ArticleEuropean geriatric medicine2023
Prediction models of grip strength in adults above 65 years using Korean National Physical Fitness Award Data from 2009 to 2019.
Article in European geriatric medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- Trial
- Machine Learning-Based Model for Grip Strength Prediction in Healthy Adults: A Nationwide Dataset-Based Study.Journal of clinical medicine · 2025Article
- Introduction of AI Technology for Objective Physical Function Assessment.Bioengineering (Basel, Switzerland) · 2024Review
- Neural network model for prediction of possible sarcopenic obesity using Korean national fitness award data (2010-2023).Scientific reports · 2024Article
- Deep-learning model for predicting physical fitness in possible sarcopenia: analysis of the Korean physical fitness award from 2010 to 2023.Frontiers in public health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
purposeWe aimed to determine the best machine learning (ML) regression model for predicting grip strength in adults above 65 years using various independent variables, such as body composition, blood pressure, and physical performance.
methodsThe data comprised 107,290 participants, of whom 33.3% were male and 66.7% were female in Korean National Fitness Award Data from 2009 to 2019. The dependent variable was grip strength, which was calculated as the mean of right and left grip strength values.
resultsThe results showed that the CatBoost Regressor had the lowest mean squared error (M [Formula: see text] SE:16.659 ± 0.549) and highest R
conclusionThe findings of this study can be used to develop more accurate predictive models of grip strength in older adults.
Indexed as
Identifiers
37392358What 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.