ArticleBMC infectious diseases2024
Establishment and validation of a clinical risk scoring model to predict fatal risk in SFTS hospitalized patients.
Article in BMC infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- A clinical scoring system for the early identification of superinfections in patients with severe fever with thrombocytopenia syndrome: An ambispective multicentre cohort study.PLoS neglected tropical diseases · 2026Article
- Predictive Value of Admission Renal Injury-Related Indicators for Fatal Outcomes in Patients with Severe Fever with Thrombocytopenia Syndrome.Current medical science · 2026Article
- Construction of a novel prognostic model for severe fever with thrombocytopenia syndrome patients based on inflammatory indicators.BMC infectious diseases · 2026Article
- Standardized LDH-to-lymphocyte ratio improves early mortality prediction in severe fever with thrombocytopenia syndrome: A 15-day competing-risk bedside model.PLoS neglected tropical diseases · 2026Article
- Machine learning models for early mortality prediction in severe fever with thrombocytopenia syndrome.iScience · 2026Article
- Development and Validation of a Novel Predictive Model and Simplified Clinical Indicator for Mortality in Severe Fever with Thrombocytopenia Syndrome Patients.Infection and drug resistance · 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
- A novel prognostic nomogram for elderly patients with severe fever with thrombocytopenia syndrome.BMC geriatrics · 2025Article
- Prediction of Mortality by Clinical Laboratory Parameters in Severe Fever with Thrombocytopenia Syndrome: A Meta-Analysis.Tropical medicine and infectious disease · 2025Review
- Dynamic biomarkers and Cox regression with time-dependent covariate for mortality prediction in severe fever with thrombocytopenia syndrome.Scientific reports · 2025Article
- Fatal risk factors and the efficacy of glucocorticoid therapy in severe fever with thrombocytopenia syndrome: a multicenter retrospective cohort study.Frontiers in cellular and infection microbiology · 2025Article
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Authors and funding
9 authors.
Funding
Abstract
backgroundSevere fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infection with a high case fatality rate. Significant gaps remain in studies analyzing the clinical characteristics of fatal cases.
methodsFrom January 2017 to June 2023, 427 SFTS cases were included in this study. A total of 67 variables about their demographic, clinical, and laboratory data were collected. Univariate logistic regression and the least absolute shrinkage and selection operator (LASSO) method was used to screen predictors from the cohort. Multivariate logistic regression was used to identify independent predictors and nomograms were developed. Calibration, decision curves and area under the curve (AUC) were used to assess model performance.
resultsThe multivariate logistic regression analysis screened out the four most significant factors, including age > 70 years (p = 0.001, OR = 2.516, 95% CI 1.452-4.360), elevated serum PT (p < 0.001, OR = 1.383, 95% CI 1.143-1.673), high viral load (p < 0. 001, OR = 1.496, 95% CI 1.290-1.735) and high level of serum urea (> 8.0 μmol/L) (p < 0.001, OR = 4.433, 95% CI 1.888-10.409). The AUC of the nomogram based on these four factors was 0.813 (95% CI, 0.758-0.868). The bootstrap resampling internal validation model performed well, and decision curve analysis indicated a high net benefit.
conclusionsThe nomogram based on age, elevated PT, high serum urea level, and high viral load can be used to help early identification of SFTS patients at risk of fatality.
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