ArticleFrontiers in public health2023
Baseline and early changes in laboratory parameters predict disease severity and fatal outcomes in COVID-19 patients.
Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Comparison of Jinzhen oral liquid and ambroxol hydrochloride and clenbuterol hydrochloride oral solution in the treatment of acute bronchitis in children: A multicenter, non-inferiority, prospective, randomized controlled trial.Acta pharmaceutica Sinica. B · 2024Trial
- Age influences blood cell-based immune deregulation antibody response and unfavorable clinical outcomes in COVID-19 patients.Scientific reports · 2025Article
- Fasting and calorie restriction modulate age-associated immunosenescence and inflammaging.Aging medicine (Milton (N.S.W)) · 2024Review
- Bacterial profile, drug resistance pattern, clinical and laboratory predictors of ascites infection in cirrhosis patients.BMC infectious diseases · 2024Article
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Coronavirus disease 2019 (COVID-19) has become the worst catastrophe of the twenty-first century and has led to the death of more than 6.9 million individuals across the globe. Despite the growing knowledge of the clinicopathological features of COVID-19, the correlation between baseline and early changes in the laboratory parameters and the clinical outcomes of patients is not entirely understood. Methods: Here, we conducted a time series cross-sectional study aimed at assessing different measured parameters and socio-demographic factors that are associated with disease severity and the outcome of the disease in 268 PCR-confirmed COVID-19 Patients. Results: We found COVID-19 patients who died had a median age of 61 years (IQR, 50 y - 70 y), which is significantly higher ( Conclusion: To conclude here, we showed that simple laboratory parameters can be used to predict severity and outcome in COVID-19 patients. As these parameters are simple, inexpensive, and radially available in most resource-limited countries, they can be extrapolated to future viral epidemics or pandemics to allocate resources to particular patients.
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