Evidence map›Paper›PMID 37435716›Full record

ArticleJournal of rehabilitation medicine2023

Physical activity and sedentary behaviour changes during and after cardiac rehabilitation: Can patients be clustered?

Marlou M Limpens, Rita J G Van den Berg, Iris Den Uijl, Madoka Sunamura, Trudy Voortman, Eric Boersma, Nienke Ter Hoeve

Abstract read
In one paragraph

Article in Journal of rehabilitation medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Observational
  2. Observational
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

7 authors.

Marlou M LimpensDepartment of Epidemiology.
Rita J G Van den BergDepartment of Rehabilitation Medicine.
Iris Den UijlDepartment of Rehabilitation Medicine; Capri Cardiac Rehabilitation, Rotterdam.
Madoka SunamuraCapri Cardiac Rehabilitation, Rotterdam.
Trudy VoortmanDepartment of Epidemiology; Division of Human Nutrition and Health, Wageningen University & Research, Wageningen, The Netherlands.
Eric BoersmaDepartment of Cardiology, Thoraxcenter, Erasmus MC, University Medical Centre Rotterdam, Rotterdam.
Nienke Ter HoeveDepartment of Rehabilitation Medicine; Capri Cardiac Rehabilitation, Rotterdam.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo identify clusters of patients according to changes in their physical behaviour during and after cardiac rehabilitation, and to predict cluster membership.

methodsThe study included 533 patients (mean age 57.9 years; 18.2% females) with a recent acute coronary syndrome who participated in a 12-week multi-disciplinary cardiac rehabilitation programme, within a cohort study design. Physical behaviour (light physical activity, moderate-to vigorous physical activity, step count, and sedentary behaviour) was measured using accelerometry at 4 timepoints. To identify clusters of patients according to changes in physical behaviour during and after cardiac rehabilitation, latent class trajectory modelling was applied. Baseline factors to predict cluster membership were assessed using multinomial logistic regression.

resultsDuring and after cardiac rehabilitation, 3 separate clusters were identified for all 4 physical behaviour outcomes: patients with steady levels (comprising 68-83% of the patients), and improving (6-21%) or deteriorating (4-23%) levels. Main predictor for membership to a specific cluster was baseline physical behaviour. Patients with higher starting physical behaviour were more likely to be a member of clusters with deteriorating levels.

conclusionSeparate clusters of physical behaviour changes during and after cardiac rehabilitation could be identified. Clusters were mainly distinguished by baseline physical behaviour level.

Indexed as

Cardiac RehabilitationSedentary BehaviorAccelerometryCohort StudiesExerciseFemaleHumansMaleMiddle Aged

Identifiers

PMID37435716
PMCPMC10364624

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