Predictors of Mortality in COVID-19 patients: An observational study
| Autor: | Muhammad Arsalan Qureshi, null Kaleem Ullah Toori, null Raja Mobeen Ahmed |
|---|---|
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Pakistan Journal of Medical Sciences. 39 |
| ISSN: | 1681-715X 1682-024X |
| Popis: | Objectives: To identify the factors that affect outcome in COVID-19 patients in the Pakistani population. Methods: A total of 225 patients of COVID-19 RT-PCR proven were included during November, 2020 to June, 2021 in this cross-sectional study. They were stratified into different disease severity categories as per WHO guidelines. The characteristics of survivors and non survivors were recorded and then compared to draw conclusions. Results: Mean age was 59 years. Majority of the patients were male (68%) and the overall mortality rate was 30.1%. The non survivors were more likely to be female, had a greater number of comorbidities, had a higher respiratory rate and lower oxygen saturations at presentation and had a greater frequency of invasive mechanical ventilation. Non survivors had higher values of TLC, CRP, D-dimers and lower values of Hemoglobin and Platelets. The non survivors had higher incidence of ARDS, Septic shock and Multiorgan involvement. A higher CURB-65 score was observed in non survivors as compared to those who survived. Multivariate analysis showed that female gender, presence of and higher number of comorbid conditions and a higher CURB-65 score was linked with mortality. Conclusion: Results are compatible with international studies; increasing age, number of comorbid conditions and high inflammatory markers are associated with increased mortality. Our study had an exception that female gender had higher mortality as compared to men. doi: https://doi.org/10.12669/pjms.39.1.6059 How to cite this: Qureshi MA, Toori KU, Ahmed RM. Predictors of Mortality in COVID-19 patients; an observational study. Pak J Med Sci. 2023;39(1):---------. doi: https://doi.org/10.12669/pjms.39.1.6059 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|