BACKGROUND Coronavirus disease 2019 (COVID-19) has a spectrum of clinical syndromes with serious involvement of the lung and frequent effection of the liver and hemostatic system. Blood biomarkers are affordable, rapid, objective, and useful in the evaluation and prognostication of COVID-19 patients. AIM To investigate the association between aspartate transferase-to-platelet ratio index (APRI) and in-hospital mortality to develop a COVID-19 mortality prediction model. METHODS A multicenter cohort study with a retrospective design was conducted. Medical records of all consecutive adult patients admitted to Al-Azhar University Hospital (Assiut, Egypt) and Chest Hospital (Assiut, Egypt) with confirmed COVID-19 from July 1, 2020 to October 1, 2020, were retrieved and analyzed. The patient cohort was classified into the following two categories based on the APRI: (1) COVID-19 presenting with APRI ≤ 0.5; and (2) COVID-19 presenting with APRI (> 0.5 and ≤ 1.5). The association between APRI and all-cause in-hospital mortality was analyzed, and the new model was developed through logistic regression analyses. RESULTS Of the 353 patients who satisfied the inclusion criteria, 10% were admitted to the intensive care unit ( n = 36) and 7% died during the hospital stay ( n = 25). The median age was 40 years and 50.7% were male. On admission, 49% had aspartate transferase-dominant liver injury. On admission, APRI (> 0.5 and ≤ 1.5) was independently associated with all-cause in-hospital mortality in unadjusted regression analysis and after adjustment for age and sex; after stepwise adjustment for several clinically relevant confounders, APRI was still significantly associated with all-cause in-hospital mortality. On admission, APRI (> 0.5 and ≤ 1.5) increased the odds of mortality by five-times ( P < 0.006). From these results, we developed a new predictive model, the APRI-plus, which includes the four predictors of age, aspartate transferase, platelets, and serum ferritin. Performance for mortality was very good, with an area under the receiver operating curve of 0.90. CONCLUSION APRI-plus is an accurate and simplified prediction model for mortality among patients with COVID-19 and is associated with in-hospital mortality, independent of other relevant predictors.

BACKGROUND Clearly, infection with severe acute respiratory syndrome coronavirus 2 is not limited to the lung but also affects other organs. We need predictive models to determine patients’ prognoses and to improve health care resource allocation during the coronavirus disease 2019 (COVID-19) pandemic. While treating COVID-19, we observed differential outcome prediction weights for markers of hepatocellular injury among hospitalized patients. AIM To investigate the association between hepatocellular injury and all-cause in-hospital mortality among patients with COVID-19. METHODS This multicentre study employed a retrospective cohort design. All adult patients admitted to Al-Azhar University Hospital, Assiut, Egypt and Abo Teeg General Hospital, Assiut, Egypt with confirmed COVID-19 from June 1, 2020, to July 30, 2020 were eligible. We categorized our cohort into three groups of (1) patients with COVID-19 presenting normal aminotransferase levels; (2) patients with COVID-19 presenting one-fold higher aminotransferase levels; and (3) patients with COVID-19 presenting two-fold higher aminotransferase levels. We analysed the association between elevated aminotransferase levels and all-cause in-hospital mortality. The survival analysis was performed using the Kaplan–Meier method and tested by log-rank analysis. RESULTS In total, 376 of 419 patients met the inclusion criteria, while 29 (8%) patients in our cohort died during the hospital stay. The median age was 40 years (range: 28-56 years), and 51% were males ( n = 194). At admission, 54% of the study cohort had liver injury. The pattern of liver injury was hepatocellular injury with an aspartate aminotransferase (AST) predominance. Admission AST levels were independently associated with all-cause in-hospital mortality in the logistic regression analysis. A one-fold increase in serum AST levels among patients with COVID-19 led to an eleven-fold increase in in-hospital mortality ( P < 0.001). Admission AST levels correlated with C-reactive protein ( r = 0.2; P < 0.003) and serum ferritin ( r = 0.2; P < 0.0002) levels. Admission alanine aminotransferase levels correlated with serum ferritin levels ( r = 0.1; P < 0.04). Serum total bilirubin levels were independently associated with in-hospital mortality in the binary logistic regression analysis after adjusting for age and sex but lost its statistical significance in the fully adjusted model. Serum ferritin levels were significantly associated with in-hospital mortality ( P < 0.01). The probability of survival was significantly different between the AST groups and showed the following order: a two-fold increase in AST levels > a one-fold increase in in AST levels > normal AST l...