Symptoms provide predictive information on daily functioning beyond signs and diseases in middle-aged and older adults, particularly those with multimorbidity.
Background In people with multimorbidity, traditional, disease-oriented approaches may overlook the impact of symptoms on daily functioning. Objective To explore the assumption that symptoms and signs provide information on functional limitations beyond that of diseases in older adults, specifically...
| Publicado en: | Age & Ageing Vol. 55; no. 2; pp. 1 - 8 |
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| Autores principales: | , , , , , , , |
| Formato: | Artículo |
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Oxford University Press / USA
Feb2026
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=192513174&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 192513174 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00020729 AGA jtl: Age & Ageing issn: 00020729 maglogo: N pubinfo: dt: Feb2026 vid: 55 iid: 2 pid: 622 pub: Oxford University Press / USA artinfo: ui: 192513174 10.1093/ageing/afag046 ppf: 1 ppct: 7 formats: tig: atl: Symptoms provide predictive information on daily functioning beyond signs and diseases in middle-aged and older adults, particularly those with multimorbidity. aug: au: Peeters, Geeske Hourican, Cillian Lees, Mike Quax, Rick Melis, René Kok, Almar Schoor, Natasja M van Rikkert, Marcel Olde affil: Department of Geriatric Medicine, Radboud University Medical Center, Nijmegen 6500 HB, The NetherlandsRadboudumc Alzheimer Center, Radboud University Medical Center, Nijmegen 6500 HB, The Netherlands Institute of Informatics, University of Amsterdam, Amsterdam, The Netherlands Institute of Informatics, University of Amsterdam, Amsterdam, The NetherlandsInstitute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands Department of Epidemiology and Data Science, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, The NetherlandsDepartment of Psychiatry, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands Amsterdam Public Health Research Institute, Amsterdam UMC Locatie VUmc—Epidemiology and Data Science, Amsterdam, Noord-Holland, The Netherlands su: Interviewing Chronic diseases Random forest algorithms Independent living Prediction models Questionnaires Geriatric assessment Research methodology Statistics Physics Confidence intervals Comorbidity Patient aftercare sug: subj: Interviewing Chronic diseases Home Health Care Services Random forest algorithms Independent living Prediction models Questionnaires Geriatric assessment Research methodology Statistics Physics Confidence intervals Comorbidity Patient aftercare keyword: aging chronic disease comorbidity copyrightHolder:British Geriatrics Society copyrightYear:2026 frailty functional limitations https://dx.doi.org/10.1093/ageing/afag046 inLanguage:en middle-aged adult multimorbidity older adult older people publisher:Oxford University Press random forest sameAs:https://pubmed.ncbi.nlm.nih.gov/41766587/ symptom burden aging chronic disease comorbidity copyrightHolder:British Geriatrics Society copyrightYear:2026 frailty functional limitations https://dx.doi.org/10.1093/ageing/afag046 inLanguage:en middle-aged adult multimorbidity older adult older people publisher:Oxford University Press random forest sameAs:https://pubmed.ncbi.nlm.nih.gov/41766587/ symptom burden ab: Background In people with multimorbidity, traditional, disease-oriented approaches may overlook the impact of symptoms on daily functioning. Objective To explore the assumption that symptoms and signs provide information on functional limitations beyond that of diseases in older adults, specifically those with multimorbidity. Subjects 4025 participants in the Longitudinal Aging Study Amsterdam (1995–2022). Methods Analyses included six symptoms, five signs and eight diseases as exposures and a sum score of six functional limitations as the outcome. Partial Information Decomposition was used to partition the total variability in functional limitations into unique, redundant and synergistic information provided by the exposures in the total sample and in the multimorbidity subgroup. Random forest prediction models were run to examine the added predictive value of symptoms, signs and diseases. Results In the total sample, 59% had multimorbidity. Symptoms, signs and diseases together explained 13.3% of variability in functional limitations. None of the three domains contributed unique information. Synergy accounted for most of the explained variability (signs = 9.2%, symptoms = 34.3%, diseases = 34.3%). In the multimorbidity subgroup, symptoms, signs and diseases together explained 8.7% of variability in functional limitations. Symptoms uniquely contributed 35.5% of their information, while signs and diseases were redundant. Prediction models showed that symptoms provided substantial predictive value beyond diseases alone, with a 110% increase in predictive agreement when symptoms were added to diseases in the multimorbidity subgroup, compared to 58% in the total sample. Conclusions In people with multimorbidity, symptoms and signs explain more variability in functional limitations than diseases alone, supporting the need for a symptom-oriented approach in clinical care and research. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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