Prediction models for functional status in community dwelling older adults: a systematic review.
ADL
Aged
Community
Disability
Functional status
Prediction
Journal
BMC geriatrics
ISSN: 1471-2318
Titre abrégé: BMC Geriatr
Pays: England
ID NLM: 100968548
Informations de publication
Date de publication:
30 05 2022
30 05 2022
Historique:
received:
13
10
2021
accepted:
12
05
2022
entrez:
31
5
2022
pubmed:
1
6
2022
medline:
3
6
2022
Statut:
epublish
Résumé
Disability poses a burden for older persons, and is associated with poor outcomes and high societal costs. Prediction models could potentially identify persons who are at risk for disability. An up to date review of such models is missing. To identify models developed for the prediction of functional status in community dwelling older persons. A systematic review was performed including studies of older persons that developed and/or validated prediction models for the outcome functional status. Medline and EMBASE were searched, and reference lists and prospective citations were screened for additional references. Risk of bias was assessed using the PROBAST-tool. The performance of models was described and summarized, and the use of predictors was collated using the bag-of-words text mining procedure. Forty-three studies were included and reported 167 evaluations of prediction models. The median c-statistic values for the multivariable development models ranged between 0.65 and 0.76 (minimum = 0.58, maximum = 0.90), and were consistently higher than the values of the validation models for which median c-statistic values ranged between 0.6 and 0.68 (minimum = 0.50, maximum = 0.81). A total of 559 predictors were used in the models. The five predictors most frequently used were gait speed (n = 47), age (n = 38), cognition (n = 27), frailty (n = 24), and gender (n = 22). No model can be recommended for implementation in practice. However, frailty models appear to be the most promising, because frailty components (e.g. gait speed) and frailty indexes demonstrated good to excellent predictive performance. However, the risk of study bias was high. Substantial improvements can be made in the methodology.
Sections du résumé
BACKGROUND
Disability poses a burden for older persons, and is associated with poor outcomes and high societal costs. Prediction models could potentially identify persons who are at risk for disability. An up to date review of such models is missing.
OBJECTIVE
To identify models developed for the prediction of functional status in community dwelling older persons.
METHODS
A systematic review was performed including studies of older persons that developed and/or validated prediction models for the outcome functional status. Medline and EMBASE were searched, and reference lists and prospective citations were screened for additional references. Risk of bias was assessed using the PROBAST-tool. The performance of models was described and summarized, and the use of predictors was collated using the bag-of-words text mining procedure.
RESULTS
Forty-three studies were included and reported 167 evaluations of prediction models. The median c-statistic values for the multivariable development models ranged between 0.65 and 0.76 (minimum = 0.58, maximum = 0.90), and were consistently higher than the values of the validation models for which median c-statistic values ranged between 0.6 and 0.68 (minimum = 0.50, maximum = 0.81). A total of 559 predictors were used in the models. The five predictors most frequently used were gait speed (n = 47), age (n = 38), cognition (n = 27), frailty (n = 24), and gender (n = 22).
CONCLUSIONS
No model can be recommended for implementation in practice. However, frailty models appear to be the most promising, because frailty components (e.g. gait speed) and frailty indexes demonstrated good to excellent predictive performance. However, the risk of study bias was high. Substantial improvements can be made in the methodology.
Identifiants
pubmed: 35637447
doi: 10.1186/s12877-022-03156-7
pii: 10.1186/s12877-022-03156-7
pmc: PMC9150308
doi:
Types de publication
Journal Article
Systematic Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
465Informations de copyright
© 2022. The Author(s).
