Confusion Assessment Method Accurately Screens for Hepatic Encephalopathy and Predicts Short-term Mortality in Hospitalized Patients with Cirrhosis

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Desai, Devika Gandhi, Chenjia Xu, Marwan Ghabril, Lauren Nephew, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1809097/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background: Hepatic encephalopathy (HE), a subtype of delirium, is common in cirrhosis and associated with poor outcomes. Yet, objective bedside screening tools for HE are lacking. Objective: We examined the relationship between an established screening tool for delirium, Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and established HE diagnostic tools as well as outcomes. Methods: Prospectively enrolled adults with cirrhosis who completed the CAM-ICU from 6/2014-6/2018 were followed for 90 days. Blinded provider-assigned West Haven Criteria (WHC) and other measures of cognitive function were collected. Logistic regression was used to test associations between CAM-ICU status and outcomes. Mortality prediction by CAM-ICU status was assessed using Area under the Receiver Operating Characteristics curves (AUROC). Results: Of 469 participants, 11% were CAM-ICU(+), 55% were male and 94% were White. Most patients were Childs-Pugh class C (59%). CAM-ICU had excellent agreement with WHC (Kappa=0.79). CAM-ICU(+) participants had similar demographic features to those CAM-ICU(-), but had higher MELD (25 vs. 19, p<0.0001), were more often admitted to the ICU (28% vs. 7%, p<0.0001), and were more likely to be admitted for HE and infection. CAM-ICU(+) participants had higher mortality (inpatient:37% vs. 3%, 30-day:51% vs. 11%, 90-day:63% vs. 23%, p<0.001). CAM-ICU status predicted mortality with AUROC of 0.85, 0.82 and 0.77 for inpatient, 30-day and 90-day mortality, respectively. Conclusions: CAM-ICU has excellent agreement with WHC and identifies a hospitalized cirrhosis cohort with high short-term mortality. Unlike WHC, CAM-ICU can be administered by any team member making it an ideal tool to identify HE. delirium hepatic encephalopathy cirrhosis Figures Figure 1 Figure 2 Introduction Delirium is a manifestation of acute brain dysfunction characterized by a wide range of neuropsychiatric abnormalities including confusion, disorientation, and hallucinations (Deksnytė et al. 2012, 2013). A subtype of delirium, hepatic encephalopathy (HE), a well-studied complication of cirrhosis that also encompasses a range of neuropsychiatric impairment from subtle personality changes to coma (Ferenci et al. 2002, 2013, Rosenberg et al. 2013, Vilstrup et al. 2014, Amodio 2018 ). Delirium is as an independent predictor of short term mortality and longer length of stay in hospitalized patients leading many hospitals to routinely screen for delirium (Ely et al. 2004). Like delirium, HE is often precipitated by infections, electrolyte disturbances, and volume imbalances and is associated with significant morbidity and mortality as well as healthcare expenditures (Stepanova et al. 2012, Patidar et al. 2014, Vilstrup et al. 2014). The gold standard tool for diagnosing and quantifying HE at the bedside is the West Haven criteria (WHC) which classifies the severity of HE on a scale of 0–4. Use of WHC are limited by lack of specific definitions for each stage and need for expertise prior to assessment, making the criteria subjective with high interobserver variability (Cordoba 2011, Vilstrup et al. 2014). Due to the overlapping features of delirium and HE, more objective screening tools for delirium may be particularly valuable in patients with cirrhosis (Vilstrup et al. 2014). Among the various delirium screening tools, the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) is a simple 4-item, objective, validated tool that aids healthcare workers in quickly and reliably diagnosing delirium (Ely et al. 2001). Due to its excellent performance characteristics, and reliability, CAM-ICU is recommended in more than 30 clinical practice guidelines, used in a variety of clinical settings and translated into 20 languages leading to worldwide use (Patel et al. 2009, Guenther et al. 2010, Wong et al. 2010, Gusmao-Flores et al. 2012). Importantly, CAM-ICU can be administered accurately by nursing staff in approximately 1 minute (Guenther et al. 2010). Despite the wide-spread use of CAM-ICU, it has been understudied in patients with cirrhosis (Cordoba 2011, Orman et al. 2015). In this prospective study, we aimed to examine the relationship between CAM-ICU status and short-term outcomes in hospitalized patients with cirrhosis. We also examined the relationship between CAM-ICU and previously established beside tools for HE diagnosis including WHC. Methods Study Design This analysis uses data from adults with cirrhosis (age ≥ 18) hospitalized at Indiana University Hospital between June 2014 and June 2018 who were prospectively enrolled during their hospitalization and followed for 90 days as previously described (Orman et al. 2021). Those in the study cohort with at least one assessment with the Richmond Agitation Sedation Scale (RASS) and/or the CAM-ICU during their hospitalization were included in this analysis (n = 469). Cirrhosis diagnosis was based on the presence of liver histology or on characteristic clinical, laboratory, and radiologic findings. Patients were excluded if they had prior solid organ transplant or were unable to provide informed consent. The study was approved by the Indiana University Institutional Review Board. Informed consent was obtained from all individual participants included in the study. Variables Measures of Cognition Patients were first assessed for level of sedation using the Richmond Agitation-Sedation Scale (RASS, Supplementary Fig. 1 ) (Sessler et al. 2002). Participants with a RASS score of − 4 (no response to voice, but movement or eye opening to physical stimulation) or − 5 (no response to voice or physical stimulation) were deemed comatose and ineligible for further assessment with CAM-ICU. For those eligible, assessment using CAM-ICU was completed ( Supplementary Fig. 1 ). Assessments were made daily by research staff. Blinded daily provider-assigned WHC was also recorded with WHC ≥ 2 defined as HE (Vilstrup et al. 2014). On the day of enrollment, participants with WHC of 0 or 1 (n = 415) also completed additional, previously established, assessments of HE: Clinical Hepatic Encephalopathy Staging Scale (CHESS), Modified-orientation log (MO-log), and Number Connection Test A (NCT). These scales were scored or timed as previously described (Amodio et al. 1999 , Ortiz et al. 2007, Salam et al. 2012). Demographic and Clinical Variables Demographic data, social history, cirrhosis etiology, presence of cirrhosis complications such as hepatocellular carcinoma, varices, ascites, prior HE, and Charlson Comorbidity Index (CCI) were retrieved from the electronic medical record. During the hospitalization, reason for admission, presence and type of infections, and laboratory studies completed at the time of admission were recorded. Child-Pugh Class and Model for End-stage liver disease (MELD) score were also calculated. Outcomes The primary outcomes were inpatient, 30-day, and 90-day mortality. 30-day readmission and length of stay were also assessed. Statistical Analysis Baseline characteristics were compared between two groups of subjects based on RASS/CAM-ICU status using Pearson’s chi-squared test or Fisher’s exact test for categorical variables, t-test for continuous variables and Wilcoxon Rank-Sum test for continuous skewed data. Concurrent validity of RASS/CAM-ICU was established through several methods. First, we compared RASS/CAM-ICU status to WHC using the agreement statistic as well as the sensitivity and specificity of HE by RASS/CAM-ICU to diagnose hepatic encephalopathy using WHC ≥ 2 as the gold standard for HE diagnosis. In addition, performance on the CHESS, MO-Log, and NCT were compared by RASS/CAM-ICU status using Wilcoxon Rank-Sum test. Logistic regression models were used to assess the association between clinical characteristics, RASS/CAM-ICU status or WHC and mortality outcomes. Variables that have a p-value < 0.1 in univariate models were considered potential confounders and added to the multivariate models. In addition, age and h/o HE were included in the models due to clinical relevance. We report the unadjusted and multivariate models testing the association between RASS/CAM-ICU status or WHC ≥ 2 and mortality outcomes. The Area under the Receiver Operating Characteristics (AUROC) curves was estimated to assess the predictability of the models. All analyses were conducted using SAS v9.4. Results Study Participant Characteristics Of 469 study participants, 51 (11%) were RASS/CAM-ICU positive (RASS=-4/-5: n = 6, CAM-ICU(+): n = 45) at some point during their hospitalization. Demographic and clinical characteristics of the study cohort are presented in Table 1 by RASS/CAM-ICU status. Of all enrolled participants, 55% were male and 94% were white. The most common etiologies of cirrhosis were non-alcoholic steatohepatitis (33%), alcohol (28%), and Hepatitis C (16%). Most participants were Childs-Pugh class C (59%). There were no significant differences in age, sex, race, alcohol use, insurance status, marital status, employment status, cirrhosis etiology, cirrhosis related complications including history of hepatic encephalopathy, and CCI between the two groups. There was a trend towards lower education level in RASS/CAM-ICU(+) individuals compared to those without delirium (p = 0.062). The average MELD score of participants who were RASS/CAM-ICU(+) was higher compared to those who were RASS/CAM-ICU(-) (25, SD 9 vs. 19 SD 7, p < 0.0001) and RASS/CAM-ICU(+) individuals tended to have a higher