Evidence map›Paper›PMID 41766587›Full record

ArticleAge and ageing2026

Symptoms provide predictive information on daily functioning beyond signs and diseases in middle-aged and older adults, particularly those with multimorbidity.

Geeske Peeters, Cillian Hourican, Mike Lees, Rick Quax, René Melis, Almar Kok, Natasja M van Schoor, Marcel Olde Rikkert

Erratum issuedAbstract read
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Article in Age and ageing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Geeske PeetersDepartment of Geriatric Medicine, Radboud University Medical Center, Nijmegen 6500 HB, The Netherlands.ORCID 0000-0003-4460-7026
Cillian HouricanInstitute of Informatics, University of Amsterdam, Amsterdam, The Netherlands.
Mike LeesInstitute of Informatics, University of Amsterdam, Amsterdam, The Netherlands.
Rick QuaxInstitute of Informatics, University of Amsterdam, Amsterdam, The Netherlands.
René MelisDepartment of Geriatric Medicine, Radboud University Medical Center, Nijmegen 6500 HB, The Netherlands.
Almar KokDepartment of Epidemiology and Data Science, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Natasja M van SchoorAmsterdam Public Health Research Institute, Amsterdam UMC Locatie VUmc-Epidemiology and Data Science, Amsterdam, Noord-Holland, The Netherlands.
Marcel Olde RikkertDepartment of Geriatric Medicine, Radboud University Medical Center, Nijmegen 6500 HB, The Netherlands.ORCID 0000-0003-1397-1677

Funding

HSRD VA CDA 10-014Netherlands Organisation for Health Research and Development 09120012010063Netherlands Organisation for Scientific Research 480-10-014
6 · The paper itself

Abstract

backgroundIn people with multimorbidity, traditional, disease-oriented approaches may overlook the impact of symptoms on daily functioning.

objectiveTo 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).

methodsAnalyses 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.

resultsIn 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.

conclusionsIn 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.

Indexed as

Activities of Daily LivingAgingGeriatric AssessmentMultimorbiditySymptom AssessmentAgedAged, 80 and overFemaleFunctional StatusHumansLongitudinal StudiesMaleMiddle AgedNetherlandsPredictive Value of Testschronic diseasecomorbidityfrailtyfunctional limitationsolder peoplesymptom burden

Identifiers

PMID41766587
PMCPMC13570245

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