Trevor C. Yuen, MS

Altered mental status (AMS) is a complex spectrum of cognitive deficits that includes orientation, memory, language, visuospatial ability, and perception.[1] The clinical definitions of both delirium and dementia include AMS as a hallmark clinical prerequisite. Regardless of etiology, this broader AMS definition is particularly salient in the hospital setting, where AMS is present in up to 60% of inpatients and is associated with longer hospital stay as well as increased morbidity and mortality.[2, 3] Not surprisingly, due to the complexity of identifying and assessing changes in mental status, clinically relevant AMS is often undetected among inpatients.[2] However, when detected, the most common causes of AMS (infection, polypharmacy, and pain) are treatable, suggesting that early AMS identification could alert clinicians to early signs of clinical decompensation, potentially improving clinical outcomes.[4]

Because rapid and systemic clinical detection of AMS is limited by the complexity of mental status, a number of assessments have been created, each with their own advantages, limitations, and target populations. These assessments are often limited by time‐intensive administration, subjectivity of mental status assessment, and lack of sensitivity in general medicine patients. Time‐intensive measures, such as the Short Portable Mental Status Questionnaire (SPMSQ) have utility in the research setting, whereas current common clinical risk stratification tools (eg, National Early Warning Score) utilize simpler measures such as the Alert, Voice, Pain, Unresponsive (AVPU) and Glasgow Coma Scale (GCS) as measures of mental status.[2, 5, 6, 7, 8, 9]

To address the need for a brief, clinically feasible, accurate tool in clinical detection of AMS, our group developed a mobile application for working memory testing, the Functional Assessment of Mentation (FAM^TM). In this study, we aimed to identify baseline scoring distributions of the FAM^TM in a nonhospitalized subgroup, as well as assess the correlation of the FAM^TM to discharge disposition and compare it to the SPMSQ in inpatients.

METHODS

FAM^TM Application

The FAM^TM application is a bedside tool for working memory assessment developed for the iPhone mobile operating system (Apple Inc., Cupertino, CA) and presented on an iPad mini (Apple). The application interface displays 4 colored rectangles individually labeled with a number (see Supporting Figure 1 in the online version of this article). The testing portion of the application presents a sequence of numbered rectangles, illuminated 1 at a time in random order. Subjects are prompted first to watch and remember the sequence and then repeat the sequence by touching the screen within each numbered rectangle. Successful reproduction of the sequence is followed by a distinct and longer sequence, whereas unsuccessful attempts are followed by a shorter sequence. The final FAM^TM score corresponds to the longest sequence of rectangles successfully repeated by the subject.

Figure 1

RESULTS

A total of 931 subjects were enrolled in the study. In the nonhospitalized subgroup, 651 consented to study participation and 612 were included in final analysis. Subjects were excluded if they started but did not complete the application (n = 36) or were under the age of 18 years (n = 3). Of the 363 hospitalized subjects approached for enrollment, 319 were included in the final analysis. Subjects were excluded if they refused to participate (n = 23), were under the age of 18 (n = 2), had technical failures (n = 5), or had physical or visual limitations that precluded them from participation (n = 14). Within the hospitalized subgroup, 268 subjects were discharged home (85%). The table displays demographics and score distributions by subgroup.1

The median FAM^TM score for the combined study population was 5 (interquartile range [IQR] 36), and median time to completion was 55 seconds (IQR 4567 seconds). A graded reduction was found in the FAM^TM score for all stepwise comparisons between nonhospitalized subjects, hospitalized subjects discharged home, and hospitalized subjects not discharged home (median 5 [IQR 47] vs 5 [IQR 36] vs 3 [IQR 15]; P < 0.001 for all pairwise comparisons). The AUC for the FAM^TM predicting discharge disposition (home vs not) was 0.66 (95% confidence interval [CI]: 0.58‐0.74]. After adjusting for confounders, higher FAM^TM scores were independently associated with not being hospitalized, being discharged home, higher levels of education, younger age, and white race (see Supporting Table 1 in the online version of this article). Additionally, in the hospitalized subgroup, decreasing FAM^TM score was significantly correlated with increasing errors on the SPMSQ (Spearman = 0.27, P < 0.001), whereas the GCS score was not correlated with the SPMSQ (Spearman = 0.05, P = 0.40) (Figure 1).

DISCUSSION

We demonstrated the utility of a rapid and accurate mobile application for assessment of mental status. The FAM^TM was able to be quickly administered with a median time to completion of approximately 1 minute. The ability to detect mild alterations in mental status was shown through concurrent validity by FAM^TM correlation with the SPMSQ and predictive validity with the association between the FAM^TM and discharge disposition. Our study highlights the potential for the FAM^TM to be used as a sensitive marker of AMS.

The novel design of the FAM^TM presents unique advantages compared to current mental status testing. First, the FAM^TM could allow patients with hearing impairment or language barriers to complete a mental status assessment. Additionally, the approximately 1‐minute median time to completion is much faster than other established mental status assessments including the SPMSQ (510 minutes). Compared to the SPMSQ taking 5 minutes, in a 400‐bed hospital, taken once per nursing shift, the FAM^TM would save approximately 20,000 hours and 10 nursing full‐time equivalents per year.[5] Finally, many current mental status tests such as the Confusion Assessment Model utilize subjective mental status assessments.[2] However, the FAM^TM is designed to be conducted through self‐assessment and, thus, could theoretically be free of observer bias. This potential for self‐administration expands beyond other proposed alternative testing mechanisms of the AMS such as ultrabrief assessments that include items such as asking subjects the months of the year backwards, and what is the day of the week?, and assessing arousal.[12, 13, 14]

In research settings and commonly in hospitals, the GCS and AVPU are used clinically for mental status assessment of hospitalized patients.[6, 15] However, similar to previous literature, our study found that the vast majority of hospitalized patients were defined as neurologically intact by the GCS, which is the more accurate predictor of the 2.[7] One major strength of the FAM^TM was that it identified an extensive gradation of scores for patients previously labeled as merely alert, providing greater resolution than the GCS in quantifying mental status.

One of the key benefits of the FAM^TM is that it can be measured longitudinally over the course of a patient's hospital stay. Therefore, once a baseline FAM^TM score is established, variation from the patient's personal baseline could indicate mental status deterioration, which would not be affected by the patient's demographics, health status, or underlying neurocognitive deficits.

