ReviewTropical medicine and infectious disease2025
Prediction of Mortality by Clinical Laboratory Parameters in Severe Fever with Thrombocytopenia Syndrome: A Meta-Analysis.
Review in Tropical medicine and infectious disease, 2025. 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.
- An Explainable Machine Learning Model for Early Prediction of Incident Myocardial Injury in Patients With Severe Fever With Thrombocytopenia Syndrome.Journal of medical virology · 2026Article
- Procalcitonin/albumin to urea nitrogen ratio: a novel prognostic indicator for severe fever with thrombocytopenia syndrome.BMC infectious diseases · 2026Observational
- Serum proteomics and machine learning identify PSMD11 as a prognostic biomarker in severe fever with thrombocytopenia syndrome.Frontiers in immunology · 2025Article
- Pathogen profile of co-infections and mortality determinants among patients with severe fever with thrombocytopenia syndrome.Frontiers in cellular and infection microbiology · 2025Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study intended to fully assess the predictive efficiency of different clinical laboratory parameters for the mortality risk in severe fever with thrombocytopenia syndrome (SFTS).
methodsWe systematically searched the Web of Science, PubMed, Cochrane Library, and Embase up to 13 December 2024 for studies on the association of laboratory parameters with SFTS mortality. Two investigators were independently responsible for the study screening and data extraction, and they assessed the study quality using the Newcastle-Ottawa Scale (NOS). Stata17.0 was adopted for the meta-analyses.
resultsWe finally included 33 observational studies involving 9502 participants (1799 deaths and 7703 survivors). The results showed that increases in the viral load (odds ratio (OR) 1.93, 95% confidence interval (CI) 1.56-2.38), neutrophil-to-lymphocyte ratio (hazard ratio (HR) 1.31, 95% CI 1.13-1.51), neutrophil percentage (HR 1.02, 95% CI 1.01-1.03), white blood cells (HR 1.06, 95% CI 1.01-1.11), activated partial thromboplastin time (OR 1.07, 95% CI 1.04-1.09), prothrombin time (OR 1.31, 95% CI 1.03-1.65), creatine kinase-myocardial band (OR 1.01, 95% CI 1.01-1.02), and procalcitonin (HR 1.27, 95% CI 1.10-1.47) greatly increased the SFTS mortality, while decreases in the lymphocyte percentage (HR 0.96, 95% CI 0.94-0.98), platelets (HR 0.98, 95% CI 0.97-0.99), and albumin (HR 0.91, 95% CI 0.86-0.96) also greatly increased the SFTS mortality; the results were all statistically significant (
conclusionAbnormalities of laboratory parameters (e.g., viral load, blood routine, coagulation, multi-organ dysfunction, and inflammation indicators) are good predictors of SFTS mortality, which can provide valuable references in clinical practice.
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