A novel nomogram to predict 90-day mortality in patients with hepatitis B virus-related acute-on-chronic liver failure: a single-center retrospective study.

BACKGROUND: Acute-on-chronic liver failure (ACLF) is a critical illness with high mortality. Herein, we developed and validated a new and simple prognostic nomogram to predict 90-day mortality in hepatitis B virus-related ACLF (HBV-ACLF) patients. METHODS: This single-center retrospective study collected data from 181 HBV-ACLF patients treated between June 2018 and March 2020. The correlation between clinical data and 90-day mortality in patients with HBV-ACLF was assessed using univariate and multivariate logistic regression analyses. RESULTS: Multivariate logistic regression analysis showed that age (p = 0.011), hepatic encephalopathy (p = 0.001), total bilirubin (p = 0.007), international normalized ratio (p = 0.006), and high-density lipoprotein cholesterol (p = 0.011) were independent predictors of 90-day mortality in HBV-ACLF patients. A nomogram was created to predict 90-day mortality using these risk factors. The C-index for the prognostic nomogram was calculated as 0.866, and confirmed to be 0.854 via bootstrapping verification. The area under the curve was 0.870 in the external validation cohort. The predictive value of the nomogram was similar to that of the Chinese Group on the Study of Severe Hepatitis B score, and exceeded the performance of other prognostic scores. CONCLUSION: The prognostic nomogram constructed using the factors identified in multivariate regression analysis might serve as a beneficial tool to predict 90-day mortality in HBV-ACLF patients.

Low T3 syndrome is associated with poor prognosis in patients with hepatitis B virus-related acute-on-chronic liver failure.

BACKGROUND: Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is a critical disease with high mortality risk. Low triiodothyronine syndrome (LT3S) is associated with various severe acute and chronic diseases. We investigated the relationship between LT3S and poor prognosis in patients with HBV-ACLF. RESEARCH DESIGN AND METHODS: A total of 198 patients with HBV-ACLF were enrolled between January 2018 and March 2019. We screened for independent risk factors for 28-day mortality using univariate and multivariate logistic regression analyses. Spearman's correlation analysis was used to evaluate the correlation between LT3S and the poor prognostic parameters of HBV-ACLF. RESULTS: LT3S was an independent risk factor for 28-day mortality in HBV-ACLF patients (odds ratio: 4.035, 95% confidence interval 1.117-14.579; p = 0.033). The death group had a lower serum FT3 level (Z-value = 2639.000, p < 0.001). Serum FT3 levels were negatively correlated with age, C-reactive protein, international normalized ratio, and neutrophil count but positively correlated with lymphocyte count. A negative correlation between FT3 and various prognostic scores was observed, indicating that a low FT3 level was closely related to a poor prognosis. CONCLUSIONS: LT3S was an independent risk factor for 28-day mortality and was correlated with poor prognosis in patients with HBV-ACLF.

Survival Prediction in Patients with Hypertensive Chronic Kidney Disease in Intensive Care Unit: A Retrospective Analysis Based on the MIMIC-III Database.

Objective: Disease prediction is crucial to treatment success. The aim of this study was to accurately and explicably predict, based on the first laboratory measurements, medications, and demographic information, the risk of death in patients with hypertensive chronic kidney disease within 1 and 3 years after admission to the Intensive Care Unit (ICU). Methods: Patients with hypertensive chronic kidney disease who had been registered in the Medical Information Mart for Intensive Care (MIMIC-III) database of critical care medicine were set as the subject of study, which was randomly divided into a training set and a validation set in a ratio of 7 : 3. Univariate Cox regression analysis and stepwise Cox regression analysis were applied in the training set to identify the predictive factors of prognosis of patients with hypertensive chronic kidney disease in ICU, and the predictive nomogram based on Cox regression model was constructed. We internally validated the model in the training set and externally validated that in the validation model. The efficacy was assessed primarily through area under the receiver operating characteristic (ROC) curve, clinical decision curves, and calibration curves. Results: A total of 1762 patients with hypertensive chronic kidney disease were finally included. During the 3-year follow-up, 667 patients (37.85%) died, with a median follow-up time of 220 days (1-1090). The data set were randomly divided into a training set (n = 1231) and a validation set (n = 531). It was identified in the training set that insurance, albumin, alkaline phosphatase, the mean corpuscular hemoglobin concentration, mean corpuscular volume, history of coronary angiogram, hyperlipemia, medication of digoxin, acute renal failure, and history of renal surgery were the most relevant features. Taking 1 year and 3 years as the cut-off points, the AUC of participants were 0.736 and 0.744, respectively, in the internal validation and were 0.775 and 0.769, respectively, in the external validation, suggesting that the model is of favorable predictive efficacy. Conclusion: We trained and validated a model using data from a large multicenter cohort, which has considerable predictive performance on an individual scale and could be used to improve treatment strategies.