Suppr超能文献

CONUT 评分可预测住院时间和长新冠风险。

The CONUT score predicts the length of hospital stay and the risk of long COVID.

机构信息

Department of Cardiology. Fujian Heart Medical Center. Fujian Institute of Coronary Heart Disease. Fujian Medical University Union Hospital. Fujian Medical University.

出版信息

Nutr Hosp. 2024 Feb 15;41(1):138-144. doi: 10.20960/nh.04656.

Abstract

Objective: the Controlling Nutritional Status (CONUT) score is an objective tool widely used to assess nutritional status of patients. We aimed to investigate the value of CONUT score on predicting length of hospital stay (LOS) and the risk of long COVID in patients with COVID-19. Methods: a total of 151 patients with COVID-19 were enrolled for analysis. Patients were followed up for two years from three months after the onset of SARS-CoV-2 infection. CONUT score was calculated on admission. The correlation between CONUT score and LOS were assessed by Spearman's rank correlation coefficient and multivariate linear analysis. The association between different CONUT grade and long COVID was evaluated by Kaplan-Meier survival curves with log-rank test and Cox proportional hazard models. Results: Spearman's rank correlation coefficient showed that CONUT scores were positively correlated with LOS (r = 0.469, p < 0.001). Multivariate linear analysis showed that CONUT score is the only independent determinant of LOS (B 2.055, 95 % CI: 1.067-3.043, p < 0.001). A total of 53 (35.10 %) patients with long COVID were identified. Kaplan-Meier cumulative survival curves and Cox proportional hazards analyses showed that the incidence of long COVID in patients with a higher CONUT score was significantly higher than in patients with lower CONUT score (p < 0.001). Conclusions: higher CONUT score predicts longer LOS and the risk of long COVID in patients with COVID-19. The CONUT score might be useful for risk stratification in COVID-19 patients and help to develop new nutritional treatment strategies for long COVID.

摘要

目的

控制营养状况(CONUT)评分是一种广泛用于评估患者营养状况的客观工具。我们旨在研究 CONUT 评分在预测 COVID-19 患者住院时间(LOS)和长新冠风险中的价值。

方法

共纳入 151 例 COVID-19 患者进行分析。患者自 SARS-CoV-2 感染后三个月开始随访两年。入院时计算 CONUT 评分。采用 Spearman 秩相关系数和多变量线性分析评估 CONUT 评分与 LOS 的相关性。采用 Kaplan-Meier 生存曲线和对数秩检验及 Cox 比例风险模型评估不同 CONUT 分级与长新冠的关系。

结果

Spearman 秩相关系数显示 CONUT 评分与 LOS 呈正相关(r = 0.469,p < 0.001)。多变量线性分析显示 CONUT 评分是 LOS 的唯一独立决定因素(B 2.055,95%CI:1.067-3.043,p < 0.001)。共确定 53 例(35.10%)长新冠患者。Kaplan-Meier 累积生存曲线和 Cox 比例风险分析显示,CONUT 评分较高的患者长新冠发生率明显高于 CONUT 评分较低的患者(p < 0.001)。

结论

较高的 CONUT 评分可预测 COVID-19 患者 LOS 延长和长新冠风险。CONUT 评分可能有助于 COVID-19 患者的风险分层,并有助于为长新冠制定新的营养治疗策略。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验