{"title":"ACCI could be a poor prognostic indicator for the in-hospital mortality of patients with SFTS.","authors":"Chen Gong, Xinjian Xiang, Baoyu Hong, Tingting Shen, Meng Zhang, Shichun Shen, Shenggang Ding","doi":"10.1017/S0950268823001930","DOIUrl":null,"url":null,"abstract":"<p><p>This study aims to evaluate the predictive role of age-adjusted Charlson comorbidity index (ACCI) scores for in-hospital prognosis of severe fever in thrombocytopenia syndrome (SFTS) patients. A total of 192 patients diagnosed with SFTS were selected as the study subjects. Clinical data were retrospectively collected. Receiver operating characteristic curves were used to evaluate the diagnostic value of ACCI for the mortality of SFTS patients, and Cox regression models were used to assess the association between predictive factors and prognosis. The 192 SFTS patients were divided into two groups according to the clinical endpoints (survivors/non-survivors). The results showed that the mortality of the 192 hospitalized SFTS patients was 26.6%. The ACCI score of the survivor group was significantly lower than that of the non-survivor group. Multivariate Cox regression analysis showed that the increased ACCI score was a significant predictor of poor prognosis in SFTS. Kaplan-Meier survival analysis showed that SFTS patients with an ACCI >2.5 had shorter mean survival times, indicating a poor prognosis. Our findings suggest that ACCI, as an easy-to-use clinical indicator, may offer a simple and feasible approach for clinicians to determine the severity of SFTS.</p>","PeriodicalId":11721,"journal":{"name":"Epidemiology and Infection","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10753457/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epidemiology and Infection","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1017/S0950268823001930","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 0
Abstract
This study aims to evaluate the predictive role of age-adjusted Charlson comorbidity index (ACCI) scores for in-hospital prognosis of severe fever in thrombocytopenia syndrome (SFTS) patients. A total of 192 patients diagnosed with SFTS were selected as the study subjects. Clinical data were retrospectively collected. Receiver operating characteristic curves were used to evaluate the diagnostic value of ACCI for the mortality of SFTS patients, and Cox regression models were used to assess the association between predictive factors and prognosis. The 192 SFTS patients were divided into two groups according to the clinical endpoints (survivors/non-survivors). The results showed that the mortality of the 192 hospitalized SFTS patients was 26.6%. The ACCI score of the survivor group was significantly lower than that of the non-survivor group. Multivariate Cox regression analysis showed that the increased ACCI score was a significant predictor of poor prognosis in SFTS. Kaplan-Meier survival analysis showed that SFTS patients with an ACCI >2.5 had shorter mean survival times, indicating a poor prognosis. Our findings suggest that ACCI, as an easy-to-use clinical indicator, may offer a simple and feasible approach for clinicians to determine the severity of SFTS.
期刊介绍:
Epidemiology & Infection publishes original reports and reviews on all aspects of infection in humans and animals. Particular emphasis is given to the epidemiology, prevention and control of infectious diseases. The scope covers the zoonoses, outbreaks, food hygiene, vaccine studies, statistics and the clinical, social and public-health aspects of infectious disease, as well as some tropical infections. It has become the key international periodical in which to find the latest reports on recently discovered infections and new technology. For those concerned with policy and planning for the control of infections, the papers on mathematical modelling of epidemics caused by historical, current and emergent infections are of particular value.