There were important limitations to this study. First, limited generalizability of these data may exist due to the single‐center setting and patient population. However, this initial study provides pilot data for further expansion into the potential broad applicability of the FAM^TM to other patient populations and settings. Additionally, the cost of large‐scale implementation of the FAM^TM is unknown and was beyond the scope of this pilot study. However, to reduce costs, the FAM^TM technology could be integrated into existing hospital technology infrastructure. Finally, the scope of this study prevented a complete assessment of all validity measures or comparison to other mental status assessments such as the digit span or serial sevens tests. However, predictive and concurrent validity were assessed with comparison by discharge disposition, SPMSQ, and GCS scores.

In conclusion, this pilot study identifies the FAM^TM application as a potentially clinically useful, novel, rapid, and feasible assessment tool of mental status in a general medicine inpatient setting.

Altered mental status (AMS) is a complex spectrum of cognitive deficits that includes orientation, memory, language, visuospatial ability, and perception.[1] The clinical definitions of both delirium and dementia include AMS as a hallmark clinical prerequisite. Regardless of etiology, this broader AMS definition is particularly salient in the hospital setting, where AMS is present in up to 60% of inpatients and is associated with longer hospital stay as well as increased morbidity and mortality.[2, 3] Not surprisingly, due to the complexity of identifying and assessing changes in mental status, clinically relevant AMS is often undetected among inpatients.[2] However, when detected, the most common causes of AMS (infection, polypharmacy, and pain) are treatable, suggesting that early AMS identification could alert clinicians to early signs of clinical decompensation, potentially improving clinical outcomes.[4]

Because rapid and systemic clinical detection of AMS is limited by the complexity of mental status, a number of assessments have been created, each with their own advantages, limitations, and target populations. These assessments are often limited by time‐intensive administration, subjectivity of mental status assessment, and lack of sensitivity in general medicine patients. Time‐intensive measures, such as the Short Portable Mental Status Questionnaire (SPMSQ) have utility in the research setting, whereas current common clinical risk stratification tools (eg, National Early Warning Score) utilize simpler measures such as the Alert, Voice, Pain, Unresponsive (AVPU) and Glasgow Coma Scale (GCS) as measures of mental status.[2, 5, 6, 7, 8, 9]

To address the need for a brief, clinically feasible, accurate tool in clinical detection of AMS, our group developed a mobile application for working memory testing, the Functional Assessment of Mentation (FAM^TM). In this study, we aimed to identify baseline scoring distributions of the FAM^TM in a nonhospitalized subgroup, as well as assess the correlation of the FAM^TM to discharge disposition and compare it to the SPMSQ in inpatients.

METHODS

FAM^TM Application

The FAM^TM application is a bedside tool for working memory assessment developed for the iPhone mobile operating system (Apple Inc., Cupertino, CA) and presented on an iPad mini (Apple). The application interface displays 4 colored rectangles individually labeled with a number (see Supporting Figure 1 in the online version of this article). The testing portion of the application presents a sequence of numbered rectangles, illuminated 1 at a time in random order. Subjects are prompted first to watch and remember the sequence and then repeat the sequence by touching the screen within each numbered rectangle. Successful reproduction of the sequence is followed by a distinct and longer sequence, whereas unsuccessful attempts are followed by a shorter sequence. The final FAM^TM score corresponds to the longest sequence of rectangles successfully repeated by the subject.

Figure 1

RESULTS

A total of 931 subjects were enrolled in the study. In the nonhospitalized subgroup, 651 consented to study participation and 612 were included in final analysis. Subjects were excluded if they started but did not complete the application (n = 36) or were under the age of 18 years (n = 3). Of the 363 hospitalized subjects approached for enrollment, 319 were included in the final analysis. Subjects were excluded if they refused to participate (n = 23), were under the age of 18 (n = 2), had technical failures (n = 5), or had physical or visual limitations that precluded them from participation (n = 14). Within the hospitalized subgroup, 268 subjects were discharged home (85%). The table displays demographics and score distributions by subgroup.1

The median FAM^TM score for the combined study population was 5 (interquartile range [IQR] 36), and median time to completion was 55 seconds (IQR 4567 seconds). A graded reduction was found in the FAM^TM score for all stepwise comparisons between nonhospitalized subjects, hospitalized subjects discharged home, and hospitalized subjects not discharged home (median 5 [IQR 47] vs 5 [IQR 36] vs 3 [IQR 15]; P < 0.001 for all pairwise comparisons). The AUC for the FAM^TM predicting discharge disposition (home vs not) was 0.66 (95% confidence interval [CI]: 0.58‐0.74]. After adjusting for confounders, higher FAM^TM scores were independently associated with not being hospitalized, being discharged home, higher levels of education, younger age, and white race (see Supporting Table 1 in the online version of this article). Additionally, in the hospitalized subgroup, decreasing FAM^TM score was significantly correlated with increasing errors on the SPMSQ (Spearman = 0.27, P < 0.001), whereas the GCS score was not correlated with the SPMSQ (Spearman = 0.05, P = 0.40) (Figure 1).

DISCUSSION

We demonstrated the utility of a rapid and accurate mobile application for assessment of mental status. The FAM^TM was able to be quickly administered with a median time to completion of approximately 1 minute. The ability to detect mild alterations in mental status was shown through concurrent validity by FAM^TM correlation with the SPMSQ and predictive validity with the association between the FAM^TM and discharge disposition. Our study highlights the potential for the FAM^TM to be used as a sensitive marker of AMS.

The novel design of the FAM^TM presents unique advantages compared to current mental status testing. First, the FAM^TM could allow patients with hearing impairment or language barriers to complete a mental status assessment. Additionally, the approximately 1‐minute median time to completion is much faster than other established mental status assessments including the SPMSQ (510 minutes). Compared to the SPMSQ taking 5 minutes, in a 400‐bed hospital, taken once per nursing shift, the FAM^TM would save approximately 20,000 hours and 10 nursing full‐time equivalents per year.[5] Finally, many current mental status tests such as the Confusion Assessment Model utilize subjective mental status assessments.[2] However, the FAM^TM is designed to be conducted through self‐assessment and, thus, could theoretically be free of observer bias. This potential for self‐administration expands beyond other proposed alternative testing mechanisms of the AMS such as ultrabrief assessments that include items such as asking subjects the months of the year backwards, and what is the day of the week?, and assessing arousal.[12, 13, 14]

In research settings and commonly in hospitals, the GCS and AVPU are used clinically for mental status assessment of hospitalized patients.[6, 15] However, similar to previous literature, our study found that the vast majority of hospitalized patients were defined as neurologically intact by the GCS, which is the more accurate predictor of the 2.[7] One major strength of the FAM^TM was that it identified an extensive gradation of scores for patients previously labeled as merely alert, providing greater resolution than the GCS in quantifying mental status.

