Accuracy of an Apparatus for Measuring Glenoid Baseplate Micromotion in Reverse Shoulder Arthroplasty
Bibliographic record
Abstract
Abstract Reverse shoulder arthroplasty (RSA) is used to treat patients with cuff tear arthropathy. Loosening remains to be one of the principal modes of implant failure and the main complication leading to revision. Excess micromotion contributes to glenoid loosening. This study sought to determine the predictive accuracy of an experimental system designed to assess factors contributing to RSA glenoid baseplate micromotion. A half-fractional factorial experiment was designed to assess 4 factors: central element type (screw versus peg), central element length (13.5 versus 23.5 mm), anterior-posterior peripheral screw type (locking versus nonlocking) and cancellous bone density (10 versus 25 pounds per cubic foot (pcf)). Four linear variable differential transducers (LVDTs) recorded micromotion from a stainless-steel disk surrounding a modified glenosphere. The displacements were used to interpolate micromotion at each peripheral screw position. The mean absolute percentage error (MAPE) was used to determine the predictive accuracy and error range of the system. The MAPE for each condition ranged from 6.8% to 12.9% for an overall MAPE of (9.5 ± 0.9)%. The system had an error range of 2.7 μm to 20.1 μm, which was lower than those reported by prior studies using optical systems. One of the eight conditions had micromotion that exceeded 150 μm. These findings support the use of displacement transducers, specifically LVDTs, as an accurate system for determining RSA baseplate micromotion in rigid polyurethane foam bone surrogates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".