Child-Pugh class (class C 60% vs. 76%, p = 0.0878). RASS/CAM-ICU(+) participants were also more likely to be in ICU at the time of admission than those who were RASS/CAM-ICU(-) (27% vs. 8%, p < .0001). The reasons for admission differed by RASS/CAM-ICU status. Encephalopathy and infection were a more common reasons for admission in the RASS/CAM-ICU(+) group vs. RASS/CAM-ICU(-) group (41% vs. 25% and 16% vs. 7%, respectively). In contrast, RASS/CAM-ICU(+) individuals were less likely to be admitted for GI bleeding (6% vs. 16%) or ascites/volume overload (6% vs. 21%, p = 0.0021). Table 1 Demographics and Clinical Characteristics of study participants with and without delirium/coma as measured by RASS/CAM-ICU RASS/CAM-ICU Negative N = 418 RASS/CAM-ICU Positive N = 51 p-value Age (mean, SD) 58 (10.8) 56.5 (11.1) 0.3454 Sex, %male 229 (54.8%) 29 (56.9%) 0.7782 White Race % 393 (94%) 49 (96.1%) 0.5511 Ongoing Alcohol Use 48 (11.6%) 10 (19.6%) 0.1006 Insurance Status 0.3044 Private 114 (27.3%) 10 (19.6%) Medicare 178 (42.6%) 22 (43.1%) Medicaid 116 (27.8%) 16 (31.4%) Other 10 (2.4%) 3 (5.9%) Married 240 (57.4%) 34 (66.7%) 0.2057 Education 0.0616 HS and < HS 212 (51.2%) 34 (68%) Some College 135 (32.6%) 9 (18%) College degree or above 67 (16.2%) 7 (14%) Employment Status 0.2453 Unemployed 227 (54.3%) 32 (62.7%) Employed 68 (16.3%) 7 (13.7%) Retired 64 (15.3%) 3 (5.9%) Disabled 59 (14.1%) 9 (17.6%) Charlson Comorbidity Index^ 6.8 (2.3) 7.3 (2.5) 0.1044 Cirrhosis Characteristics Cirrhosis Etiology 0.5858 Alcohol 116 (27.8%) 16 (31.4%) Hepatitis C 65 (15.6%) 10 (19.6%) Hepatitis C + Alcohol 34 (8.1%) 2 (3.9%) NASH 135 (32.3%) 18 (35.3%) Other 68 (16.3%) 5 (9.8%) MELD^ 18.9 (7) 25.2 (8.9) < 0.0001 Childs-Pugh Class 0.0878 A 16 (4%) 1 (2%) B 147 (36.4%) 11 (22%) C 241 (59.7%) 38 (76%) H/o Hepatic Encephalopathy 293(70.1%) 41(80.4%) 0.1252 Ascites 0.6772 None 87 (20.8%) 11 (21.6%) Controlled 114 (27.3%) 11 (21.6%) Uncontrolled 217 (51.9%) 29 (56.9%) Hepatocellular Carcinoma 45 (10.8%) 4 (7.8%) 0.5195 Varices 0.2854 None 148 (38.8%) 21 (50%) Non-bleeding 110 (28.9%) 8 (19%) Bleeding 123 (32.3%) 13 (31%) h/o TIPS 57 (13.6%) 9 (17.6%) 0.4368 Hospitalization Characteristics ICU at admission 32 (7.7%) 14 (27.5%) < 0.0001 Reason for Admission 0.0021 Encephalopathy 105 (25.1%) 21 (41.2%) GI bleed 67 (16%) 3 (5.9%) Ascites/Volume Overload 88 (21.1%) 3 (5.9%) AKI 39(9.3%) 4(7.8%) Infection 28(6.7%) 8(15.7%) Other 91(21.8%) 12(23.5%) Leukocyte Count 7.4 (4.4) 11.4 (8.5) < 0.0001 Platelet Count 112.3 (74.4) 111.9 (98.3) 0.9721 Sodium 132.7 (5.8) 133.6 (6.5) 0.3020 Creatinine 1.5 (1.2) 1.9 (1.1) 0.0153 Albumin 2.9 (0.6) 2.7 (0.6) 0.0082 Bilirubin 4.4 (5.1) 8.3 (9.5) < 0.0001 INR 1.81 (1.9) 2.2 (0.9) 0.1220 ^ mean (SD) Concurrent Validity between West Haven Criteria and RASS/CAM-ICU RASS/CAM-ICU demonstrated concurrent validity when compared to WHC ≥ 2 for hepatic encephalopathy (Table 2 ). There was strong agreement between WHC and RASS/CAM-ICU (κ = 0.79). When compared to WHC, the sensitivity of RASS/CAM-ICU for HE is 92.5% and the specificity is 96.7%. Notably, 14 participants screened positive by RASS/CAM-ICU despite being categorized as WHC < 2 by the clinical team. Table 2 Performance of RAAS/CAM-ICU compared to West Haven Criteria and other beside measures of cognition. RASS/CAM-ICU Negative (n = 418) RASS/CAM-ICU Positive (n = 51) West Haven Criteria* Normal 275 2 Grade 1 140 12 Grade 2 3 16 Grade 3 0 16 Grade 4 0 5 RASS/CAM-ICU Negative (n = 418) RASS/CAM-ICU Positive (n = 30) p-value Measures of Cognition^ MO-Log Score 24 (24–24) 21 (13–24) < .0001 CHESS Score 0 (0–0) 1 (0–3) < .0001 NCT Time (sec) 61 (49–73) 79 (66–104) < .0001 * CAM-ICU Sensitivity for HE diagnosis based on gold standard WH ≥ 2: 37/(37 + 3) = 92.5%, Specificity: 415/(415 + 14) = 96.7% ^ Only completed in those with WH ≤ 2, median (IQR) reported. MO-Log score missing in n = 16 (15 RASS/CAM-ICU negative and 1 RASS/CAM-IUC positive); CHESS score missing n = 18 (17 RASS/CAM-ICU negative and 1 RASS/CAM-IUC positive); and NCT timing missing in n = 83 (71 RASS/CAM-ICU negative and 12 RASS/CAM-ICU positive). Concurrent Validity between RASS/CAM-ICU and Objective Instruments of Cognitive Function RASS/CAM-ICU demonstrated concurrent validity when compared to objective measures of cognitive function including CHESS, MO-Log, and NCT in those with West Haven score ≤ 1 (Table 2 ). Compared to RASS/CAM-ICU(+) individuals, the median score for MO-Log was lower than those RASS/CAM-ICU(-) (21, IQR:13–24 vs. 24, IQR:24–24, p < 0.0001). RASS/CAM-ICU(+) individuals also scored higher on CHESS than those RASS/CAM-ICU(-) (1, IQR:0–3 vs. 0, IQR:0–0, p < 0.0001). On NCT-A, the median time for completion was longer in RASS/CAM-ICU(+) individuals vs. those RASS/CAM-ICU(-) (79 seconds, IQR:64–104 vs. 61 seconds, IQR:49–73, p = 0.0001). Comparison of Outcomes based on Delirium Status Next, we examined inpatient and short-term outcomes by those RASS/CAM-ICU status (Fig. 1 ). RASS/CAM-ICU(+) participants were found to have a considerably longer length of hospitalization than those RASS/CAM-ICU(-) individuals (15 days, IQR:8-21.5 vs. 4 days, IQR:3–8, p < 0.0001). In addition, RASS/CAM-ICU(+) participants had significantly higher inpatient mortality than those RASS/CAM-ICU(-) (37.3% vs. 2.9%, p < 0.0001). For those who survived to end of the hospitalization, RASS/CAM-ICU(+) individuals also had significantly higher 30-day and 90-day mortality compared to those RASS/CAM-ICU(-) (30-day: 51% vs. 11.5%, p < 0.0001; 90-day: 62.7% vs. 23.0%, p < 0.0001). Rates of readmission at 30 days by RASS/CAM-ICU status were not different (33.7% vs. 40.6%, p = 0.4241). Given the impact of RASS/CAM-ICU status on inpatient and short-term mortality, we sought to assess if RASS/CAM-ICU status improved prediction of inpatient mortality, 30-day mortality, and 90-day mortality. We first examined individual and clinical characteristics associated with inpatient, 30-day, and 90-day mortality ( Supplementary Table 1 ). On this analysis, MELD, CCI, ICU at admission and RASS/CAM-ICU(+) status were significantly associated with inpatient, 30-day, and 90-day mortality. Specifically, RASS/CAM-ICU(+) status increased the odds of inpatient mortality by 20-fold (OR 20.09, CI 8.96–45.04, p < 0.0001), 30-day mortality by 8-fold (OR 8.02, 95% CI 4.29-15.00, p < 0.0001), and 90-day mortality by nearly 6-fold (OR 5.65, 95% CI 3.06–10.41, p < 0.0001). While not significant, those with ascites tended to have higher inpatient mortality rates compared to those without (OR 4.07, CI .95-17.36, p = 0.0579) but similar 30- and 90-day mortality. Age, sex, race, cirrhosis etiology, history of HCC, and history of hepatic encephalopathy were not significantly associated with mortality outcomes. RASS/CAM-ICU(+) status remained independently associated with higher odds of each outcome after adjusting for adjusting for MELD, CCI and ICU at admission (Table 3 ). These models showed strong AUROC curves of 0.85, 0.82 and 0.77 for inpatient, 30-day and 90-day mortality, respectively (Fig. 2 A-C). Notably, these models performed similarly to a model using WHC ≥ 2 instead of those RASS/CAM-ICU(+) status to predict short-term mortality (Fig. 2 A-C). In addition to adjusting for MELD, we looked at AUROC curves in different MELD sub-groups and found that AUC of RASS/CAM-ICU status for predicting inpatient, 30-day and 90-day mortality tended to be highest in those with MELD > 30, however, they were not statistically different than AUCs in MELD < 20 or MELD 20–29. Table 3 Risk of death during hospitalization, 30-days and 90-days when delirium/coma present. Outcome Unadjusted OR (95% CI) p-value Adjusted OR* (95% CI) p-value Inpatient Mortality 20.1 (9.0–45.0) < .0001 13.8 (5.3–35.8) < .0001 30-day Mortality 8.0 (4.3–15) < .0001 6.4 (2.9–14.2) < .0001 90-day Mortality 5.7 (3.1–10.4) < .0001 4.9 (2.3–10.4) < .0001 *Adjusted for: Age, MELD, ICU at admission, ascites, Charlson, h/o HE (yes vs. no) Discussion HE is a subtype of delirium and defining feature of decompensated cirrhosis (Ferenci et al. 2002, 2013, Rosenberg et al. 2013, Vilstrup et al. 2014, Amodio 2018 ). HE remains an important target for quality improvement in hospital-based care (Bajaj et al. 2019 ). Importantly, both delirium and HE have been associated with longer hospitalizations, higher health care costs, and increased mortality (Ely et al. 2004, Stepanova et al. 2012, Patidar et al. 2014, Vilstrup et al. 2014). Despite these similarities and impact on outcomes, few studies have examined the value of an objective screening tool in patients with cirrhosis (Vilstrup et al. 2014, Orman et al. 2015). In this large prospective cohort of hospitalized patients with cirrhosis, we found substantial agreement between the most commonly used bedside measures of delirium and HE: RASS/CAM-ICU and WHC. We established concurrent validity of RASS/CAM-ICU by noting lower performance on previously established measures of cognitive function in cirrhosis. Finally, we show a strong association between RASS/CAM-ICU status and short-term outcomes allowing for accurate prediction of these outcomes using the RASS/CAM-ICU tool. Use of RASS/CAM-ICU has several potential advantages over the WHC. RASS/CAM-ICU is disease agnostic, easy to perform with minimal training, and already in widespread use in the healthcare system. It can therefore be implemented in diverse settings, including centers lacking expertise in end-stage liver disease (Ely et al. 2001, Patel et al. 2009, Guenther et al. 2010, Wong et al. 2010, Gusmao-Flores et al. 2012). In contrast, the WHC, although easy to understand and intuitive, does require a deeper familiarity with cirrhosis that may not be available in hospitals without hepatology expertise. The WHC also suffers from subjectivity and interobserver variability