Journal Article

The Multidimensional Prognostic Index predicts incident delirium among hospitalized older patients with COVID-19: a multicenter prospective European study

Morganti, Wanda, Zieschang, Tania, von Arnim, Christine A. F., Polidori, M. Cristina, Custureri, Romina, Michalkova, Helena, Castagna, Alberto, Padovani, Alessandro, Seminerio, Emanuele, Sanchez‐Garcia, Elisabet, Azzini, Margherita, Pilotto, Alberto, Gruner, Heidi, Cenderello, Giovanni, Veronese, Nicola, Cruz‐Jentoft, Alfonso J., Custodero, Carlo, Topinkova, Eva

2024

Overview

Key summary points Aim Testing the role of the Multidimensional Prognostic Index (MPI), based on the Comprehensive Geriatric Assessment (CGA), in predicting the risk of incident delirium in hospitalized older patients with COVID-19. Findings The MPI showed a good accuracy in predicting incident delirium (AUC = 0.71). Its accuracy is higher than the ones of two validated predictive models (AWOL delirium risk-stratification score’s AUC = 0.63; Martinez Model’s AUC = 0.61; p < 0.0001 for both comparisons). Message The MPI is a sensitive tool for risk-stratification of the incident delirium in hospitalized older COVID-19 patients. Purpose 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. Methods 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). Results 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). Conclusions The MPI is a sensitive tool for early identification of older patients with incident delirium.

• Publisher: Springer International Publishing,Springer Nature B.V
• Subject: Accuracy / Age / Aged / Aged, 80 and over / Cognitive ability / Cognitive impairment / Comprehensive geriatric assessment / COVID-19 / COVID-19 - complications / COVID-19 - diagnosis / COVID-19 - epidemiology / Delirium / Delirium - diagnosis / Delirium - epidemiology / Delirium prediction / Dementia / Europe - epidemiology / Female / Frailty / Geriatric Assessment - methods / Geriatrics / Geriatrics and Gerontology / Geriatrics/Gerontology / Gerontology / Hospitalization / Hospitalization - statistics & numerical data / Humans / Incidence / Informed consent / Internal Medicine / Male / Medicine / Medicine & Public Health / Mortality / Multidimensional Prognostic Index / Older people / Polypharmacy / Prognosis / Prospective Studies / Research Paper / Risk Assessment / Risk Factors / SARS-CoV-2 / Systematic review