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

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2024年6月15日

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Wanda Morganti,
Carlo Custodero,
Nicola Veronese,
Eva Topinkova,
Helena Michalkova,
M. Cristina Polidori,
Alfonso J. Cruz‐Jentoft,
Christine A. F. von Arnim,
Margherita Azzini,
Heidi Gruner,
Alberto Castagna,
Giovanni Cenderello,
Romina Custureri,
Emanuele Seminerio,
Tania Zieschang,
Alessandro Padovani,
Elisabet Sanchez‐Garcia,
Alberto Pilotto,
Mario Barbagallo,
Marina Barbagelata,
Simone Dini,
Naima Madlen Diesner,
Marilia Fernandes,
Federica Gandolfo,
Sara Garaboldi,
Clarissa Musacchio,
Andrea Pilotto,
Lena Pickert,
Silvia Podestà,
Giovanni Ruotolo,
Katiuscia Sciolè,
Julia Schlotmann

摘要

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.