compared to RASS/CAM-ICU which is more objective and reproducible (Ferenci et al. 2002, Prakash and Mullen 2010, Vilstrup et al. 2014). Other objective bedside measures of HE have been developed such as MO-log and CHESS and we show that RASS/CAM-ICU shares concurrent validity with these tools, however, these tools have not been widely validated as has RASS/CAM-ICU and do share its ease of use. Despite excellent agreement between WHC and RASS/CAM-ICU, 14 participants without overt HE by WHC had a positive RASS/CAM-ICU. Although this amounts to only 3% of those without overt HE, positive CAM-ICU screens in this group may provide an opportunity for earlier intervention for patients who may not otherwise be identified as being at risk for cognitive impairment. In prior studies, CAM-ICU had the added advantage of early identification of hypoactive delirium characterized by flat affect or apathy in calm and outwardly alert individuals (Truman and Ely 2003). This form of delirium was noted to be the most common subtype of delirium and may be associated with a worse prognosis (Camus et al. 2000, Ely et al. 2001). Future studies could follow such patients longitudinally to assess for downstream cognitive outcomes and to investigate whether early treatment for delirium and/or HE may mitigate such outcomes. Notably, only 3 patients with WH grade 2 HE did not screen positive with RASS/CAM-ICU. Our study also establishes that screening with RASS/CAM-ICU can identify those at high risk for poor outcomes. Those who screened positive with RASS/CAMI-ICU in our study experienced dramatically high rates of death: 37%, 51% and 62% during hospitalization, 30 days and 90 days post-discharge, respectively. RASS/CAM-ICU was found to have very good predictive validity for short- and intermediate-term mortality with AUC ~ 0.8 after adjusting for important covariates. These findings are consistent with prior work demonstrating poor outcomes associated with delirium in a variety of disease states including those with cirrhosis (Stepanova et al. 2012, Orman et al. 2015, Maldonado 2017). In addition, RASS/CAM-ICU performed similarly to the WHC, suggesting that outcome prediction can be maintained without relying on the subjective WHC. Interestingly, despite the value of RASS/CAM-ICU screening in predicting mortality, RASS/CAM-ICU did not distinguish risk of 30-day readmission. Delirium has been associated with early readmission in older adults in a general medical population (LaHue et al. 2019). However, readmission in the cirrhosis population is notoriously difficult to predict, with risk prediction models achieving only fair-to-poor discrimination despite employing a broad array of analytic techniques and considering multidimensional risk factors (Desai and Reau 2016, Koola et al. 2020, Hu et al. 2021, Orman et al. 2021). Nevertheless, readmission should be considered as a potential outcome when evaluating interventions targeting HE and/or delirium. We noted that RASS/CAM-ICU status was associated with several measures of disease severity, including MELD and ICU admission, and, as expected, it was more common in those admitted for encephalopathy or infection. Demographic characteristics were otherwise largely similar between RASS/CAM-ICU(+) and (-) individuals, except for a trend toward lower education level in the RASS/CAM-ICU(+) group. A similar association between RASS/CAM-ICU(+) status and educational level has been found elsewhere, attributed to enhanced cognitive reserve in those with greater educational attainment (Jones et al. 2006). In cirrhosis populations, cognitive impairment has also been linked to lower socioeconomic status (Bajaj et al. 2013, Tapper et al. 2019). Our work further supports the use of RAAS/CAM-ICU as a valid, objective screening tool for cognitive impairment in cirrhosis whose performance is not greatly impacted by demographic features of the individual. This prospective study builds on prior retrospective work by incorporating real-time physician assessments of HE using WHC as a gold standard comparator for RASS/CAM-ICU. Research assessors and physicians were blinded to the WHC and RASS/CAM-ICU ratings, respectively, to prevent biased assessments. The prospective design also allowed for assessment of RASS/CAM-ICU predictive validity using short-term mortality, length of stay, and readmissions as outcomes of interest. However, these results must be interpreted in the context of the study design. Although WHC and RASS/CAM-ICU assessments were performed on the same day for comparison, they may have occurred at different times during the day. Both HE and delirium are characterized by fluctuating symptoms, and such fluctuations occurring during even short delays between assessments could account for some of the observed disagreements. Despite this possibility, disagreements between instruments were relatively rare. Additionally, RASS/CAM-ICU is largely validated in an ICU setting as opposed to CAM, which has more evidence for those admitted to general hospital ward beds. However, 10% of the study cohort was admitted to the ICU, and RASS/CAM-ICU can be performed for those on mechanical ventilation. Thus, use of RASS/CAM-ICU allowed a standard assessment and comparison for the entire cohort, including those in the ICU. As compared to the WHC, a limitation of RASS/CAM-ICU is that it does not grade severity of HE and delirium. Newer tools such as CAM-7, which can measure delirium severity, may have additional usefulness in this population, and are deserving of further study (Khan et al. 2017). Lastly, similar to any bedside tool, training of staff is important but can be easily accomplished with published instruction manuals. In conclusion, CAM-ICU is a valuable well-validated screening tool for HE that is widely utilized in a variety of hospital settings and has inherent advantages over WHC. Our study extends the validity of CAM-ICU to screen for delirium and HE in the hospitalized cirrhotic. The use of CAM-ICU by bedside staff may allow for earlier recognition and interventions for this common complication. Additionally, CAM-ICU status predicts important outcomes of in-hospital mortality, 30-day mortality, and 90-day mortality independent of liver disease severity and comorbidity burden. Future studies exploring the incorporation of CAM-ICU scores to liver-specific mortality prognosticating scores such as MELD-Na are needed. Declarations Funding: APD is funded by National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under award number K23DK123408. ESO is funded by National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under award number K23DK109202. The funder was not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. Competing Interests: The authors declare that they have no conflict of interests which are directly relevant to this work. For full disclosure, relationships unrelated to this work are listed. Dr. Naga Chalasani served as a paid consultant to Abbvie, Madrigal, Zydus, Galectin, Boehringer-Ingelheim, Lilly, and Altimmune. He has research funding from NIH, Galectin, DSM, and Exact Sciences. Dr. Chalasani has equity in RestUp, Inc, a start-up specializing in health care staff placement. Dr. Boustani receives consulting fees and honoria from Lilly, Eisa, BioGen, Genetech, ACADIA, Merck. Additionally, he has patents pending for the “ABC Took Kit” and Agile Processes and has stock options in PPHM, RestUP and BlueAgillis. Author Contributions: Study Concept and Design: Archita Desai, MD; Eric S. Orman, MD, MS Data Analysis: Devika Gandhi, MD; Chenjia Xu, PhD; Archita Desai, MD; Eric S. 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Gordon, F. E. Harrell, S. K. Inouye, G. R. Bernard and R. S. Dittus (2004). "Delirium as a predictor of mortality in mechanically ventilated patients in the intensive care unit." JAMA 291 (14): 1753-1762. DOI: 10.1001/jama.291.14.1753. Ferenci, P., A. Lockwood, K. Mullen, R. Tarter, K. Weissenborn and A. T. Blei (2002). "Hepatic encephalopathy--definition, nomenclature, diagnosis, and quantification: final report of the working party at the 11th World Congresses of Gastroenterology, Vienna, 1998." Hepatology 35 (3): 716-721. DOI: 10.1053/jhep.2002.31250. Guenther, U., J. Popp, L. Koecher, T. Muders, H. Wrigge, E. W. Ely and C. Putensen (2010). "Validity and reliability of the CAM-ICU Flowsheet to diagnose delirium in surgical ICU patients." J Crit Care 25 (1): 144-151. DOI: 10.1016/j.jcrc.2009.08.005. Gusmao-Flores, D., J. I. Salluh, R. A. Chalhub and L. C. Quarantini (2012). "The confusion assessment method for the intensive care unit (CAM-ICU) and intensive care delirium screening checklist (ICDSC) for the diagnosis of delirium: a systematic review and meta-analysis of clinical studies." Crit Care 16 (4): R115. DOI: 10.1186/cc11407. Hu, C., V. Anjur, K. Saboo, K. R. Reddy, J. O'Leary, P. Tandon, F. Wong, G. Garcia-Tsao, P. S. Kamath, J. C. Lai, S. W. Biggins, M. B. Fallon, P. Thuluvath, R. M. Subramanian, B. Maliakkal, H. Vargas, L. R. Thacker, R. K. Iyer and J. S. Bajaj (2021). "Low Predictability of Readmissions and Death Using Machine Learning in Cirrhosis." Am J Gastroenterol 116 (2): 336-346. DOI: 10.14309/ajg.0000000000000971. Jones, R. N., F. M. Yang, Y. Zhang, D. K. Kiely, E. R. Marcantonio and S. K. Inouye (2006). "Does educational attainment contribute to risk for delirium? A potential role for cognitive reserve." The journals of gerontology. Series A, Biological sciences and medical sciences 61 (12): 1307-1311. DOI: 10.1093/gerona/61.12.1307. Khan, B. A., A. J. Perkins, S. Gao, S. L. Hui, N. L. Campbell, M. O. Farber, L. L. Chlan and M. A. Boustani (2017). "The Confusion Assessment Method for the ICU-7 Delirium Severity Scale: A Novel Delirium Severity Instrument for Use in the ICU." Crit Care Med 45 (5): 