Eva Gallego González1, Francisco Javier Ortiz Alonso2, Maria Teresa Vidán Astiz3, Selene Soria Felix4, Verónica García Cárdenas5, John Omonte Guzmán6, Pedro Abizanda7, Maria Isabel Valadés Malagón8, Silvia Oreja Sevilla9, José Antonio Serra Rexach10. 1. Hospital Universitario de Canarias, Geriatric Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitaria Gregorio Marañón, CIBERFES, Madrid, Spain. Electronic address: dra.egallego@gmail.com. 2. Instituto de Investigación Sanitaria Gregorio Marañón, CIBERFES, Madrid, Spain; Geriatrics Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain. Electronic address: jortiz.hgugm@salud.madrid.org. 3. Instituto de Investigación Sanitaria Gregorio Marañón, CIBERFES, Madrid, Spain; Geriatrics Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Facultad de Medicina, Universidad Complutense de Madrid, CIBERFES, Spain. Electronic address: mvidan.hgugm@salud.madrid.org. 4. Geriatrics Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain. Electronic address: selene_soria@hotmail.com. 5. Geriatrics Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain. Electronic address: veronicaliz80@yahoo.es. 6. Geriatrics Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain. Electronic address: j_omonte@hotmail.com. 7. Geriatrics Department, Complejo Hospitalario Universitario de Albacete, CIBERFES, Albacete, Spain. Electronic address: pabizanda@sescam.jccm.es. 8. Geriatrics Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain. Electronic address: maribelvalades79@hotmail.com. 9. Geriatrics Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain. Electronic address: silvi_os@hotmail.com. 10. Instituto de Investigación Sanitaria Gregorio Marañón, CIBERFES, Madrid, Spain; Geriatrics Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Facultad de Medicina, Universidad Complutense de Madrid, CIBERFES, Spain. Electronic address: joseantonio.serra.hgugm@salud.madrid.org.
Abstract
BACKGROUND/AIM: Estimation of mortality in elderly patients is difficult yet very important when planning care. Previous tools are complicated or do no take into account some major determinants of mortality (i.e., frailty). We designed a simple, accurate, and non-disease-specific tool to predict individual mortality risk after hospital discharge in older adults. METHODS: Patients admitted to the Acute Geriatric Unit were assessed at adission and at discharge and contacted 6 and 12 months later. Determinants of mortality were obtained. Using multivariable analysis, beta coeffcicients were calculated to build 2 scores able to predict mortality at 6 and 12 months after discharge. The scores were tested on a sample comprising 75% of the patients, who were randomly selected; they were validated using the remaining 25%. Discrimination was assessed using ROC curves. Scores were calculated for each patient and divided into tertiles. Survival analysis was performed. RESULTS: Determinants of mortality at 6 months were dependent ambulation at baseline, full dependence at discharge, length of stay, pluripatology, pressure ulcers, low grip strength, malignacy, and male gender. At 12 months the determinants were: dependent amblation at baseline, full dependence at discharge, pluripatology, low BMI, low grip strength, heart failure, malignacy, and male gender. Discrimination and calibration were excellent. Survival analysis demonstrated different survival trajectories (p<0.001) for each tertile in both scores. CONCLUSIONS: Our incices provide accurate prognostic information in elderly patients after discharge. They can be calculated easily, quickly and do not require technical or laboratory support, thus endorsing their value in dalily clinical practice.
BACKGROUND/AIM: Estimation of mortality in elderly patients is difficult yet very important when planning care. Previous tools are complicated or do no take into account some major determinants of mortality (i.e., frailty). We designed a simple, accurate, and non-disease-specific tool to predict individual mortality risk after hospital discharge in older adults. METHODS:Patients admitted to the Acute Geriatric Unit were assessed at adission and at discharge and contacted 6 and 12 months later. Determinants of mortality were obtained. Using multivariable analysis, beta coeffcicients were calculated to build 2 scores able to predict mortality at 6 and 12 months after discharge. The scores were tested on a sample comprising 75% of the patients, who were randomly selected; they were validated using the remaining 25%. Discrimination was assessed using ROC curves. Scores were calculated for each patient and divided into tertiles. Survival analysis was performed. RESULTS: Determinants of mortality at 6 months were dependent ambulation at baseline, full dependence at discharge, length of stay, pluripatology, pressure ulcers, low grip strength, malignacy, and male gender. At 12 months the determinants were: dependent amblation at baseline, full dependence at discharge, pluripatology, low BMI, low grip strength, heart failure, malignacy, and male gender. Discrimination and calibration were excellent. Survival analysis demonstrated different survival trajectories (p<0.001) for each tertile in both scores. CONCLUSIONS: Our incices provide accurate prognostic information in elderly patients after discharge. They can be calculated easily, quickly and do not require technical or laboratory support, thus endorsing their value in dalily clinical practice.
Authors: Eva Gallego-González; Jennifer Mayordomo-Cava; María T Vidán; María I Valadés-Malagón; José A Serra-Rexach; Javier Ortiz-Alonso Journal: Front Physiol Date: 2022-09-14 Impact factor: 4.755