Anna Maria Meyer1, Ingrid Becker2, Giacomo Siri3, Paul Thomas Brinkkötter4, Thomas Benzing4, Alberto Pilotto5, M Cristina Polidori6. 1. Ageing Clinical Research, Dpt. II for Internal Medicine, University Hospital of Cologne, Cologne, Germany. 2. Institute of Medical Statistics and Computational Biology, University Hospital of Cologne, Cologne, Germany. 3. Scientific Directorate - Biostatistics, E.O. Galliera Hospital, Genova, Italy. 4. Nephrology, Rheumatology, Diabetology and Internal Medicine, Dpt. II for Internal Medicine, University Hospital of Cologne, Cologne, Germany. 5. Department Geriatric Care, Orthogeriatrics and Rehabilitation, Frailty Area, E.O. Galliera Hospital, Genova, Italy. 6. Ageing Clinical Research, Dpt. II for Internal Medicine, University Hospital of Cologne, Cologne, Germany. maria.polidori-nelles@uk-koeln.de.
Abstract
BACKGROUND: The multidimensional prognostic index (MPI) is a validated, sensitive, and specific prognosis estimation tool based on a comprehensive geriatric assessment (CGA). The MPI accurately predicts mortality after 1 month and 1 year in older, multimorbid patients with acute disease or relapse of chronic conditions. OBJECTIVE: To evaluate whether the MPI predicts indicators of healthcare resources, i.e. grade of care (GC), length of hospital stay (LHS) and destination after hospital discharge in older patients in an acute medical setting. MATERIAL AND METHODS: In this study 135 hospitalized patients aged 70 years and older underwent a CGA evaluation to calculate the MPI on admission and discharge. Accordingly, patients were subdivided in low (MPI‑1, score 0-0.33), moderate (MPI-2, score 0.34-0.66) and high (MPI-3, score 0.67-1) risk of mortality. The GC, LHS and the discharge allocation were also recorded. RESULTS: The MPI score was significantly related to LHS (p = 0.011) and to GC (p < 0.001). In addition, MPI-3 patients were significantly more often transferred from other hospital settings (p = 0.007) as well as significantly less likely to be discharged home (p = 0.04) than other groups. CONCLUSION: The CGA-based MPI values are significantly associated with use of indicators of healthcare resources, including GC, LHS and discharge allocation. These findings suggest that the MPI may be useful for resource planning in the care of older multimorbid patients admitted to hospital.
BACKGROUND: The multidimensional prognostic index (MPI) is a validated, sensitive, and specific prognosis estimation tool based on a comprehensive geriatric assessment (CGA). The MPI accurately predicts mortality after 1 month and 1 year in older, multimorbid patients with acute disease or relapse of chronic conditions. OBJECTIVE: To evaluate whether the MPI predicts indicators of healthcare resources, i.e. grade of care (GC), length of hospital stay (LHS) and destination after hospital discharge in older patients in an acute medical setting. MATERIAL AND METHODS: In this study 135 hospitalized patients aged 70 years and older underwent a CGA evaluation to calculate the MPI on admission and discharge. Accordingly, patients were subdivided in low (MPI‑1, score 0-0.33), moderate (MPI-2, score 0.34-0.66) and high (MPI-3, score 0.67-1) risk of mortality. The GC, LHS and the discharge allocation were also recorded. RESULTS: The MPI score was significantly related to LHS (p = 0.011) and to GC (p < 0.001). In addition, MPI-3 patients were significantly more often transferred from other hospital settings (p = 0.007) as well as significantly less likely to be discharged home (p = 0.04) than other groups. CONCLUSION: The CGA-based MPI values are significantly associated with use of indicators of healthcare resources, including GC, LHS and discharge allocation. These findings suggest that the MPI may be useful for resource planning in the care of older multimorbid patients admitted to hospital.
Authors: Volker Burst; Maria Cristina Polidori; Marcel Pascal Rarek; Anna Maria Meyer; Lena Pickert; Alberto Pilotto; Thomas Benzing Journal: Aging Clin Exp Res Date: 2020-11-01 Impact factor: 3.636
Authors: A Heeß; A M Meyer; I Becker; N Noetzel; J Verleysdonk; M Rarek; T Benzing; M C Polidori Journal: Z Gerontol Geriatr Date: 2021-10-06 Impact factor: 1.281
Authors: Nicolas Noetzel; Anna Maria Meyer; Giacomo Siri; Lena Pickert; Annika Heeß; Joshua Verleysdonk; Thomas Benzing; Alberto Pilotto; Anna Greta Barbe; Maria Cristina Polidori Journal: Eur Geriatr Med Date: 2020-11-18 Impact factor: 1.710
Authors: Alberto Pilotto; Carlo Custodero; Stefania Maggi; Maria Cristina Polidori; Nicola Veronese; Luigi Ferrucci Journal: Ageing Res Rev Date: 2020-03-21 Impact factor: 10.895
Authors: Aafke J de Groot; Elizabeth M Wattel; Carmen S van Dam; Romke van Balen; Johannes C van der Wouden; Cees M P M Hertogh Journal: Age Ageing Date: 2022-02-02 Impact factor: 10.668
Authors: Erik Lagolio; Jacopo Demurtas; Thomas Benzing; Maria Cristina Polidori; Roberto Buzzetti; Giorgio Cortassa; Stefania Bottone; Laura Spadafora; Cristina Cocino; Lee Smith Journal: Intern Emerg Med Date: 2021-07-28 Impact factor: 5.472
Authors: Anna Maria Meyer; Lena Pickert; Annika Heeß; Ingrid Becker; Christine Kurschat; Malte P Bartram; Thomas Benzing; Maria Cristina Polidori Journal: Biomolecules Date: 2022-03-09