ArticleOpen forum infectious diseases2025
Retrospective Analysis of Severe Fever With Thrombocytopenia Syndrome and Construction of a Nomogram Prediction Model for Mortality Risk Factors.
Article in Open forum infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Clinical Predictors of Mortality in Severe Fever with Thrombocytopenia Syndrome: An Updated Systematic Review and Meta-Analysis.Pathogens (Basel, Switzerland) · 2026Pooled it
- 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
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging zoonotic infectious disease caused by the SFTS virus and is characterized by a high mortality rate. The primary objective of this study was to investigate high-mortality risk factors in SFTS and to create a nomogram model for personalized prediction. Methods: A total of 523 patients with SFTS who were admitted to the Second Hospital of Nanjing, Nanjing University of Chinese Medicine, between January 2020 and December 2023 were retrospectively analyzed: 75 cases were classified in the death group and 448 cases in the survival group. Development of a predictive nomogram model was based on the independent risk factors that were stepwise screened through univariate analysis, LASSO analysis (least absolute shrinkage and selection operator), and multivariate logistic regression analysis. Results: Based on stepwise variable screening by univariate analysis, LASSO analysis, and multivariate logistic regression, the following were independent mortality risk factors in patients with SFTS: age (odds ratio [OR], 1.06; 95% CI, 1.03-1.10; Conclusions: A nomogram model consisting of 7 risk factors was successfully constructed, which can be used to predict SFTS mortality risk factors early.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.