Abstract
Objectives: This study was conducted to collect evidence that specified the role of demographic findings (emphasizing age) and systemic inflammatory indicators in the coronavirus disease 2019 (COVID-19) and the outcome of disease which could help clinicians to predict mortality and intensive care unit (ICU) admission of COVID-19 patients.
Design: A retrospective cohort study.
Setting (s): Tabriz, the capital city of the East Azerbaijan Province in northwestern Iran.
Participants: This retrospective cohort study involved analyzing the medical records of 311 COVID-19 patients from 22 July, 2020 to 22 August, 2020.
Outcome measures: The demographic, clinical, and laboratory data and outcomes such as death, ICU admission, and discharge were extracted from medical records and electronic case records.
Results: The analysis of collected data revealed that the average age of non-survivor patients was 68.53±14.68 which was significantly higher than that of survivor patients (59.30±16.44). Furthermore, the comparison of data showed that ischemic heart disease (IHD), respiratory diseases, hemoglobin, derived neutrophil-to-lymphocyte ratio (dNLR), NLR, platelet-to-lymphocyte ratio (PLR), and lactate dehydrogenase (LDH) were higher in non-survivors and ICU admitted patients than in survivors and non-ICU admitted patients. Moreover, multivariate logistic regression analysis indicated that only hypertension (Odds ratio [OR]: 3.18, P=0.02) is an independent risk factor of death in COVID-19 patients, and PLR (OR: 1.02, P=0.05), hypertension (OR: 4.00, P=0.002), and IHD (OR: 5.15, P=0.008) were independent risk factor of ICU admission in COVID-19 patients.
Conclusions: Elderly patients were at higher risk of death and ICU admission compared to others. Further, demographic characteristics and systemic inflammatory indicators were valuable factors for predicting mortality and ICU admission of COVID-19 patients. Collective data regarding the role of demographic characteristics and systemic inflammation indicators for predicting disease outcomes provide strong evidence for the clinical use of these indicators prospectively.