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RESEARCH PRODUCT
Development and Validation of a Self-Administered Multidimensional Prognostic Index to Predict Negative Health Outcomes in Community-Dwelling Persons
Alberto PilottoNicola VeroneseKaterin Leslie Quispe GuerreroSabrina ZoraAn L.d. BooneMatteo PuntoniAngela GiorgeschiAlberto CellaInes Rey HidalgoYves-marie PersAlberto FerriJose Ramon Hevia FernandezMarta Pisano GonzalezMarta Pisano GonzalezAn L.d. BooneInés ReyRaquel Ochoa GonzalezJ.r. Hevia FernandezY.m. PersChristian JorgensenValsecchi VerushkaRosanna FerreiraAdrien DurandCristina BalaguerCéline CardosoManuel RamosGraham BakerDanni BrownSuzanne LucasS.s. TanX. ZhangP. De VriesH. RaatAlberto PilottoSabrina ZoraAlberto FerriAlberto CellaAlessandra ArgustiBárbara BranchiniJorge Garcéssubject
Male0301 basic medicineGerontologySelf-assessmentendocrine systemAgingIndex (economics)Self AdministrationHealth outcomes03 medical and health sciences0302 clinical medicineall-cause mortality risk factor multidimensional prognostic index self-assessment comprehensive geriatric assessment socioeconomic analysissocioeconomic analysisActivities of Daily LivingHumansMedicineRisk factorAgedAged 80 and overbusiness.industryGeriatric assessmentOriginal ArticlesMiddle Agedcomprehensive geriatric assessmentPrognosisself-assessmentmultidimensional prognostic index030104 developmental biologyrisk factorSelf-Administeredall-cause mortalityFemaleIndependent LivingPublic HealthGeriatrics and Gerontologybusiness030217 neurology & neurosurgeryAll cause mortalitydescription
The multidimensional prognostic index (MPI) is a comprehensive geriatric assessment (CGA)-based tool that accurately predicts negative health outcomes in older subjects with different diseases and settings. To calculate the MPI several validated tools are assessed by health care professionals according to the CGA, whereas self-reported information by the patients is not available, but it could be of importance for the early identification of frailty. We aimed to develop and validate a self-administered MPI (SELFY-MPI) in community-dwelling subjects. For this reason, we enrolled 167 subjects (mean age = 67.3, range = 20-88 years, 51% = men). All subjects underwent a CGA-based assessment to calculate the MPI and the SELFY-MPI. The SELFY-MPI included the assessment of (1) basic and instrumental activities of daily living, (2) mobility, (3) memory, (4) nutrition, (5) comorbidity, (6) number of medications, and (7) socioeconomic situation. The Bland-Altman methodology was used to measure the agreement between MPI and SELFY-MPI. The mean MPI and SELFY-MPI values were 0.147 and 0.145, respectively. The mean difference was +0.002 ± standard deviation of 0.07. Lower and upper 95% limits of agreement were -0.135 and +0.139, respectively, with only 5 of 167 (3%) of observations outside the limits. Stratified analysis by age provided similar results for younger (≤65 years old, n = 45) and older subjects (>65 years, n = 122). The analysis of variances in subjects subdivided according to different year decades showed no differences of agreement according to age. In conclusion, the SELFY-MPI can be used as a prognostic tool in subjects of different ages. © 2019 Alberto Pilotto et al.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-01-01 |