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A nomogram to predict mortality in patients with severe fever with thrombocytopenia syndrome at the early stage—A multicenter study in China

Author

Listed:
  • Lin Wang
  • Gang Wan
  • Yi Shen
  • Zhenghua Zhao
  • Ling Lin
  • Wei Zhang
  • Rui Song
  • Di Tian
  • Jing Wen
  • Yongxiang Zhao
  • Xiaoli Yu
  • Li Liu
  • Yang Feng
  • Yuanni Liu
  • Chunqian Qiang
  • Jianping Duan
  • Yanli Ma
  • Ying Liu
  • Yanan Liu
  • Chong Chen
  • Ziruo Ge
  • Xingwang Li
  • Zhihai Chen
  • Tianli Fan
  • Wei Li

Abstract

Background: Severe fever with thrombocytopenia syndrome (SFTS) caused by the SFTS virus is an emerging infectious disease that was first identified in the rural areas of China in 2011. Severe cases often result in death due to multiple organ failure. To date, there are still numerous problems remain unresolved in SFTS, including unclear pathogenesis, lack of specific treatment, and no effective vaccines available. Aim: To analyze the clinical information of patients with early-stage SFTS and to establish a nomogram for the mortality risk. Methods: Between April 2011 and December 2018, data on consecutive patients who were diagnosed with SFTS were prospectively collected from five medical centers distributed in central and northeastern China. Multivariable Cox analyses were used to identify the factors independently associated with mortality. A nomogram for mortality was established using those factors. Results: During the study period, 429 consecutive patients were diagnosed with SFTS at the early stage of the disease (within 7 days of fever), among whom 69 (16.1%) died within 28 days. The multivariable Cox proportional hazard regression analysis showed that low lymphocyte percentage, early-stage encephalopathy, and elevated concentration of serum LDH and BUN were independent risk factors for fatal outcomes. Received-operating characteristic curves for 7-, 14-, and 28-days survival had AUCs of 0.944 (95% CI: 0.920–0.968), 0.924 (95% CI: 0.896–0.953), and 0.924 (95% CI: 0.895–0.952), respectively. Among low-risk patients, 6 patients died (2.2%). Among moderate-risk patients, 25 patients died (24.0%, hazard ratio (HR) = 11.957). Among high-risk patients, the mortality rate was 69.1% (HR = 57.768). Conclusion: We established a simple and practical clinical scoring system, through which we can identify critically ill patients and provide intensive medical intervention for patients as soon as possible to reduce mortality. Author summary: We established a SFTS nomogram scoring system, which is the first nomogram for this disease. According to this nomogram, patients were divided into three levels of mortality risk: low, moderate, and high. This scoring system is helpful to identify critically ill patients, allowing for early intervention and intensive care, which may contribute to reducing the mortality of SFTS.

Suggested Citation

  • Lin Wang & Gang Wan & Yi Shen & Zhenghua Zhao & Ling Lin & Wei Zhang & Rui Song & Di Tian & Jing Wen & Yongxiang Zhao & Xiaoli Yu & Li Liu & Yang Feng & Yuanni Liu & Chunqian Qiang & Jianping Duan & Y, 2019. "A nomogram to predict mortality in patients with severe fever with thrombocytopenia syndrome at the early stage—A multicenter study in China," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 13(11), pages 1-17, November.
  • Handle: RePEc:plo:pntd00:0007829
    DOI: 10.1371/journal.pntd.0007829
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    Cited by:

    1. Limin Yu & Alexandra Halalau & Bhavinkumar Dalal & Amr E Abbas & Felicia Ivascu & Mitual Amin & Girish B Nair, 2021. "Machine learning methods to predict mechanical ventilation and mortality in patients with COVID-19," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-18, April.

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