851-857. DOI: 10.1097/CCM.0000000000002368. Koola, J. D., S. B. Ho, A. Cao, G. Chen, A. M. Perkins, S. E. Davis and M. E. Matheny (2020). "Predicting 30-Day Hospital Readmission Risk in a National Cohort of Patients with Cirrhosis." Dig Dis Sci 65 (4): 1003-1031. DOI: 10.1007/s10620-019-05826-w. LaHue, S. C., V. C. Douglas, T. Kuo, C. A. Conell, V. X. Liu, S. A. Josephson, C. Angel and K. B. Brooks (2019). "Association between Inpatient Delirium and Hospital Readmission in Patients >/= 65 Years of Age: A Retrospective Cohort Study." J Hosp Med 14 (4): 201-206. DOI: 10.12788/jhm.3130. Maldonado, J. R. (2017). "Acute Brain Failure: Pathophysiology, Diagnosis, Management, and Sequelae of Delirium." Crit Care Clin 33 (3): 461-519. DOI: 10.1016/j.ccc.2017.03.013. Orman, E. S., M. S. Ghabril, A. P. Desai, L. Nephew, K. R. Patidar, S. Gao, C. Xu and N. Chalasani (2021). "Patient-Reported Outcome Measures Modestly Enhance Prediction of Readmission in Patients with Cirrhosis." Clin Gastroenterol Hepatol. DOI: 10.1016/j.cgh.2021.07.032. Orman, E. S., A. Perkins, M. Ghabril, B. A. Khan, N. Chalasani and M. A. Boustani (2015). "The confusion assessment method for the intensive care unit in patients with cirrhosis." Metab Brain Dis 30 (4): 1063-1071. DOI: 10.1007/s11011-015-9679-8. Ortiz, M., J. Cordoba, E. Doval, C. Jacas, F. Pujadas, R. Esteban and J. Guardia (2007). "Development of a clinical hepatic encephalopathy staging scale." Aliment Pharmacol Ther 26 (6): 859-867. DOI: 10.1111/j.1365-2036.2007.03394.x. Patel, R. P., M. Gambrell, T. Speroff, T. A. Scott, B. T. Pun, J. Okahashi, C. Strength, P. Pandharipande, T. D. Girard, H. Burgess, R. S. Dittus, G. R. Bernard and E. W. Ely (2009). "Delirium and sedation in the intensive care unit: survey of behaviors and attitudes of 1384 healthcare professionals." Crit Care Med 37 (3): 825-832. DOI: 10.1097/CCM.0b013e31819b8608. Patidar, K. R., L. R. Thacker, J. B. Wade, R. K. Sterling, A. J. Sanyal, M. S. Siddiqui, S. C. Matherly, R. T. Stravitz, P. Puri, V. A. Luketic, M. Fuchs, M. B. White, N. A. Noble, A. B. Unser, H. Gilles, D. M. Heuman and J. S. Bajaj (2014). "Covert hepatic encephalopathy is independently associated with poor survival and increased risk of hospitalization." The American journal of gastroenterology 109 (11): 1757-1763. DOI: 10.1038/ajg.2014.264. Prakash, R. and K. D. Mullen (2010). "Mechanisms, diagnosis and management of hepatic encephalopathy." Nat Rev Gastroenterol Hepatol 7 (9): 515-525. DOI: 10.1038/nrgastro.2010.116. Rosenberg, R., S. G. Renvillard and S. Hjerrild (2013). "Organic delirious states and other psychiatric disorders: lessons for the hepatologists." Metabolic brain disease 28 (2): 235-238. DOI: 10.1007/s11011-012-9340-8. Salam, M., S. Matherly, I. S. Farooq, R. T. Stravitz, R. K. Sterling, A. J. Sanyal, D. P. Gibson, J. B. Wade, L. R. Thacker, D. M. Heuman, M. Fuchs, P. Puri, V. Luketic, S. J. Bickston and J. S. Bajaj (2012). "Modified-orientation log to assess hepatic encephalopathy." Aliment Pharmacol Ther 35 (8): 913-920. DOI: 10.1111/j.1365-2036.2012.05038.x. Sessler, C. N., M. S. Gosnell, M. J. Grap, G. M. Brophy, P. V. O'Neal, K. A. Keane, E. P. Tesoro and R. K. Elswick (2002). "The Richmond Agitation-Sedation Scale: validity and reliability in adult intensive care unit patients." Am J Respir Crit Care Med 166 (10): 1338-1344. DOI: 10.1164/rccm.2107138. Stepanova, M., A. Mishra, C. Venkatesan and Z. M. Younossi (2012). "In-hospital mortality and economic burden associated with hepatic encephalopathy in the United States from 2005 to 2009." Clin Gastroenterol Hepatol 10 (9): 1034-1041 e1031. DOI: 10.1016/j.cgh.2012.05.016. Tapper, E. B., J. B. Henderson, N. D. Parikh, G. N. Ioannou and A. S. Lok (2019). "Incidence of and Risk Factors for Hepatic Encephalopathy in a Population-Based Cohort of Americans With Cirrhosis." Hepatology communications 3 (11): 1510-1519. DOI: 10.1002/hep4.1425. Truman, B. and E. W. Ely (2003). "Monitoring delirium in critically ill patients. Using the confusion assessment method for the intensive care unit." Crit Care Nurse 23 (2): 25-36; quiz 37-28. Vilstrup, H., P. Amodio, J. Bajaj, J. Cordoba, P. Ferenci, K. D. Mullen, K. Weissenborn and P. Wong (2014). "Hepatic encephalopathy in chronic liver disease: 2014 Practice Guideline by the American Association for the Study of Liver Diseases and the European Association for the Study of the Liver." Hepatology 60 (2): 715-735. DOI: 10.1002/hep.27210. Wong, C. L., J. Holroyd-Leduc, D. L. Simel and S. E. Straus (2010). "Does this patient have delirium?: value of bedside instruments." JAMA 304 (7): 779-786. DOI: 10.1001/jama.2010.1182. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1809097","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":120082281,"identity":"026f7e88-f3ef-470e-9487-dc6d85ada083","order_by":0,"name":"Archita P. Desai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAr0lEQVRIiWNgGAWjYDCCA0CcwMAgxwbi8JCixZhELUCQ2EC0Fr7j7Q8/PKi5l94nkcD44G0bEVokz5wxlkg4VpzbJpHAbDiXGC0GN3IYJBLYEkBa2KR5idJy//njHwn/EtLZJBLYfxOn5QaDmURiW0ICUAsbM1FaJM/kmFkk9iUYtvE8bJacc44ILXzHjz+++eNbgrx8e/LBD2/KiNCCBBgbSFM/CkbBKBgFowA3AABPxzWNcOcczwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-8731-2370","institution":"Indiana University School of Medicine","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Archita","middleName":"P.","lastName":"Desai","suffix":""},{"id":120082282,"identity":"27fc7bcb-3ad4-4b35-bec3-08cc6faee10b","order_by":1,"name":"Devika Gandhi","email":"","orcid":"","institution":"Loma Linda University Health","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Devika","middleName":"","lastName":"Gandhi","suffix":""},{"id":120082283,"identity":"820134a8-80c6-4354-a593-fe086cd1d467","order_by":2,"name":"Chenjia Xu","email":"","orcid":"","institution":"Eli Lilly and Company","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chenjia","middleName":"","lastName":"Xu","suffix":""},{"id":120082284,"identity":"a5af4793-d183-44b2-84d7-009b24b06260","order_by":3,"name":"Marwan Ghabril","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marwan","middleName":"","lastName":"Ghabril","suffix":""},{"id":120082285,"identity":"57eec321-994a-42c0-b8fc-c434692d27aa","order_by":4,"name":"Lauren Nephew","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lauren","middleName":"","lastName":"Nephew","suffix":""},{"id":120082286,"identity":"d5de481c-a3a5-47e0-b43d-86a17671835d","order_by":5,"name":"Kavish R. 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Orman","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Eric","middleName":"S.","lastName":"Orman","suffix":""}],"badges":[],"createdAt":"2022-06-29 19:32:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1809097/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1809097/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":23992970,"identity":"86ea8556-6dba-4e9b-bee8-17828c98e3df","added_by":"auto","created_at":"2022-07-18 16:24:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":133755,"visible":true,"origin":"","legend":"\u003cp\u003eHospitalization and short-term mortality outcomes by RASS/CAM-ICU status\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1809097/v1/3efdbf39168e3a54f3494e06.png"},{"id":23992972,"identity":"65cf94c1-6028-4dc4-978d-08fdf726fe90","added_by":"auto","created_at":"2022-07-18 16:24:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":906646,"visible":true,"origin":"","legend":"\u003cp\u003ePrediction of inpatient, 30-day and 90-day mortality using RASS/CAM-ICU or West Haven Criteria. Models adjusted for age, MELD, ICU at admission, Charlson Co-morbidity score, ascites and history of hepatic encephalopathy.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1809097/v1/be8cb39f9704e1e48c44074b.png"},{"id":23992973,"identity":"71afba21-ac52-46f0-b1ad-eb4723bffd53","added_by":"auto","created_at":"2022-07-18 16:24:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":493535,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1809097/v1/65620cc1-43ee-4679-95c6-78b8a2abb36b.pdf"},{"id":23992971,"identity":"3f5f92ab-f856-467d-9dfc-00c494d08dab","added_by":"auto","created_at":"2022-07-18 16:24:46","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":769258,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTablesFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-1809097/v1/60bc362f19b7421b7191db7d.docx"}],"financialInterests":"","formattedTitle":"Confusion Assessment Method Accurately Screens for Hepatic Encephalopathy and Predicts Short-term Mortality in Hospitalized Patients with Cirrhosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDelirium is a manifestation of acute brain dysfunction characterized by a wide range of neuropsychiatric abnormalities including confusion, disorientation, and hallucinations (Deksnytė et al. 2012, 2013). A subtype of delirium, hepatic encephalopathy (HE), a well-studied complication of cirrhosis that also encompasses a range of neuropsychiatric impairment from subtle personality changes to coma (Ferenci et al. 2002, 2013, Rosenberg et al. 2013, Vilstrup et al. 2014, Amodio \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Delirium is as an independent predictor of short term mortality and longer length of stay in hospitalized patients leading many hospitals to routinely screen for delirium (Ely et al. 2004). Like delirium, HE is often precipitated by infections, electrolyte disturbances, and volume imbalances and is associated with significant morbidity and mortality as well as healthcare expenditures (Stepanova et al. 2012, Patidar et al. 2014, Vilstrup et al. 2014).