Retrospective Analysis of Severe Fever With Thrombocytopenia Syndrome and Construction of a Nomogram Prediction Model for Mortality Risk Factors

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; P < .001), hemorrhagic symptoms (OR, 3.39; 95% CI, 1.31-8.78; P = .012), neurologic symptoms (OR, 4.89; 95% CI, 2.72-8.77; P < .001), platelet count (OR, 0.99; 95% CI, .98-.99; P = .045), prothrombin time (OR, 1.32; 95% CI, 1.11-1.56; P = .001), activated partial thromboplastin time (OR, 1.02; 95% CI, 1.01-1.03; P = .007), and viral load ≥10⁷copies/mL (OR, 2.66; 95% CI, 1.36-5.20; P = .004). The area under the curve (0.87; 95% CI, .832-.909) showed excellent predictive power. Calibration curves showed the accuracy of the assessed nomograms. Decision curve analysis results showed a greater net benefit when the threshold probability of patient death was between 0.02 and 0.75.

Conclusions: A nomogram model consisting of 7 risk factors was successfully constructed, which can be used to predict SFTS mortality risk factors early.

Keywords: SFTS; epidemiological; nomogram prediction model; retrospective analysis; risk factors.

Figure 1.

Flowchart of the study process. Abbreviations: D, death; LASSO, least absolute shrinkage and selection operator; S, survival; SFTS, severe fever with thrombocytopenia syndrome.

Figure 2.

Yearly distribution of severe fever with thrombocytopenia syndrome cases from 2020 to 2023. Abbreviations: D, death; S, survival.

Figure 3.

Monthly distribution of SFTS cases from 2020 to 2023. The horizontal axis represents January to December from 2020 to 2023. The left vertical axis represents the counts of SFTS cases by year. The right vertical axis represents the total cases in the 2021–2023 period. Abbreviations: SFTS, severe fever with thrombocytopenia syndrome.

Figure 4.

LASSO regression chart of 13 risk factors associated with SFTS death in patients. A, The λ value and coefficient of 13 variables that match the trend chart. B, The correlation between the LASSO regression coefficient and the λ value. The log(λ) value at λ minimum is shown on both plots by the intersection of the left-most vertical dashed line and the log(λ) axis, while the log(λ) value at 1-SE λ is represented by the intersection of the right-most vertical dashed line and the log(λ) axis. Error bars indicate 95% CI. Abbreviations: LASSO, least absolute shrinkage and selection operator; SFTS, severe fever with thrombocytopenia syndrome.

Figure 5.

Nomogram model for predicting mortality risk for patients with SFTS. A score is obtained by drawing a vertical line upward from the position of each independent predictor. The total points are calculated by adding the scores of the 7 predictors. A vertical line is drawn downward from the position of the total points on the horizontal axis of total points to obtain the probability value on risk of SFTS death. This is the risk of death for patients with SFTS. Viral load indicates ≥107 copies/mL. Abbreviations: APTT, activated partial thromboplastin time; HS, hemorrhagic symptoms; NS, neuropsychiatric symptoms; PT, prothrombin time; SFTS, severe fever with thrombocytopenia syndrome.

Figure 6.

The performance evaluation of the nomogram. A, The area under the curve (AUC) of the nomogram. B, The calibration curve of the nomogram. C, The decision curve analysis of the nomogram.