The Multidimensional Prognostic Index in general practice: One‐year follow‐up study

Abstract

Background Older patients’ health problems in general practice (GP) can often not be assigned to a specific disease, requiring a paradigm shift to goal‐oriented, personalised care for clinical decision making. Purpose To investigate the predictive value of the comprehensive geriatric assessment (CGA)‐based Multidimensional Prognostic Index (MPI) in a GP setting with respect to the main healthcare indicators during the 12 months following initial evaluation. Methods One hundred twenty‐five consecutive patients aged 70 years and older were enrolled in a GP and followed up to one year. All patients underwent a CGA based on which the MPI was calculated and subdivided into three risk groups (MPI‐1, 0‐0.33 = low risk, MPI‐2, 0.34‐0.66 = moderate risk and MPI‐3, 0.67‐1, severe risk). Grade of Care (GC), hospitalization rate, mortality, nursing home admission, use of home care services, falls, number of general practitioner contacts (GPC), of geriatric resources (GR) and geriatric syndromes (GS) during the 12 months following initial evaluation were collected. Results The MPI was significantly associated with number of GS (P < .001), GR (P < .001), GC (P < .001) as well as with the average number of GPC per year (mean 10.4, P = .046). Interestingly, the clinical judgement of the general practitioner, in this case knowing his patients for 16 years on average, was associated with adverse outcomes to a similar extent than the prediction offered by the MPI (GP/adverse outcomes and MPI/adverse outcomes P < .001). Conclusion The MPI is strongly associated with adverse outcomes in older GP patients and strongly predicts the number of GPC up to one year after initial evaluation. Considering the feasibility and the strong clinimetric properties of the MPI, its collection should be encouraged as early as possible to disclose risk conditions, implement tailored preventive strategies and improve cost‐effectiveness of healthcare resources use.

A rapid and feasible tool for clinical decision making in community-dwelling patients with COVID-19 and those admitted to emergency departments: the Braden-LDH-HorowITZ Assessment—BLITZ

“…A metanalysis of 29 randomized controlled trials conducted in over 14,000 older patients have shown that the CGA is highly effective in improving diagnosis and management [ 28 ]. Recent studies employing CGA-based innovative, feasible tools for the assessment of multidimensional, individualized prognosis clearly showed that the latter disclose critical factors for trajectories which go beyond organ-center medicine and chronological age [ 29 – 31 ] and apply also during the ongoing pandemic [ 11 , 23 ]. Of note, in our analysis the Braden scale but not the Conley scale—which addresses physical factors only—reached and surpassed the predictive power of the P/F or of the LDH levels, supporting the knowledge that functions escaping diagnostics in usual care influence the ability to thrive in advanced age.…”

The Multidimensional Prognostic Index as a Measure of Frailty in Elderly Patients with Head and Neck Cancer

“…A higher MPI-score is associated with increased 1-year mortality, hospitalization or admission to a healthcare institution. [15][16][17][18][19][20] The MPI, which was originally developed to predict mortality, has also been suggested as a frailty assessment model. 21,22 However, whether the MPI-score reflect the degree of frailty has not been studied yet.…”

Implementation of the SELFY-MPI in five European countries: a multicenter international feasibility study

“…hearth failure, 7 chronic kidney disease, 8 cancer, 9 dementia, 10 neuropsychological disorders 11 and diabetes mellitus, 12 and in several settings such as in hospitalized patients, 4,27 in the community-dwelling subjects who underwent a CGA to be admitted to nursing homes or homecare services, 5 as well as at population level 28 and at the ambulatory of the General Practitioner. 29 A previous study has already showed the strong association and validity between the SELFY-MPI and the MPI. 13 This study explores the feasibility of the SELFY-MPI in people of different ages and from different countries.…”