended use. Due to limitations in most computerized physician order entry systems, it is not feasible to mandate the RAMs for only those patients not ordered for VTE prophylaxis (nor would it be sensible to restrict performing the assessment to low-risk patients, as the point of RAMs is to help risk stratify and not simply validate whatever determinations were already made by other means). As virtually every class of inpatient has some risk of VTE development, these factors effectively require that a score be tabulated on all admitted patients, giving the measure an enormous footprint on clinical operations. This is important because the permissible RAMs can sometimes be quite burdensome to complete faithfully. For instance, the Caprini Score necessitates the fairly prodigious collection and input of up to 26 data points. Some of the questions require exceedingly granular data, such as whether there is any “history of unexplained stillborn infant, recurrent spontaneous abortion (more than 3), premature birth with toxemia or growth restricted infant.”5 This clearly is far outside the scope of most focused admission assessments. Already deluged with the number of clicks inherent to the workflow of most electronic health records,6 it seems likely that some providers default to selecting “no” for such prompts as a time-saving measure, potentially sabotaging the goal of linking patients with a risk-appropriate method of prophylaxis. Meanwhile, those who are diligent about completing the assessment honestly will find themselves rewarded with less time to dedicate to other critical aspects of patient care.7
The small number of RAMs accepted under the measure also fails to account for the breadth of clinical circumstances providers faced. Although the permitted models are validated in certain patient populations, they exclude some that might be better suited for many practice environments. The University of California San Diego “3 bucket” design, for instance, has been shown to result in high levels of risk-appropriate prophylaxis, has high inter-user agreement, and perhaps most importantly, is relatively quick and easy to use.8 Also critical, it is easier to integrate into the admission workflow for under-resourced hospitals that might not have the ability to incorporate a point-based risk score calculator into their electronic health records.
Finally, the relative abruptness with which the changes were made complicated the task for institutions to integrate the RAMs into their applicable order sets in a user-friendly fashion. The new guidelines were released only 6 months before taking effect,9 and the RAM requirement was not widely advertised. This left a fairly short window that does not seem to reflect an understanding by the Joint Commission of the process required by hospitals to make such a transition responsibly. This should involve obtaining inputs from multiple specialty stakeholders on which RAM to employ, working with information system specialists on how to restructure key order sets, and education of end-users on how to apply them correctly.10
RECOMMENDATIONS
For these reasons, the rollout of the VTE-6 update falls well short of its ambitions. Satisfying the measure necessitates a substantial investment of time and effort by providers and yet forcing the use of such decidedly imperfect RAMs could paradoxically worsen accurate risk stratification and appropriate use of prophylaxis. Also, while it represents only a small slice of pay-for-performance initiatives, its broader impact should not be underestimated. Unlike many of the more specific items, the VTE measures affect the workflow related to virtually all hospitalized patients. Therefore, it is imperative that regulators “get it right,” as it might only take one poorly conceived mandate of this type to risk permanently souring providers and hospitals on the idea of value-based purchasing. The Joint Commission and CMS ought to seriously consider retracting the new provisions until the role of RAMs for VTE prevention is better understood. This would buy time to reconfigure the measure in a way that is compatible with actual clinical care and for hospitals to thoughtfully design how new requirements can best be implemented.
Disclosurses
The author has nothing to disclose.
1. Clagett GP, Anderson FA Jr, Heit J, Levine MN, Wheeler HB. Prevention of venous thromboembolism. Chest. 1995;108(4 Suppl):312S-334S. PubMed
2. Center for Medicare and Medicaid Studies. Hospital value based purchasing. https://www.cms.gov/Outreach-and-Education/Medicare-Learning-Network-MLN/MLNProducts/downloads/Hospital_VBPurchasing_Fact_Sheet_ICN907664.pdf. Accessed December 18, 2017.
3. The Joint Commission. Specifications manual for national hospital inpatient quality measures. https://www.jointcommission.org/specifications_manual_for_national_hospital_inpatient_quality_measures.aspx. Accessed December 18, 2017.
4. The Joint Commission. Specifications manual for national hospital inpatient quality measures. https://www.jointcommission.org/specifications_manual_for_national_hospital_inpatient_quality_measures.aspx. Accessed December 18, 2017.
5. Venous Resource Center. Caprini score: DVT risk assessment. https://venousdisease.com/dvt-risk-assessment-online. Accessed December 19, 2017.
6. Hill RG, Sears LM, Melanson SW. 4000 Clicks: A productivity analysis of electronic medical records in a community hospital ED. Am J Emerg Med. 2013;31(11):1591-1594. PubMed
7. Clynch N, Kellett J. Medical documentation: Part of the solution, or part of the problem? A narrative review of the literature on the time spent on and value of medical documentation. Int J Med Inform. 2015;84(4):221-228. PubMed
8. Maynard GA, Morris TA, Jenkins IH, et al. Optimizing prevention of hospital-acquired venous thromboembolism (VTE): Prospective validation of a VTE risk assessment model. J Hosp Med. 2010;5(1):10-18. PubMed
9. The Joint Commission. Specifications manual for national hospital inpatient quality measures release notes v5.2. Available at: https://www.jointcommission.org/specifications_manual_for_national_hospital_inpatient_quality_measures.aspx. Accessed December 18, 2017.
10. Agency for Healthcare Quality and Research. Preventing hospital acquired venous thromboembolism: A guide for effective quality improvement. Available at: https://www.ahrq.gov/sites/default/files/publications/files/vteguide.pdf. Accessed December 18, 2017.
As a hospital-acquired condition responsible for a significant share of preventable deaths in the United States,1 venous thromboembolism (VTE) prevention should remain a high priority for healthcare organizations. Pursuant to the goal of reducing the frequency of this and other hospital-acquired conditions, several performance measures have been developed by third-party payers in the United States to provide incentives for inpatients to receive prophylaxis measures appropriate to their specific level of risk. Perhaps the best known of these is the Hospital Value-Based Purchasing Program, initiated by the Center for Medicare and Medicaid Studies (CMS) in 2013 as a provision of the Affordable Care Act.2 The Joint Commission, as steward of the 6 VTE-related measures,3 dictates the criteria for assessing performance. However, recent adjustments to one of these measures have been performed in such a way that neglects real-world considerations faced by providers and threatens to delegitimize the important role that value-based purchasing should have in reimbursement.
Effective in 2017, the guidelines pertaining to abstraction-based reporting added a new component to the VTE-6 measure, which applies to those inpatients not ordered to receive mechanical or pharmacologic prophylaxis who go on to suffer VTE. Specifically, it is concerned with how accurately hospitals stratify such patients as low risk before the decision is made to not order either method of prophylaxis. With the update, to satisfy the measure, a formal assessment confirming a patient’s low-risk status must have been documented between arrival and the time the VTE diagnostic test was performed. The guidelines explicitly note that only 3 risk assessment models (RAMs) are accepted, including the Caprini DVT Prediction Score, Padua Prediction Score, and IMPROVE VTE Risk Score.4 The rationale for this addition to the measure clearly is to protect patients from being incorrectly designated as low risk and subsequently receiving inadequate prophylaxis that could increase their likelihood of developing preventable VTE. Unfortunately, in its current form, it imposes a substantial burden on providers and healthcare organizations, without much promise of significantly reducing rates of this pervasive threat to patient safety.
LIMITATIONS
Although the aim of reducing the incidence of VTE is laudable, this updated requirement for VTE-6 is problematic on several levels. First, there is considerable uncertainty regarding how to implement the RAMs clinically in a user-friendly way that is conducive to their intended use. Due to limitations in most computerized physician order entry systems, it is not feasible to mandate the RAMs for only those patients not ordered for VTE prophylaxis (nor would it be sensible to restrict performing the assessment to low-risk patients, as the point of RAMs is to help risk stratify and not simply validate whatever determinations were already made by other means). As virtually every class of inpatient has some risk of VTE development, these factors effectively require that a score be tabulated on all admitted patients, giving the measure an enormous footprint on clinical operations. This is important because the permissible RAMs can sometimes be quite burdensome to complete faithfully. For instance, the Caprini Score necessitates the fairly prodigious collection and input of up to 26 data points. Some of the questions require exceedingly granular data, such as whether there is any “history of unexplained stillborn infant, recurrent spontaneous abortion (more than 3), premature birth with toxemia or growth restricted infant.”5 This clearly is far outside the scope of most focused admission assessments. Already deluged with the number of clicks inherent to the workflow of most electronic health records,6 it seems likely that some providers default to selecting “no” for such prompts as a time-saving measure, potentially sabotaging the goal of linking patients with a risk-appropriate method of prophylaxis. Meanwhile, those who are diligent about completing the assessment honestly will find themselves rewarded with less time to dedicate to other critical aspects of patient care.7
The small number of RAMs accepted under the measure also fails to account for the breadth of clinical circumstances providers faced. Although the permitted models are validated in certain patient populations, they exclude some that might be better suited for many practice environments. The University of California San Diego “3 bucket” design, for instance, has been shown to result in high levels of risk-appropriate prophylaxis, has high inter-user agreement, and perhaps most importantly, is relatively quick and easy to use.8 Also critical, it is easier to integrate into the admission workflow for under-resourced hospitals that might not have the ability to incorporate a point-based risk score calculator into their electronic health records.
Finally, the relative abruptness with which the changes were made complicated the task for institutions to integrate the RAMs into their applicable order sets in a user-friendly fashion. The new guidelines were released only 6 months before taking effect,9 and the RAM requirement was not widely advertised. This left a fairly short window that does not seem to reflect an understanding by the Joint Commission of the process required by hospitals to make such a transition responsibly. This should involve obtaining inputs from multiple specialty stakeholders on which RAM to employ, working with information system specialists on how to restructure key order sets, and education of end-users on how to apply them correctly.10
RECOMMENDATIONS
For these reasons, the rollout of the VTE-6 update falls well short of its ambitions. Satisfying the measure necessitates a substantial investment of time and effort by providers and yet forcing the use of such decidedly imperfect RAMs could paradoxically worsen accurate risk stratification and appropriate use of prophylaxis. Also, while it represents only a small slice of pay-for-performance initiatives, its broader impact should not be underestimated. Unlike many of the more specific items, the VTE measures affect the workflow related to virtually all hospitalized patients. Therefore, it is imperative that regulators “get it right,” as it might only take one poorly conceived mandate of this type to risk permanently souring providers and hospitals on the idea of value-based purchasing. The Joint Commission and CMS ought to seriously consider retracting the new provisions until the role of RAMs for VTE prevention is better understood. This would buy time to reconfigure the measure in a way that is compatible with actual clinical care and for hospitals to thoughtfully design how new requirements can best be implemented.
