A prediction model to discriminate severe fever with thrombocytopenia syndrome with hemorrhagic fever with renal syndrome
<p>The Bunyavirales order encompasses hantavirus and severe fever with thrombocytopenia syndrome virus (SFTSV), which could cause hemorrhagic fever with renal syndrome (HFRS) and severe fever with thrombocytopenia syndrome (SFTS), respectively. Both are types of viral hemorrhagic fever (VHF),...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , , , , |
| منشور في: |
2025
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| الوسوم: |
إضافة وسم
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| الملخص: | <p>The Bunyavirales order encompasses hantavirus and severe fever with thrombocytopenia syndrome virus (SFTSV), which could cause hemorrhagic fever with renal syndrome (HFRS) and severe fever with thrombocytopenia syndrome (SFTS), respectively. Both are types of viral hemorrhagic fever (VHF), posing challenges for early differentiation. We focused on identifying predictors for two diseases, assisting clinicians to make diagnosis.</p> <p>We conducted a retrospective analysis of clinical records from patients with SFTS and HFRS patients who were hospitalized at Qingdao No. 6 People’s Hospital and Yantai Qishan Hospital between 2021 and 2023. Independent factors were explored by logistic regression and Lasso regression analysis, following a model was established. The model’s performance was carried out by the receiver operating characteristic curve (ROC) and the area under the curve (AUC), with predictors visualized by nomogram and clinical benefit assessed by decision curve analysis.</p> <p>Our study included 129 SFTS patients and 89 HFRS patients. Independent predictors included headache (OR: 0.098, 95% CI: 0.015–0.624, <i>p</i> = 0.014), conjunctival congestion (OR: 0.021, 95% CI: 0.002–0.253, <i>p</i> = 0.002), mucosal hemorrhage (OR: 0.003, 95% CI: 0.000–0.049, <i>p </i>< 0.001), white blood cell count (WBC): 4–10 (OR: 0.019, 95% CI: 0.002–0.186, <i>p</i> = 0.001), WBC > 10 (OR: 0.011, 95% CI: 0.001–0.132, <i>p</i> < 0.001), CD4+ T cells ≥500 (OR: 0.013, 95% CI: 0.001–0.127, <i>p</i> < 0.001). WBC had the strongest predictive power (AUC: 0.916, <i>p </i>< 0.001). The model had optimal predictive ability and clinical net benefit, with an AUC of 0.988.</p> <p>Effective predictors were CD4+ T cells, WBC (elevated in HFRS, decreased in SFTS), headache and hemorrhage symptoms.</p> |
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