One of the key benefits of the FAM^TM is that it can be measured longitudinally over the course of a patient's hospital stay. Therefore, once a baseline FAM^TM score is established, variation from the patient's personal baseline could indicate mental status deterioration, which would not be affected by the patient's demographics, health status, or underlying neurocognitive deficits.

There were important limitations to this study. First, limited generalizability of these data may exist due to the single‐center setting and patient population. However, this initial study provides pilot data for further expansion into the potential broad applicability of the FAM^TM to other patient populations and settings. Additionally, the cost of large‐scale implementation of the FAM^TM is unknown and was beyond the scope of this pilot study. However, to reduce costs, the FAM^TM technology could be integrated into existing hospital technology infrastructure. Finally, the scope of this study prevented a complete assessment of all validity measures or comparison to other mental status assessments such as the digit span or serial sevens tests. However, predictive and concurrent validity were assessed with comparison by discharge disposition, SPMSQ, and GCS scores.

In conclusion, this pilot study identifies the FAM^TM application as a potentially clinically useful, novel, rapid, and feasible assessment tool of mental status in a general medicine inpatient setting.

Altered mental status (AMS) is a complex spectrum of cognitive deficits that includes orientation, memory, language, visuospatial ability, and perception.[1] The clinical definitions of both delirium and dementia include AMS as a hallmark clinical prerequisite. Regardless of etiology, this broader AMS definition is particularly salient in the hospital setting, where AMS is present in up to 60% of inpatients and is associated with longer hospital stay as well as increased morbidity and mortality.[2, 3] Not surprisingly, due to the complexity of identifying and assessing changes in mental status, clinically relevant AMS is often undetected among inpatients.[2] However, when detected, the most common causes of AMS (infection, polypharmacy, and pain) are treatable, suggesting that early AMS identification could alert clinicians to early signs of clinical decompensation, potentially improving clinical outcomes.[4]

Because rapid and systemic clinical detection of AMS is limited by the complexity of mental status, a number of assessments have been created, each with their own advantages, limitations, and target populations. These assessments are often limited by time‐intensive administration, subjectivity of mental status assessment, and lack of sensitivity in general medicine patients. Time‐intensive measures, such as the Short Portable Mental Status Questionnaire (SPMSQ) have utility in the research setting, whereas current common clinical risk stratification tools (eg, National Early Warning Score) utilize simpler measures such as the Alert, Voice, Pain, Unresponsive (AVPU) and Glasgow Coma Scale (GCS) as measures of mental status.[2, 5, 6, 7, 8, 9]

To address the need for a brief, clinically feasible, accurate tool in clinical detection of AMS, our group developed a mobile application for working memory testing, the Functional Assessment of Mentation (FAM^TM). In this study, we aimed to identify baseline scoring distributions of the FAM^TM in a nonhospitalized subgroup, as well as assess the correlation of the FAM^TM to discharge disposition and compare it to the SPMSQ in inpatients.

METHODS

FAM^TM Application

The FAM^TM application is a bedside tool for working memory assessment developed for the iPhone mobile operating system (Apple Inc., Cupertino, CA) and presented on an iPad mini (Apple). The application interface displays 4 colored rectangles individually labeled with a number (see Supporting Figure 1 in the online version of this article). The testing portion of the application presents a sequence of numbered rectangles, illuminated 1 at a time in random order. Subjects are prompted first to watch and remember the sequence and then repeat the sequence by touching the screen within each numbered rectangle. Successful reproduction of the sequence is followed by a distinct and longer sequence, whereas unsuccessful attempts are followed by a shorter sequence. The final FAM^TM score corresponds to the longest sequence of rectangles successfully repeated by the subject.

Figure 1

RESULTS

A total of 931 subjects were enrolled in the study. In the nonhospitalized subgroup, 651 consented to study participation and 612 were included in final analysis. Subjects were excluded if they started but did not complete the application (n = 36) or were under the age of 18 years (n = 3). Of the 363 hospitalized subjects approached for enrollment, 319 were included in the final analysis. Subjects were excluded if they refused to participate (n = 23), were under the age of 18 (n = 2), had technical failures (n = 5), or had physical or visual limitations that precluded them from participation (n = 14). Within the hospitalized subgroup, 268 subjects were discharged home (85%). The table displays demographics and score distributions by subgroup.1

The median FAM^TM score for the combined study population was 5 (interquartile range [IQR] 36), and median time to completion was 55 seconds (IQR 4567 seconds). A graded reduction was found in the FAM^TM score for all stepwise comparisons between nonhospitalized subjects, hospitalized subjects discharged home, and hospitalized subjects not discharged home (median 5 [IQR 47] vs 5 [IQR 36] vs 3 [IQR 15]; P < 0.001 for all pairwise comparisons). The AUC for the FAM^TM predicting discharge disposition (home vs not) was 0.66 (95% confidence interval [CI]: 0.58‐0.74]. After adjusting for confounders, higher FAM^TM scores were independently associated with not being hospitalized, being discharged home, higher levels of education, younger age, and white race (see Supporting Table 1 in the online version of this article). Additionally, in the hospitalized subgroup, decreasing FAM^TM score was significantly correlated with increasing errors on the SPMSQ (Spearman = 0.27, P < 0.001), whereas the GCS score was not correlated with the SPMSQ (Spearman = 0.05, P = 0.40) (Figure 1).

DISCUSSION

We demonstrated the utility of a rapid and accurate mobile application for assessment of mental status. The FAM^TM was able to be quickly administered with a median time to completion of approximately 1 minute. The ability to detect mild alterations in mental status was shown through concurrent validity by FAM^TM correlation with the SPMSQ and predictive validity with the association between the FAM^TM and discharge disposition. Our study highlights the potential for the FAM^TM to be used as a sensitive marker of AMS.