\u003c/p\u003e \u003cp\u003eThe gold standard tool for diagnosing and quantifying HE at the bedside is the West Haven criteria (WHC) which classifies the severity of HE on a scale of 0\u0026ndash;4. Use of WHC are limited by lack of specific definitions for each stage and need for expertise prior to assessment, making the criteria subjective with high interobserver variability (Cordoba 2011, Vilstrup et al. 2014). Due to the overlapping features of delirium and HE, more objective screening tools for delirium may be particularly valuable in patients with cirrhosis (Vilstrup et al. 2014). Among the various delirium screening tools, the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) is a simple 4-item, objective, validated tool that aids healthcare workers in quickly and reliably diagnosing delirium (Ely et al. 2001). Due to its excellent performance characteristics, and reliability, CAM-ICU is recommended in more than 30 clinical practice guidelines, used in a variety of clinical settings and translated into 20 languages leading to worldwide use (Patel et al. 2009, Guenther et al. 2010, Wong et al. 2010, Gusmao-Flores et al. 2012). Importantly, CAM-ICU can be administered accurately by nursing staff in approximately 1 minute (Guenther et al. 2010). Despite the wide-spread use of CAM-ICU, it has been understudied in patients with cirrhosis (Cordoba 2011, Orman et al. 2015).\u003c/p\u003e \u003cp\u003eIn this prospective study, we aimed to examine the relationship between CAM-ICU status and short-term outcomes in hospitalized patients with cirrhosis. We also examined the relationship between CAM-ICU and previously established beside tools for HE diagnosis including WHC.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis analysis uses data from adults with cirrhosis (age\u0026thinsp;\u0026ge;\u0026thinsp;18) hospitalized at Indiana University Hospital between June 2014 and June 2018 who were prospectively enrolled during their hospitalization and followed for 90 days as previously described (Orman et al. 2021). Those in the study cohort with at least one assessment with the Richmond Agitation Sedation Scale (RASS) and/or the CAM-ICU during their hospitalization were included in this analysis (n\u0026thinsp;=\u0026thinsp;469). Cirrhosis diagnosis was based on the presence of liver histology or on characteristic clinical, laboratory, and radiologic findings. Patients were excluded if they had prior solid organ transplant or were unable to provide informed consent. The study was approved by the Indiana University Institutional Review Board. Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eVariables\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eMeasures of Cognition\u003c/h2\u003e \u003cp\u003ePatients were first assessed for level of sedation using the Richmond Agitation-Sedation Scale (RASS, \u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e) (Sessler et al. 2002). Participants with a RASS score of \u0026minus;\u0026thinsp;4 (no response to voice, but movement or eye opening to physical stimulation) or \u0026minus;\u0026thinsp;5 (no response to voice or physical stimulation) were deemed comatose and ineligible for further assessment with CAM-ICU. For those eligible, assessment using CAM-ICU was completed (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e). Assessments were made daily by research staff. Blinded daily provider-assigned WHC was also recorded with WHC\u0026thinsp;\u0026ge;\u0026thinsp;2 defined as HE (Vilstrup et al. 2014). On the day of enrollment, participants with WHC of 0 or 1 (n\u0026thinsp;=\u0026thinsp;415) also completed additional, previously established, assessments of HE: Clinical Hepatic Encephalopathy Staging Scale (CHESS), Modified-orientation log (MO-log), and Number Connection Test A (NCT). These scales were scored or timed as previously described (Amodio et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1999\u003c/span\u003e, Ortiz et al. 2007, Salam et al. 2012).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eDemographic and Clinical Variables\u003c/h2\u003e \u003cp\u003eDemographic data, social history, cirrhosis etiology, presence of cirrhosis complications such as hepatocellular carcinoma, varices, ascites, prior HE, and Charlson Comorbidity Index (CCI) were retrieved from the electronic medical record. During the hospitalization, reason for admission, presence and type of infections, and laboratory studies completed at the time of admission were recorded. Child-Pugh Class and Model for End-stage liver disease (MELD) score were also calculated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eOutcomes\u003c/h2\u003e \u003cp\u003eThe primary outcomes were inpatient, 30-day, and 90-day mortality. 30-day readmission and length of stay were also assessed.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eBaseline characteristics were compared between two groups of subjects based on RASS/CAM-ICU status using Pearson\u0026rsquo;s chi-squared test or Fisher\u0026rsquo;s exact test for categorical variables, t-test for continuous variables and Wilcoxon Rank-Sum test for continuous skewed data.\u003c/p\u003e \u003cp\u003eConcurrent validity of RASS/CAM-ICU was established through several methods. First, we compared RASS/CAM-ICU status to WHC using the agreement statistic as well as the sensitivity and specificity of HE by RASS/CAM-ICU to diagnose hepatic encephalopathy using WHC\u0026thinsp;\u0026ge;\u0026thinsp;2 as the gold standard for HE diagnosis. In addition, performance on the CHESS, MO-Log, and NCT were compared by RASS/CAM-ICU status using Wilcoxon Rank-Sum test.\u003c/p\u003e \u003cp\u003eLogistic regression models were used to assess the association between clinical characteristics, RASS/CAM-ICU status or WHC and mortality outcomes. Variables that have a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.1 in univariate models were considered potential confounders and added to the multivariate models. In addition, age and h/o HE were included in the models due to clinical relevance. We report the unadjusted and multivariate models testing the association between RASS/CAM-ICU status or WHC\u0026thinsp;\u0026ge;\u0026thinsp;2 and mortality outcomes. The Area under the Receiver Operating Characteristics (AUROC) curves was estimated to assess the predictability of the models.\u003c/p\u003e \u003cp\u003eAll analyses were conducted using SAS v9.4.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStudy Participant Characteristics\u003c/h2\u003e \u003cp\u003eOf 469 study participants, 51 (11%) were RASS/CAM-ICU positive (RASS=-4/-5: n\u0026thinsp;=\u0026thinsp;6, CAM-ICU(+): n\u0026thinsp;=\u0026thinsp;45) at some point during their hospitalization. Demographic and clinical characteristics of the study cohort are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e by RASS/CAM-ICU status. Of all enrolled participants, 55% were male and 94% were white. The most common etiologies of cirrhosis were non-alcoholic steatohepatitis (33%), alcohol (28%), and Hepatitis C (16%). Most participants were Childs-Pugh class C (59%). There were no significant differences in age, sex, race, alcohol use, insurance status, marital status, employment status, cirrhosis etiology, cirrhosis related complications including history of hepatic encephalopathy, and CCI between the two groups. There was a trend towards lower education level in RASS/CAM-ICU(+) individuals compared to those without delirium (p\u0026thinsp;=\u0026thinsp;0.062). The average MELD score of participants who were RASS/CAM-ICU(+) was higher compared to those who were RASS/CAM-ICU(-) (25, SD 9 vs. 19 SD 7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and RASS/CAM-ICU(+) individuals tended to have a higher Child-Pugh class (class C 60% vs. 76%, p\u0026thinsp;=\u0026thinsp;0.0878). RASS/CAM-ICU(+) participants were also more likely to be in ICU at the time of admission than those who were RASS/CAM-ICU(-) (27% vs. 8%, p\u0026thinsp;\u0026lt;\u0026thinsp;.0001). The reasons for admission differed by RASS/CAM-ICU status. Encephalopathy and infection were a more common reasons for admission in the RASS/CAM-ICU(+) group vs. RASS/CAM-ICU(-) group (41% vs. 25% and 16% vs. 7%, respectively). In contrast, RASS/CAM-ICU(+) individuals were less likely to be admitted for GI bleeding (6% vs. 16%) or ascites/volume overload (6% vs. 21%, p\u0026thinsp;=\u0026thinsp;0.0021).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographics and Clinical Characteristics of study participants with and without delirium/coma as measured by RASS/CAM-ICU\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRASS/CAM-ICU Negative\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;418\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRASS/CAM-ICU\u003c/p\u003e \u003cp\u003ePositive\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;51\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (mean, SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.5 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3454\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, %male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e229 (54.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (56.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7782\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u0026nbsp;Race %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e393 (94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (96.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5511\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOngoing Alcohol Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (11.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (19.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsurance Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (19.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e178 (42.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (43.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicaid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (31.