Disclosurses
The author has nothing to disclose.
As a hospital-acquired condition responsible for a significant share of preventable deaths in the United States,1 venous thromboembolism (VTE) prevention should remain a high priority for healthcare organizations. Pursuant to the goal of reducing the frequency of this and other hospital-acquired conditions, several performance measures have been developed by third-party payers in the United States to provide incentives for inpatients to receive prophylaxis measures appropriate to their specific level of risk. Perhaps the best known of these is the Hospital Value-Based Purchasing Program, initiated by the Center for Medicare and Medicaid Studies (CMS) in 2013 as a provision of the Affordable Care Act.2 The Joint Commission, as steward of the 6 VTE-related measures,3 dictates the criteria for assessing performance. However, recent adjustments to one of these measures have been performed in such a way that neglects real-world considerations faced by providers and threatens to delegitimize the important role that value-based purchasing should have in reimbursement.
Effective in 2017, the guidelines pertaining to abstraction-based reporting added a new component to the VTE-6 measure, which applies to those inpatients not ordered to receive mechanical or pharmacologic prophylaxis who go on to suffer VTE. Specifically, it is concerned with how accurately hospitals stratify such patients as low risk before the decision is made to not order either method of prophylaxis. With the update, to satisfy the measure, a formal assessment confirming a patient’s low-risk status must have been documented between arrival and the time the VTE diagnostic test was performed. The guidelines explicitly note that only 3 risk assessment models (RAMs) are accepted, including the Caprini DVT Prediction Score, Padua Prediction Score, and IMPROVE VTE Risk Score.4 The rationale for this addition to the measure clearly is to protect patients from being incorrectly designated as low risk and subsequently receiving inadequate prophylaxis that could increase their likelihood of developing preventable VTE. Unfortunately, in its current form, it imposes a substantial burden on providers and healthcare organizations, without much promise of significantly reducing rates of this pervasive threat to patient safety.
LIMITATIONS
Although the aim of reducing the incidence of VTE is laudable, this updated requirement for VTE-6 is problematic on several levels. First, there is considerable uncertainty regarding how to implement the RAMs clinically in a user-friendly way that is conducive to their intended use. Due to limitations in most computerized physician order entry systems, it is not feasible to mandate the RAMs for only those patients not ordered for VTE prophylaxis (nor would it be sensible to restrict performing the assessment to low-risk patients, as the point of RAMs is to help risk stratify and not simply validate whatever determinations were already made by other means). As virtually every class of inpatient has some risk of VTE development, these factors effectively require that a score be tabulated on all admitted patients, giving the measure an enormous footprint on clinical operations. This is important because the permissible RAMs can sometimes be quite burdensome to complete faithfully. For instance, the Caprini Score necessitates the fairly prodigious collection and input of up to 26 data points. Some of the questions require exceedingly granular data, such as whether there is any “history of unexplained stillborn infant, recurrent spontaneous abortion (more than 3), premature birth with toxemia or growth restricted infant.”5 This clearly is far outside the scope of most focused admission assessments. Already deluged with the number of clicks inherent to the workflow of most electronic health records,6 it seems likely that some providers default to selecting “no” for such prompts as a time-saving measure, potentially sabotaging the goal of linking patients with a risk-appropriate method of prophylaxis. Meanwhile, those who are diligent about completing the assessment honestly will find themselves rewarded with less time to dedicate to other critical aspects of patient care.7
The small number of RAMs accepted under the measure also fails to account for the breadth of clinical circumstances providers faced. Although the permitted models are validated in certain patient populations, they exclude some that might be better suited for many practice environments. The University of California San Diego “3 bucket” design, for instance, has been shown to result in high levels of risk-appropriate prophylaxis, has high inter-user agreement, and perhaps most importantly, is relatively quick and easy to use.8 Also critical, it is easier to integrate into the admission workflow for under-resourced hospitals that might not have the ability to incorporate a point-based risk score calculator into their electronic health records.
Finally, the relative abruptness with which the changes were made complicated the task for institutions to integrate the RAMs into their applicable order sets in a user-friendly fashion. The new guidelines were released only 6 months before taking effect,9 and the RAM requirement was not widely advertised. This left a fairly short window that does not seem to reflect an understanding by the Joint Commission of the process required by hospitals to make such a transition responsibly. This should involve obtaining inputs from multiple specialty stakeholders on which RAM to employ, working with information system specialists on how to restructure key order sets, and education of end-users on how to apply them correctly.10
RECOMMENDATIONS
For these reasons, the rollout of the VTE-6 update falls well short of its ambitions. Satisfying the measure necessitates a substantial investment of time and effort by providers and yet forcing the use of such decidedly imperfect RAMs could paradoxically worsen accurate risk stratification and appropriate use of prophylaxis. Also, while it represents only a small slice of pay-for-performance initiatives, its broader impact should not be underestimated. Unlike many of the more specific items, the VTE measures affect the workflow related to virtually all hospitalized patients. Therefore, it is imperative that regulators “get it right,” as it might only take one poorly conceived mandate of this type to risk permanently souring providers and hospitals on the idea of value-based purchasing. The Joint Commission and CMS ought to seriously consider retracting the new provisions until the role of RAMs for VTE prevention is better understood. This would buy time to reconfigure the measure in a way that is compatible with actual clinical care and for hospitals to thoughtfully design how new requirements can best be implemented.
Disclosurses
The author has nothing to disclose.
1. Clagett GP, Anderson FA Jr, Heit J, Levine MN, Wheeler HB. Prevention of venous thromboembolism. Chest. 1995;108(4 Suppl):312S-334S. PubMed
2. Center for Medicare and Medicaid Studies. Hospital value based purchasing. https://www.cms.gov/Outreach-and-Education/Medicare-Learning-Network-MLN/MLNProducts/downloads/Hospital_VBPurchasing_Fact_Sheet_ICN907664.pdf. Accessed December 18, 2017.
3. The Joint Commission. Specifications manual for national hospital inpatient quality measures. https://www.jointcommission.org/specifications_manual_for_national_hospital_inpatient_quality_measures.aspx. Accessed December 18, 2017.
4. The Joint Commission. Specifications manual for national hospital inpatient quality measures. https://www.jointcommission.org/specifications_manual_for_national_hospital_inpatient_quality_measures.aspx. Accessed December 18, 2017.
5. Venous Resource Center. Caprini score: DVT risk assessment. https://venousdisease.com/dvt-risk-assessment-online. Accessed December 19, 2017.
6. Hill RG, Sears LM, Melanson SW. 4000 Clicks: A productivity analysis of electronic medical records in a community hospital ED. Am J Emerg Med. 2013;31(11):1591-1594. PubMed
7. Clynch N, Kellett J. Medical documentation: Part of the solution, or part of the problem? A narrative review of the literature on the time spent on and value of medical documentation. Int J Med Inform. 2015;84(4):221-228. PubMed
8. Maynard GA, Morris TA, Jenkins IH, et al. Optimizing prevention of hospital-acquired venous thromboembolism (VTE): Prospective validation of a VTE risk assessment model. J Hosp Med. 2010;5(1):10-18. PubMed
9. The Joint Commission. Specifications manual for national hospital inpatient quality measures release notes v5.2. Available at: https://www.jointcommission.org/specifications_manual_for_national_hospital_inpatient_quality_measures.aspx. Accessed December 18, 2017.
10. Agency for Healthcare Quality and Research. Preventing hospital acquired venous thromboembolism: A guide for effective quality improvement. Available at: https://www.ahrq.gov/sites/default/files/publications/files/vteguide.pdf. Accessed December 18, 2017.
1. Clagett GP, Anderson FA Jr, Heit J, Levine MN, Wheeler HB. Prevention of venous thromboembolism. Chest. 1995;108(4 Suppl):312S-334S. PubMed
2. Center for Medicare and Medicaid Studies. Hospital value based purchasing. https://www.cms.gov/Outreach-and-Education/Medicare-Learning-Network-MLN/MLNProducts/downloads/Hospital_VBPurchasing_Fact_Sheet_ICN907664.pdf. Accessed December 18, 2017.
3. The Joint Commission. Specifications manual for national hospital inpatient quality measures. https://www.jointcommission.org/specifications_manual_for_national_hospital_inpatient_quality_measures.aspx. Accessed December 18, 2017.
4. The Joint Commission. Specifications manual for national hospital inpatient quality measures. https://www.jointcommission.org/specifications_manual_for_national_hospital_inpatient_quality_measures.aspx. Accessed December 18, 2017.
5. Venous Resource Center. Caprini score: DVT risk assessment. https://venousdisease.com/dvt-risk-assessment-online. Accessed December 19, 2017.
6. Hill RG, Sears LM, Melanson SW. 4000 Clicks: A productivity analysis of electronic medical records in a community hospital ED. Am J Emerg Med. 2013;31(11):1591-1594. PubMed
7. Clynch N, Kellett J. Medical documentation: Part of the solution, or part of the problem? A narrative review of the literature on the time spent on and value of medical documentation. Int J Med Inform. 2015;84(4):221-228. PubMed
8. Maynard GA, Morris TA, Jenkins IH, et al. Optimizing prevention of hospital-acquired venous thromboembolism (VTE): Prospective validation of a VTE risk assessment model. J Hosp Med. 2010;5(1):10-18. PubMed
9. The Joint Commission. Specifications manual for national hospital inpatient quality measures release notes v5.2. Available at: https://www.jointcommission.org/specifications_manual_for_national_hospital_inpatient_quality_measures.aspx. Accessed December 18, 2017.
