Development and validation of a multivariable risk prediction model for hepatic steatosis in patients with HIV infection.

OBJECTIVE: Early detection of hepatic steatosis in people with HIV (PWH) could prevent progression and inflammation. The aim was to develop and validate a multivariable risk prediction model for hepatic steatosis in German PWH. DESIGN: In this cohort study, 282 PWH were prospectively enrolled, and hepatic steatosis was defined via controlled attenuation parameter (CAP; ≥275 dB/m) using vibration-controlled transient elastography. METHODS: Three multivariable logistic regression models were conducted. Missing values were imputed with multiple imputation. Cut-offs were derived based on Youden-Indices. Performance was assessed via discriminatory and calibrative ability and accuracy via Brier Skill Score. Sensitivity, specificity, and predictive values were calculated. Internal validation was performed via bootstrapping. RESULTS: The prevalence of hepatic steatosis was 35.3% (100/282). Univariate analyses revealed associations with age, waist circumference, BMI, hypertension, hyperlipidemia and gamma-gt. In multivariable analyses, male sex [odds ratio (OR) 2.07, 95% confidence interval (CI) 1.42-3.00, P  = 0.001] and BMI (OR 1.27, 95% CI 1.18-1.36, P  < 0.001) were identified as independent predictors of hepatic steatosis. The naive and optimism-corrected c -statistic of 79% showed a good discriminatory ability, the calibration was well with a slight tendency for overestimation for predicted probabilities above 70%. At the cutoff of 1.95, the specificity was 71% and the negative-predictive value 82.3%. Twenty-seven percent of the 282 patients would be misclassified, 17% as false positives and 10% as false negatives. CONCLUSION: The developed prediction model contributes to the lack of validated noninvasive tools to predict hepatic steatosis in people with HIV. Future studies should include more candidate predictors and externally validate the model.

Changes in the alcohol-specific disease burden during the COVID-19 pandemic in Germany: interrupted time series analyses.

BACKGROUND: The coronavirus disease 2019 pandemic has been linked to changes in alcohol consumption, access to healthcare services and alcohol-attributable harm. In this contribution, we quantify changes in alcohol-specific mortality and hospitalizations at the onset of the COVID-19 pandemic in March 2020 in Germany. METHODS: We obtained monthly counts of deaths and hospital discharges between January 2013 and December 2020 (n = 96 months). Alcohol-specific (International Classification of Diseases, tenth revision codes: F10.X; G31.2, G62.1, G72.1, I42.6, K29.2, K70.X, K85.2, K86.0, Q86.0, T51.X) diagnoses were further split into codes reflective of acute vs. chronic harm from alcohol consumption. To quantify the change in alcohol-specific deaths and hospital discharges, we performed sex-stratified interrupted time series analyses using generalized additive mixed models for the population aged 45-74. Immediate (step) and cumulative (slope) changes were considered. RESULTS: Following March 2020, we observed immediate increases in alcohol-specific mortality among women but not among men. Between the years of 2019 and 2020, we estimate that alcohol-specific mortality among women has increased by 10.8%. Hospital discharges were analyzed separately for acute and chronic conditions. The total number of hospital discharges fell by 21.4% and 25.1% for acute alcohol-specific conditions for women and men, respectively. The total number of hospital discharges for chronic alcohol-specific conditions fell by 7.4% and 8.1% for women and men, respectively. CONCLUSIONS: Increased consumption among people with heavy drinking patterns and reduced utilization of addiction-specific healthcare services during the pandemic might explain excess mortality. During times of public health crises, access to addiction-specific services needs to be ensured.