SynthesisFrontiers in microbiology2023
A model based on meta-analysis to evaluate poor prognosis of patients with severe fever with thrombocytopenia syndrome.
Synthesis in Frontiers in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 16 citations in OpenAlex.
- Integrative analysis of mortality risk in SFTS using machine learning and genetic approaches.mSphere · 2026Article
- Epidemiological characteristics of severe fever with thrombocytopenia syndrome (SFTS) in China, 2010-2024: a fifteen-year national surveillance analysis.BMC infectious diseases · 2026Article
- Development and validation of a nomogram for predicting 30-day mortality in DBV-induced sepsis with pancreatic injury.iScience · 2026Article
- Risk factor analysis and construction of risk nomogram for severe fever with thrombocytopenia syndrome based on clinical classification.Scientific reports · 2026Article
- A novel scoring system for precise severity quantification in severe fever with thrombocytopenia syndrome: development and application based on dynamic clinical data.Frontiers in microbiology · 2026Article
- Prediction models for encephalitis and in-hospital death associated with severe fever with thrombocytopenia syndrome.BMC infectious diseases · 2025Article
- Prediction of Mortality by Clinical Laboratory Parameters in Severe Fever with Thrombocytopenia Syndrome: A Meta-Analysis.Tropical medicine and infectious disease · 2025Review
- Severe fever thrombocytopenia syndrome proceeding east.Journal of rural medicine : JRM · 2025Article
- Retrospective Analysis of Severe Fever With Thrombocytopenia Syndrome and Construction of a Nomogram Prediction Model for Mortality Risk Factors.Open forum infectious diseases · 2025Article
- Metabolic Profiling Reveals Potential Prognostic Biomarkers for SFTS: Insights into Disease Severity and Clinical Outcomes.Metabolites · 2025Article
- A multicenter study on developing a prognostic model for severe fever with thrombocytopenia syndrome using machine learning.Frontiers in microbiology · 2025Article
- Aspartate aminotransferase to platelet ratio correlates with poor prognosis and metabolic alterations inFrontiers in immunology · 2024Article
- Machine learning for identifying risk of death in patients with severe fever with thrombocytopenia syndrome.Frontiers in microbiology · 2024Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Early identification of risk factors associated with poor prognosis in Severe fever with thrombocytopenia syndrome (SFTS) patients is crucial to improving patient survival. Method: Retrieve literature related to fatal risk factors in SFTS patients in the database, extract the risk factors and corresponding RRs and 95% CIs, and merge them. Statistically significant factors were included in the model, and stratified and assigned a corresponding score. Finally, a validation cohort from Yantai Qishan Hospital in 2021 was used to verify its predictive ability. Result: A total of 24 articles were included in the meta-analysis. The model includes six risk factors: age, hemorrhagic manifestations, encephalopathy, Scr and BUN. The analysis of lasso regression and multivariate logistic regression shows that model score is an independent risk factor (OR = 1.032, 95% CI 1.002-1.063, Conclusion: The prediction model for the fatal outcome of SFTS patients has shown positive outcomes.
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