10. Agency for Healthcare Quality and Research. Preventing hospital acquired venous thromboembolism: A guide for effective quality improvement. Available at: https://www.ahrq.gov/sites/default/files/publications/files/vteguide.pdf. Accessed December 18, 2017.
© 2018 Society of Hospital Medicine
Hospital Readmissions in Patients with Cirrhosis: A Systematic Review
Cirrhosis is a morbid condition characterized by complications such as ascites, gastrointestinal bleeding, and hepatic encephalopathy. These complications frequently require hospitalization, which is a substantial burden to the healthcare system. In 2012, liver disease was responsible for nearly 250,000 admissions across the United States, costing $3 billion.1 Despite this substantial resource utilization, outcomes remain poor, with an inpatient mortality of 6%. For those that survive, many experience hospital readmission.
More generally, early readmission reflects poor quality of care in the US. In 2004, 30-day readmissions occurred in nearly 20% of Medicare beneficiaries and costed over $17 billion.2 In response to this problem, the Affordable Care Act established the Hospital Readmissions Reduction Program (HRRP), which reduces Centers for Medicare & Medicaid Services (CMS) payments to hospitals with excess 30-day readmissions for high-risk conditions, including pneumonia and heart failure.3 Heart failure, in particular, has been the subject of numerous studies detailing risk factors and interventions to predict and prevent readmission.4-6 Based on this extensive evidence, guidelines recommend disease management programs to reduce readmissions in this population.7 In contrast, readmission in the cirrhosis population has received limited attention.
We therefore conducted a systematic review aiming to examine the range of readmission risk noted in the literature, with a focus on the model for end-stage liver disease (MELD) score as a risk factor for readmission.
METHODS
Search Strategy
We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for conducting and reporting systematic reviews.8 A literature search was performed by a medical librarian using the following databases: Ovid MEDLINE, PubMed, EMBASE, CINAHL, the full Cochrane Library, Scopus, Google Scholar, and ClinicalTrials.gov. All the databases were searched from 2000 to May 2017. We did not include older reports because the review focused on contemporary care; earlier studies may not reflect current cirrhosis management. To ensure literature saturation, included articles’ reference lists were reviewed.
Search strategies were developed by combining database-specific subject headings and keywords for readmissions with those for cirrhosis or its complications (Supplementary Material). Google Scholar and ClinicalTrials.gov were searched using keywords only. All results were limited to the English language and those published in 2000 or later, but no other limits were applied.
Identified records were reviewed based on strict criteria. We excluded case reports, case series, reviews, editorials, letters, and meeting abstracts without final peer-reviewed publication. We also excluded studies of pediatric populations (age < 18 years), patients without cirrhosis, and patients with liver transplants. We excluded studies in which patients were not hospitalized at study onset and those where the index admission was for an elective procedure. Because our interest was to identify factors associated with early readmission, we excluded studies that did not report readmissions within 90 days or those with a mean or median follow-up of less than 30 days. We also excluded studies that did not examine the association between readmission and at least 1 independent variable or intervention. Duplicate reports of a common sample were excluded unless the duplicate provided additional information, and such reports were examined together in our synthesis.
Two authors identified potentially eligible records by independently screening titles and abstracts. At this stage, records that did not meet the eligibility criteria were excluded, and the reasons for exclusion were not recorded. Records with disagreement were retained for full-text review. After this initial exclusion of records, the remaining full-text records were reviewed independently. For this full-text review, we recorded exclusion reasons and disagreements were resolved through discussion.
Data Collection
Data were abstracted from each study by 2 authors independently and recorded in a REDCap database.9 Discrepancies were resolved through discussion. We recorded study characteristics, including study design, setting, population (including the inclusion/exclusion criteria, sample size, and patient and hospitalization characteristics), interventions, and comparisons. To facilitate comparisons across studies, we employed validated methods to approximate means and standard deviations (SD).10 We recorded detailed information on outcomes including readmissions, preventability, independent variables, and mortality. Studies that focused on a single independent factor or intervention were classified as “focused,” while those that examined multiple factors were classified as “broad.” We used the Newcastle–Ottawa Scale to assess the risk of bias in each study.11 This instrument uses a 9-point scale to gauge methodological quality based on selection, group comparability, and exposure/outcome assessment.
Statistical Analysis
Analyses were performed using Stata 13.1 (StataCorp LP, College Station, Texas). We determined the pooled proportion of patients with 30-day readmission using a random-effects model, with the Freeman–Tukey double-arcsine transformation for meta-analysis of proportions.12 We investigated the heterogeneity by stratifying analyses according to prespecified study characteristics, including “broad” versus “focused.” However, the readmission risk was not different in the stratified analysis; therefore, we chose to pool the findings. For point estimates, 95% confidence intervals (CIs) were calculated, and a P-value < .05 was considered statistically significant.
RESULTS
Search Results
Study Characteristics
Two studies were performed in Australia, 4 in Europe, and the remainder in North America. Twenty one of the 26 studies were retrospective cohort studies (Table 1). Twenty studies were single-center studies (of which half were performed at transplant centers), and 4 of the 6 multicenter studies were based on administrative data with large samples (173,254 patients). The inclusion/exclusion criteria varied widely (Supplementary Material). Some studies only included patients admitted for specific cirrhosis complications, while others included those admitted for any reason. Two studies excluded patients admitted in the prior 30 days, and 6 excluded patients discharged to hospice. The mean risk of bias score was 7.5 (SD 1.3) out of a possible 9 points, with most lacking an adequate description of follow-up and several lacking adjustment for confounders.
Outcomes
Readmission and MELD
DISCUSSION
Hospital readmission is a costly and common problem in the US.2 In addition to the negative impact that readmissions have on patients’ lives,40 readmissions are increasingly being used to measure quality. Unplanned 30-day readmissions are posted publicly, and excess readmissions for high-risk conditions are penalized through HRRP.3 Although HRRP does not currently include cirrhosis, the program has expanded to include several conditions that were not included in the initial iteration. Whether cirrhosis will be included in future iterations remains to be seen; however, increasing scrutiny is likely to continue. Of specific populations at risk, patients with cirrhosis are particularly vulnerable due to several features. Ascites management often requires hospitalization due to diuretic titration and poor access to paracentesis, and hepatic encephalopathy treatment requires complex lactulose titration.16 Other features of cirrhosis, such as gastrointestinal bleeding, infections, and renal failure, also place patients at risk of poor outcomes. The resulting readmission burden is high, with a pooled 30-day readmission rate of 26%. Other associated outcomes are also poor, with a consistent relationship between readmission and subsequent mortality.
We found striking heterogeneity in various aspects. First, the inclusion/exclusion criteria varied widely, both cirrhosis-specific (eg, spontaneous bacterial peritonitis) and more general (patients admitted within the prior 30 days). Some of these criteria may bias readmission estimates; the risk of readmission may be reduced in those on hospice, as patients forgo curative therapy. Additionally, an established risk factor for readmission is prior hospitalization41; excluding patients with prior admissions prohibits analysis of this variable. Another aspect is the capture of readmissions: readmissions outside of the index hospital were not included in most studies. In those that did include outside readmissions, the burden was sizeable: 17% in 1 single-center study and 23% in a multistate administrative database.16,36 These outside readmissions must be included in future studies; they are as important as same-center readmissions both to patients and CMS.3 Despite this heterogeneity, the studies scored relatively high on the Newcastle–Ottawa risk of bias scale, with the only common deficiency being an inadequate description of follow-up.
Building on the findings of this review, an important step will be the design of interventions to reduce readmissions. Such interventions require a full understanding of this population’s characteristics and needs. Critically, we found a lack of data on social determinants of health. Impairments in these factors are well-established contributors to readmission risk in other populations,4,40 and are highly prevalent in cirrhosis.42 Indeed, CMS has focused resources toward social determinants of health in the effort to reduce utilization and improve outcomes. This lack of data on social determinants of health, as well as other understudied factors, represents an important opportunity for future research efforts to better define the modifiable features that could be targeted in the future to prevent readmissions. Such research is urgently needed and will likely require prospective studies to gather these important factors. Notably, most studies in this systematic review were retrospective and therefore unable to examine many of these understudied factors. Another important aspect that has received little attention is readmission preventability: only 2 studies assessed preventability, both through unstructured chart review. Preventability assessments in noncirrhotic populations have used wide-ranging methodologies, yielding inconsistent results.43 This variability prompted recommendations that preventability should be assessed by multiple reviewers guided by explicit parameters.43 Such detailed attention to preventability is urgently needed to better inform interventions.
In contrast to the lack of data on social factors, we found that the MELD score was examined in most studies and was frequently associated with readmission. Despite this consistent association, differences in the MELD scores between studies limit inferences into specific cutoff values that could identify the highest risk patients. Because of its existing widespread clinical use, the MELD score may prove to be important in readmission risk stratification. Efforts to develop a useful model including the MELD score are needed to target interventions to the highest risk patients.
This review has several limitations. Although we used a broad search strategy to capture studies, some may not have been included due to our selection criteria. For instance, 1 retrospective paper described factors associated with high admission density during 1 year but did not specifically report the frequency of early readmissions.44 Similarly, a randomized trial of a disease management program did not specifically examine early readmissions.45 Another quasi-experimental study of a quality improvement initiative was not included because a large proportion of their subjects was post liver transplant.46 However, the inclusion of these papers is unlikely to change our conclusions; the retrospective study identified factors similar to those in the included studies, and the quasi-experimental study overlapped with the included study that assessed frailty.27 Another potential limitation is the exclusion of studies published in abstract form only. Such studies may be important, as the field of cirrhosis readmissions is relatively young. However, including only full-paper publications ensures the inclusion of only higher quality studies scrutinized during the peer-review process. Similarly, newer published studies may have been missed due to the abundant interest in this topic and ongoing research. Lastly, the significant heterogeneity of the studies limits conclusions that can be made regarding the pooled readmission rates.
