摘要
目的系统评价控制营养状态(controlling nutritional status,CONUT)评分对脑卒中短期神经功能及临床结局的预测价值。方法计算机检索Cochrane library、PubMed、Web of Science、Embase、中国知网、万方数据知识服务平台、维普网、中国生物医学文献数据库的相关文献,查找从建库至2023年4月11日有关使用CONUT评分评价脑卒中患者营养状况并进行随访的研究。由2名研究者独立检索并筛选文献,运用纽卡斯尔-渥太华质量评估表(Newcastle-Ottawa scale,NOS)进行质量评价,采用Stata 15.0软件进行Meta分析。结果共纳入12篇文献,均为高质量文献。Meta分析结果显示,高CONUT评分(≥2分)与较差功能结局密切相关(OR=1.41,95%CI:1.25~1.60,P<0.001,I 2=49.4%),与病死率(OR=2.85,95%CI:2.03~4.00,P<0.001,I 2=0)增加相关。结论高CONUT评分可能是脑卒中患者神经功能恢复状况和生存结局的预测因子,但其机制尚不明确,有待于进一步研究证实。
Objective To systematically evaluate the predictive value of controlling nutritional status(CONUT)score for short-term neurological function and clinical outcome of stroke.Methods Cochrane library,PubMed,Web of Science,Embase,CNKI,Wanfang,VIP,and CBM were searched by computer to find studies on the use of CONUT score to evaluate the nutritional status and follow-up of stroke patients from the establishment of the database to April 11,2023.Literature was searched and screened independently by two researchers.The Newcastle-Ottawa scale(NOS)was used to evaluate the quality of the included studies.Stata 15.0software was used for Meta-analysis.Results A total of 12 literatures were included,all of which were high quality.Meta-analysis results showed that high CONUT score(≥2)was strongly associated with poorer functional outcomes(OR=1.41,95%CI:1.25-1.60,P<0.001,I 2=49.4%),and associated with increased mortality(OR=2.85,95%CI:2.03-4.00,P<0.001,I 2=0)increase.Conclusion High CONUT score may be a predictor of neurological recovery status and survival outcome in patients after stroke,and the prognostic mechanism of CONUT score in stroke patients is unclear and needs to be confirmed by further studies.
作者
凌克玉
郭子宁
陈述凡
李海涵
徐玲
曾司甯
朱晓萍
LING Keyu;GUO Zining;CHEN Shufan(Tongji University School of Medicine,Shanghai 200092,China)
出处
《医学研究杂志》
2024年第8期34-41,共8页
Journal of Medical Research
基金
国家自然科学基金资助项目(72074168)
上海市护理学会科研项目(2022MS-B06)。
关键词
脑卒中
控制营养状态
预后结局
预测价值
META分析
Stroke
Controlling nutritional status
Prognostic outcome
Predictive value
Meta-analysis