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e240 (57.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2057\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0616\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHS\u0026nbsp;and \u0026lt;\u0026thinsp;HS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e212\u0026nbsp;(51.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome College\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135 (32.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege degree or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment\u0026nbsp;Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2453\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e227 (54.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (62.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (16.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (13.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64 (15.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisabled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharlson Comorbidity Index^\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.8 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.3 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCirrhosis Characteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCirrhosis Etiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5858\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (31.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (15.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (19.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis C\u0026thinsp;+\u0026thinsp;Alcohol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNASH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135 (32.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (35.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (16.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (9.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMELD^\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.9 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.2 (8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChilds-Pugh\u0026nbsp;Class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0878\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147 (36.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e241 (59.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH/o Hepatic Encephalopathy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e293(70.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41(80.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1252\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAscites\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6772\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87 (20.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (21.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControlled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (21.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUncontrolled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e217 (51.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (56.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatocellular Carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (10.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5195\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVarices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2854\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148 (38.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-bleeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110 (28.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBleeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123 (32.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eh/o TIPS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (13.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4368\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization Characteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU at admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (27.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReason for Admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEncephalopathy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105 (25.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (41.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGI bleed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAscites/Volume Overload\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (21.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39(9.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28(6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(15.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91(21.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(23.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukocyte Count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.4 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.4 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet Count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112.3 (74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111.9 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9721\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132.7 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e133.6 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.9 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0153\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.9 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0082\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBilirubin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.4 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.3 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.81 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.2 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e^ mean (SD)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eConcurrent Validity between West Haven Criteria and RASS/CAM-ICU\u003c/h2\u003e \u003cp\u003eRASS/CAM-ICU demonstrated concurrent validity when compared to WHC\u0026thinsp;\u0026ge;\u0026thinsp;2 for hepatic encephalopathy (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). There was strong agreement between WHC and RASS/CAM-ICU (κ\u0026thinsp;=\u0026thinsp;0.79). When compared to WHC, the sensitivity of RASS/CAM-ICU for HE is 92.5% and the specificity is 96.7%. Notably, 14 participants screened positive by RASS/CAM-ICU despite being categorized as WHC\u0026thinsp;\u0026lt;\u0026thinsp;2 by the clinical team.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePerformance of RAAS/CAM-ICU compared to West Haven Criteria and other beside measures of cognition.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRASS/CAM-ICU Negative\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;418)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRASS/CAM-ICU Positive\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;51)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eWest Haven Criteria*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNormal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eGrade 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eGrade 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eGrade 3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eGrade 4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRASS/CAM-ICU Negative\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(n\u0026thinsp;=\u0026thinsp;418)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eRASS/CAM-ICU Positive\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(n\u0026thinsp;=\u0026thinsp;30)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eMeasures of Cognition^\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMO-Log Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (24\u0026ndash;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (13\u0026ndash;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCHESS Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0\u0026ndash;3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNCT Time (sec)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (49\u0026ndash;73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79 (66\u0026ndash;104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e* CAM-ICU Sensitivity for HE diagnosis based on gold standard WH\u0026thinsp;\u0026ge;\u0026thinsp;2: 37/(37\u0026thinsp;+\u0026thinsp;3)\u0026thinsp;=\u0026thinsp;92.5%, Specificity: 415/(415\u0026thinsp;+\u0026thinsp;14)\u0026thinsp;=\u0026thinsp;96.7%\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e^ Only completed in those with WH\u0026thinsp;\u0026le;\u0026thinsp;2, median (IQR) reported. MO-Log score missing in n\u0026thinsp;=\u0026thinsp;16 (15 RASS/CAM-ICU negative and 1 RASS/CAM-IUC positive); CHESS score missing n\u0026thinsp;=\u0026thinsp;18 (17 RASS/CAM-ICU negative and 1 RASS/CAM-IUC positive); and NCT timing missing in n\u0026thinsp;=\u0026thinsp;83 (71 RASS/CAM-ICU negative and 12 RASS/CAM-ICU positive).