In summary, we found that patients with cirrhosis experience a high incidence of hospital readmissions. Several processes of care may be associated with readmissions, suggesting room for improvement in caring for this population and reducing readmissions. However, we identified several gaps in the literature, which does not adequately describe social factors and is lacking details on readmission preventability assessment. Future studies should attempt to address these issues so that interventions can be targeted to the highest risk patients and designed to best meet the needs of patients with cirrhosis.
Disclosures
Dr. Orman, Dr. Ghabril, and Dr. Emmett report no potential conflicts of interest. Dr. Chalasani reports personal fees from Lilly, personal fees from Abbvie, personal fees from Tobira/Allergan, personal fees from Ardelyx, personal fees from Amarin, personal fees from Shire, personal fees from Madrigal, personal fees from DS Biopharma (Afimmune), personal fees from Cempra, personal fees from NuSirt, grants from Galectin, grants from Gilead, grants from Intercept, grants from Cumberland, grants from Conatus, personal fees from Immuron, and personal fees from Axovant, outside the submitted work.
Funding Information
This work was supported, in part, by the National Institutes of Health, KL2 TR001106 and K23 DK109202
1. Peery AF, Crockett SD, Barritt AS, et al. Burden of gastrointestinal, liver, and pancreatic diseases in the United States. Gastroenterology. 2015;149(7):1731-1741.e3. DOI: 10.1053/j.gastro.2015.08.045. PubMed
13. Bini EJ, Weinshel EH, Generoso R, et al. Impact of gastroenterology consultation on the outcomes of patients admitted to the hospital with decompensated cirrhosis. Hepatology. 2001;34(6):1089-1095. DOI: 10.1053/jhep.2001.29204. PubMed
14. Berman K, Tandra S, Forssell K, et al. Incidence and predictors of 30-day readmission among patients hospitalized for advanced liver disease. Clin Gastroenterol Hepatol. 2011;9(3):254-259. DOI: 10.1016/j.cgh.2010.10.035. PubMed
15. Johnson EA, Spier BJ, Leff JA, Lucey MR, Said A. Optimising the care of patients with cirrhosis and gastrointestinal haemorrhage: a quality improvement study. Aliment Pharmacol Ther. 2011;34(1):76-82. DOI: 10.1111/j.1365-2036.2011.04692.x. PubMed
16. Volk ML, Tocco RS, Bazick J, Rakoski MO, Lok AS. Hospital readmissions among patients with decompensated cirrhosis. Am J Gastroenterol. 2012;107(2):247-252. DOI: 10.1038/ajg.2011.314. PubMed
17. Barsuk JH, Cohen ER, Feinglass J, McGaghie WC, Wayne DB. Clinical outcomes after bedside and interventional radiology paracentesis procedures. Am J Med. 2013;126(4):349-356. DOI: 10.1016/j.amjmed.2012.09.016. PubMed
18. Deitelzweig S, Amin A, Christian R, Friend K, Lin J, Lowe TJ. Hyponatremia-associated healthcare burden among US patients hospitalized for cirrhosis. Adv Ther. 2013;30(1):71-80. DOI: 10.1007/s12325-012-0073-1. PubMed
19. Morando F, Maresio G, Piano S, et al. How to improve care in outpatients with cirrhosis and ascites: a new model of care coordination by consultant hepatologists. J Hepatol. 2013;59(2):257-264. DOI: 10.1016/j.jhep.2013.03.010. PubMed
20. Singal AG, Rahimi RS, Clark C, et al. An automated model using electronic medical record data identifies patients with cirrhosis at high risk for readmission. Clin Gastroenterol Hepatol. 2013;11(10):1335-1341.e1. DOI: 10.1016/j.cgh.2013.03.022. PubMed
21. Desai AP, Satoskar R, Appannagari A, et al. Co-management between hospitalist and hepatologist improves the quality of care of inpatients with chronic liver disease. J Clin Gastroenterol. 2014;48(4):e30-e36. DOI: 10.1097/MCG.0b013e3182a87f70. PubMed
22. Fagan KJ, Zhao EY, Horsfall LU, et al. Burden of decompensated cirrhosis and ascites on hospital services in a tertiary care facility: time for change? Intern Med J. 2014;44(9):865-872. DOI: 10.1111/imj.12491. PubMed
23. Gaduputi V, Chandrala C, Abbas N, Tariq H, Chilimuri S, Balar B. Prognostic significance of hypokalemia in hepatic encephalopathy. Hepatogastroenterology. 2014;61(133):1170-1174. PubMed
26. Agrawal K, Kumar P, Markert R, Agrawal S. Risk factors for 30-day readmissions of individuals with decompensated cirrhosis. South Med J. 2015;108(11):682-687. DOI: 10.14423/SMJ.0000000000000371. PubMed
27. Tapper EB, Finkelstein D, Mittleman MA, Piatkowski G, Lai M. Standard assessments of frailty are validated predictors of mortality in hospitalized patients with cirrhosis. Hepatology. 2015;62(2):584-590. DOI: 10.1002/hep.27830. PubMed
28. Atla PR, Sheikh MY, Gill F, Kundu R, Choudhury J. Predictors of hospital re-admissions among Hispanics with hepatitis C-related cirrhosis. Ann Gastroenterol. 2016;29(4):515-520. DOI: 10.20524/aog.2016.0072. PubMed
29. Bajaj JS, Reddy KR, Tandon P, et al. The 3-month readmission rate remains unacceptably high in a large North American cohort of patients with cirrhosis. Hepatology. 2016;64(1):200-208. DOI: 10.1002/hep.28414. PubMed
30. Courson A, Jones GM, Twilla JD. Treatment of acute hepatic encephalopathy: comparing the effects of adding rifaximin to lactulose on patient outcomes. J Pharm Pract. 2016;29(3):212-217. DOI: 10.1177/0897190014566312. PubMed
31. Graupera I, Solà E, Fabrellas N, et al. Urine monocyte chemoattractant protein-1 is an independent predictive factor of hospital readmission and survival in cirrhosis. PLOS ONE. 2016;11(6):e0157371. DOI: 10.1371/journal.pone.0157371. PubMed
32. Kanwal F, Asch SM, Kramer JR, Cao Y, Asrani S, El-Serag HB. Early outpatient follow-up and 30-day outcomes in patients hospitalized with cirrhosis. Hepatology. 2016;64(2):569-581. DOI: 10.1002/hep.28558. PubMed
46. Tapper EB, Finkelstein D, Mittleman MA, Piatkowski G, Chang M, Lai M. A quality improvement initiative reduces 30-day rate of readmission for patients with cirrhosis. Clin Gastroenterol Hepatol. 2016;14(5):753-759. DOI: 10.1016/j.cgh.2015.08.041. PubMed
45. Wigg AJ, McCormick R, Wundke R, Woodman RJ. Efficacy of a chronic disease management model for patients with chronic liver failure. Clin Gastroenterol Hepatol. 2013;11(7):850-8.e1. DOI: 10.1016/j.cgh.2013.01.014. PubMed
44. Ganesh S, Rogal SS, Yadav D, Humar A, Behari J. Risk factors for frequent readmissions and barriers to transplantation in patients with cirrhosis. PLOS ONE. 2013;8(1):e55140. DOI: 10.1371/journal.pone.0055140. PubMed
43. van Walraven C, Bennett C, Jennings A, Austin PC, Forster AJ. Proportion of hospital readmissions deemed avoidable: a systematic review. CMAJ. 2011;183(7):E391-E402. DOI: 10.1503/cmaj.101860. PubMed
42. Bajaj JS, Wade JB, Gibson DP, et al. The multi-dimensional burden of cirrhosis and hepatic encephalopathy on patients and caregivers. Am J Gastroenterol. 2011;106(9):1646-1653. DOI: 10.1038/ajg.2011.157. PubMed
41. van Walraven C, Dhalla IA, Bell C, et al. Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community. CMAJ. 2010;182(6):551-557. DOI: 10.1503/cmaj.091117. PubMed
40. Rodríguez-Artalejo F, Guallar-Castillón P, Pascual CR, et al. Health-related quality of life as a predictor of hospital readmission and death among patients with heart failure. Arch Intern Med. 2005;165(11):1274-1279. DOI: 10.1001/archinte.165.11.1274. PubMed
39. Strömdahl M, Helgeson J, Kalaitzakis E. Emergency readmission following acute upper gastrointestinal bleeding. Eur J Gastroenterol Hepatol. 2017;29(1):73-77. DOI: 10.1097/MEG.0000000000000746. PubMed
38. Morales BP, Planas R, Bartoli R, et al. Early hospital readmission in decompensated cirrhosis: incidence, impact on mortality, and predictive factors. Dig Liver Dis. 2017;49(8):903-909. DOI: 10.1016/j.dld.2017.03.005. PubMed
37. Lyon KC, Likar E, Martello JL, Regier M. Retrospective cross-sectional pilot study of rifaximin dosing for the prevention of recurrent hepatic encephalopathy. J Gastroenterol Hepatol. 2017;32(9):1548-1552. DOI: 10.1111/jgh.13759. PubMed
36. Tapper EB, Halbert B, Mellinger J. Rates of and reasons for hospital readmissions in patients with cirrhosis: a multistate population-based cohort study. Clin Gastroenterol Hepatol. 2016;14(8):1181-1188.e2. DOI: 10.1016/j.cgh.2016.04.009. PubMed
35. Rassameehiran S, Mankongpaisarnrung C, Sutamtewagul G, Klomjit S, Rakvit A. Predictor of 90-day readmission rate for hepatic encephalopathy. South Med J. 2016;109(6):365-369. DOI: 10.14423/SMJ.0000000000000475. PubMed
34. Moon AM, Dominitz JA, Ioannou GN, Lowy E, Beste LA. Use of antibiotics among patients with cirrhosis and upper gastrointestinal bleeding is associated with reduced mortality. Clin Gastroenterol Hepatol. 2016;14(11):1629-1637.e1. DOI: 10.1016/j.cgh.2016.05.040. PubMed
33. Le S, Spelman T, Chong CP, et al. Could adherence to quality of care indicators for hospitalized patients with cirrhosis-related ascites improve clinical outcomes? Am J Gastroenterol. 2016;111(1):87-92. DOI: .10.1038/ajg.2015.402. PubMed
Cirrhosis is a morbid condition characterized by complications such as ascites, gastrointestinal bleeding, and hepatic encephalopathy. These complications frequently require hospitalization, which is a substantial burden to the healthcare system. In 2012, liver disease was responsible for nearly 250,000 admissions across the United States, costing $3 billion.1 Despite this substantial resource utilization, outcomes remain poor, with an inpatient mortality of 6%. For those that survive, many experience hospital readmission.
