Literature DB >> 25043078

Comparison of Charlson's weighted index of comorbidities with the chronic health score for the prediction of mortality in septic patients.

Yunliang Cui1, Tao Wang2, Jun Bao3, Zhaotao Tian1, Zhaofen Lin3, Dechang Chen4.   

Abstract

BACKGROUND: Comorbidity is one of the most important determinants of short-term and long-term outcomes in septic patients. Charlson's weighted index of comorbidities (WIC) and the chronic health score (CHS), which is a component of the acute physiology and chronic health evaluation (APACHE) II, are two frequently-used measures of comorbidity. In this study, we assess the performance of WIC and CHS in predicting the hospital mortality of intensive care unit (ICU) patients with sepsis.
METHODS: A total of 338 adult patients with sepsis were admitted to a multisystem ICU between October 2010 and August 2012. Clinical data were collected, including age, gender, underlying diseases, key predisposing causes, severity-of-sepsis, and hospital mortality. The APACHE II, CHS, acute physiology score (APS), sequential organ failure assessment (SOFA) and WIC scores were assessed within the first 24 hours of admission. Univariate and multiple Logistic regression analyses were used to compare the performance of WIC and CHS. The area under the receiver operating characteristic curve (AUC) was used to predict hospital mortality over classes of risk.
RESULTS: Of all the enrolled patients, 224 patients survived and 114 patients died. The surviving patients had significantly lower WIC, CHS, APACHE II, and SOFA scores than the non-surviving patients (P < 0.05). Combining WIC or CHS with other administrative data showed that the hospital mortality was significantly associated with age, severe sepsis, key predisposing causes such as pneumonia, a history of underlying diseases such as hypertension and congestive cardiac failure, and WIC, CHS and APS scores (P < 0.05). The AUC for the hospital mortality were 0.564 (95% confidence interval (CI) 0.496-0.631) of CHS, 0.663 (95% CI 0.599-0.727) of WIC, 0.770 (95% CI 0.718-0.822) of APACHE II, 0.856 (95% CI 0.815-0.897) of the CHS combined with other administrative data, and 0.857 (95% CI 0.817-0.897) of the WIC combined with other administrative data. The diagnostic value of WIC was better than that of CHS (P = 0.0015).
CONCLUSIONS: The WIC and CHS scores might be independent determinants for hospital mortality among ICU patients with sepsis. WIC might be an even better predictor of the mortality of septic patients with comorbidities than CHS.

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Year:  2014        PMID: 25043078

Source DB:  PubMed          Journal:  Chin Med J (Engl)        ISSN: 0366-6999            Impact factor:   2.628


  5 in total

1.  APACHE III Outcome Prediction in Patients Admitted to the Intensive Care Unit with Sepsis Associated Acute Lung Injury.

Authors:  Zhongheng Zhang; Kun Chen; Lin Chen
Journal:  PLoS One       Date:  2015-09-30       Impact factor: 3.240

2.  Dynamic Change of Red Cell Distribution Width Levels in Prediction of Hospital Mortality in Chinese Elderly Patients with Septic Shock.

Authors:  Xue-Feng Ju; Fei Wang; Li Wang; Xiao Wu; Ting-Ting Jiang; Da-Li You; Bing-Hua Yang; Jian-Jun Xia; Shan-You Hu
Journal:  Chin Med J (Engl)       Date:  2017-05-20       Impact factor: 2.628

Review 3.  Why Septic Patients Remain Sick After Hospital Discharge?

Authors:  Raquel Bragante Gritte; Talita Souza-Siqueira; Rui Curi; Marcel Cerqueira Cesar Machado; Francisco Garcia Soriano
Journal:  Front Immunol       Date:  2021-02-15       Impact factor: 7.561

4.  Noninvasive Real-Time Mortality Prediction in Intensive Care Units Based on Gradient Boosting Method: Model Development and Validation Study.

Authors:  Huizhen Jiang; Longxiang Su; Hao Wang; Dongkai Li; Congpu Zhao; Na Hong; Yun Long; Weiguo Zhu
Journal:  JMIR Med Inform       Date:  2021-03-25

5.  Risk factors for death in septic shock: A retrospective cohort study comparing trauma and non-trauma patients.

Authors:  Sophie Medam; Laurent Zieleskiewicz; Gary Duclos; Karine Baumstarck; Anderson Loundou; Julie Alingrin; Emmanuelle Hammad; Coralie Vigne; François Antonini; Marc Leone
Journal:  Medicine (Baltimore)       Date:  2017-12       Impact factor: 1.817

  5 in total

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