Evidence map›Paper›PMID 38712968›Full record

ArticleJournal of rehabilitation medicine2024

Early functional factors for predicting outcome of independence in daily living after stroke: a decision tree analysis.

Heegoo Kim, Chanmi Lee, Nayeong Kim, Eunhye Chung, HyeongMin Jeon, Seyoung Shin, MinYoung Kim

Abstract read
In one paragraph

Article in Journal of rehabilitation medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Heegoo KimDepartment of Rehabilitation Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea; Digital Therapeutics Research Team, CHA Future Medicine Research Institute, Seongnam, Republic of Korea.
Chanmi LeeDepartment of Rehabilitation Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea; Digital Therapeutics Research Team, CHA Future Medicine Research Institute, Seongnam, Republic of Korea.
Nayeong KimDepartment of Rehabilitation Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea; Digital Therapeutics Research Team, CHA Future Medicine Research Institute, Seongnam, Republic of Korea.
Eunhye ChungDepartment of Rehabilitation Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea; Digital Therapeutics Research Team, CHA Future Medicine Research Institute, Seongnam, Republic of Korea.
HyeongMin JeonDepartment of Rehabilitation Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea; Digital Therapeutics Research Team, CHA Future Medicine Research Institute, Seongnam, Republic of Korea.
Seyoung ShinDepartment of Rehabilitation Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea; Digital Therapeutics Research Team, CHA Future Medicine Research Institute, Seongnam, Republic of Korea; Rehabilitation and Regeneration Research Center, CHA University School of Medicine, Seongnam, Republic of Korea.
MinYoung KimDepartment of Rehabilitation Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea; Digital Therapeutics Research Team, CHA Future Medicine Research Institute, Seongnam, Republic of Korea; Rehabilitation and Regeneration Research Center, CHA University School of Medicine, Seongnam, Republic of Korea. kmin@cha.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to investigate the predictive functional factors influencing the acquisition of basic activities of daily living performance abilities during the early stages of stroke rehabilitation using classification and regression analysis trees.

methodsThe clinical data of 289 stroke patients who underwent rehabilitation during hospitalization (164 males; mean age: 62.2 ± 13.9 years) were retrospectively collected and analysed. The follow-up period between admission and discharge was approximately 6 weeks. Medical records, including demographic characteristics and various functional assessments with item scores, were extracted. The modified Barthel Index on discharge served as the target outcome for analysis. A "good outcome" was defined as a modified Barthel Index score ≥ 75 on discharge, while a modified Barthel Index score < 75 was classified as a "poor outcome."

resultsTwo classification and regression analysis tree models were developed. The first model, predicting activities of daily living outcomes based on early motor functions, achieved an accuracy of 92.4%. Among patients with a "good outcome", 70.9% exhibited (i) ≥ 4 points in the "sitting-to-standing" category in the motor assessment scale and (ii) 32 points on the Berg Balance Scale score. The second model, predicting activities of daily living outcome based on early cognitive functions, achieved an accuracy of 82.7%. Within the "poor outcome" group, 52.2% had (i) ≤ 21 points in the "visuomotor organization" category of Lowenstein Occupational Therapy Cognitive Assessment, (ii) ≤ 1 point in the "time orientation" category of the Mini Mental State Examination.

conclusionThe ability to perform "sitting-to-standing" and visuomotor organization functions at the beginning of rehabilitation emerged as the most significant predictors for achieving successful basic activities of daily living on discharge after stroke.

Indexed as

Activities of Daily LivingDecision TreesStroke RehabilitationAgedDisability EvaluationFemaleHumansIndependent LivingMaleMiddle AgedRecovery of FunctionRetrospective StudiesStrokeTreatment Outcome

Identifiers

PMID38712968
PMCPMC11093115

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Registered trials

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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.