More generally, early readmission reflects poor quality of care in the US. In 2004, 30-day readmissions occurred in nearly 20% of Medicare beneficiaries and costed over $17 billion.2 In response to this problem, the Affordable Care Act established the Hospital Readmissions Reduction Program (HRRP), which reduces Centers for Medicare & Medicaid Services (CMS) payments to hospitals with excess 30-day readmissions for high-risk conditions, including pneumonia and heart failure.3 Heart failure, in particular, has been the subject of numerous studies detailing risk factors and interventions to predict and prevent readmission.4-6 Based on this extensive evidence, guidelines recommend disease management programs to reduce readmissions in this population.7 In contrast, readmission in the cirrhosis population has received limited attention.
We therefore conducted a systematic review aiming to examine the range of readmission risk noted in the literature, with a focus on the model for end-stage liver disease (MELD) score as a risk factor for readmission.
METHODS
Search Strategy
We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for conducting and reporting systematic reviews.8 A literature search was performed by a medical librarian using the following databases: Ovid MEDLINE, PubMed, EMBASE, CINAHL, the full Cochrane Library, Scopus, Google Scholar, and ClinicalTrials.gov. All the databases were searched from 2000 to May 2017. We did not include older reports because the review focused on contemporary care; earlier studies may not reflect current cirrhosis management. To ensure literature saturation, included articles’ reference lists were reviewed.
Search strategies were developed by combining database-specific subject headings and keywords for readmissions with those for cirrhosis or its complications (Supplementary Material). Google Scholar and ClinicalTrials.gov were searched using keywords only. All results were limited to the English language and those published in 2000 or later, but no other limits were applied.
Identified records were reviewed based on strict criteria. We excluded case reports, case series, reviews, editorials, letters, and meeting abstracts without final peer-reviewed publication. We also excluded studies of pediatric populations (age < 18 years), patients without cirrhosis, and patients with liver transplants. We excluded studies in which patients were not hospitalized at study onset and those where the index admission was for an elective procedure. Because our interest was to identify factors associated with early readmission, we excluded studies that did not report readmissions within 90 days or those with a mean or median follow-up of less than 30 days. We also excluded studies that did not examine the association between readmission and at least 1 independent variable or intervention. Duplicate reports of a common sample were excluded unless the duplicate provided additional information, and such reports were examined together in our synthesis.
Two authors identified potentially eligible records by independently screening titles and abstracts. At this stage, records that did not meet the eligibility criteria were excluded, and the reasons for exclusion were not recorded. Records with disagreement were retained for full-text review. After this initial exclusion of records, the remaining full-text records were reviewed independently. For this full-text review, we recorded exclusion reasons and disagreements were resolved through discussion.
Data Collection
Data were abstracted from each study by 2 authors independently and recorded in a REDCap database.9 Discrepancies were resolved through discussion. We recorded study characteristics, including study design, setting, population (including the inclusion/exclusion criteria, sample size, and patient and hospitalization characteristics), interventions, and comparisons. To facilitate comparisons across studies, we employed validated methods to approximate means and standard deviations (SD).10 We recorded detailed information on outcomes including readmissions, preventability, independent variables, and mortality. Studies that focused on a single independent factor or intervention were classified as “focused,” while those that examined multiple factors were classified as “broad.” We used the Newcastle–Ottawa Scale to assess the risk of bias in each study.11 This instrument uses a 9-point scale to gauge methodological quality based on selection, group comparability, and exposure/outcome assessment.
Statistical Analysis
Analyses were performed using Stata 13.1 (StataCorp LP, College Station, Texas). We determined the pooled proportion of patients with 30-day readmission using a random-effects model, with the Freeman–Tukey double-arcsine transformation for meta-analysis of proportions.12 We investigated the heterogeneity by stratifying analyses according to prespecified study characteristics, including “broad” versus “focused.” However, the readmission risk was not different in the stratified analysis; therefore, we chose to pool the findings. For point estimates, 95% confidence intervals (CIs) were calculated, and a P-value < .05 was considered statistically significant.
RESULTS
Search Results
Study Characteristics
Two studies were performed in Australia, 4 in Europe, and the remainder in North America. Twenty one of the 26 studies were retrospective cohort studies (Table 1). Twenty studies were single-center studies (of which half were performed at transplant centers), and 4 of the 6 multicenter studies were based on administrative data with large samples (173,254 patients). The inclusion/exclusion criteria varied widely (Supplementary Material). Some studies only included patients admitted for specific cirrhosis complications, while others included those admitted for any reason. Two studies excluded patients admitted in the prior 30 days, and 6 excluded patients discharged to hospice. The mean risk of bias score was 7.5 (SD 1.3) out of a possible 9 points, with most lacking an adequate description of follow-up and several lacking adjustment for confounders.
Outcomes
Readmission and MELD
DISCUSSION
Hospital readmission is a costly and common problem in the US.2 In addition to the negative impact that readmissions have on patients’ lives,40 readmissions are increasingly being used to measure quality. Unplanned 30-day readmissions are posted publicly, and excess readmissions for high-risk conditions are penalized through HRRP.3 Although HRRP does not currently include cirrhosis, the program has expanded to include several conditions that were not included in the initial iteration. Whether cirrhosis will be included in future iterations remains to be seen; however, increasing scrutiny is likely to continue. Of specific populations at risk, patients with cirrhosis are particularly vulnerable due to several features. Ascites management often requires hospitalization due to diuretic titration and poor access to paracentesis, and hepatic encephalopathy treatment requires complex lactulose titration.16 Other features of cirrhosis, such as gastrointestinal bleeding, infections, and renal failure, also place patients at risk of poor outcomes. The resulting readmission burden is high, with a pooled 30-day readmission rate of 26%. Other associated outcomes are also poor, with a consistent relationship between readmission and subsequent mortality.
We found striking heterogeneity in various aspects. First, the inclusion/exclusion criteria varied widely, both cirrhosis-specific (eg, spontaneous bacterial peritonitis) and more general (patients admitted within the prior 30 days). Some of these criteria may bias readmission estimates; the risk of readmission may be reduced in those on hospice, as patients forgo curative therapy. Additionally, an established risk factor for readmission is prior hospitalization41; excluding patients with prior admissions prohibits analysis of this variable. Another aspect is the capture of readmissions: readmissions outside of the index hospital were not included in most studies. In those that did include outside readmissions, the burden was sizeable: 17% in 1 single-center study and 23% in a multistate administrative database.16,36 These outside readmissions must be included in future studies; they are as important as same-center readmissions both to patients and CMS.3 Despite this heterogeneity, the studies scored relatively high on the Newcastle–Ottawa risk of bias scale, with the only common deficiency being an inadequate description of follow-up.
Building on the findings of this review, an important step will be the design of interventions to reduce readmissions. Such interventions require a full understanding of this population’s characteristics and needs. Critically, we found a lack of data on social determinants of health. Impairments in these factors are well-established contributors to readmission risk in other populations,4,40 and are highly prevalent in cirrhosis.42 Indeed, CMS has focused resources toward social determinants of health in the effort to reduce utilization and improve outcomes. This lack of data on social determinants of health, as well as other understudied factors, represents an important opportunity for future research efforts to better define the modifiable features that could be targeted in the future to prevent readmissions. Such research is urgently needed and will likely require prospective studies to gather these important factors. Notably, most studies in this systematic review were retrospective and therefore unable to examine many of these understudied factors. Another important aspect that has received little attention is readmission preventability: only 2 studies assessed preventability, both through unstructured chart review. Preventability assessments in noncirrhotic populations have used wide-ranging methodologies, yielding inconsistent results.43 This variability prompted recommendations that preventability should be assessed by multiple reviewers guided by explicit parameters.43 Such detailed attention to preventability is urgently needed to better inform interventions.
In contrast to the lack of data on social factors, we found that the MELD score was examined in most studies and was frequently associated with readmission. Despite this consistent association, differences in the MELD scores between studies limit inferences into specific cutoff values that could identify the highest risk patients. Because of its existing widespread clinical use, the MELD score may prove to be important in readmission risk stratification. Efforts to develop a useful model including the MELD score are needed to target interventions to the highest risk patients.
This review has several limitations. Although we used a broad search strategy to capture studies, some may not have been included due to our selection criteria. For instance, 1 retrospective paper described factors associated with high admission density during 1 year but did not specifically report the frequency of early readmissions.44 Similarly, a randomized trial of a disease management program did not specifically examine early readmissions.45 Another quasi-experimental study of a quality improvement initiative was not included because a large proportion of their subjects was post liver transplant.46 However, the inclusion of these papers is unlikely to change our conclusions; the retrospective study identified factors similar to those in the included studies, and the quasi-experimental study overlapped with the included study that assessed frailty.27 Another potential limitation is the exclusion of studies published in abstract form only. Such studies may be important, as the field of cirrhosis readmissions is relatively young. However, including only full-paper publications ensures the inclusion of only higher quality studies scrutinized during the peer-review process. Similarly, newer published studies may have been missed due to the abundant interest in this topic and ongoing research. Lastly, the significant heterogeneity of the studies limits conclusions that can be made regarding the pooled readmission rates.
