{"title":"Retrospective analysis of COVID-19 clinical and laboratory data: Constructing a multivariable model across different comorbidities","authors":"Mahdieh Shokrollahi Barough , Mohammad Darzi , Masoud Yunesian , Danesh Amini Panah , Yekta Ghane , Sam Mottahedan , Sohrab Sakinehpour , Tahereh Kowsarirad , Zahra Hosseini-Farjam , Mohammad Reza Amirzargar , Samaneh Dehghani , Fahimeh Shahriyary , Mohammad Mahdi Kabiri , Marzieh Nojomi , Neda Saraygord-Afshari , Seyedeh Ghazal Mostofi , Zeynab Yassin , Nazanin Mojtabavi","doi":"10.1016/j.jiph.2024.102566","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>The clinical pathogenesis of COVID-19 necessitates a comprehensive and homogeneous study to understand the disease mechanisms. Identifying clinical symptoms and laboratory parameters as key predictors can guide prognosis and inform effective treatment strategies. This study analyzed comorbidities and laboratory metrics to predict COVID-19 mortality using a homogeneous model.</div></div><div><h3>Method</h3><div>A retrospective cohort study was conducted on 7500 COVID-19 patients admitted to Rasoul Akram Hospital between 2022 and 2022. Clinical and laboratory data, along with comorbidity information, were collected and analyzed using advanced coding, data alignment, and regression analyses. Machine learning algorithms were employed to identify relevant features and calculate predictive probability scores.</div></div><div><h3>Results</h3><div>The frequency and mortality rates of COVID-19 among males (19.3 %) were higher than those among females (17 %) (p = 0.01, OR = 0.85, 95 % CI = 0.76–0.96). Cancer (p < 0.05, OR = 1.9, 95 % CI = 1.48–2.4) and Alzheimer's (p < 0.05, OR = 2.36, 95 % CI = 1.89–2.9) were the two most common comorbidities associated with long-term hospitalization (LTH). Kidney disease (KD) was identified as the most lethal comorbidity (45 % of KD patients) (OR = 5.6, 95 % CI = 5.05–6.04, p < 0.001). Age > 55 was the most predictive parameter for mortality (p < 0.001, OR = 6.5, 95 % CI = 1.03–1.04), and the CT scan score showed no predictive value for death (p > 0.05). WBC, Cr, CRP, ALP, and VBG-HCO3 were the most significant critical data associated with death prediction across all comorbidities (p < 0.05).</div></div><div><h3>Conclusion</h3><div>COVID-19 is particularly lethal for elderly adults; thus, age plays a crucial role in disease prognosis. Regarding death prediction, various comorbidities rank differently, with KD having a significant impact on mortality outcomes.</div></div>","PeriodicalId":16087,"journal":{"name":"Journal of Infection and Public Health","volume":null,"pages":null},"PeriodicalIF":4.7000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Infection and Public Health","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1876034124003009","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 0
Abstract
Background
The clinical pathogenesis of COVID-19 necessitates a comprehensive and homogeneous study to understand the disease mechanisms. Identifying clinical symptoms and laboratory parameters as key predictors can guide prognosis and inform effective treatment strategies. This study analyzed comorbidities and laboratory metrics to predict COVID-19 mortality using a homogeneous model.
Method
A retrospective cohort study was conducted on 7500 COVID-19 patients admitted to Rasoul Akram Hospital between 2022 and 2022. Clinical and laboratory data, along with comorbidity information, were collected and analyzed using advanced coding, data alignment, and regression analyses. Machine learning algorithms were employed to identify relevant features and calculate predictive probability scores.
Results
The frequency and mortality rates of COVID-19 among males (19.3 %) were higher than those among females (17 %) (p = 0.01, OR = 0.85, 95 % CI = 0.76–0.96). Cancer (p < 0.05, OR = 1.9, 95 % CI = 1.48–2.4) and Alzheimer's (p < 0.05, OR = 2.36, 95 % CI = 1.89–2.9) were the two most common comorbidities associated with long-term hospitalization (LTH). Kidney disease (KD) was identified as the most lethal comorbidity (45 % of KD patients) (OR = 5.6, 95 % CI = 5.05–6.04, p < 0.001). Age > 55 was the most predictive parameter for mortality (p < 0.001, OR = 6.5, 95 % CI = 1.03–1.04), and the CT scan score showed no predictive value for death (p > 0.05). WBC, Cr, CRP, ALP, and VBG-HCO3 were the most significant critical data associated with death prediction across all comorbidities (p < 0.05).
Conclusion
COVID-19 is particularly lethal for elderly adults; thus, age plays a crucial role in disease prognosis. Regarding death prediction, various comorbidities rank differently, with KD having a significant impact on mortality outcomes.
期刊介绍:
The Journal of Infection and Public Health, first official journal of the Saudi Arabian Ministry of National Guard Health Affairs, King Saud Bin Abdulaziz University for Health Sciences and the Saudi Association for Public Health, aims to be the foremost scientific, peer-reviewed journal encompassing infection prevention and control, microbiology, infectious diseases, public health and the application of healthcare epidemiology to the evaluation of health outcomes. The point of view of the journal is that infection and public health are closely intertwined and that advances in one area will have positive consequences on the other.
The journal will be useful to all health professionals who are partners in the management of patients with communicable diseases, keeping them up to date. The journal is proud to have an international and diverse editorial board that will assist and facilitate the publication of articles that reflect a global view on infection control and public health, as well as emphasizing our focus on supporting the needs of public health practitioners.
It is our aim to improve healthcare by reducing risk of infection and related adverse outcomes by critical review, selection, and dissemination of new and relevant information in the field of infection control, public health and infectious diseases in all healthcare settings and the community.