Weight-Bearing Monitoring Devices in Lower Extremity Fractures: A Scoping Review
Bibliographic record
Abstract
Jackson Robinson, Alice Wei Ting Wang, David J Stockton Department of Orthopaedics, The University of British Columbia Faculty of Medicine, Vancouver, BC, CanadaCorrespondence: David J Stockton, Email david.stockton@vch.caBackground: Orthopaedic surgeons commonly prescribe weight-bearing parameters for their patients for a variety of reasons. Weight-bearing may be limited in order to control the healing environment, but advancing a patient’s weight-bearing status is preferably done as quickly as possible to maximize functional recovery. However, it is entirely unclear to what extent these prescriptions are followed in practice. The purpose of this scoping review is to identify and compare non-invasive devices used for the measurement of weight-bearing following lower extremity fractures.Methods: Database searches of MEDLINE, EMBASE and the Cochrane Central Register of Controlled Trials (CENTRAL) were completed to identify relevant studies. Titles were screened for relevance, and abstracts were screened against the eligibility criteria. We identified studies that investigated the use of external force, pedal pressure, or activity monitoring devices used in adults after lower extremity fractures and excluded studies involving compartment pressure measurement.Findings: Sixty-two studies met the inclusion criteria. About 39% of studies used an insole-type device, which could be worn in a shoe or integrated into a removable boot. Other device types included step count or activity monitors (52%), force plates (18%), pressure film (2%) and external pedobarography systems (27%).Interpretation: We found that different monitors offered varying types of measurements and are suitable for a variety of applications. Therefore, selecting the ideal device depends on the metric of interest. Further high-quality prospective studies utilizing device monitoring are needed to validate the theory that early weight-bearing is beneficial and safe for patients with lower extremity fractures.Keywords: trauma, fracture, lower extremity, weight-bearing, monitoring
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".