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eConcurrent Validity between RASS/CAM-ICU and Objective Instruments of Cognitive Function\u003c/h2\u003e \u003cp\u003eRASS/CAM-ICU demonstrated concurrent validity when compared to objective measures of cognitive function including CHESS, MO-Log, and NCT in those with West Haven score\u0026thinsp;\u0026le;\u0026thinsp;1 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Compared to RASS/CAM-ICU(+) individuals, the median score for MO-Log was lower than those RASS/CAM-ICU(-) (21, IQR:13\u0026ndash;24 vs. 24, IQR:24\u0026ndash;24, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). RASS/CAM-ICU(+) individuals also scored higher on CHESS than those RASS/CAM-ICU(-) (1, IQR:0\u0026ndash;3 vs. 0, IQR:0\u0026ndash;0, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). On NCT-A, the median time for completion was longer in RASS/CAM-ICU(+) individuals vs. those RASS/CAM-ICU(-) (79 seconds, IQR:64\u0026ndash;104 vs. 61 seconds, IQR:49\u0026ndash;73, p\u0026thinsp;=\u0026thinsp;0.0001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eComparison of Outcomes based on Delirium Status\u003c/h2\u003e \u003cp\u003eNext, we examined inpatient and short-term outcomes by those RASS/CAM-ICU status (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). RASS/CAM-ICU(+) participants were found to have a considerably longer length of hospitalization than those RASS/CAM-ICU(-) individuals (15 days, IQR:8-21.5 vs. 4 days, IQR:3\u0026ndash;8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). In addition, RASS/CAM-ICU(+) participants had significantly higher inpatient mortality than those RASS/CAM-ICU(-) (37.3% vs. 2.9%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). For those who survived to end of the hospitalization, RASS/CAM-ICU(+) individuals also had significantly higher 30-day and 90-day mortality compared to those RASS/CAM-ICU(-) (30-day: 51% vs. 11.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; 90-day: 62.7% vs. 23.0%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Rates of readmission at 30 days by RASS/CAM-ICU status were not different (33.7% vs. 40.6%, p\u0026thinsp;=\u0026thinsp;0.4241).\u003c/p\u003e \u003cp\u003eGiven the impact of RASS/CAM-ICU status on inpatient and short-term mortality, we sought to assess if RASS/CAM-ICU status improved prediction of inpatient mortality, 30-day mortality, and 90-day mortality. We first examined individual and clinical characteristics associated with inpatient, 30-day, and 90-day mortality (\u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e). On this analysis, MELD, CCI, ICU at admission and RASS/CAM-ICU(+) status were significantly associated with inpatient, 30-day, and 90-day mortality. Specifically, RASS/CAM-ICU(+) status increased the odds of inpatient mortality by 20-fold (OR 20.09, CI 8.96\u0026ndash;45.04, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), 30-day mortality by 8-fold (OR 8.02, 95% CI 4.29-15.00, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and 90-day mortality by nearly 6-fold (OR 5.65, 95% CI 3.06\u0026ndash;10.41, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). While not significant, those with ascites tended to have higher inpatient mortality rates compared to those without (OR 4.07, CI .95-17.36, p\u0026thinsp;=\u0026thinsp;0.0579) but similar 30- and 90-day mortality. Age, sex, race, cirrhosis etiology, history of HCC, and history of hepatic encephalopathy were not significantly associated with mortality outcomes.\u003c/p\u003e \u003cp\u003eRASS/CAM-ICU(+) status remained independently associated with higher odds of each outcome after adjusting for adjusting for MELD, CCI and ICU at admission (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These models showed strong AUROC curves of 0.85, 0.82 and 0.77 for inpatient, 30-day and 90-day mortality, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-C). Notably, these models performed similarly to a model using WHC\u0026thinsp;\u0026ge;\u0026thinsp;2 instead of those RASS/CAM-ICU(+) status to predict short-term mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-C). In addition to adjusting for MELD, we looked at AUROC curves in different MELD sub-groups and found that AUC of RASS/CAM-ICU status for predicting inpatient, 30-day and 90-day mortality tended to be highest in those with MELD\u0026thinsp;\u0026gt;\u0026thinsp;30, however, they were not statistically different than AUCs in MELD\u0026thinsp;\u0026lt;\u0026thinsp;20 or MELD 20\u0026ndash;29.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRisk of death during hospitalization, 30-days and 90-days when delirium/coma present.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnadjusted OR\u0026nbsp;(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted OR* (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInpatient Mortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.1 (9.0\u0026ndash;45.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.8 (5.3\u0026ndash;35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e30-day Mortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.0 (4.3\u0026ndash;15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.4 (2.9\u0026ndash;14.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e90-day Mortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.7 (3.1\u0026ndash;10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.9 (2.3\u0026ndash;10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Adjusted for: Age, MELD, ICU at admission, ascites, Charlson, h/o HE (yes vs. no)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eHE is a subtype of delirium and defining feature of decompensated cirrhosis (Ferenci et al. 2002, 2013, Rosenberg et al. 2013, Vilstrup et al. 2014, Amodio \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). HE remains an important target for quality improvement in hospital-based care (Bajaj et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Importantly, both delirium and HE have been associated with longer hospitalizations, higher health care costs, and increased mortality (Ely et al. 2004, Stepanova et al. 2012, Patidar et al. 2014, Vilstrup et al. 2014). Despite these similarities and impact on outcomes, few studies have examined the value of an objective screening tool in patients with cirrhosis (Vilstrup et al. 2014, Orman et al. 2015). In this large prospective cohort of hospitalized patients with cirrhosis, we found substantial agreement between the most commonly used bedside measures of delirium and HE: RASS/CAM-ICU and WHC. We established concurrent validity of RASS/CAM-ICU by noting lower performance on previously established measures of cognitive function in cirrhosis. Finally, we show a strong association between RASS/CAM-ICU status and short-term outcomes allowing for accurate prediction of these outcomes using the RASS/CAM-ICU tool.\u003c/p\u003e \u003cp\u003eUse of RASS/CAM-ICU has several potential advantages over the WHC. RASS/CAM-ICU is disease agnostic, easy to perform with minimal training, and already in widespread use in the healthcare system. It can therefore be implemented in diverse settings, including centers lacking expertise in end-stage liver disease (Ely et al. 2001, Patel et al. 2009, Guenther et al. 2010, Wong et al. 2010, Gusmao-Flores et al. 2012). In contrast, the WHC, although easy to understand and intuitive, does require a deeper familiarity with cirrhosis that may not be available in hospitals without hepatology expertise. The WHC also suffers from subjectivity and interobserver variability compared to RASS/CAM-ICU which is more objective and reproducible (Ferenci et al. 2002, Prakash and Mullen 2010, Vilstrup et al. 2014). Other objective bedside measures of HE have been developed such as MO-log and CHESS and we show that RASS/CAM-ICU shares concurrent validity with these tools, however, these tools have not been widely validated as has RASS/CAM-ICU and do share its ease of use.\u003c/p\u003e \u003cp\u003eDespite excellent agreement between WHC and RASS/CAM-ICU, 14 participants without overt HE by WHC had a positive RASS/CAM-ICU. Although this amounts to only 3% of those without overt HE, positive CAM-ICU screens in this group may provide an opportunity for earlier intervention for patients who may not otherwise be identified as being at risk for cognitive impairment. In prior studies, CAM-ICU had the added advantage of early identification of hypoactive delirium characterized by flat affect or apathy in calm and outwardly alert individuals (Truman and Ely 2003). This form of delirium was noted to be the most common subtype of delirium and may be associated with a worse prognosis (Camus et al. 2000, Ely et al. 2001). Future studies could follow such patients longitudinally to assess for downstream cognitive outcomes and to investigate whether early treatment for delirium and/or HE may mitigate such outcomes. Notably, only 3 patients with WH grade 2 HE did not screen positive with RASS/CAM-ICU.\u003c/p\u003e \u003cp\u003eOur study also establishes that screening with RASS/CAM-ICU can identify those at high risk for poor outcomes. Those who screened positive with RASS/CAMI-ICU in our study experienced dramatically high rates of death: 37%, 51% and 62% during hospitalization, 30 days and 90 days post-discharge, respectively. RASS/CAM-ICU was found to have very good predictive validity for short- and intermediate-term mortality with AUC\u0026thinsp;~\u0026thinsp;0.8 after adjusting for important covariates. These findings are consistent with prior work demonstrating poor outcomes associated with delirium in a variety of disease states including those with cirrhosis (Stepanova et al. 2012, Orman et al. 2015, Maldonado 2017). In addition, RASS/CAM-ICU performed similarly to the WHC, suggesting that outcome prediction can be maintained without relying on the subjective WHC. Interestingly, despite the value of RASS/CAM-ICU screening in predicting mortality, RASS/CAM-ICU did not distinguish risk of 30-day readmission. Delirium has been associated with early readmission in older adults in a general medical population (LaHue et al. 2019). However, readmission in the cirrhosis population is notoriously difficult to predict, with risk prediction models achieving only fair-to-poor discrimination despite employing a broad array of analytic techniques and considering multidimensional risk factors (Desai and Reau 2016, Koola et al. 2020, Hu et al. 2021, Orman et al. 2021). Nevertheless, readmission should be considered as a potential outcome when evaluating interventions targeting HE and/or delirium.