Published online Apr 28, 2022. doi: 10.3748/wjg.v28.i16.1671
Peer-review started: November 16, 2021
First decision: January 11, 2022
Revised: January 21, 2022
Accepted: March 16, 2022
Article in press: March 16, 2022
Published online: April 28, 2022
Processing time: 158 Days and 16.7 Hours
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.
To investigate the association between aspartate transferase-to-platelet ratio index (APRI) and in-hospital mortality to develop a COVID-19 mortality prediction model.
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.
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.
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.
Core Tip: Aspartate transferase-to-platelet ratio index-plus can be used to predict the severity of coronavirus disease 2019. The performance of the model for mortality was very good, with an area under the receiver operating curve of 0.90. This new prediction model could help in estimating the risk of mortality and may, therefore, assist in triaging patients. Moreover, our study confirmed that an aspartate transferase-dominant pattern, diabetes mellites, leukocytosis, and increased ferritin levels are associated with fatal outcomes.