Predictive value of the geriatric nutrition risk index for postoperative delirium in elderly patients undergoing cardiac surgery

医学 交货地点 逻辑回归 混淆 接收机工作特性 优势比 内科学 谵妄 心脏外科 虚弱指数 外科 重症监护医学 农学 生物
作者
Zhiqiang Chen,Quanshui Hao,Rao Sun,Yanjing Zhang,Hui Fu,Shile Liu,Chenglei Luo,Hanwen Chen,Yiwen Zhang
出处
期刊:CNS Neuroscience & Therapeutics [Wiley]
卷期号:30 (2) 被引量:23
标识
DOI:10.1111/cns.14343
摘要

Abstract Aims The aims of the study were to determine the relationship between preoperative geriatric nutritional risk index (GNRI) and the occurrence of postoperative delirium (POD) in elderly patients after cardiac surgery and to evaluate the additive value of GNRI for predicting POD. Methods The data were extracted from the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC‐IV) database. Patients who underwent cardiac surgery and were aged 65 or older were included. The relationship between preoperative GNRI and POD was investigated using logistic regression. We determined the added predictive value of preoperative GNRI for POD by measuring the changes in the area under the receiver operating characteristic curve (AUC) and calculating the net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results A total of 4286 patients were included in the study, and 659 (16.1%) developed POD. Patients with POD had significantly lower GNRI scores than patients without POD (median 111.1 vs. 113.4, p < 0.001). Malnourished patients (GNRI ≤ 98) had a significantly higher risk of POD (odds ratio, 1.83, 90% CI, 1.42–2.34, p < 0.001) than those without malnutrition (GNRI > 98). This correlation remains after adjusting for confounding variables. The addition of GNRI to the multivariable models slightly but not significantly increases the AUCs (all p > 0.05). Incorporating GNRI increases NRIs in some models and IDIs in all models (all p < 0.05). Conclusions Our results showed a negative association between preoperative GNRI and POD in elderly patients undergoing cardiac surgery. The addition of GNRI to POD prediction models may improve their predictive accuracy. However, these findings were based on a single‐center cohort and will need to be validated in future studies involving multiple centers.

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