In summary, we found that patients with cirrhosis experience a high incidence of hospital readmissions. Several processes of care may be associated with readmissions, suggesting room for improvement in caring for this population and reducing readmissions. However, we identified several gaps in the literature, which does not adequately describe social factors and is lacking details on readmission preventability assessment. Future studies should attempt to address these issues so that interventions can be targeted to the highest risk patients and designed to best meet the needs of patients with cirrhosis.
Disclosures
Dr. Orman, Dr. Ghabril, and Dr. Emmett report no potential conflicts of interest. Dr. Chalasani reports personal fees from Lilly, personal fees from Abbvie, personal fees from Tobira/Allergan, personal fees from Ardelyx, personal fees from Amarin, personal fees from Shire, personal fees from Madrigal, personal fees from DS Biopharma (Afimmune), personal fees from Cempra, personal fees from NuSirt, grants from Galectin, grants from Gilead, grants from Intercept, grants from Cumberland, grants from Conatus, personal fees from Immuron, and personal fees from Axovant, outside the submitted work.
Funding Information
This work was supported, in part, by the National Institutes of Health, KL2 TR001106 and K23 DK109202
Cirrhosis is a morbid condition characterized by complications such as ascites, gastrointestinal bleeding, and hepatic encephalopathy. These complications frequently require hospitalization, which is a substantial burden to the healthcare system. In 2012, liver disease was responsible for nearly 250,000 admissions across the United States, costing $3 billion.1 Despite this substantial resource utilization, outcomes remain poor, with an inpatient mortality of 6%. For those that survive, many experience hospital readmission.
More generally, early readmission reflects poor quality of care in the US. In 2004, 30-day readmissions occurred in nearly 20% of Medicare beneficiaries and costed over $17 billion.2 In response to this problem, the Affordable Care Act established the Hospital Readmissions Reduction Program (HRRP), which reduces Centers for Medicare & Medicaid Services (CMS) payments to hospitals with excess 30-day readmissions for high-risk conditions, including pneumonia and heart failure.3 Heart failure, in particular, has been the subject of numerous studies detailing risk factors and interventions to predict and prevent readmission.4-6 Based on this extensive evidence, guidelines recommend disease management programs to reduce readmissions in this population.7 In contrast, readmission in the cirrhosis population has received limited attention.
We therefore conducted a systematic review aiming to examine the range of readmission risk noted in the literature, with a focus on the model for end-stage liver disease (MELD) score as a risk factor for readmission.
METHODS
Search Strategy
We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for conducting and reporting systematic reviews.8 A literature search was performed by a medical librarian using the following databases: Ovid MEDLINE, PubMed, EMBASE, CINAHL, the full Cochrane Library, Scopus, Google Scholar, and ClinicalTrials.gov. All the databases were searched from 2000 to May 2017. We did not include older reports because the review focused on contemporary care; earlier studies may not reflect current cirrhosis management. To ensure literature saturation, included articles’ reference lists were reviewed.
Search strategies were developed by combining database-specific subject headings and keywords for readmissions with those for cirrhosis or its complications (Supplementary Material). Google Scholar and ClinicalTrials.gov were searched using keywords only. All results were limited to the English language and those published in 2000 or later, but no other limits were applied.
Identified records were reviewed based on strict criteria. We excluded case reports, case series, reviews, editorials, letters, and meeting abstracts without final peer-reviewed publication. We also excluded studies of pediatric populations (age < 18 years), patients without cirrhosis, and patients with liver transplants. We excluded studies in which patients were not hospitalized at study onset and those where the index admission was for an elective procedure. Because our interest was to identify factors associated with early readmission, we excluded studies that did not report readmissions within 90 days or those with a mean or median follow-up of less than 30 days. We also excluded studies that did not examine the association between readmission and at least 1 independent variable or intervention. Duplicate reports of a common sample were excluded unless the duplicate provided additional information, and such reports were examined together in our synthesis.
Two authors identified potentially eligible records by independently screening titles and abstracts. At this stage, records that did not meet the eligibility criteria were excluded, and the reasons for exclusion were not recorded. Records with disagreement were retained for full-text review. After this initial exclusion of records, the remaining full-text records were reviewed independently. For this full-text review, we recorded exclusion reasons and disagreements were resolved through discussion.
Data Collection
Data were abstracted from each study by 2 authors independently and recorded in a REDCap database.9 Discrepancies were resolved through discussion. We recorded study characteristics, including study design, setting, population (including the inclusion/exclusion criteria, sample size, and patient and hospitalization characteristics), interventions, and comparisons. To facilitate comparisons across studies, we employed validated methods to approximate means and standard deviations (SD).10 We recorded detailed information on outcomes including readmissions, preventability, independent variables, and mortality. Studies that focused on a single independent factor or intervention were classified as “focused,” while those that examined multiple factors were classified as “broad.” We used the Newcastle–Ottawa Scale to assess the risk of bias in each study.11 This instrument uses a 9-point scale to gauge methodological quality based on selection, group comparability, and exposure/outcome assessment.
Statistical Analysis
Analyses were performed using Stata 13.1 (StataCorp LP, College Station, Texas). We determined the pooled proportion of patients with 30-day readmission using a random-effects model, with the Freeman–Tukey double-arcsine transformation for meta-analysis of proportions.12 We investigated the heterogeneity by stratifying analyses according to prespecified study characteristics, including “broad” versus “focused.” However, the readmission risk was not different in the stratified analysis; therefore, we chose to pool the findings. For point estimates, 95% confidence intervals (CIs) were calculated, and a P-value < .05 was considered statistically significant.
RESULTS
Search Results
Study Characteristics
Two studies were performed in Australia, 4 in Europe, and the remainder in North America. Twenty one of the 26 studies were retrospective cohort studies (Table 1). Twenty studies were single-center studies (of which half were performed at transplant centers), and 4 of the 6 multicenter studies were based on administrative data with large samples (173,254 patients). The inclusion/exclusion criteria varied widely (Supplementary Material). Some studies only included patients admitted for specific cirrhosis complications, while others included those admitted for any reason. Two studies excluded patients admitted in the prior 30 days, and 6 excluded patients discharged to hospice. The mean risk of bias score was 7.5 (SD 1.3) out of a possible 9 points, with most lacking an adequate description of follow-up and several lacking adjustment for confounders.
Outcomes
Readmission and MELD
DISCUSSION
Hospital readmission is a costly and common problem in the US.2 In addition to the negative impact that readmissions have on patients’ lives,40 readmissions are increasingly being used to measure quality. Unplanned 30-day readmissions are posted publicly, and excess readmissions for high-risk conditions are penalized through HRRP.3 Although HRRP does not currently include cirrhosis, the program has expanded to include several conditions that were not included in the initial iteration. Whether cirrhosis will be included in future iterations remains to be seen; however, increasing scrutiny is likely to continue. Of specific populations at risk, patients with cirrhosis are particularly vulnerable due to several features. Ascites management often requires hospitalization due to diuretic titration and poor access to paracentesis, and hepatic encephalopathy treatment requires complex lactulose titration.16 Other features of cirrhosis, such as gastrointestinal bleeding, infections, and renal failure, also place patients at risk of poor outcomes. The resulting readmission burden is high, with a pooled 30-day readmission rate of 26%. Other associated outcomes are also poor, with a consistent relationship between readmission and subsequent mortality.
We found striking heterogeneity in various aspects. First, the inclusion/exclusion criteria varied widely, both cirrhosis-specific (eg, spontaneous bacterial peritonitis) and more general (patients admitted within the prior 30 days). Some of these criteria may bias readmission estimates; the risk of readmission may be reduced in those on hospice, as patients forgo curative therapy. Additionally, an established risk factor for readmission is prior hospitalization41; excluding patients with prior admissions prohibits analysis of this variable. Another aspect is the capture of readmissions: readmissions outside of the index hospital were not included in most studies. In those that did include outside readmissions, the burden was sizeable: 17% in 1 single-center study and 23% in a multistate administrative database.16,36 These outside readmissions must be included in future studies; they are as important as same-center readmissions both to patients and CMS.3 Despite this heterogeneity, the studies scored relatively high on the Newcastle–Ottawa risk of bias scale, with the only common deficiency being an inadequate description of follow-up.
Building on the findings of this review, an important step will be the design of interventions to reduce readmissions. Such interventions require a full understanding of this population’s characteristics and needs. Critically, we found a lack of data on social determinants of health. Impairments in these factors are well-established contributors to readmission risk in other populations,4,40 and are highly prevalent in cirrhosis.42 Indeed, CMS has focused resources toward social determinants of health in the effort to reduce utilization and improve outcomes. This lack of data on social determinants of health, as well as other understudied factors, represents an important opportunity for future research efforts to better define the modifiable features that could be targeted in the future to prevent readmissions. Such research is urgently needed and will likely require prospective studies to gather these important factors. Notably, most studies in this systematic review were retrospective and therefore unable to examine many of these understudied factors. Another important aspect that has received little attention is readmission preventability: only 2 studies assessed preventability, both through unstructured chart review. Preventability assessments in noncirrhotic populations have used wide-ranging methodologies, yielding inconsistent results.43 This variability prompted recommendations that preventability should be assessed by multiple reviewers guided by explicit parameters.43 Such detailed attention to preventability is urgently needed to better inform interventions.
In contrast to the lack of data on social factors, we found that the MELD score was examined in most studies and was frequently associated with readmission. Despite this consistent association, differences in the MELD scores between studies limit inferences into specific cutoff values that could identify the highest risk patients. Because of its existing widespread clinical use, the MELD score may prove to be important in readmission risk stratification. Efforts to develop a useful model including the MELD score are needed to target interventions to the highest risk patients.
