Risk factors identification of COVID‐19 patients with chronic obstructive pulmonary disease: A retrospective study in Punjab‐Pakistan

Abstract

Abstract Background Accessibility to the immense collection of studies on noncommunicable diseases related to coronavirus disease of 2019 (COVID‐19) and severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is an immediate focus of researchers. However, there is a scarcity of information about chronic obstructed pulmonary disease (COPD), which is associated with a high rate of infection in COVID‐19 patients. Moreover, by combining the effects of the SARS‐CoV‐2 on COPD patients, we may be able to overcome formidable obstacles factors, and diagnosis influencers. Materials and Methods A retrospective study of 280 patients was conducted at DHQ Hospital Muzaffargarh in Punjab, Pakistan. Negative binomial regression describes the risk of fixed successive variables. The association is described by the Cox proportional hazard model and the model coefficient is determined through log‐likelihood observation. Patients with COPD had their survival and mortality plotted on Kaplan–Meier curves. Results The increased risk of death in COPD patients was due to the effects of variables such as cough, lower respiratory tract infection (LRTI), tuberculosis (TB), and body‐aches being 1.369, 0.693, 0.170, and 0.217 times higher at (95% confidence interval [CI]: 0.747–1.992), (95% CI: 0.231–1.156), (95% CI: 0.008–0.332), and (95% CI: −0.07 to 0.440) while it decreased 0.396 in normal condition. Conclusion We found that the symptoms of COPD (cough, LRTI, TB, and bodyaches) are statistically significant in patients who were most infected by SARS‐CoV‐2.

Keywords

• COPD
• COVID‐19
• Cox proportional hazard model and negative binomial distribution
• SARS‐CoV‐2