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

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  • Kai Yang
  • Yu Wang
  • Jiepeng Huang
  • Lingyan Xiao
  • Dongyang Shi
  • Daguang Cui
  • Tongyue Du
  • Yishan Zheng

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

Suggested Citation

  • Kai Yang & Yu Wang & Jiepeng Huang & Lingyan Xiao & Dongyang Shi & Daguang Cui & Tongyue Du & Yishan Zheng, 2024. "Establishment and validation of a prognostic nomogram for severe fever with thrombocytopenia syndrome: A retrospective observational study," PLOS ONE, Public Library of Science, vol. 19(10), pages 1-17, October.
    • Handle: RePEc:plo:pone00:0311924
    DOI: 10.1371/journal.pone.0311924
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    References listed on IDEAS

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    1. Kursa, Miron B. & Rudnicki, Witold R., 2010. "Feature Selection with the Boruta Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i11).
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