A novel easy-to-use index to predict institutionalization and death in older population - a 10-year population-based follow-up study.

Humans Aged Aged, 80 and over Follow-Up Studies Prospective Studies Institutionalization
Aged Index Institutionalization Mortality

Journal

BMC geriatrics
ISSN: 1471-2318
Titre abrégé: BMC Geriatr
Pays: England
ID NLM: 100968548

Informations de publication

Date de publication:
07 02 2023
Historique:
received: 19 01 2022
accepted: 13 01 2023
entrez: 8 2 2023
pubmed: 9 2 2023
medline: 10 2 2023
Statut: epublish

Résumé

Various indexes have been developed to estimate the risk for mortality, institutionalization, and other adverse outcomes for older people. Most indexes are based on a large number of clinical or laboratory parameters. An index based on only a few parameters would be more practical to use in every-day clinical practice. Our aim was to create an index to predict the risk for mortality and institutionalization with as few parameters as possible without compromising their predictive ability. A prospective study with a 10-year follow-up period. Thirty-six clinical and fourteen laboratory parameters were combined to form an index. Cox regression model was used to analyze the association of the index with institutionalization and mortality. A backward statistical method was used to reduce the number of parameters to form an easy-to-use index for predicting institutionalization and mortality. The mean age of the participants (n = 1172) was 73.1 (SD 6.6, range 64‒97) years. Altogether, 149 (14%) subjects were institutionalized, and 413 (35%) subjects deceased during the follow-up. Institutionalization and mortality rates increased as index scores increased both for the large 50-parameter combined index and for the reduced indexes. After a backward variable selection in the Cox regression model, three clinical parameters remained in the index to predict institutionalization and six clinical and three laboratory parameters in the index to predict mortality. The reduced indexes showed a slightly better predictive value for both institutionalization and mortality compared to the full index. A large index with fifty parameters included many unimportant parameters that did not increase its predictive value, and therefore could be replaced with a reduced index with only a few carefully chosen parameters, that were individually associated with institutionalization or death.

Sections du résumé

BACKGROUND
Various indexes have been developed to estimate the risk for mortality, institutionalization, and other adverse outcomes for older people. Most indexes are based on a large number of clinical or laboratory parameters. An index based on only a few parameters would be more practical to use in every-day clinical practice. Our aim was to create an index to predict the risk for mortality and institutionalization with as few parameters as possible without compromising their predictive ability.
METHODS
A prospective study with a 10-year follow-up period. Thirty-six clinical and fourteen laboratory parameters were combined to form an index. Cox regression model was used to analyze the association of the index with institutionalization and mortality. A backward statistical method was used to reduce the number of parameters to form an easy-to-use index for predicting institutionalization and mortality.
RESULTS
The mean age of the participants (n = 1172) was 73.1 (SD 6.6, range 64‒97) years. Altogether, 149 (14%) subjects were institutionalized, and 413 (35%) subjects deceased during the follow-up. Institutionalization and mortality rates increased as index scores increased both for the large 50-parameter combined index and for the reduced indexes. After a backward variable selection in the Cox regression model, three clinical parameters remained in the index to predict institutionalization and six clinical and three laboratory parameters in the index to predict mortality. The reduced indexes showed a slightly better predictive value for both institutionalization and mortality compared to the full index.
CONCLUSIONS
A large index with fifty parameters included many unimportant parameters that did not increase its predictive value, and therefore could be replaced with a reduced index with only a few carefully chosen parameters, that were individually associated with institutionalization or death.

Identifiants

DOI: 10.1186/s12877-023-03760-1 PMID: 36750784 PMC: PMC9903495
pubmed: 36750784
doi: 10.1186/s12877-023-03760-1
pii: 10.1186/s12877-023-03760-1
pmc: PMC9903495
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

80

Informations de copyright

© 2023. The Author(s).

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Auteurs

Elisa Heikkilä (E)

Faculty of Medicine, Department of Clinical Medicine, Unit of Clinical Chemistry, Turku University, FI-20014 University of Turku, 20521, Turku, Finland. etmhei@utu.fi.
Tykslab, Laboratory Division, Turku University Hospital, Hospital District of Southwest Finland, Turku, Finland. etmhei@utu.fi.
ORCID: 0000-0002-6768-6890

Marika Salminen (M)

Faculty of Medicine, Department of Clinical Medicine, Unit of Family Medicine, University of Turku and Turku University Hospital, 20014, Turku, Finland.
City of Turku, Welfare Division/Turku City Hospital, Kunnallissairaalantie 20, 20700, Turku, Finland.

Anna Viljanen (A)

Municipality of Lieto, Health Care Center, 21420, Lieto, Finland.
Faculty of Medicine, Department of Geriatrics, Turku City Hospital, University of Turku, Kunnallissairaalantie 20, 20700, Turku, Finland.

Taina Katajamäki (T)

Faculty of Medicine, Department of Clinical Medicine, Unit of Clinical Chemistry, Turku University, FI-20014 University of Turku, 20521, Turku, Finland.
Tykslab, Laboratory Division, Turku University Hospital, Hospital District of Southwest Finland, Turku, Finland.

Marja-Kaisa Koivula (MK)

HUS Diagnostic Center, Helsinki University Hospital, Hospital District of Helsinki and Uusimaa (HUS), Helsinki, Finland.
Diagnostic Center, Clinical Chemistry and Hematology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.

Kari Pulkki (K)

HUS Diagnostic Center, Helsinki University Hospital, Hospital District of Helsinki and Uusimaa (HUS), Helsinki, Finland.
Diagnostic Center, Clinical Chemistry and Hematology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.

Raimo Isoaho (R)

Faculty of Medicine, Department of Clinical Medicine, Unit of Family Medicine, University of Turku and Turku University Hospital, 20014, Turku, Finland.
City of Vaasa, Social and Health Care, 65101, Vaasa, Finland.

Sirkka-Liisa Kivelä (SL)

Faculty of Medicine, Department of Clinical Medicine, Unit of Family Medicine, University of Turku and Turku University Hospital, 20014, Turku, Finland.
Faculty of Pharmacy, Division of Social Pharmacy, University of Helsinki, 00014, Helsinki, Finland.

Matti Viitanen (M)

Faculty of Medicine, Department of Geriatrics, Turku City Hospital, University of Turku, Kunnallissairaalantie 20, 20700, Turku, Finland.

Minna Löppönen (M)

City of Raisio, Social and Health Care for Elderly, 21200, Raisio, Finland.

Tero Vahlberg (T)

Faculty of Medicine, Department of Clinical Medicine, Unit of Biostatistics, University of Turku, Turku, Finland.

Mikko S Venäläinen (MS)

Turku Bioscience Centre, University of Turku and Åbo Akademi University, 20520, Turku, Finland.

Laura L Elo (LL)

Turku Bioscience Centre, University of Turku and Åbo Akademi University, 20520, Turku, Finland.
Institute of Biomedicine, University of Turku, Turku, Finland.

Laura Viikari (L)

City of Turku, Welfare Division/Turku City Hospital, Kunnallissairaalantie 20, 20700, Turku, Finland.
Faculty of Medicine, Department of Geriatrics, Turku City Hospital, University of Turku, Kunnallissairaalantie 20, 20700, Turku, Finland.

Kerttu Irjala (K)

Faculty of Medicine, Department of Clinical Medicine, Unit of Clinical Chemistry, Turku University, FI-20014 University of Turku, 20521, Turku, Finland.

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