Development and Validation of a Model Consisting of Comorbidity Burden to Calculate Risk of Death Within 6 Months for Patients With Suspected Drug-Induced Liver Injury.

BACKGROUND & AIMS: Patients with drug-induced liver injury (DILI) frequently have comorbid conditions, but the effects of non-liver comorbidities on outcomes are not well understood. We investigated the association between comorbidity burden and outcomes of patients with DILI, and developed and validated a model to calculate risk of death within 6 months. METHODS: A multiple logistic regression model identified variables independently associated with death within 6 months of presenting with suspected DILI (6-month mortality) for 306 patients enrolled in the Drug-Induced Liver Injury Network prospective study at Indiana University (discovery cohort). The model was validated using data from 247 patients with suspected DILI enrolled in the same study at the University of North Carolina (validation cohort). Medical comorbidity burden was calculated using the Charlson Comorbidity Index-patients with scores higher than 2 were considered to have significant comorbidities. RESULTS: Six-month mortality was 8.5% in the discovery cohort and 4.5% in the validation cohort. In the discovery cohort, significant comorbidities (odds ratio, 5.4; 95% confidence interval [CI], 2.1-13.8), Model for End-Stage Liver Disease score (odds ratio, 1.11; 95% CI, 1.04-1.17), and serum level of albumin at presentation (odds ratio, 0.39; 95% CI, 0.2-0.76) were independently associated with 6-month mortality. A model based on these 3 variables identified patients who died within 6 months, with c-statistic values of 0.89 (95% CI, 0.86-0.94) in the discovery cohort and 0.91 (95% CI, 0.83-0.99) in the validation cohort. We developed a web-based calculator for use in the clinic to determine risk of death within 6 months for patients with suspected DILI. CONCLUSIONS: We developed and validated a model based on comorbidity burden, Model for End-Stage Liver Disease score, and serum level of albumin that predicts 6-month mortality in patients with suspected DILI.

An Outbreak Presents An Opportunity to Learn About A Rare Phenotype: Autoimmune Hepatitis After Acute Hepatitis A.

There are rare instances where patients with acute hepatitis A virus infection subsequently developed autoimmune hepatitis. The diagnosis of autoimmune hepatitis in this setting is challenging. Furthermore, information on treatment with steroids or other immune suppressants, duration of therapy and possibility of treatment discontinuation is currently unclear. Here we report a case series of four patients with histology proven autoimmune hepatitis after hepatitis A virus infection. We describe the presenting features, diagnosis, treatment and long-term outcomes of these cases. This case series provides a insight into the clinical presentation and treatment of autoimmune hepatitis after hepatitis A infection with interesting take home points for clinical hepatologists.

Attendance at a Transitional Liver Clinic May Be Associated with Reduced Readmissions for Patients with Liver Disease.

INTRODUCTION: Patients with liver disease have high rates of early hospital readmission, but there are no studies of effective, scalable interventions to reduce this risk. In this study, we examined the impact of a Physician Assistant (PA)-led post-discharge Transitional Liver Clinic (TLC) on hospital readmissions. METHODS: We performed a cohort study of all adults seen by a hepatologist during admission to a tertiary care center in 2019 (excluding transplant patients). We compared those who attended the TLC with those who did not, with respect to 30-day readmission and mortality. Propensity score-adjusted modeling was used to control for confounding. RESULTS: Of 498 patients, 98 were seen in the TLC; 35% had alcoholic liver disease and 58% had cirrhosis. Attendees were similar to non-attendees with respect to demographics, liver disease characteristics and severity, comorbidities, and discharge disposition. Thirty-day cumulative incidence of readmissions was 12% in TLC attendees, compared with 22% in non-attendees (P = .02), while 30-day mortality was similar (2.0% vs 4.3%; P = .29). In a model using propensity score adjustment, TLC attendance remained associated with reduced readmissions (subhazard ratio 0.52; 95% confidence interval, 0.27-0.997; P = .049). The effect of TLC was greater in women compared with men (P = .07) and in those without chronic kidney disease (P = .02), but there were no differences across other subgroups. CONCLUSIONS: Patients with liver disease seen in a PA-led TLC may have a significant reduction in the 30-day readmission rate. Randomized trials are needed to establish the efficacy of PA-led post-discharge transitional care for this population.

Significant Medical Comorbidities Are Associated With Lower Causality Scores in Patients Presenting With Suspected Drug-Induced Liver Injury.

INTRODUCTION: Drug-induced liver injury (DILI) is a diagnosis of exclusion, and it can be challenging to adjudicate when there are multiple comorbidities and concomitant medications. In this study, we tested the hypothesis that comorbidity burden impacts the causality adjudication in patients with suspected DILI. METHODS: We studied consecutive patients with suspected DILI enrolled in the Drug-Induced Liver Injury Network Prospective Study at 2 centers between 2003 and 2017. The comorbidity burden at presentation was determined using the Charlson Comorbidity Index (CCI). We analyzed the association between significant comorbidity (CCI > 75th percentile) and (i) the adjudication of DILI by expert consensus as definite, highly likely, or probable (high-confidence DILI) and (ii) the Roussel Uclaf Causality Assessment Method (RUCAM) scores. RESULTS: Our cohort consisted of 551 patients who were classified as "no comorbidity" (54%, CCI = 0), "mild comorbidity" (29%, CCI = 1 or 2), and "significant comorbidity" (17%, CCI > 2). The probability of high-confidence DILI was significantly lower in patients with significant comorbidity compared with those with mild or no comorbidities (67% vs 76% vs 87%, respectively, P < 0.001). The mean RUCAM scores decreased with increasing comorbidity (no comorbidity 6.6 ± 2, mild comorbidity 6 ± 2.4, and significant comorbidity 5.6 ± 2.7, P < 0.001). In the multiple logistic regression, significant comorbidity had an independent inverse relationship with DILI (odds ratio: 0.37, 95% confidence interval: 0.2-0.69, P = 0.001). DISCUSSION: Higher comorbidity burden impacts the causality assessment in patients with suspected DILI. Further studies are needed to investigate the utility of comorbidity burden as a variable in the DILI causality instruments.