Références
Prev Chronic Dis. 2016 Nov 03;13:E151
pubmed: 27809419
J Gerontol A Biol Sci Med Sci. 2013 May;68(5):624-30
pubmed: 23105042
J Am Geriatr Soc. 2004 Aug;52(8):1343-8
pubmed: 15271124
BMC Med. 2019 Dec 16;17(1):230
pubmed: 31842878
Geriatr Gerontol Int. 2012 Oct;12(4):659-66
pubmed: 22360443
BMC Fam Pract. 2015 Mar 03;16:30
pubmed: 25888485
J Am Med Dir Assoc. 2020 Mar;21(3):440.e1-440.e8
pubmed: 31678074
J Gerontol A Biol Sci Med Sci. 2000 Apr;55(4):M221-31
pubmed: 10811152
BMC Geriatr. 2017 Nov 10;17(1):262
pubmed: 29126383
Maturitas. 2015 Sep;82(1):3-21
pubmed: 25866212
J Am Geriatr Soc. 2019 Mar;67(3):477-483
pubmed: 30468258
Gerontology. 2018;64(3):212-221
pubmed: 29232671
Soc Sci Med. 1999 Feb;48(4):445-69
pubmed: 10075171
Med Care. 2012 Jun;50(6):534-9
pubmed: 22581013
Ann Intern Med. 2019 Jan 1;170(1):51-58
pubmed: 30596875
Popul Health Manag. 2019 Apr;22(2):127-137
pubmed: 30096023
J Clin Epidemiol. 2014 Oct;67(10):1121-30
pubmed: 25103817
Gerontologist. 2014 Dec;54(6):919-29
pubmed: 23969256
J Am Geriatr Soc. 1997 Apr;45(4):441-5
pubmed: 9100712
Am J Phys Med Rehabil. 2018 Oct;97(10):698-707
pubmed: 29634614
PLoS One. 2016 Oct 19;11(10):e0165127
pubmed: 27760234
Arch Intern Med. 2008 Feb 25;168(4):382-9
pubmed: 18299493
J Vasc Bras. 2020 Dec 11;19:e20200186
pubmed: 34211533
J Am Med Dir Assoc. 2020 Oct;21(10):1481-1489.e3
pubmed: 32768375
J Geriatr Phys Ther. 2012 Jul-Sep;35(3):112-7
pubmed: 22314273
J Clin Epidemiol. 2005 Nov;58(11):1180-7
pubmed: 16223662
Eur J Ageing. 2019 Feb 19;16(3):387-394
pubmed: 31543731
Biomed Res Int. 2018 Jun 20;2018:1340479
pubmed: 30027095
Arch Gerontol Geriatr. 2016 Jul-Aug;65:239-47
pubmed: 27131227
Health Qual Life Outcomes. 2015 Oct 15;13:168
pubmed: 26467295
J Am Geriatr Soc. 2010 May;58(5):844-52
pubmed: 20406319
Age Ageing. 2015 Mar;44(2):275-82
pubmed: 25349151
BMC Geriatr. 2011 May 10;11:22
pubmed: 21569279
Aging Clin Exp Res. 2019 Jan;31(1):59-66
pubmed: 29594823
PLoS One. 2015 Sep 25;10(9):e0138901
pubmed: 26407207
Pharmacoepidemiol Drug Saf. 2015 Jan;24(1):59-66
pubmed: 25335470
BMC Geriatr. 2020 Mar 30;20(1):124
pubmed: 32228469
BMC Geriatr. 2019 Jun 27;19(1):179
pubmed: 31248370
Gerontologist. 2012 Oct;52(5):619-31
pubmed: 22217462
PLoS One. 2012;7(2):e32844
pubmed: 22393453
Aging Clin Exp Res. 2022 Jun;34(6):1267-1274
pubmed: 35147921
BMC Med Res Methodol. 2018 Nov 16;18(1):138
pubmed: 30445915
J Am Geriatr Soc. 2003 Mar;51(3):314-22
pubmed: 12588574
Arch Phys Med Rehabil. 2014 Oct;95(10):1954-61
pubmed: 24977931
PLoS One. 2016 Aug 23;11(8):e0160742
pubmed: 27551749
J Aging Health. 2013 Dec;25(8 Suppl):163S-85S
pubmed: 24385635
BMJ. 2009 Jul 21;339:b2535
pubmed: 19622551
J Am Med Dir Assoc. 2017 Jul 1;18(7):637.e13-637.e19
pubmed: 28648903
J Clin Epidemiol. 2020 Oct;126:207-216
pubmed: 32712176
Stat Methods Med Res. 2018 Jan;27(1):185-197
pubmed: 27460537
J Am Med Dir Assoc. 2017 Feb 1;18(2):152-157
pubmed: 27742583
Health Serv Res. 2016 Feb;51(1):262-81
pubmed: 26015332
Geriatr Gerontol Int. 2015 Feb;15(2):133-40
pubmed: 25303103
J Aging Health. 2017 Aug;29(5):880-892
pubmed: 27166414
J Am Geriatr Soc. 1997 Jan;45(1):92-100
pubmed: 8994496
Epidemiology. 2010 Jan;21(1):128-38
pubmed: 20010215
J Gerontol A Biol Sci Med Sci. 2005 Jan;60(1):74-9
pubmed: 15741286
BMC Geriatr. 2011 Jul 01;11:33
pubmed: 21722355
J Gerontol A Biol Sci Med Sci. 2016 Jan;71(1):63-71
pubmed: 26297942
Soc Sci Med. 1994 Jan;38(1):1-14
pubmed: 8146699
Annu Rev Public Health. 1996;17:25-46
pubmed: 8724214
Med Care. 2006 Feb;44(2):149-57
pubmed: 16434914
J Appl Gerontol. 2015 Apr;34(3):329-42
pubmed: 24652867