Background: prediction of length of stay (LOS) may be useful to optimise care plans to reduce the negative outcomes relatedto hospitalisation. Objective: to evaluate whether the Multidimensional Prognostic Index (MPI), based on a Comprehensive Geriatric Assessment(CGA), may predict LOS in hospitalised older patients. Design: prospective multicentre cohort study. Setting: twenty Geriatrics Units. Participants: patients aged 65 and older consecutively admitted to Geriatrics Units. Measurement: at admission, the CGA-based MPI was calculated by using a validated algorithm that included information onbasal and instrumental activities of daily living, cognitive status, nutritional status, the risk of pressures sores, co-morbidity,number of drugs and co-habitation status. According to validated cut-offs, subjects were divided into three groups of risk,i.e. MPI-1 low risk (value≤0.33), MPI-2 moderate risk (value 0.34–0.66) and MPI-3 severe risk of mortality (value≥0.67). Results: two thousand and thirty-three patients were included; 1,159 were women (57.0%). Age- and sex-adjusted mean LOSin patients divided according to the MPI grade was MPI-1 = 10.1 (95% CI 8.6–11.8), MPI-2 = 12.47 (95% CI 10.7–14.68) andMPI-3 = 13.41 (95% CI 11.5–15.7) days (Pfor trend <0.001). The overall accuracy of the MPI to predict LOS was good(C-statistic 0.74, 95% CI 0.72–0.76). Moreover, a statistically significant trend of LOS means was found even in patients strati-fied according to their International Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM) main diagnosis. Conclusions: the MPI is an accurate predictor of LOS in older patients hospitalised with the most frequent diseases.

The Multidimensional Prognostic Index Predicts in-hospital length of stay in older patients: A multicentre prospective study

Pilotto A.;
2016-01-01

Abstract

Background: prediction of length of stay (LOS) may be useful to optimise care plans to reduce the negative outcomes relatedto hospitalisation. Objective: to evaluate whether the Multidimensional Prognostic Index (MPI), based on a Comprehensive Geriatric Assessment(CGA), may predict LOS in hospitalised older patients. Design: prospective multicentre cohort study. Setting: twenty Geriatrics Units. Participants: patients aged 65 and older consecutively admitted to Geriatrics Units. Measurement: at admission, the CGA-based MPI was calculated by using a validated algorithm that included information onbasal and instrumental activities of daily living, cognitive status, nutritional status, the risk of pressures sores, co-morbidity,number of drugs and co-habitation status. According to validated cut-offs, subjects were divided into three groups of risk,i.e. MPI-1 low risk (value≤0.33), MPI-2 moderate risk (value 0.34–0.66) and MPI-3 severe risk of mortality (value≥0.67). Results: two thousand and thirty-three patients were included; 1,159 were women (57.0%). Age- and sex-adjusted mean LOSin patients divided according to the MPI grade was MPI-1 = 10.1 (95% CI 8.6–11.8), MPI-2 = 12.47 (95% CI 10.7–14.68) andMPI-3 = 13.41 (95% CI 11.5–15.7) days (Pfor trend <0.001). The overall accuracy of the MPI to predict LOS was good(C-statistic 0.74, 95% CI 0.72–0.76). Moreover, a statistically significant trend of LOS means was found even in patients strati-fied according to their International Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM) main diagnosis. Conclusions: the MPI is an accurate predictor of LOS in older patients hospitalised with the most frequent diseases.
File in questo prodotto:
File Dimensione Formato  
The Multidimensional Prognostic Index predicts.pdf

accesso aperto

Tipologia: Documento in Versione Editoriale
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 181.7 kB
Formato Adobe PDF
181.7 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/251662
Citazioni
  • ???jsp.display-item.citation.pmc??? 8
  • Scopus 27
  • ???jsp.display-item.citation.isi??? 24
social impact