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Predicting prognosis of heart failure using common malnutrition assessment tools: A systematic review and meta-analysis  ( SCI-EXPANDED收录)   被引量:7

文献类型:期刊文献

英文题名:Predicting prognosis of heart failure using common malnutrition assessment tools: A systematic review and meta-analysis

作者:Ni, Jianchao[1];Fang, Yuanyuan[1];Zhang, Jianhai[1];Chen, Xiaoyan[2]

机构:[1]Shaoxing Univ, Dept Geriatr, Affiliated Hosp, Shaoxing City, Peoples R China;[2]Zhuji Peoples Hosp Zhejiang Prov, Dept Gen Phys, 9 Jianmin Rd, Zhuji 311800, Zhejiang, Peoples R China

年份:2022

卷号:67

期号:4

起止页码:157

外文期刊名:SCOTTISH MEDICAL JOURNAL

收录:SCI-EXPANDED(收录号:WOS:000849063000001)、、WOS

语种:英文

外文关键词:Heart failure; malnutrition assessment; CONUT; GNRI; PNI

外文摘要:Background and aims COUNT score, PNI score, and GNRI scores are associated with cardiovascular events. This review identifies the most accurate malnutrition assessment tools based on these scores in predicting mortality and readmission outcomes in HF patients. Material and Methods PubMed via MEDLINE, EMBASE were searched to identify studies assessing malnutrition using CONUT, PNI and GNRI. A meta-analysis was carried out to pool the hazard ratios on mortality and readmission rates. The methodological quality was assessed using the Newcastle-Ottawa Scale. Results The mortality in HF patients with malnutrition assessed by CONUT showed pooled HR of 1.23. HF patients with all severe, moderate, and mild risk of malnutrition showed mortality with HR 3.56, 2.71 and 1.57 respectively. For malnutrition assessed with GNRI, HF patients with all severe, moderate, and mild risk of malnutrition showed mortality with HR 4.17, 2.73 and 1.73 respectively. No significance difference in association of CONUT score with pooled HR of readmission rate was observed HR 0.99. With PNI, HF patients with all severe and moderate risk of malnutrition showed mortality with HR 2.14 and HR 1.68 respectively, although they failed to achieve significance. Conclusion CONUT and GNRI are the superior prognostic indicator than PNI in prediction of mortality associated with risk of malnutrition.

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