The novel design of the FAM^TM presents unique advantages compared to current mental status testing. First, the FAM^TM could allow patients with hearing impairment or language barriers to complete a mental status assessment. Additionally, the approximately 1‐minute median time to completion is much faster than other established mental status assessments including the SPMSQ (510 minutes). Compared to the SPMSQ taking 5 minutes, in a 400‐bed hospital, taken once per nursing shift, the FAM^TM would save approximately 20,000 hours and 10 nursing full‐time equivalents per year.[5] Finally, many current mental status tests such as the Confusion Assessment Model utilize subjective mental status assessments.[2] However, the FAM^TM is designed to be conducted through self‐assessment and, thus, could theoretically be free of observer bias. This potential for self‐administration expands beyond other proposed alternative testing mechanisms of the AMS such as ultrabrief assessments that include items such as asking subjects the months of the year backwards, and what is the day of the week?, and assessing arousal.[12, 13, 14]

In research settings and commonly in hospitals, the GCS and AVPU are used clinically for mental status assessment of hospitalized patients.[6, 15] However, similar to previous literature, our study found that the vast majority of hospitalized patients were defined as neurologically intact by the GCS, which is the more accurate predictor of the 2.[7] One major strength of the FAM^TM was that it identified an extensive gradation of scores for patients previously labeled as merely alert, providing greater resolution than the GCS in quantifying mental status.

One of the key benefits of the FAM^TM is that it can be measured longitudinally over the course of a patient's hospital stay. Therefore, once a baseline FAM^TM score is established, variation from the patient's personal baseline could indicate mental status deterioration, which would not be affected by the patient's demographics, health status, or underlying neurocognitive deficits.

There were important limitations to this study. First, limited generalizability of these data may exist due to the single‐center setting and patient population. However, this initial study provides pilot data for further expansion into the potential broad applicability of the FAM^TM to other patient populations and settings. Additionally, the cost of large‐scale implementation of the FAM^TM is unknown and was beyond the scope of this pilot study. However, to reduce costs, the FAM^TM technology could be integrated into existing hospital technology infrastructure. Finally, the scope of this study prevented a complete assessment of all validity measures or comparison to other mental status assessments such as the digit span or serial sevens tests. However, predictive and concurrent validity were assessed with comparison by discharge disposition, SPMSQ, and GCS scores.

In conclusion, this pilot study identifies the FAM^TM application as a potentially clinically useful, novel, rapid, and feasible assessment tool of mental status in a general medicine inpatient setting.

Altered mental status (AMS), characterized by abnormal changes in a patient's arousal and/or cognition, is a significant predictor of hospital mortality.[1, 2, 3] Yet despite its prevalence[3, 4, 5] and importance, up to three‐quarters of AMS events go unrecognized by caregivers.[6, 7, 8] Acute changes in mental status, often caused by delirium in the hospitalized patient,[3] can present nonspecifically, making it difficult to detect and distinguish from other diagnoses such as depression or dementia.[7, 9] Further complicating the recognition of AMS, numerous and imprecise qualitative descriptors such as confused and alert and oriented are used in clinical practice to describe the mental status of patients.[10] Thus, more objective measures may result in improved detection of altered mental status and in earlier diagnostic and therapeutic interventions.

In critically ill patients, several scales have been widely adopted for quantifying mental status. The Richmond Agitation and Sedation Scale (RASS) was created to optimize sedation.[11] The Glasgow Coma Scale (GCS) was developed for head‐trauma patients[12] and is now a standardized assessment tool in intensive care units,[13] the emergency department,[14] and the prehospital setting.[15] In addition, a simplified scale, AVPU (Alert, responsive to Verbal stimuli, responsive to Painful stimuli, and Unresponsive) was initially used in the primary survey of trauma patients[16] but is now a common component of early‐warning scores and rapid response activation criteria, such as the Modified Early Warning Score (MEWS).[17, 18] In fact, in a systematic review of 72 distinct early‐warning scores, 89% of the scores used AVPU as the measure of mentation.[17] However, the utility of these 3 scales is not well established in the general‐ward setting. Our aim was therefore to compare the accuracies of AVPU, GCS, and RASS for predicting mortality in hospitalized general‐ward patients to provide insight into the accuracy of these different scores for clinical deterioration.

METHODS

RESULTS

During the study period, 313,577 complete GCS and 305,177 RASS scores were recorded in the electronic health record by nursing staff. A total of 26,806 (17,603 GCS and 9203 RASS) observations were excluded due to nonsimultaneous measurement of the other score, resulting in 295,974 paired mental‐status observations. These observations were obtained from 26,873 admissions in 17,660 unique patients, with a median MEWS at ward admission of 1 (IQR 11). The mean patient age was 57 years (SD 17), and 23% were surgical patients (Table 1). Patients spent a median 63.9 hours (IQR 26.7118.6) on the wards per admission and contributed a median of 3 paired observations (IQR 24) per day, with 91% of patients having at least 2 observations per day. A total of 417 (1.6%) general‐ward admissions resulted in death during the hospitalization, with 354 mental‐status observations occurring within 24 hours of a death. In addition, 26,618 (99.9%) admissions had at least 1 paired mental‐status observation within the last 24 hours of their ward stay.

AVPU was moderately correlated with GCS (Spearman's =0.56) (Figure 1a) and weakly correlated with RASS (Spearman's =0.28) (Figure 1b). GCS scores were also weakly correlated to RASS (Spearman's =0.13, P<0.001). Notably, AVPU mapped to distinct levels of GCS, with Alert associated with a median GCS total score of 15, Voice a score of 12, Pain a score of 8, and Unresponsive a score of 5. Abnormal mental‐status scores on any scale were associated with significantly higher odds of death within 24 hours than normal mental‐status scores (Table 2). This association was consistent within the 3 subscales of GCS and for scores in both the sedation (<0) and agitation (>0) ranges of RASS.

Figure 1

AVPU was the least accurate predictor of mortality (AUC 0.73 [95% confidence interval {CI}: 0.710.76]), whereas simultaneous use of GCS and RASS was the most accurate predictor (AUC 0.85 [95% CI: 0.820.87] (Figure 2). The accuracies of GCS and RASS were not significantly different from one another in the total study population (AUC 0.80 [95% CI: 0.770.83] and 0.82 [0.790.84], respectively, P=0.13). Ten‐fold cross‐validation to estimate the internal validity of the RASS model resulted in a lower AUC (0.78 [95% CI: 0.750.81]) for RASS as a predictor of 24‐hour mortality. Subgroup analysis indicated that RASS was more accurate than GCS in younger patients (<57 years old) and in surgical patients (Figure 3).

Figure 2

Figure 3

Removal of the 255 admissions missing a paired mental‐status observation within the last 24 hours of their ward stay resulted in no change in the AUC values. A sensitivity analysis for prediction of a combined secondary outcome of 24‐hour intensive care unit ICU transfer or cardiac arrest yielded lower AUCs for each mental‐status scale, with no change in the association among scales.