\u003c/p\u003e \u003cp\u003eWe noted that RASS/CAM-ICU status was associated with several measures of disease severity, including MELD and ICU admission, and, as expected, it was more common in those admitted for encephalopathy or infection. Demographic characteristics were otherwise largely similar between RASS/CAM-ICU(+) and (-) individuals, except for a trend toward lower education level in the RASS/CAM-ICU(+) group. A similar association between RASS/CAM-ICU(+) status and educational level has been found elsewhere, attributed to enhanced cognitive reserve in those with greater educational attainment (Jones et al. 2006). In cirrhosis populations, cognitive impairment has also been linked to lower socioeconomic status (Bajaj et al. 2013, Tapper et al. 2019). Our work further supports the use of RAAS/CAM-ICU as a valid, objective screening tool for cognitive impairment in cirrhosis whose performance is not greatly impacted by demographic features of the individual.\u003c/p\u003e \u003cp\u003eThis prospective study builds on prior retrospective work by incorporating real-time physician assessments of HE using WHC as a gold standard comparator for RASS/CAM-ICU. Research assessors and physicians were blinded to the WHC and RASS/CAM-ICU ratings, respectively, to prevent biased assessments. The prospective design also allowed for assessment of RASS/CAM-ICU predictive validity using short-term mortality, length of stay, and readmissions as outcomes of interest. However, these results must be interpreted in the context of the study design. Although WHC and RASS/CAM-ICU assessments were performed on the same day for comparison, they may have occurred at different times during the day. Both HE and delirium are characterized by fluctuating symptoms, and such fluctuations occurring during even short delays between assessments could account for some of the observed disagreements. Despite this possibility, disagreements between instruments were relatively rare. Additionally, RASS/CAM-ICU is largely validated in an ICU setting as opposed to CAM, which has more evidence for those admitted to general hospital ward beds. However, 10% of the study cohort was admitted to the ICU, and RASS/CAM-ICU can be performed for those on mechanical ventilation. Thus, use of RASS/CAM-ICU allowed a standard assessment and comparison for the entire cohort, including those in the ICU. As compared to the WHC, a limitation of RASS/CAM-ICU is that it does not grade severity of HE and delirium. Newer tools such as CAM-7, which can measure delirium severity, may have additional usefulness in this population, and are deserving of further study (Khan et al. 2017). Lastly, similar to any bedside tool, training of staff is important but can be easily accomplished with published instruction manuals.\u003c/p\u003e \u003cp\u003eIn conclusion, CAM-ICU is a valuable well-validated screening tool for HE that is widely utilized in a variety of hospital settings and has inherent advantages over WHC. Our study extends the validity of CAM-ICU to screen for delirium and HE in the hospitalized cirrhotic. The use of CAM-ICU by bedside staff may allow for earlier recognition and interventions for this common complication. Additionally, CAM-ICU status predicts important outcomes of in-hospital mortality, 30-day mortality, and 90-day mortality independent of liver disease severity and comorbidity burden. Future studies exploring the incorporation of CAM-ICU scores to liver-specific mortality prognosticating scores such as MELD-Na are needed.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eFunding:\u003c/u\u003eAPD is funded by National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under award number K23DK123408. ESO is funded by National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under award number K23DK109202. The funder was not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eCompeting Interests:\u003c/u\u003e The authors declare that they have no conflict of interests which are directly relevant to this work. For full disclosure, relationships unrelated to this work are listed. Dr.\u0026nbsp;Naga Chalasani served as a paid consultant to Abbvie, Madrigal, Zydus, Galectin, Boehringer-Ingelheim, Lilly, and Altimmune. \u0026nbsp;He has research funding from NIH, Galectin, DSM, and Exact Sciences. Dr. Chalasani has equity in RestUp, Inc, a start-up specializing in health care staff placement. Dr. Boustani receives consulting fees and honoria from Lilly, Eisa, BioGen, Genetech, ACADIA, Merck. Additionally, he has patents pending for the \u0026ldquo;ABC Took Kit\u0026rdquo; and Agile Processes and has stock options in PPHM, RestUP and BlueAgillis.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAuthor Contributions:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eStudy Concept and Design: Archita Desai, MD; Eric S. Orman, MD, MS\u003c/p\u003e\n\u003cp\u003eData Analysis: Devika Gandhi, MD; Chenjia Xu, PhD; Archita Desai, MD; Eric S. Orman, MD, MS\u003c/p\u003e\n\u003cp\u003eManuscript Preparation: Devika Gandhi, MD; Archita Desai, MD\u003c/p\u003e\n\u003cp\u003eCritical Manuscript Review: All authors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e\u003cbr\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e. \"CAM-ICU Training Manual.\"\u0026nbsp;\u0026nbsp; Retrieved 02/23/2022, 2022, from \u003ca href=\"https://www.icudelirium.org/resource-downloads/cam-icu-training-manual\"\u003ehttps://www.icudelirium.org/resource-downloads/cam-icu-training-manual\u003c/a\u003e.\u003c/li\u003e\n\u003cli\u003e(2013). Diagnostic and statistical manual of mental disorders : DSM-5. 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DOI: 10.1001/jama.2010.1182.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"metabolic-brain-disease","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mebr","sideBox":"Learn more about [Metabolic Brain Disease](https://www.springer.com/journal/11011)","snPcode":"11011","submissionUrl":"https://submission.nature.com/new-submission/11011/3","title":"Metabolic Brain Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"delirium, hepatic encephalopathy, cirrhosis","lastPublishedDoi":"10.21203/rs.3.rs-1809097/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1809097/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Hepatic encephalopathy (HE), a subtype of delirium, is common in cirrhosis and associated with poor outcomes. Yet, objective bedside screening tools for HE are lacking. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e We examined the relationship between an established screening tool for delirium, Confusion Assessment Method for the Intensive Care Unit\u003cstrong\u003e \u003c/strong\u003e(CAM-ICU) and established HE diagnostic tools as well as outcomes. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Prospectively enrolled adults with cirrhosis who completed the CAM-ICU from 6/2014-6/2018 were followed for 90 days. Blinded provider-assigned West Haven Criteria (WHC) and other measures of cognitive function were collected. Logistic regression was used to test associations between CAM-ICU status and outcomes. Mortality prediction by CAM-ICU status was assessed using Area under the Receiver Operating Characteristics curves (AUROC).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOf 469 participants, 11% were CAM-ICU(+), 55% were male and 94% were White. Most patients were Childs-Pugh class C (59%). CAM-ICU had excellent agreement with WHC (Kappa=0.79). CAM-ICU(+) participants had similar demographic features to those CAM-ICU(-), but had higher MELD (25 vs. 19, p\u0026lt;0.0001), were more often admitted to the ICU (28% vs. 7%, p\u0026lt;0.0001), and were more likely to be admitted for HE and infection. CAM-ICU(+) participants had higher mortality (inpatient:37% vs. 3%, 30-day:51% vs. 11%, 90-day:63% vs. 23%, p\u0026lt;0.001). CAM-ICU status predicted mortality with AUROC of 0.85, 0.82 and 0.77 for inpatient, 30-day and 90-day mortality, respectively.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eCAM-ICU has excellent agreement with WHC and identifies a hospitalized cirrhosis cohort with high short-term mortality. Unlike WHC, CAM-ICU can be administered by any team member making it an ideal tool to identify HE. \u003c/p\u003e","manuscriptTitle":"Confusion Assessment Method Accurately Screens for Hepatic Encephalopathy and Predicts Short-term Mortality in Hospitalized Patients with Cirrhosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-07-18 16:24:44","doi":"10.21203/rs.3.rs-1809097/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2022-07-11T19:02:01+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-07-11T08:15:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-07-05T01:01:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Metabolic Brain Disease","date":"2022-06-29T15:30:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"metabolic-brain-disease","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mebr","sideBox":"Learn more about [Metabolic Brain Disease](https://www.springer.com/journal/11011)","snPcode":"11011","submissionUrl":"https://submission.nature.com/new-submission/11011/3","title":"Metabolic Brain Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ec1d4e4a-170a-4d85-a82f-02b3698ef9d3","owner":[],"postedDate":"July 18th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-12-14T17:32:02+00:00","versionOfRecord":[],"versionCreatedAt":"2022-07-18 16:24:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1809097","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1809097","identity":"rs-1809097","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}