ArticlePeerJ2021
Development and validation of bioimpedance prediction equations for fat-free mass in unilateral male amputees.
Article in PeerJ, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05360667 (The Clinical Effectiveness of Exergame-based Exercise Training in the Prevention of Fragile Syndrome and Sarcopenia Among Elders in Rural Long-term Care Facilities), which is not on this map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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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.
The Clinical Effectiveness of Exergame-based Exercise Training in the Prevention of Fragile Syndrome and Sarcopenia Among Elders in Rural Long-term Care Facilities
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review.Journal of translational medicine · 2024Pooled it
- Multi-Frequency Bioimpedance Analysis in Practice: A Review of Validated Prediction Equations for Key Body Composition Parameters.Physiological research · 2025Review
- A Comparative Study of Paralympic Veterans with Either a Spinal Cord Injury or an Amputation: Implications for Personalized Nutritional Advice.Journal of functional morphology and kinesiology · 2025Article
- Calculation of Integral Indicators of the Metabolic Status and Filtration Function of Kidneys in Patients with a Combat Mine-Explosive Injury who Lost Significant Body Weight due to Limb Amputation.Acta medica Lituanic · 2025Article
- Using exergame-based exercise to prevent and postpone the loss of muscle mass, muscle strength, cognition, and functional performance among elders in rural long-term care facilities: A protocol for a randomized controlled trial.Frontiers in medicine · 2022Article
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 at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMetabolic disease due to increased fat mass is observed in amputees (APTs), thereby restricting their activity. Systemic health management with periodic body composition (BC) testing is essential for healthy living. Bioelectrical impedance analysis (BIA) is a non-invasive and low-cost method to test BC; however, the APTs are classified as being exempted in the BIA.
objectiveTo develop segmental estimated regression equations (sEREs) for determining the fat-free mass (FFM, kg) suitable for APTs and improve the accuracy and validity of the sERE.
methodsSeventy-five male APTs participated in this cross-sectional study. Multiple regression analysis was performed to develop highly accurate sEREs of BIA based on independent variables derived from anthropometric measurements, dual-energy X-ray absorptiometry (DXA), and BIA parameters. The difference in validity between the predicted DXA and sum of the segmentally-predicted FFM values by sEREs (Sum_sEREs) values was evaluated using bivariate linear regression analysis and the Bland-Altman plot.
resultsThe coefficient of determination (
conclusionsWe confirmed the possibility of evaluating the FFM of APTs through the sEREs developed in this study. We also identified several independent variables that should be considered while developing such sEREs. Further studies are required to determine the validity of our sEREs and the most appropriate BIA frequencies for measuring FFM in APTs.
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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.