This review has several limitations. Although we used a broad search strategy to capture studies, some may not have been included due to our selection criteria. For instance, 1 retrospective paper described factors associated with high admission density during 1 year but did not specifically report the frequency of early readmissions.44 Similarly, a randomized trial of a disease management program did not specifically examine early readmissions.45 Another quasi-experimental study of a quality improvement initiative was not included because a large proportion of their subjects was post liver transplant.46 However, the inclusion of these papers is unlikely to change our conclusions; the retrospective study identified factors similar to those in the included studies, and the quasi-experimental study overlapped with the included study that assessed frailty.27 Another potential limitation is the exclusion of studies published in abstract form only. Such studies may be important, as the field of cirrhosis readmissions is relatively young. However, including only full-paper publications ensures the inclusion of only higher quality studies scrutinized during the peer-review process. Similarly, newer published studies may have been missed due to the abundant interest in this topic and ongoing research. Lastly, the significant heterogeneity of the studies limits conclusions that can be made regarding the pooled readmission rates.
In summary, we found that patients with cirrhosis experience a high incidence of hospital readmissions. Several processes of care may be associated with readmissions, suggesting room for improvement in caring for this population and reducing readmissions. However, we identified several gaps in the literature, which does not adequately describe social factors and is lacking details on readmission preventability assessment. Future studies should attempt to address these issues so that interventions can be targeted to the highest risk patients and designed to best meet the needs of patients with cirrhosis.
Disclosures
Dr. Orman, Dr. Ghabril, and Dr. Emmett report no potential conflicts of interest. Dr. Chalasani reports personal fees from Lilly, personal fees from Abbvie, personal fees from Tobira/Allergan, personal fees from Ardelyx, personal fees from Amarin, personal fees from Shire, personal fees from Madrigal, personal fees from DS Biopharma (Afimmune), personal fees from Cempra, personal fees from NuSirt, grants from Galectin, grants from Gilead, grants from Intercept, grants from Cumberland, grants from Conatus, personal fees from Immuron, and personal fees from Axovant, outside the submitted work.
Funding Information
This work was supported, in part, by the National Institutes of Health, KL2 TR001106 and K23 DK109202
1. Peery AF, Crockett SD, Barritt AS, et al. Burden of gastrointestinal, liver, and pancreatic diseases in the United States. Gastroenterology. 2015;149(7):1731-1741.e3. DOI: 10.1053/j.gastro.2015.08.045. PubMed
13. Bini EJ, Weinshel EH, Generoso R, et al. Impact of gastroenterology consultation on the outcomes of patients admitted to the hospital with decompensated cirrhosis. Hepatology. 2001;34(6):1089-1095. DOI: 10.1053/jhep.2001.29204. PubMed
14. Berman K, Tandra S, Forssell K, et al. Incidence and predictors of 30-day readmission among patients hospitalized for advanced liver disease. Clin Gastroenterol Hepatol. 2011;9(3):254-259. DOI: 10.1016/j.cgh.2010.10.035. PubMed
15. Johnson EA, Spier BJ, Leff JA, Lucey MR, Said A. Optimising the care of patients with cirrhosis and gastrointestinal haemorrhage: a quality improvement study. Aliment Pharmacol Ther. 2011;34(1):76-82. DOI: 10.1111/j.1365-2036.2011.04692.x. PubMed
16. Volk ML, Tocco RS, Bazick J, Rakoski MO, Lok AS. Hospital readmissions among patients with decompensated cirrhosis. Am J Gastroenterol. 2012;107(2):247-252. DOI: 10.1038/ajg.2011.314. PubMed
17. Barsuk JH, Cohen ER, Feinglass J, McGaghie WC, Wayne DB. Clinical outcomes after bedside and interventional radiology paracentesis procedures. Am J Med. 2013;126(4):349-356. DOI: 10.1016/j.amjmed.2012.09.016. PubMed
18. Deitelzweig S, Amin A, Christian R, Friend K, Lin J, Lowe TJ. Hyponatremia-associated healthcare burden among US patients hospitalized for cirrhosis. Adv Ther. 2013;30(1):71-80. DOI: 10.1007/s12325-012-0073-1. PubMed
19. Morando F, Maresio G, Piano S, et al. How to improve care in outpatients with cirrhosis and ascites: a new model of care coordination by consultant hepatologists. J Hepatol. 2013;59(2):257-264. DOI: 10.1016/j.jhep.2013.03.010. PubMed
20. Singal AG, Rahimi RS, Clark C, et al. An automated model using electronic medical record data identifies patients with cirrhosis at high risk for readmission. Clin Gastroenterol Hepatol. 2013;11(10):1335-1341.e1. DOI: 10.1016/j.cgh.2013.03.022. PubMed
21. Desai AP, Satoskar R, Appannagari A, et al. Co-management between hospitalist and hepatologist improves the quality of care of inpatients with chronic liver disease. J Clin Gastroenterol. 2014;48(4):e30-e36. DOI: 10.1097/MCG.0b013e3182a87f70. PubMed
22. Fagan KJ, Zhao EY, Horsfall LU, et al. Burden of decompensated cirrhosis and ascites on hospital services in a tertiary care facility: time for change? Intern Med J. 2014;44(9):865-872. DOI: 10.1111/imj.12491. PubMed
23. Gaduputi V, Chandrala C, Abbas N, Tariq H, Chilimuri S, Balar B. Prognostic significance of hypokalemia in hepatic encephalopathy. Hepatogastroenterology. 2014;61(133):1170-1174. PubMed
26. Agrawal K, Kumar P, Markert R, Agrawal S. Risk factors for 30-day readmissions of individuals with decompensated cirrhosis. South Med J. 2015;108(11):682-687. DOI: 10.14423/SMJ.0000000000000371. PubMed
27. Tapper EB, Finkelstein D, Mittleman MA, Piatkowski G, Lai M. Standard assessments of frailty are validated predictors of mortality in hospitalized patients with cirrhosis. Hepatology. 2015;62(2):584-590. DOI: 10.1002/hep.27830. PubMed
28. Atla PR, Sheikh MY, Gill F, Kundu R, Choudhury J. Predictors of hospital re-admissions among Hispanics with hepatitis C-related cirrhosis. Ann Gastroenterol. 2016;29(4):515-520. DOI: 10.20524/aog.2016.0072. PubMed
29. Bajaj JS, Reddy KR, Tandon P, et al. The 3-month readmission rate remains unacceptably high in a large North American cohort of patients with cirrhosis. Hepatology. 2016;64(1):200-208. DOI: 10.1002/hep.28414. PubMed
30. Courson A, Jones GM, Twilla JD. Treatment of acute hepatic encephalopathy: comparing the effects of adding rifaximin to lactulose on patient outcomes. J Pharm Pract. 2016;29(3):212-217. DOI: 10.1177/0897190014566312. PubMed
31. Graupera I, Solà E, Fabrellas N, et al. Urine monocyte chemoattractant protein-1 is an independent predictive factor of hospital readmission and survival in cirrhosis. PLOS ONE. 2016;11(6):e0157371. DOI: 10.1371/journal.pone.0157371. PubMed
32. Kanwal F, Asch SM, Kramer JR, Cao Y, Asrani S, El-Serag HB. Early outpatient follow-up and 30-day outcomes in patients hospitalized with cirrhosis. Hepatology. 2016;64(2):569-581. DOI: 10.1002/hep.28558. PubMed
46. Tapper EB, Finkelstein D, Mittleman MA, Piatkowski G, Chang M, Lai M. A quality improvement initiative reduces 30-day rate of readmission for patients with cirrhosis. Clin Gastroenterol Hepatol. 2016;14(5):753-759. DOI: 10.1016/j.cgh.2015.08.041. PubMed
45. Wigg AJ, McCormick R, Wundke R, Woodman RJ. Efficacy of a chronic disease management model for patients with chronic liver failure. Clin Gastroenterol Hepatol. 2013;11(7):850-8.e1. DOI: 10.1016/j.cgh.2013.01.014. PubMed
44. Ganesh S, Rogal SS, Yadav D, Humar A, Behari J. Risk factors for frequent readmissions and barriers to transplantation in patients with cirrhosis. PLOS ONE. 2013;8(1):e55140. DOI: 10.1371/journal.pone.0055140. PubMed
43. van Walraven C, Bennett C, Jennings A, Austin PC, Forster AJ. Proportion of hospital readmissions deemed avoidable: a systematic review. CMAJ. 2011;183(7):E391-E402. DOI: 10.1503/cmaj.101860. PubMed
42. Bajaj JS, Wade JB, Gibson DP, et al. The multi-dimensional burden of cirrhosis and hepatic encephalopathy on patients and caregivers. Am J Gastroenterol. 2011;106(9):1646-1653. DOI: 10.1038/ajg.2011.157. PubMed
41. van Walraven C, Dhalla IA, Bell C, et al. Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community. CMAJ. 2010;182(6):551-557. DOI: 10.1503/cmaj.091117. PubMed
40. Rodríguez-Artalejo F, Guallar-Castillón P, Pascual CR, et al. Health-related quality of life as a predictor of hospital readmission and death among patients with heart failure. Arch Intern Med. 2005;165(11):1274-1279. DOI: 10.1001/archinte.165.11.1274. PubMed
39. Strömdahl M, Helgeson J, Kalaitzakis E. Emergency readmission following acute upper gastrointestinal bleeding. Eur J Gastroenterol Hepatol. 2017;29(1):73-77. DOI: 10.1097/MEG.0000000000000746. PubMed