DISCUSSION

To our knowledge, this study is the first to compare the accuracies of AVPU, GCS, and RASS for predicting mortality in the general‐ward setting. Similar to McNarry and Goldhill, we demonstrated that AVPU scores mapped to distinct levels of GCS. Although our study reports the same median GCS scores of 15 and 8 for AVPU levels of Alert and Pain, respectively, we indicate slightly lower corresponding median GCS scores for AVPU scores of Voice (12 vs 13) and Unresponsive (5 vs 6) than their previous work.[21] We found that AVPU was the least accurate predictor of mortality within 24 hours of an observation, and the combination of GCS and RASS was the most accurate. RASS was at least as accurate a predictor for 24‐hour mortality in comparison to GCS total in the overall study population. However, the RASS score was the most accurate individual score in surgical and younger patients. These findings suggest that changing from the commonly used AVPU scale to the RASS and/or GCS would improve the prognostic ability of mental‐status assessments on the general wards.

Buist and colleagues have previously demonstrated altered mental status to be one of the strongest predictors of death on the wards. In that study, a GCS score of 3 and a decrease in GCS score by more than 2 points were independently associated with mortality (odds ratio 6.1 [95% CI: 3.111.8] and 5.5 [95% CI: 2.611.9], respectively).[22] We have also previously shown that after adjusting for vital signs, being unresponsive to pain was associated with a 4.5‐fold increase in the odds of death within 24 hours,[23]whereas Subbe and colleagues showed a relative risk ratio of 5.2 (95% CI: 1.518.1) for the combined endpoint of cardiac arrest, death at 60 days, or admission to the intensive care/high dependency unit.[19] In the current study, the magnitude of these associations was even stronger, with a GCS score <13 correlating with a 55‐fold increase in the odds of death, compared to a normal GCS, and not being alert being associated with a 33.8‐fold increase in the odds of death. This difference in magnitude is likely a product of the univariate nature of the current analysis, compared to both the Buist et al. and Churpek et al. studies, which adjusted for vital signs, thereby lessening the impact of any single predictor. Because this study was designed to compare mental‐status variables to one another for future model inclusion, and all the analyses were paired, confounding by additional predictors of death was not a concern.

One of the potential strengths of RASS over GCS and AVPU is its ability to measure agitation levels, in addition to depressed mentation, a feature that has been shown to be present in up to 60% of delirium episodes.[24] This may also explain why RASS was the most accurate predictor of mortality in our subset of younger patients and surgical patients, because hyperactive delirium is more common in younger and healthier patients, which surgical patients tend to be as compared to medical patients.[25, 26] In this study, we found negative RASS scores portending a worse prognosis than positive ones, which supports previous findings that hypoactive delirium had a higher association with mortality than hyperactive delirium at 6 months (hazard ratio 1.90 vs 1.37) and at 1 year (hazard ratio 1.60 vs 1.30) in elderly patients at postacute‐care facilities in 2 separate studies.[27, 28] However, a study of patients undergoing surgery for hip fracture found that patients with hyperactive delirium were more likely to die or be placed in a nursing home at 1 month follow‐up when compared to patients with purely hypoactive delirium (79% vs 32%, P=0.003).[29]

We found the assessment of RASS and GCS by ward nurses to be highly feasible. During the study period, nurses assessed mental status with the GCS and RASS scales at least once per 12‐hour shift in 91% of patients. GCS has been shown to be reliably and accurately recorded by experienced nurses (reliability coefficient=0.944 with 96.4% agreement with expert ratings).[30] RASS can take <30 seconds to administer, and in previous studies of the ICU setting has been shown to have over 94% nurse compliance for administration,[31] and good inter‐rater reliability (weighted kappa 0.66 and 0.89, respectively).[31, 32] Further, in a prior survey of 55 critical care nurses, 82% agreed that RASS was easy to score and clinically relevant.[31]

This study has several limitations. First, it was conducted in a single academic institution, which may limit generalizability to other hospitals. Second, baseline cognition and comorbidities were not available in the dataset, so we were unable to conduct additional subgroup analyses by these categories. However, we used age and hospital admission type as proxies. Third, the AVPU scores in this study were extracted from the Eye subset of the GCS scale, as AVPU was not directly assessed on our wards during the study period. Clinical assessment of mental status on the AVPU scale notes the presence of any active patient response (eg, eye opening, grunting, moaning, movement) to increasingly noxious stimuli. As such, our adaptation of AVPU using only eye‐opening criteria may underestimate the true number of patients correctly classified as alert, or responding to vocal/painful stimuli. However, a sensitivity analysis comparing directly assessed AVPU during a 3‐year period prior to the study implementation at our institution, and AVPU derived from the GCS Eye subscale for the study period, indicated no difference in predictive value for 24‐hour mortality. Fourth, we did not perform trend analyses for change from baseline mental status or evolution of AMS, which may more accurately predict 24‐hour mortality than discrete mental‐status observations. Finally, the 3 scales we compared differ in length, which may bias the AUC against AVPU, a 4‐point scale with a trapezoidal ROC curve compared to the smoother curve generated by the 15‐point GCS scale, for example. However, the lack of discrimination of the AVPU is the likely source of its lesser accuracy.

CONCLUSION

In the general‐ward setting, routine collection of GCS and RASS is feasible, and both are significantly more accurate for predicting mortality than the more commonly used AVPU scale. In addition, the combination of GCS and RASS has greater accuracy than any of the 3 individual scales. RASS may be particularly beneficial in the assessment of younger and/or surgical patients. Routine documentation and tracking of GCS and/or RASS by nurses may improve the detection of clinical deterioration in general‐ward patients. In addition, future early‐warning scores may benefit from the inclusion of GCS and/or RASS in lieu of AVPU.

Altered mental status (AMS), characterized by abnormal changes in a patient's arousal and/or cognition, is a significant predictor of hospital mortality.[1, 2, 3] Yet despite its prevalence[3, 4, 5] and importance, up to three‐quarters of AMS events go unrecognized by caregivers.[6, 7, 8] Acute changes in mental status, often caused by delirium in the hospitalized patient,[3] can present nonspecifically, making it difficult to detect and distinguish from other diagnoses such as depression or dementia.[7, 9] Further complicating the recognition of AMS, numerous and imprecise qualitative descriptors such as confused and alert and oriented are used in clinical practice to describe the mental status of patients.[10] Thus, more objective measures may result in improved detection of altered mental status and in earlier diagnostic and therapeutic interventions.

