Related Experiment Videos
Development and validation of a multidimensional prognostic index for one-year mortality from comprehensive geriatric
Alberto Pilotto1, Luigi Ferrucci, Marilisa Franceschi
1Department of Medical Sciences & Gerontology and Geriatrics Laboratory, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy. alberto.pilotto@operapadrepio.it
Insights
A new Multidimensional Prognostic Index (MPI) accurately predicts 1-year mortality in elderly patients using Comprehensive Geriatric Assessment (CGA) data. This tool helps stratify patients by mortality risk, aiding clinical decision-making.
Area of Science:
- Gerontology
- Clinical Epidemiology
- Biostatistics
Background:
- Comprehensive Geriatric Assessment (CGA) is crucial for evaluating elderly patients.
- Accurate prognostic tools are needed to predict mortality risk in hospitalized older adults.
- Existing assessments may not fully capture the multidimensional nature of geriatric health.
Purpose of the Study:
- To develop and validate a Multidimensional Prognostic Index (MPI) for predicting 1-year mortality.
- To utilize data from routine Comprehensive Geriatric Assessment (CGA) for MPI construction.
- To stratify elderly hospitalized patients into distinct mortality risk groups.
Main Methods:
- Developed MPI by aggregating scores from eight domains of a 63-item CGA.
- Utilized proportional hazard models to assess the predictive value of MPI for 1-year all-cause mortality.
- Validated the MPI in a separate cohort of consecutively hospitalized elderly patients.
Main Results:
- MPI successfully stratified patients into low (0.0-0.33), moderate (0.34-0.66), and severe (0.67-1.0) risk groups.
- Higher MPI scores correlated significantly with older age, female sex, lower education, and increased mortality.
- The MPI demonstrated good agreement between estimated and observed mortality, with a ROC area of 0.751 at 1 year.
Conclusions:
- The developed MPI accurately stratifies hospitalized elderly patients based on 1-year mortality risk.
- MPI is a reliable prognostic tool derived from standardized CGA data.
- This index can aid clinicians in risk assessment and management of elderly patients.
Abstract:
Our objective was to construct and validate a Multidimensional Prognostic Index (MPI) for 1-year mortality from a Comprehensive Geriatric Assessment (CGA) routinely carried out in elderly patients in a geriatric acute ward. The CGA included clinical, cognitive, functional, nutritional, and social parameters and was carried out using six standardized scales and information on medications and social support network, for a total of 63 items in eight domains. A MPI was developed from CGA data by aggregating the total scores of the eight domains and expressing it as a score from 0 to 1. Three grades of MPI were identified: low risk, 0.0-0.33; moderate risk, 0.34-0.66; and severe risk, 0.67-1.0. Using the proportional hazard models, we studied the predictive value of the MPI for all causes of mortality over a 12-month follow-up period. MPI was then validated in a different cohort of consecutively hospitalized patients. The development cohort included 838 and the validation cohort 857 elderly hospitalized patients. Of the patients in the two cohorts, 53.3 and 54.9% were classified in the low-risk group, respectively (MPI mean value, 0.18 +/- 0.09 and 0.18 +/- 0.09); 31.2 and 30.6% in the moderate-risk group (0.48 +/- 0.09 and 0.49 +/- 0.09); 15.4 and 14.2% in the severe-risk group (0.77 +/- 0.08 and 0.75 +/- 0.07). In both cohorts, higher MPI scores were significantly associated with older age (p = 0.0001), female sex (p = 0.0001), lower educational level (p = 0.0001), and higher mortality (p = 0.0001). In both cohorts, a close agreement was found between the estimated mortality and the observed mortality after both 6 months and 1 year of follow-up. The discrimination of the MPI was also good, with a ROC area of 0.751 (95%CI, 0.70-0.80) at 6 months and 0.751 (95%CI, 0.71-0.80) at 1 year of follow-up. We conclude that this MPI, calculated from information collected in a standardized CGA, accurately stratifies hospitalized elderly patients into groups at varying risk of mortality.