Background. Predicting the severity of the COVID-19 infection in patients with leukemia would be helpful in the proper management of the infection in these patients. In this regard, this study aimed to identify predictive biomarkers in leukemic patients diagnosed with COVID-19. Methods. In this retrospective cross-sectional study, the data of 173 leukemic patients who were diagnosed with COVID-19 were used. These patients were admitted to Taleghani Hospital in Tehran, Iran, from March 2020 to September 2022. Results. The mean age of patients was 52.1±16.8, ranging from 14 to 87 years. Most of them had AML (35.1%), and CKD (19.1%) was the most prevalent underlying disease among them. The mean time of hospitalization was 16.8 days, and 46.8% of leukemia patients with COVID-19 died during hospitalization. The mean level of AST (157.3±82, P<0.018), age (57.8±15.6, P<0.002), and the rate of HTN (24.1%, P<0.044) were significantly higher in patients who were admitted to the ICU than in those who were not admitted. The mean age (P<0.001) and the mean levels of BUN (P<0.001), Cr (P=0.003), CRP (P=0.001), and LDH (P=0.007) in deceased patients were significantly higher compared to surviving patients (P<0.05). CKD (P=0.004) and CHF (P<0.001) comorbidity was more prevalent in deceased patients compared to survivors. Kaplan-Meier survival curves and multivariate Cox regression models showed significantly lower survival with higher levels of LDH (HR: 1.81, 95% CL: 1.1-0.3, P=0.022) and BUN (HR: 3.04, 95% CL: 1.91-4.83, P<0.001) and older age (HR: 2.13, 95% CL: 1.36-3.31, P<0.001). Conclusion. Our findings showed that aging and having some underlying diseases increase the risk of ICU admission as well as the mortality rate in leukemia patients with COVID-19. Practical Implications. The results of this study will be useful in identifying risk factors in patients who have leukemia and COVID-19 comorbidity.
Masoud et al. (Sun,) studied this question.