Abnormal liver tests in patients with SARS-CoV-2 or influenza - prognostic similarities and temporal disparities.
2021
Abstract Background & Aims Abnormal liver tests are common in patients with severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) infection, but a possible direct role of the virus in liver injury and its association with short-term outcomes are controversial. Therefore, we aimed to compare the pattern of abnormal liver tests in SARS-CoV-2 patients with those of patients infected with influenza, a non-hepatotropic respiratory virus, and their association with worse outcomes during hospitalization. Methods A retrospective cohort study of 1737 hospitalized patients (865 with influenza and 872 with SARS-Cov-2) in a tertiary medical center. We defined abnormal liver tests as GPT or GOT ≥40IU/ML at any time-point during hospitalization. Results Abnormal liver tests were mild-moderate in the majority of patients regardless of infection type, but the majority of patients with influenza had a transaminases peak earlier during hospitalization compared to patients with SARS-Cov-2. Abnormal liver tests correlated with markers of severe disease in either influenza or SARS-Cov-2 infections, and were associated with death, occurring mainly in patients with severe liver tests abnormalities (>200IU/L) (38.7% and 60% of patients with influenza or SARS-Cov-2, respectively). In multivariate analysis, controlling for age, gender, lymphopenia and CRP, liver tests abnormalities remained significantly associated with death for influenza (OR= 4.344, 95% CI 2.218-8.508) and SARS-Cov-2 (OR= 3.898, 95% CI 2.203-6.896). These results were confirmed upon propensity score matching. Conclusions Abnormal liver tests during hospitalization with SARS-Cov-2 or influenza infections are common, may differ in their time-course and reflect disease severity. They are associated with worse outcomes, mainly in patients with severe liver test abnormalities, regardless of infection type.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
27
References
0
Citations
NaN
KQI