Clinical Characteristics and a Novel Prediction Nomogram (EASTAR) for Patients with Hemorrhagic Fever with Renal Syndrome: A Multicenter Retrospective Study.

IF 2.8 4区 医学 Q2 INFECTIOUS DISEASES
Ke Ma, Ting Wu, Wei Guo, Jun Wang, Quan Ming, Jun Zhu, Hongwu Wang, Guang Chen, Xiaojing Wang, Weiming Yan, Xiaoping Luo, Tao Chen, Qin Ning
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引用次数: 0

Abstract

Background: The fatality rate of hemorrhagic fever with renal syndrome (HFRS), due to hantavirus transmitted by rodents, ranges from 1% to 12%. This study aims to delineate the clinical and laboratory characteristics of HFRS, identify factors associated with disease severity, and construct and validate a nomogram for prognosis prediction of HFRS in the central part of China.

Methods: Out of 598 HFRS patients diagnosed via serology tests from four hospitals in Hubei Province, 551 were included. Clinical data were gathered and analyzed, followed by logistic univariate and multivariate analyses to identify independent prognostic factors. A nomogram was developed and validated to forecast the patient's prognosis.

Results: Vaccination led to a notable drop in HFRS incidence from 2018 to 2019, and seasonal trends exhibited bimodal changes with peaks from May to July and November to January. The 30-day mortality rate was 4.17% (23/551). Red blood cell count (RBC), age, two-stage overlap, qSOFA ≥ 2, aspartate aminotransferase (AST), and three-stage overlap were identified as independent prognostic factors. A predictive risk classification system using a nomogram chart was developed, and Kaplan-Meier curves indicated that the new system accurately distinguished 30-day mortality among the three risk groups.

Conclusions: The risk score (EASTAR) system demonstrated good predictive performance for prognostic prediction, and it can be applied to quickly screen patients who require ICU admission.

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来源期刊
Tropical Medicine and Infectious Disease
Tropical Medicine and Infectious Disease Medicine-Public Health, Environmental and Occupational Health
CiteScore
3.90
自引率
10.30%
发文量
353
审稿时长
11 weeks
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