Why the study?
Does the Multidimensional Prognostic Index (MPI) predict in-hospital length of stay in older patients?
Does the Multidimensional Prognostic Index (MPI) predict in-hospital length of stay in older patients?
The Multidimensional Prognostic Index is an accurate predictor of in-hospital length of stay in older patients, which may help optimize care plans.
BACKGROUND: prediction of length of stay (LOS) may be useful to optimise care plans to reduce the negative outcomes related to 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 on basal 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 LOS in 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) and MPI-3 = 13.41 (95% CI 11.5-15.7) days (P for 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 stratified 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.
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Pilotto et al. (2016) studied this question.
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