ArticleJournal of Korean medical science2020
Clinical Score System to Differentiate Severe Fever with Thrombocytopenia Syndrome Patients from Patients with Scrub Typhus or Hemorrhagic Fever with Renal Syndrome in Korea.
Article in Journal of Korean medical science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- The role of toll-like receptor 7 signaling in mice infected by severe fever with thrombocytopenia syndrome virus.Scientific reports · 2026Article
- A prediction model to discriminate severe fever with thrombocytopenia syndrome with hemorrhagic fever with renal syndrome.Annals of medicine · 2025Article
- Biomarkers for Early Predicting In-Hospital Mortality in Severe Fever with Thrombocytopenia Syndrome and Differentiating It from Hemorrhagic Fever with Renal Syndrome.Infection and drug resistance · 2025Article
- Double-Stranded RNA-Based Method for Diagnosing Severe Fever with Thrombocytopenia.Journal of clinical medicine · 2024Article
- Clinical Differentiation of Severe Fever with Thrombocytopenia Syndrome from Japanese Spotted Fever.Viruses · 2022Article
- Pathogenicity of severe fever with thrombocytopenia syndrome virus in mice regulated in type I interferon signaling: Severe fever with thrombocytopenia and type I interferon.Laboratory animal research · 2020Article
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Authors and funding
18 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSevere fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with high mortality in East Asia. This study aimed to develop, for primary care providers, a prediction score using initial symptoms and basic laboratory blood tests to differentiate between SFTS and other endemic zoonoses in Korea.
methodsPatients aged ≥ 18 years diagnosed with endemic zoonoses during a 3-year period (between January 2015 and December 2017) were retrospectively enrolled from 4 tertiary university hospitals. A prediction score was built based on multivariate logistic regression analyses.
resultsOf 84 patients, 35 with SFTS and 49 with other endemic zoonoses were enrolled. In multivariate logistic regression analysis, independent predictors of SFTS included neurologic symptoms (odds ratio [OR], 12.915; 95% confidence interval [CI], 2.173-76.747), diarrhea (OR, 10.306; 95% CI, 1.588-66.895), leukopenia (< 4,000/mm³) (OR, 19.400; 95% CI, 3.290-114.408), and normal C-reactive protein (< 0.5 mg/dL) (OR, 24.739; 95% CI, 1.812-337.742). We set up a prediction score by assigning one point to each of these four predictors. A score of ≥ 2 had 82.9% sensitivity (95% CI, 71.7%-87.5%) and 95.9% specificity (95% CI, 88.0%-99.2%). The area under the curve of the clinical prediction score was 0.950 (95% CI, 0.903-0.997).
conclusionThis study finding suggests a simple and useful scoring system to predict SFTS in patients with endemic zoonoses. We expect this strategic approach to facilitate early differentiation of SFTS from other endemic zoonoses, especially by primary care providers, and to improve the clinical outcomes.
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