The Impact of a Gap Balancing or Measured Resection Surgical Technique on Posterior Condylar Offset and Patient-Reported Outcome Measures
Bibliographic record
Abstract
Background To increase total knee arthroplasty procedure satisfaction, surgeons are exploring improvements in surgical technique. The impact of gap balancing or measured resection approach on posterior condylar offset (PCO) is not well understood. Methods We reviewed the clinical and radiographic results of 498 unilateral posterior stabilized total knee arthroplasties. Radiographs were assessed to measure the primary endpoints of anterior-posterior width, PCO, and anterior condylar offset. Clinical outcome measures were used to assess patient improvement measures. Multiple linear regression analyses were performed to determine the clinical factors related to our primary endpoints. Results No significant difference was observed between groups in anterior-posterior width ( P = .24) and PCO ( P = .78). Significant positive correlations were observed between postoperative PCO and knee range of motion (r = 0.12, P = .04) and total Knee Society Scores (r = 0.14, P = .02). Conclusion No impact of surgical technique on PCO was observed. Correlations were observed between postoperative PCO and the functional subscore and total Knee Society Score. All patients reported clinical improvements at 1 year postoperatively.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".