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. 2025 Jan 13;19(1):e0012793.
doi: 10.1371/journal.pntd.0012793. eCollection 2025 Jan.

Early therapy contributes to the normalization of platelet in patients with severe fever with thrombocytopenia syndrome during the convalescent phase

Affiliations

Early therapy contributes to the normalization of platelet in patients with severe fever with thrombocytopenia syndrome during the convalescent phase

Xiaoyu Xue et al. PLoS Negl Trop Dis. .

Abstract

Background: Platelet recovery was an important prognostic indicator in severe fever with thrombocytopenia syndrome (SFTS). This study focused on risk factors affecting platelet recovery in surviving SFTS patients, which can assist clinicians in the early screening of patients associated with a greater risk of mortality.

Method: We retrospectively analyzed the clinical data of SFTS patients admitted to Yantai Qishan Hospital throughout 2023. According to the Diagnosis and Treatment Guideline (2023 edition), the platelet recovery in 14 days was set as outcome. The multivariate Cox regression was used to identify independent risk factors affecting platelet recovery and the Kaplan-Meier was performed to evaluate the probability of 14-day platelet recovery, using receiver operating characteristic (ROC) curve and area under the curve (AUC) to measure the model's performance, with clinical benefit assessed by decision curve analysis (DCA).

Results: 168 SFTS patients were enrolled in the study, with 76.2% (128/168) achieving platelet (PLT) recovery within 14 days. Independent risk factors were baseline PLT > 90 × 109/L (HR: 7.929, 95%CI: 1.066-58.990, P = 0.043), days from onset to admission >6 days (HR: 0.444, 95%CI: 0.259-0.763, P = 0.003) and baseline prothrombin time (PT) >13 s (HR: 0.547, 95%CI: 0.373-0.800, P = 0.002), with an AUC of 0.745 (95% CI: 0.656-0.834, P < 0.001). DCA demonstrated that when the recovery probability beyond approximately 50%, the clinical net benefit from focusing on the PLT stratification model consistently surpassed that from the all-intervention model. The nomogram further visualized the model.

Conclusion: Early diagnosis and timely therapy contributed to recovery during convalescence in SFTS patients, with baseline PT as a strong predictor.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Flowchart of SFTS patients for inclusion in study analysis.
Abbreviations: SFTS: severe fever with thrombocytopenia syndrome, ROC: receiver operating characteristic, PLT: platelet.
Fig 2
Fig 2. Probability of PLT recovery in SFTS patients.
(A) The probability of PLT recovery estimated by the Kapla-Meier method. (B) Probability of PLT recovery by baseline platelet count. (C) Probability of PLT recovery by PT at baseline. (D) Probability of PLT recovery by the days from onset to admission. Abbreviations: PLT: platelet, PT: prothrombin time. SFTS: severe fever with thrombocytopenia syndrome.
Fig 3
Fig 3. Time-dependent receiver operating characteristic (ROC) curve of the Cox regression model for predicting the likelihood of PLT recovery within 14 days in SFTS patients, which led to a diagnostic yield of 74.5% measured by the area under the ROC curve (AUC) (95% CI,0.656–0.834, P < 0.001).
Abbreviations: CI: confidence interval, AUC: area under the curve, SFTS: severe fever with thrombocytopenia syndrome, ROC: receiver operating characteristic, PLT: platelet.
Fig 4
Fig 4. The nomogram predicted the PLT recovery rate of SFTS patients in the 14-day.
To use the nomogram, the value of an individual patient is located on each variable axis, and a line is drawn upward to determine the number of points received for the value of each variable. The sum of these numbers is located on the total point axis, and a line is drawn downward to the 14-day axes to determine the likelihood of PLT recovery. 0 points were assigned for PLT ≤ 30 × 109/L, PT > 13s, and days from onset to admission > 6 days, and 100 points were assigned for PLT > 90 × 109/L. Abbreviations: PLT: platelet, PT: prothrombin time, SFTS: severe fever with thrombocytopenia syndrome.
Fig 5
Fig 5. Decision curve analyses showed the clinical benefit of the different indexes.
The model-predicted probabilities of 14-day recovery were compared with PLT stratification-predicted probabilities of 14-day recovery. Solid lines indicate the net benefits of the predictive indexes across a range of threshold probabilities (black: Restoration model; orange: PLT stratification). The horizontal solid red line represents the assumption that no patient will experience the event, and the solid blue line indicates the assumption that all patients will experience the event. Abbreviations: PLT: platelet.

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