38. Morales BP, Planas R, Bartoli R, et al. Early hospital readmission in decompensated cirrhosis: incidence, impact on mortality, and predictive factors. Dig Liver Dis. 2017;49(8):903-909. DOI: 10.1016/j.dld.2017.03.005. PubMed
37. Lyon KC, Likar E, Martello JL, Regier M. Retrospective cross-sectional pilot study of rifaximin dosing for the prevention of recurrent hepatic encephalopathy. J Gastroenterol Hepatol. 2017;32(9):1548-1552. DOI: 10.1111/jgh.13759. PubMed
36. Tapper EB, Halbert B, Mellinger J. Rates of and reasons for hospital readmissions in patients with cirrhosis: a multistate population-based cohort study. Clin Gastroenterol Hepatol. 2016;14(8):1181-1188.e2. DOI: 10.1016/j.cgh.2016.04.009. PubMed
35. Rassameehiran S, Mankongpaisarnrung C, Sutamtewagul G, Klomjit S, Rakvit A. Predictor of 90-day readmission rate for hepatic encephalopathy. South Med J. 2016;109(6):365-369. DOI: 10.14423/SMJ.0000000000000475. PubMed
34. Moon AM, Dominitz JA, Ioannou GN, Lowy E, Beste LA. Use of antibiotics among patients with cirrhosis and upper gastrointestinal bleeding is associated with reduced mortality. Clin Gastroenterol Hepatol. 2016;14(11):1629-1637.e1. DOI: 10.1016/j.cgh.2016.05.040. PubMed
33. Le S, Spelman T, Chong CP, et al. Could adherence to quality of care indicators for hospitalized patients with cirrhosis-related ascites improve clinical outcomes? Am J Gastroenterol. 2016;111(1):87-92. DOI: .10.1038/ajg.2015.402. PubMed
1. Peery AF, Crockett SD, Barritt AS, et al. Burden of gastrointestinal, liver, and pancreatic diseases in the United States. Gastroenterology. 2015;149(7):1731-1741.e3. DOI: 10.1053/j.gastro.2015.08.045. PubMed
13. Bini EJ, Weinshel EH, Generoso R, et al. Impact of gastroenterology consultation on the outcomes of patients admitted to the hospital with decompensated cirrhosis. Hepatology. 2001;34(6):1089-1095. DOI: 10.1053/jhep.2001.29204. PubMed
14. Berman K, Tandra S, Forssell K, et al. Incidence and predictors of 30-day readmission among patients hospitalized for advanced liver disease. Clin Gastroenterol Hepatol. 2011;9(3):254-259. DOI: 10.1016/j.cgh.2010.10.035. PubMed
15. Johnson EA, Spier BJ, Leff JA, Lucey MR, Said A. Optimising the care of patients with cirrhosis and gastrointestinal haemorrhage: a quality improvement study. Aliment Pharmacol Ther. 2011;34(1):76-82. DOI: 10.1111/j.1365-2036.2011.04692.x. PubMed
16. Volk ML, Tocco RS, Bazick J, Rakoski MO, Lok AS. Hospital readmissions among patients with decompensated cirrhosis. Am J Gastroenterol. 2012;107(2):247-252. DOI: 10.1038/ajg.2011.314. PubMed
17. Barsuk JH, Cohen ER, Feinglass J, McGaghie WC, Wayne DB. Clinical outcomes after bedside and interventional radiology paracentesis procedures. Am J Med. 2013;126(4):349-356. DOI: 10.1016/j.amjmed.2012.09.016. PubMed
18. Deitelzweig S, Amin A, Christian R, Friend K, Lin J, Lowe TJ. Hyponatremia-associated healthcare burden among US patients hospitalized for cirrhosis. Adv Ther. 2013;30(1):71-80. DOI: 10.1007/s12325-012-0073-1. PubMed
19. Morando F, Maresio G, Piano S, et al. How to improve care in outpatients with cirrhosis and ascites: a new model of care coordination by consultant hepatologists. J Hepatol. 2013;59(2):257-264. DOI: 10.1016/j.jhep.2013.03.010. PubMed
20. Singal AG, Rahimi RS, Clark C, et al. An automated model using electronic medical record data identifies patients with cirrhosis at high risk for readmission. Clin Gastroenterol Hepatol. 2013;11(10):1335-1341.e1. DOI: 10.1016/j.cgh.2013.03.022. PubMed
21. Desai AP, Satoskar R, Appannagari A, et al. Co-management between hospitalist and hepatologist improves the quality of care of inpatients with chronic liver disease. J Clin Gastroenterol. 2014;48(4):e30-e36. DOI: 10.1097/MCG.0b013e3182a87f70. PubMed
22. Fagan KJ, Zhao EY, Horsfall LU, et al. Burden of decompensated cirrhosis and ascites on hospital services in a tertiary care facility: time for change? Intern Med J. 2014;44(9):865-872. DOI: 10.1111/imj.12491. PubMed
23. Gaduputi V, Chandrala C, Abbas N, Tariq H, Chilimuri S, Balar B. Prognostic significance of hypokalemia in hepatic encephalopathy. Hepatogastroenterology. 2014;61(133):1170-1174. PubMed
26. Agrawal K, Kumar P, Markert R, Agrawal S. Risk factors for 30-day readmissions of individuals with decompensated cirrhosis. South Med J. 2015;108(11):682-687. DOI: 10.14423/SMJ.0000000000000371. PubMed
27. Tapper EB, Finkelstein D, Mittleman MA, Piatkowski G, Lai M. Standard assessments of frailty are validated predictors of mortality in hospitalized patients with cirrhosis. Hepatology. 2015;62(2):584-590. DOI: 10.1002/hep.27830. PubMed
28. Atla PR, Sheikh MY, Gill F, Kundu R, Choudhury J. Predictors of hospital re-admissions among Hispanics with hepatitis C-related cirrhosis. Ann Gastroenterol. 2016;29(4):515-520. DOI: 10.20524/aog.2016.0072. PubMed
29. Bajaj JS, Reddy KR, Tandon P, et al. The 3-month readmission rate remains unacceptably high in a large North American cohort of patients with cirrhosis. Hepatology. 2016;64(1):200-208. DOI: 10.1002/hep.28414. PubMed
30. Courson A, Jones GM, Twilla JD. Treatment of acute hepatic encephalopathy: comparing the effects of adding rifaximin to lactulose on patient outcomes. J Pharm Pract. 2016;29(3):212-217. DOI: 10.1177/0897190014566312. PubMed
31. Graupera I, Solà E, Fabrellas N, et al. Urine monocyte chemoattractant protein-1 is an independent predictive factor of hospital readmission and survival in cirrhosis. PLOS ONE. 2016;11(6):e0157371. DOI: 10.1371/journal.pone.0157371. PubMed
32. Kanwal F, Asch SM, Kramer JR, Cao Y, Asrani S, El-Serag HB. Early outpatient follow-up and 30-day outcomes in patients hospitalized with cirrhosis. Hepatology. 2016;64(2):569-581. DOI: 10.1002/hep.28558. PubMed
46. Tapper EB, Finkelstein D, Mittleman MA, Piatkowski G, Chang M, Lai M. A quality improvement initiative reduces 30-day rate of readmission for patients with cirrhosis. Clin Gastroenterol Hepatol. 2016;14(5):753-759. DOI: 10.1016/j.cgh.2015.08.041. PubMed
45. Wigg AJ, McCormick R, Wundke R, Woodman RJ. Efficacy of a chronic disease management model for patients with chronic liver failure. Clin Gastroenterol Hepatol. 2013;11(7):850-8.e1. DOI: 10.1016/j.cgh.2013.01.014. PubMed
44. Ganesh S, Rogal SS, Yadav D, Humar A, Behari J. Risk factors for frequent readmissions and barriers to transplantation in patients with cirrhosis. PLOS ONE. 2013;8(1):e55140. DOI: 10.1371/journal.pone.0055140. PubMed
43. van Walraven C, Bennett C, Jennings A, Austin PC, Forster AJ. Proportion of hospital readmissions deemed avoidable: a systematic review. CMAJ. 2011;183(7):E391-E402. DOI: 10.1503/cmaj.101860. PubMed
42. Bajaj JS, Wade JB, Gibson DP, et al. The multi-dimensional burden of cirrhosis and hepatic encephalopathy on patients and caregivers. Am J Gastroenterol. 2011;106(9):1646-1653. DOI: 10.1038/ajg.2011.157. PubMed
41. van Walraven C, Dhalla IA, Bell C, et al. Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community. CMAJ. 2010;182(6):551-557. DOI: 10.1503/cmaj.091117. PubMed
40. Rodríguez-Artalejo F, Guallar-Castillón P, Pascual CR, et al. Health-related quality of life as a predictor of hospital readmission and death among patients with heart failure. Arch Intern Med. 2005;165(11):1274-1279. DOI: 10.1001/archinte.165.11.1274. PubMed
39. Strömdahl M, Helgeson J, Kalaitzakis E. Emergency readmission following acute upper gastrointestinal bleeding. Eur J Gastroenterol Hepatol. 2017;29(1):73-77. DOI: 10.1097/MEG.0000000000000746. PubMed
38. Morales BP, Planas R, Bartoli R, et al. Early hospital readmission in decompensated cirrhosis: incidence, impact on mortality, and predictive factors. Dig Liver Dis. 2017;49(8):903-909. DOI: 10.1016/j.dld.2017.03.005. PubMed
37. Lyon KC, Likar E, Martello JL, Regier M. Retrospective cross-sectional pilot study of rifaximin dosing for the prevention of recurrent hepatic encephalopathy. J Gastroenterol Hepatol. 2017;32(9):1548-1552. DOI: 10.1111/jgh.13759. PubMed
36. Tapper EB, Halbert B, Mellinger J. Rates of and reasons for hospital readmissions in patients with cirrhosis: a multistate population-based cohort study. Clin Gastroenterol Hepatol. 2016;14(8):1181-1188.e2. DOI: 10.1016/j.cgh.2016.04.009. PubMed
35. Rassameehiran S, Mankongpaisarnrung C, Sutamtewagul G, Klomjit S, Rakvit A. Predictor of 90-day readmission rate for hepatic encephalopathy. South Med J. 2016;109(6):365-369. DOI: 10.14423/SMJ.0000000000000475. PubMed
34. Moon AM, Dominitz JA, Ioannou GN, Lowy E, Beste LA. Use of antibiotics among patients with cirrhosis and upper gastrointestinal bleeding is associated with reduced mortality. Clin Gastroenterol Hepatol. 2016;14(11):1629-1637.e1. DOI: 10.1016/j.cgh.2016.05.040. PubMed
33. Le S, Spelman T, Chong CP, et al. Could adherence to quality of care indicators for hospitalized patients with cirrhosis-related ascites improve clinical outcomes? Am J Gastroenterol. 2016;111(1):87-92. DOI: .10.1038/ajg.2015.402. PubMed
© 2018 Society of Hospital Medicine