Evidence map›Paper›PMID 31248370›Full record

ArticleBMC geriatrics2019

Development of a clinical prediction model for the onset of functional decline in people aged 65-75 years: pooled analysis of four European cohort studies.

Nini H Jonkman, Marco Colpo, Jochen Klenk, Chris Todd, Trynke Hoekstra, Vieri Del Panta, Kilian Rapp, Natasja M van Schoor, Stefania Bandinelli, Martijn W Heymans and 8 more

Abstract read
In one paragraph

Article in BMC geriatrics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Nini H JonkmanDepartment of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081, BT, Amsterdam, The Netherlands.
Marco ColpoLaboratory of Clinical Epidemiology, InCHIANTI Study Group, LHTC Local Health Tuscany Center, Firenze, Italy.
Jochen KlenkDepartment of Clinical Gerontology, Robert Bosch Hospital, Stuttgart, Germany.
Chris ToddSchool of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
Trynke HoekstraDepartment of Health Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Vieri Del PantaLaboratory of Clinical Epidemiology, InCHIANTI Study Group, LHTC Local Health Tuscany Center, Firenze, Italy.
Kilian RappDepartment of Clinical Gerontology, Robert Bosch Hospital, Stuttgart, Germany.
Natasja M van SchoorAmsterdam Public Health Research Institute, Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands.
Stefania BandinelliLaboratory of Clinical Epidemiology, InCHIANTI Study Group, LHTC Local Health Tuscany Center, Firenze, Italy.
Martijn W HeymansAmsterdam Public Health Research Institute, Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands.
Dominique MaugerSchool of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
Luca CattelaniDepartment of Computer Science and Engineering, University of Bologna, Bologna, Italy.
Michael D DenkingerInstitute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.
Dietrich RothenbacherInstitute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.
Jorunn L HelbostadDepartment of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway.
Beatrix VereijkenDepartment of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway.
Andrea B MaierDepartment of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081, BT, Amsterdam, The Netherlands.
Mirjam PijnappelsDepartment of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081, BT, Amsterdam, The Netherlands. m.pijnappels@vu.nl.ORCID 0000-0001-8416-2602

Funding

Project-001R01AG017644 · NIA · UNIVERSITY OF LONDON INST OF NEUROLOGY · PI Andrew Steptoe · 2000 to 2026
$56.2M
HISPANIC SECONDARY STROKE PREVENTION INITIATIVER01MD009164 · NIMHD · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI CARRASQUILLO, OLVEEN · 2014 to 2018
$1.9M
NIA NIH HHS R01 AG017644NIMHD NIH HHS R01 MD009164
6 · The paper itself

Abstract

backgroundIdentifying those people at increased risk of early functional decline in activities of daily living (ADL) is essential for initiating preventive interventions. The aim of this study is to develop and validate a clinical prediction model for onset of functional decline in ADL in three years of follow-up in older people of 65-75 years old.

methodsFour population-based cohort studies were pooled for the analysis: ActiFE-ULM (Germany), ELSA (United Kingdom), InCHIANTI (Italy), LASA (Netherlands). Included participants were 65-75 years old at baseline and reported no limitations in functional ability in ADL at baseline. Functional decline was assessed with two items on basic ADL and three items on instrumental ADL. Participants who reported at least some limitations at three-year follow-up on any of the five items were classified as experiencing functional decline. Multiple logistic regression analysis was used to develop a prediction model, with subsequent bootstrapping for optimism-correction. We applied internal-external cross-validation by alternating the data from the four cohort studies to assess the discrimination and calibration across the cohorts.

resultsTwo thousand five hundred sixty community-dwelling people were included in the analyses (mean age 69.7 ± 3.0 years old, 47.4% female) of whom 572 (22.3%) reported functional decline at three-year follow-up. The final prediction model included 10 out of 22 predictors: age, handgrip strength, gait speed, five-repeated chair stands time (non-linear association), body mass index, cardiovascular disease, diabetes, chronic obstructive pulmonary disease, arthritis, and depressive symptoms. The optimism-corrected model showed good discrimination with a C statistic of 0.72. The calibration intercept was 0.06 and the calibration slope was 1.05. Internal-external cross-validation showed consistent performance of the model across the four cohorts.

conclusionsBased on pooled cohort data analyses we were able to show that the onset of functional decline in ADL in three years in older people aged 65-75 years can be predicted by specific physical performance measures, age, body mass index, presence of depressive symptoms, and chronic conditions. The prediction model showed good discrimination and calibration, which remained stable across the four cohorts, supporting external validity of our findings.

Indexed as

Activities of Daily LivingAgedCardiovascular DiseasesChronic DiseaseCognitive DysfunctionCohort StudiesDepressionFemaleFollow-Up StudiesGermanyHand StrengthHumansIndependent LivingItalyMaleNetherlandsActive agingFunctioningIndividual patient dataMiddle agedPersonalised carePreventive medicine

Identifiers

PMID31248370
PMCPMC6595632

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.