In critically ill patients, several scales have been widely adopted for quantifying mental status. The Richmond Agitation and Sedation Scale (RASS) was created to optimize sedation.[11] The Glasgow Coma Scale (GCS) was developed for head‐trauma patients[12] and is now a standardized assessment tool in intensive care units,[13] the emergency department,[14] and the prehospital setting.[15] In addition, a simplified scale, AVPU (Alert, responsive to Verbal stimuli, responsive to Painful stimuli, and Unresponsive) was initially used in the primary survey of trauma patients[16] but is now a common component of early‐warning scores and rapid response activation criteria, such as the Modified Early Warning Score (MEWS).[17, 18] In fact, in a systematic review of 72 distinct early‐warning scores, 89% of the scores used AVPU as the measure of mentation.[17] However, the utility of these 3 scales is not well established in the general‐ward setting. Our aim was therefore to compare the accuracies of AVPU, GCS, and RASS for predicting mortality in hospitalized general‐ward patients to provide insight into the accuracy of these different scores for clinical deterioration.

METHODS

RESULTS

During the study period, 313,577 complete GCS and 305,177 RASS scores were recorded in the electronic health record by nursing staff. A total of 26,806 (17,603 GCS and 9203 RASS) observations were excluded due to nonsimultaneous measurement of the other score, resulting in 295,974 paired mental‐status observations. These observations were obtained from 26,873 admissions in 17,660 unique patients, with a median MEWS at ward admission of 1 (IQR 11). The mean patient age was 57 years (SD 17), and 23% were surgical patients (Table 1). Patients spent a median 63.9 hours (IQR 26.7118.6) on the wards per admission and contributed a median of 3 paired observations (IQR 24) per day, with 91% of patients having at least 2 observations per day. A total of 417 (1.6%) general‐ward admissions resulted in death during the hospitalization, with 354 mental‐status observations occurring within 24 hours of a death. In addition, 26,618 (99.9%) admissions had at least 1 paired mental‐status observation within the last 24 hours of their ward stay.

AVPU was moderately correlated with GCS (Spearman's =0.56) (Figure 1a) and weakly correlated with RASS (Spearman's =0.28) (Figure 1b). GCS scores were also weakly correlated to RASS (Spearman's =0.13, P<0.001). Notably, AVPU mapped to distinct levels of GCS, with Alert associated with a median GCS total score of 15, Voice a score of 12, Pain a score of 8, and Unresponsive a score of 5. Abnormal mental‐status scores on any scale were associated with significantly higher odds of death within 24 hours than normal mental‐status scores (Table 2). This association was consistent within the 3 subscales of GCS and for scores in both the sedation (<0) and agitation (>0) ranges of RASS.

Figure 1

AVPU was the least accurate predictor of mortality (AUC 0.73 [95% confidence interval {CI}: 0.710.76]), whereas simultaneous use of GCS and RASS was the most accurate predictor (AUC 0.85 [95% CI: 0.820.87] (Figure 2). The accuracies of GCS and RASS were not significantly different from one another in the total study population (AUC 0.80 [95% CI: 0.770.83] and 0.82 [0.790.84], respectively, P=0.13). Ten‐fold cross‐validation to estimate the internal validity of the RASS model resulted in a lower AUC (0.78 [95% CI: 0.750.81]) for RASS as a predictor of 24‐hour mortality. Subgroup analysis indicated that RASS was more accurate than GCS in younger patients (<57 years old) and in surgical patients (Figure 3).

Figure 2

Figure 3

Removal of the 255 admissions missing a paired mental‐status observation within the last 24 hours of their ward stay resulted in no change in the AUC values. A sensitivity analysis for prediction of a combined secondary outcome of 24‐hour intensive care unit ICU transfer or cardiac arrest yielded lower AUCs for each mental‐status scale, with no change in the association among scales.

DISCUSSION

To our knowledge, this study is the first to compare the accuracies of AVPU, GCS, and RASS for predicting mortality in the general‐ward setting. Similar to McNarry and Goldhill, we demonstrated that AVPU scores mapped to distinct levels of GCS. Although our study reports the same median GCS scores of 15 and 8 for AVPU levels of Alert and Pain, respectively, we indicate slightly lower corresponding median GCS scores for AVPU scores of Voice (12 vs 13) and Unresponsive (5 vs 6) than their previous work.[21] We found that AVPU was the least accurate predictor of mortality within 24 hours of an observation, and the combination of GCS and RASS was the most accurate. RASS was at least as accurate a predictor for 24‐hour mortality in comparison to GCS total in the overall study population. However, the RASS score was the most accurate individual score in surgical and younger patients. These findings suggest that changing from the commonly used AVPU scale to the RASS and/or GCS would improve the prognostic ability of mental‐status assessments on the general wards.

Buist and colleagues have previously demonstrated altered mental status to be one of the strongest predictors of death on the wards. In that study, a GCS score of 3 and a decrease in GCS score by more than 2 points were independently associated with mortality (odds ratio 6.1 [95% CI: 3.111.8] and 5.5 [95% CI: 2.611.9], respectively).[22] We have also previously shown that after adjusting for vital signs, being unresponsive to pain was associated with a 4.5‐fold increase in the odds of death within 24 hours,[23]whereas Subbe and colleagues showed a relative risk ratio of 5.2 (95% CI: 1.518.1) for the combined endpoint of cardiac arrest, death at 60 days, or admission to the intensive care/high dependency unit.[19] In the current study, the magnitude of these associations was even stronger, with a GCS score <13 correlating with a 55‐fold increase in the odds of death, compared to a normal GCS, and not being alert being associated with a 33.8‐fold increase in the odds of death. This difference in magnitude is likely a product of the univariate nature of the current analysis, compared to both the Buist et al. and Churpek et al. studies, which adjusted for vital signs, thereby lessening the impact of any single predictor. Because this study was designed to compare mental‐status variables to one another for future model inclusion, and all the analyses were paired, confounding by additional predictors of death was not a concern.

