Evaluating the Effect of Underlying Pulmonary Disease on the Clinical Outcome and survival among Patients with COVID-19: Using Propensity Score Matching

Abstract

Background: Coronavirus (Covid-19) is a life-threatening factor throughout the world. Having an underlying disease among the patients with this disease diminishes the clinical effectiveness and increases their mortality rate. Hence, the study was carried out to compare the clinical outcomes in patients with COVID-19 with and without pulmonary disease using propensity score matching. Methods: This case-control study was conducted on 299 COVID-19 patients with pulmonary disease (case group) and 299 COVID-19 patients without pulmonary diseases (control group). Matching the patients in the case and control groups was done using propensity score matching. Logistic regression was used to assess the effect of factors on the patient's clinical outcome (recovery-death), and the Cox model was used to determine the factors affecting patient survival. Data were analyzed in R software. Results: The mean (SD) of the patients' age in the case and control groups was 65.49 (15.55) and 65.67 (15.55), respectively. The results of the logistic regression model showed that age, pulmonary disease, nausea, and blood oxygen affect patient death. The results of the Cox proportional-hazards model indicated that the variables of age, blood oxygen, and pulmonary had a significant effect on patient survival. Conclusion: Given the high mortality rate among patients with COVID-19 and chronic pulmonary disease, these patients are considered a high-risk group and need special care.