Establishment and validation of a prognostic nomogram for severe fever with thrombocytopenia syndrome: A retrospective observational study

Abstract

Background: Several scoring systems have been proposed to predict the risk of death due to severe fever with thrombocytopenia syndrome (STFS), but they have limitations. We developed a new prognostic nomogram for STFS-related death and compared its performance with previous scoring systems and the Acute Physiology and Chronic Health Evaluation score (APACHE II Score).

Methods: A total of 292 STFS patients were retrospectively enrolled between January 2016 and March 2023. Boruta's algorithm and backward stepwise regression were used to select variables for constructing the nomogram. Time-dependent receiver operating characteristic (ROC) curves and clinical decision curves were generated to compare the strengths of the nomogram with others.

Results: Age, Sequential Organ Failure Assessment Score (SOFA score), state of consciousness, continuous renal replacement therapy (CRRT), and D-dimer were significantly correlated with mortality in both univariate and multivariate analyses (P<0.05). We developed a nomogram using these variables to predict mortality risk, which outperformed the SFTS and APACHE II scores (Training ROC: 0.929 vs. 0.848 vs. 0.792; Validation ROC: 0.938 vs. 0.839 vs. 0.851; P<0.001). In the validation set, the SFTS model achieved an accuracy of 76.14%, a sensitivity of 95.31%, a specificity of 25.00%, a precision of 77.22%, and an F1 score of 85.32%. The nomogram showed a superior performance with an accuracy of 86.36%, a precision of 88.24%, a recall of 93.75%, and an F1 score of 90.91%.

Conclusion: Age, consciousness, SOFA Score, CRRT, and D-Dimer are independent risk factors for STFS-related death. The nomogram based on these factors has an excellent performance in predicting STFS-related death and is recommended for clinical practice.

Fig 1. Study flowchart.

Fig 2. Filtering of prognostic factors.

(A) Boruta variable selection graph; (B) Boruta iterative trajectory diagram.

Fig 3. Variable evaluation and construction of a prognostic nomogram.

(A) VIF values of less than 2 for each independent influencing factor; (B) MeanDecreaseGini and MeanDecreaseAccuracy analyses; (C) Nomogram scoring system. CRRT = Continuous Renal Replacement Therapy; SOFA score = Sequential Organ Failure Assessment Score; VIF = Variance Inflation Factor.

Fig 4. Time-dependent ROC curves comparing the nomogram, SFTS score, and APACHEII score in predicting the death risk in patients with SFTS.

(A) Training set; (B) Validation set.

Fig 5. Calibration plot of the nomogram predicting the death risk in patients with SFTS.

(A) Training set; (B) Validation set.

Fig 6. Accuracy comparison between the nomogram and SFTS score in the validation set.

(A) Nomogram; (B) SFTS score.

Fig 7. Decision curve comparison among the nomogram, SFTS score, and APACHE II score in predicting the death risk in patients with SFTS.

(A) Training set; (B) Validation set.