One of the potential strengths of RASS over GCS and AVPU is its ability to measure agitation levels, in addition to depressed mentation, a feature that has been shown to be present in up to 60% of delirium episodes.[24] This may also explain why RASS was the most accurate predictor of mortality in our subset of younger patients and surgical patients, because hyperactive delirium is more common in younger and healthier patients, which surgical patients tend to be as compared to medical patients.[25, 26] In this study, we found negative RASS scores portending a worse prognosis than positive ones, which supports previous findings that hypoactive delirium had a higher association with mortality than hyperactive delirium at 6 months (hazard ratio 1.90 vs 1.37) and at 1 year (hazard ratio 1.60 vs 1.30) in elderly patients at postacute‐care facilities in 2 separate studies.[27, 28] However, a study of patients undergoing surgery for hip fracture found that patients with hyperactive delirium were more likely to die or be placed in a nursing home at 1 month follow‐up when compared to patients with purely hypoactive delirium (79% vs 32%, P=0.003).[29]

We found the assessment of RASS and GCS by ward nurses to be highly feasible. During the study period, nurses assessed mental status with the GCS and RASS scales at least once per 12‐hour shift in 91% of patients. GCS has been shown to be reliably and accurately recorded by experienced nurses (reliability coefficient=0.944 with 96.4% agreement with expert ratings).[30] RASS can take <30 seconds to administer, and in previous studies of the ICU setting has been shown to have over 94% nurse compliance for administration,[31] and good inter‐rater reliability (weighted kappa 0.66 and 0.89, respectively).[31, 32] Further, in a prior survey of 55 critical care nurses, 82% agreed that RASS was easy to score and clinically relevant.[31]

This study has several limitations. First, it was conducted in a single academic institution, which may limit generalizability to other hospitals. Second, baseline cognition and comorbidities were not available in the dataset, so we were unable to conduct additional subgroup analyses by these categories. However, we used age and hospital admission type as proxies. Third, the AVPU scores in this study were extracted from the Eye subset of the GCS scale, as AVPU was not directly assessed on our wards during the study period. Clinical assessment of mental status on the AVPU scale notes the presence of any active patient response (eg, eye opening, grunting, moaning, movement) to increasingly noxious stimuli. As such, our adaptation of AVPU using only eye‐opening criteria may underestimate the true number of patients correctly classified as alert, or responding to vocal/painful stimuli. However, a sensitivity analysis comparing directly assessed AVPU during a 3‐year period prior to the study implementation at our institution, and AVPU derived from the GCS Eye subscale for the study period, indicated no difference in predictive value for 24‐hour mortality. Fourth, we did not perform trend analyses for change from baseline mental status or evolution of AMS, which may more accurately predict 24‐hour mortality than discrete mental‐status observations. Finally, the 3 scales we compared differ in length, which may bias the AUC against AVPU, a 4‐point scale with a trapezoidal ROC curve compared to the smoother curve generated by the 15‐point GCS scale, for example. However, the lack of discrimination of the AVPU is the likely source of its lesser accuracy.

CONCLUSION

In the general‐ward setting, routine collection of GCS and RASS is feasible, and both are significantly more accurate for predicting mortality than the more commonly used AVPU scale. In addition, the combination of GCS and RASS has greater accuracy than any of the 3 individual scales. RASS may be particularly beneficial in the assessment of younger and/or surgical patients. Routine documentation and tracking of GCS and/or RASS by nurses may improve the detection of clinical deterioration in general‐ward patients. In addition, future early‐warning scores may benefit from the inclusion of GCS and/or RASS in lieu of AVPU.

Altered mental status (AMS), characterized by abnormal changes in a patient's arousal and/or cognition, is a significant predictor of hospital mortality.[1, 2, 3] Yet despite its prevalence[3, 4, 5] and importance, up to three‐quarters of AMS events go unrecognized by caregivers.[6, 7, 8] Acute changes in mental status, often caused by delirium in the hospitalized patient,[3] can present nonspecifically, making it difficult to detect and distinguish from other diagnoses such as depression or dementia.[7, 9] Further complicating the recognition of AMS, numerous and imprecise qualitative descriptors such as confused and alert and oriented are used in clinical practice to describe the mental status of patients.[10] Thus, more objective measures may result in improved detection of altered mental status and in earlier diagnostic and therapeutic interventions.

In critically ill patients, several scales have been widely adopted for quantifying mental status. The Richmond Agitation and Sedation Scale (RASS) was created to optimize sedation.[11] The Glasgow Coma Scale (GCS) was developed for head‐trauma patients[12] and is now a standardized assessment tool in intensive care units,[13] the emergency department,[14] and the prehospital setting.[15] In addition, a simplified scale, AVPU (Alert, responsive to Verbal stimuli, responsive to Painful stimuli, and Unresponsive) was initially used in the primary survey of trauma patients[16] but is now a common component of early‐warning scores and rapid response activation criteria, such as the Modified Early Warning Score (MEWS).[17, 18] In fact, in a systematic review of 72 distinct early‐warning scores, 89% of the scores used AVPU as the measure of mentation.[17] However, the utility of these 3 scales is not well established in the general‐ward setting. Our aim was therefore to compare the accuracies of AVPU, GCS, and RASS for predicting mortality in hospitalized general‐ward patients to provide insight into the accuracy of these different scores for clinical deterioration.

METHODS

RESULTS

During the study period, 313,577 complete GCS and 305,177 RASS scores were recorded in the electronic health record by nursing staff. A total of 26,806 (17,603 GCS and 9203 RASS) observations were excluded due to nonsimultaneous measurement of the other score, resulting in 295,974 paired mental‐status observations. These observations were obtained from 26,873 admissions in 17,660 unique patients, with a median MEWS at ward admission of 1 (IQR 11). The mean patient age was 57 years (SD 17), and 23% were surgical patients (Table 1). Patients spent a median 63.9 hours (IQR 26.7118.6) on the wards per admission and contributed a median of 3 paired observations (IQR 24) per day, with 91% of patients having at least 2 observations per day. A total of 417 (1.6%) general‐ward admissions resulted in death during the hospitalization, with 354 mental‐status observations occurring within 24 hours of a death. In addition, 26,618 (99.9%) admissions had at least 1 paired mental‐status observation within the last 24 hours of their ward stay.

AVPU was moderately correlated with GCS (Spearman's =0.56) (Figure 1a) and weakly correlated with RASS (Spearman's =0.28) (Figure 1b). GCS scores were also weakly correlated to RASS (Spearman's =0.13, P<0.001). Notably, AVPU mapped to distinct levels of GCS, with Alert associated with a median GCS total score of 15, Voice a score of 12, Pain a score of 8, and Unresponsive a score of 5. Abnormal mental‐status scores on any scale were associated with significantly higher odds of death within 24 hours than normal mental‐status scores (Table 2). This association was consistent within the 3 subscales of GCS and for scores in both the sedation (<0) and agitation (>0) ranges of RASS.

