Development and Application of a Novel Metric to Characterize Comprehensive Range of Motion of Reverse Total Shoulder Arthroplasty
Bibliographic record
Abstract
Active range of motion (ROM) of reverse total shoulder arthroplasty (rTSA) can be limited by bony impingement, muscle inability, and joint instability. The aim of this study was to develop a novel metric representative of comprehensive ROM of rTSA, which is evaluated in the context of all three factors. It was hypothesized that the metric, termed global circumduction ROM (GC-ROM), would capture differences resulting from directional changes in rTSA design parameters known to increase ROM. GC-ROM was calculated for a set of 18 rTSA configurations with humeral polyethylene cup depths of 6 and 8.1 mm, glenosphere lateralization (GLat) distances of 0, 5, and 10 mm, and neck-shaft angles (NSA) of 135°, 145°, and 155°. For any implant configuration, arm positions were defined by internal/external (IE) rotation angle and two spherical coordinates representing the elevation plane angle and elevation angle. At each IE rotation angle, incremental positions with variable elevation plane and elevation angles were checked for feasibility based on impingement, muscle ability, and risk of instability. Coordinates of feasible positions were mapped to unit spheres and connected to form regions, of which the surface area was calculated to represent allowable circumduction ROM. ROMs were averaged across all IE rotation angles to produce a single metric, GC-ROM. The results showed that decreasing cup depth and increasing GLat and NSA increased GC-ROM. In conclusion, a novel metric to characterize comprehensive ROM, evaluated based on several ROM-limiting factors, was developed as a performance metric through which rTSA designs can be compared. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 38:880-887, 2020.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".