ArticleMedicine2026
Predicting independent dressing after stroke using path and neural network analyses.
Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Various motor and cognitive functions affect dressing skill. Evaluating the hierarchy of factors that influence performance in daily dressing and predicting this performance are crucial for effective rehabilitation. This study aims to clarify the interrelationships among motor function, cognitive function, dressing skill, speed of dressing, and performance of dressing in daily living, and to predict the latter using a convolutional neural network (CNN) model. We conducted a retrospective study. A total of 243 stroke patients were enrolled in this study, which comprised 2 rounds of data analysis. The first round involved all 243 patients and aimed to identify the hierarchical structure in the performance of dressing in daily living. The second round focused on 153 of these patients to predict dressing performance among those able to dress themselves in a rehabilitation setting. In the first round, path analysis was used to examine the interrelationships among motor function, cognitive function, dressing skills, speed of dressing, and performance of dressing in daily living. In the second round, a predictive algorithm for dressing in daily living was developed using a CNN. The model's performance was evaluated using the area under the receiver operating characteristic curve. The model analyzing the performance of dressing in daily living revealed statistically significant causal relationships among the path coefficients for the severity of paresis, unilateral spatial neglect, attention disorder, dressing skill, and speed of dressing. Speed of dressing directly influenced the performance of dressing in daily living, exhibiting the highest standardized path coefficient in each of the path models. The CNN model, which predicts the speed of dressing and the performance of dressing in daily living, performed well, achieving the highest area under the receiver operating characteristic curve of 0.939 ± 0.015. The severity of paresis, unilateral spatial neglect, attention disorder, and dressing skill had indirect effects on the performance of dressing in daily living by influencing the speed of dressing. The speed of dressing could predict the performance of dressing in daily living with high accuracy. Our results suggest that the performance of dressing in daily living strongly depends on the speed of dressing.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.