Figure 1

AVPU was the least accurate predictor of mortality (AUC 0.73 [95% confidence interval {CI}: 0.710.76]), whereas simultaneous use of GCS and RASS was the most accurate predictor (AUC 0.85 [95% CI: 0.820.87] (Figure 2). The accuracies of GCS and RASS were not significantly different from one another in the total study population (AUC 0.80 [95% CI: 0.770.83] and 0.82 [0.790.84], respectively, P=0.13). Ten‐fold cross‐validation to estimate the internal validity of the RASS model resulted in a lower AUC (0.78 [95% CI: 0.750.81]) for RASS as a predictor of 24‐hour mortality. Subgroup analysis indicated that RASS was more accurate than GCS in younger patients (<57 years old) and in surgical patients (Figure 3).

Figure 2

Figure 3

Removal of the 255 admissions missing a paired mental‐status observation within the last 24 hours of their ward stay resulted in no change in the AUC values. A sensitivity analysis for prediction of a combined secondary outcome of 24‐hour intensive care unit ICU transfer or cardiac arrest yielded lower AUCs for each mental‐status scale, with no change in the association among scales.

DISCUSSION

To our knowledge, this study is the first to compare the accuracies of AVPU, GCS, and RASS for predicting mortality in the general‐ward setting. Similar to McNarry and Goldhill, we demonstrated that AVPU scores mapped to distinct levels of GCS. Although our study reports the same median GCS scores of 15 and 8 for AVPU levels of Alert and Pain, respectively, we indicate slightly lower corresponding median GCS scores for AVPU scores of Voice (12 vs 13) and Unresponsive (5 vs 6) than their previous work.[21] We found that AVPU was the least accurate predictor of mortality within 24 hours of an observation, and the combination of GCS and RASS was the most accurate. RASS was at least as accurate a predictor for 24‐hour mortality in comparison to GCS total in the overall study population. However, the RASS score was the most accurate individual score in surgical and younger patients. These findings suggest that changing from the commonly used AVPU scale to the RASS and/or GCS would improve the prognostic ability of mental‐status assessments on the general wards.

Buist and colleagues have previously demonstrated altered mental status to be one of the strongest predictors of death on the wards. In that study, a GCS score of 3 and a decrease in GCS score by more than 2 points were independently associated with mortality (odds ratio 6.1 [95% CI: 3.111.8] and 5.5 [95% CI: 2.611.9], respectively).[22] We have also previously shown that after adjusting for vital signs, being unresponsive to pain was associated with a 4.5‐fold increase in the odds of death within 24 hours,[23]whereas Subbe and colleagues showed a relative risk ratio of 5.2 (95% CI: 1.518.1) for the combined endpoint of cardiac arrest, death at 60 days, or admission to the intensive care/high dependency unit.[19] In the current study, the magnitude of these associations was even stronger, with a GCS score <13 correlating with a 55‐fold increase in the odds of death, compared to a normal GCS, and not being alert being associated with a 33.8‐fold increase in the odds of death. This difference in magnitude is likely a product of the univariate nature of the current analysis, compared to both the Buist et al. and Churpek et al. studies, which adjusted for vital signs, thereby lessening the impact of any single predictor. Because this study was designed to compare mental‐status variables to one another for future model inclusion, and all the analyses were paired, confounding by additional predictors of death was not a concern.

One of the potential strengths of RASS over GCS and AVPU is its ability to measure agitation levels, in addition to depressed mentation, a feature that has been shown to be present in up to 60% of delirium episodes.[24] This may also explain why RASS was the most accurate predictor of mortality in our subset of younger patients and surgical patients, because hyperactive delirium is more common in younger and healthier patients, which surgical patients tend to be as compared to medical patients.[25, 26] In this study, we found negative RASS scores portending a worse prognosis than positive ones, which supports previous findings that hypoactive delirium had a higher association with mortality than hyperactive delirium at 6 months (hazard ratio 1.90 vs 1.37) and at 1 year (hazard ratio 1.60 vs 1.30) in elderly patients at postacute‐care facilities in 2 separate studies.[27, 28] However, a study of patients undergoing surgery for hip fracture found that patients with hyperactive delirium were more likely to die or be placed in a nursing home at 1 month follow‐up when compared to patients with purely hypoactive delirium (79% vs 32%, P=0.003).[29]

We found the assessment of RASS and GCS by ward nurses to be highly feasible. During the study period, nurses assessed mental status with the GCS and RASS scales at least once per 12‐hour shift in 91% of patients. GCS has been shown to be reliably and accurately recorded by experienced nurses (reliability coefficient=0.944 with 96.4% agreement with expert ratings).[30] RASS can take <30 seconds to administer, and in previous studies of the ICU setting has been shown to have over 94% nurse compliance for administration,[31] and good inter‐rater reliability (weighted kappa 0.66 and 0.89, respectively).[31, 32] Further, in a prior survey of 55 critical care nurses, 82% agreed that RASS was easy to score and clinically relevant.[31]

This study has several limitations. First, it was conducted in a single academic institution, which may limit generalizability to other hospitals. Second, baseline cognition and comorbidities were not available in the dataset, so we were unable to conduct additional subgroup analyses by these categories. However, we used age and hospital admission type as proxies. Third, the AVPU scores in this study were extracted from the Eye subset of the GCS scale, as AVPU was not directly assessed on our wards during the study period. Clinical assessment of mental status on the AVPU scale notes the presence of any active patient response (eg, eye opening, grunting, moaning, movement) to increasingly noxious stimuli. As such, our adaptation of AVPU using only eye‐opening criteria may underestimate the true number of patients correctly classified as alert, or responding to vocal/painful stimuli. However, a sensitivity analysis comparing directly assessed AVPU during a 3‐year period prior to the study implementation at our institution, and AVPU derived from the GCS Eye subscale for the study period, indicated no difference in predictive value for 24‐hour mortality. Fourth, we did not perform trend analyses for change from baseline mental status or evolution of AMS, which may more accurately predict 24‐hour mortality than discrete mental‐status observations. Finally, the 3 scales we compared differ in length, which may bias the AUC against AVPU, a 4‐point scale with a trapezoidal ROC curve compared to the smoother curve generated by the 15‐point GCS scale, for example. However, the lack of discrimination of the AVPU is the likely source of its lesser accuracy.

CONCLUSION

In the general‐ward setting, routine collection of GCS and RASS is feasible, and both are significantly more accurate for predicting mortality than the more commonly used AVPU scale. In addition, the combination of GCS and RASS has greater accuracy than any of the 3 individual scales. RASS may be particularly beneficial in the assessment of younger and/or surgical patients. Routine documentation and tracking of GCS and/or RASS by nurses may improve the detection of clinical deterioration in general‐ward patients. In addition, future early‐warning scores may benefit from the inclusion of GCS and/or RASS in lieu of AVPU.