ArticleThe Journal of hand surgery2026
Use of Wearable Sensors to Measure Improvements in Real World Upper Extremity Activity After Brachial Plexus Reconstruction.
Article in The Journal of hand surgery, 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
4 authors.
Funding
Abstract
purposeCurrent functional assessments after brachial plexus (BP) reconstruction, including surgeon-graded active range of motion and strength scores, and patient-reported outcomes (PROs), have limitations. This study evaluated the feasibility of wearable sensors to quantify recovery and functional outcomes following BP reconstruction. We hypothesized that sensor-derived measures of daily upper-extremity use would correlate with PROs and that real-world upper-extremity use would improve.
methodsTraumatic BP injury patients wore bilateral wrist accelerometers for 7-day periods at 3- to 6-month intervals. Data were grouped relative to timing of reconstruction. Duration and magnitude of upper-extremity activity were expressed as ratios of injured to uninjured limb (use and magnitude ratios). Disabilities of the Arm, Shoulder, and Hand; Impact of BP Injury; 36-Item Short Form Health Survey; and Patient-Reported Outcomes Measurement Information System-Upper Extremity scores were collected. Correlations assessed relationships between accelerometry data and PROs. Linear mixed models characterized changes in these relationships over time and the effect of time from surgery on accelerometry data.
resultsTwenty-seven participants were enrolled (82% male, 78% White). Mean age at injury and surgery were 41.7 ± 14.0 years and 42.5 ± 14.3 years, respectively. The use ratio correlated significantly with Disabilities of the Arm, Shoulder, and Hand (r = -0.45, P < .05), Impact Disability (r = -0.56, P < .05), 36-Item Short Form Health Survey Physical Function (r = 0.26, P < .05), and Patient-Reported Outcomes Measurement Information System-Upper Extremity (r = 0.38, P < .05) scores. The magnitude ratio significantly correlated with Disabilities of the Arm, Shoulder, and Hand (r = -0.44, P < .05), Impact Disability (r = -0.50, P < .05), and Patient-Reported Outcomes Measurement Information System-Upper Extremity (r = 0.47, P < .05) scores. Linear mixed models supported these associations but showed no effect of time from surgery on use or magnitude ratios.
conclusionsWearable sensor-derived use and magnitude ratios demonstrate convergent validity with PROs following BP reconstruction. CLINICAL RELEVANCE: Wearable sensors may offer a more direct, objective assessment of functional recovery to support postoperative assessment, prognostication, treatment planning, and counseling beyond traditional clinical measures.
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.