Department of Geriatric Care, Neurology and Rehabilitation, Galliera Hospital, Genoa, Italy.
Department of Interdisciplinary Medicine, "Aldo Moro" University of Bari, Bari, Italy.
Eur Geriatr Med. 2024 Aug;15(4):961-969. doi: 10.1007/s41999-024-00987-y. Epub 2024 Jun 15.
Incident delirium is a frequent complication among hospitalized older people with COVID-19, associated with increased length of hospital stay, higher morbidity and mortality rates. Although delirium is preventable with early detection, systematic assessment methods and predictive models are not universally defined, thus delirium is often underrated. In this study, we tested the role of the Multidimensional Prognostic Index (MPI), a prognostic tool based on Comprehensive Geriatric Assessment, to predict the risk of incident delirium.
Hospitalized older patients (≥ 65 years) with COVID-19 infection were enrolled (n = 502) from ten centers across Europe. At hospital admission, the MPI was administered to all the patients and two already validated delirium prediction models were computed (AWOL delirium risk-stratification score and Martinez model). Delirium occurrence during hospitalization was ascertained using the 4A's Test (4AT). Accuracy of the MPI and the other delirium predictive models was assessed through logistic regression models and the area under the curve (AUC).
We analyzed 293 patients without delirium at hospital admission. Of them 33 (11.3%) developed delirium during hospitalization. Higher MPI score at admission (higher multidimensional frailty) was associated with higher risk of incident delirium also adjusting for the other delirium predictive models and COVID-19 severity (OR = 12.72, 95% CI = 2.11-76.86 for MPI-2 vs MPI-1, and OR = 33.44, 95% CI = 4.55-146.61 for MPI-3 vs MPI-1). The MPI showed good accuracy in predicting incident delirium (AUC = 0.71) also superior to AWOL tool, (AUC = 0.63) and Martinez model (AUC = 0.61) (p < 0.0001 for both comparisons).
The MPI is a sensitive tool for early identification of older patients with incident delirium.
在感染 COVID-19 的住院老年患者中，谵妄是一种常见并发症，与住院时间延长、更高的发病率和死亡率相关。尽管谵妄可以通过早期发现来预防，但系统的评估方法和预测模型并未得到普遍定义，因此谵妄常常被低估。在这项研究中，我们测试了多维预后指数（MPI）的作用，MPI 是一种基于全面老年评估的预后工具，用于预测新发谵妄的风险。
从欧洲的 10 个中心招募了患有 COVID-19 感染的住院老年患者（≥65 岁；n=502）。在入院时，所有患者均接受了 MPI 评估，并计算了两个已验证的谵妄预测模型（AWOL 谵妄风险分层评分和 Martinez 模型）。使用 4A's Test（4AT）确定住院期间谵妄的发生情况。通过逻辑回归模型和曲线下面积（AUC）评估 MPI 和其他谵妄预测模型的准确性。
我们分析了 293 名入院时无谵妄的患者。其中 33 名（11.3%）在住院期间发生了谵妄。入院时更高的 MPI 评分（更高的多维脆弱性）与新发谵妄的风险增加相关，即使在调整了其他谵妄预测模型和 COVID-19 严重程度后也是如此（OR=12.72，95%CI=2.11-76.86，MPI-2 与 MPI-1 相比；OR=33.44，95%CI=4.55-146.61，MPI-3 与 MPI-1 相比）。MPI 在预测新发谵妄方面具有良好的准确性（AUC=0.71），优于 AWOL 工具（AUC=0.63）和 Martinez 模型（AUC=0.61）（p<0.0001，两者比较）。
MPI 是一种早期识别新发谵妄的老年患者的敏感工具。
