Learning curve with a new primary total knee arthroplasty implant: a multicenter perspective with more than 2000 patients
Bibliographic record
Abstract
BACKGROUND: This study provides an example for evaluating learning curve when introducing a new knee system. METHODS: Thirty-five investigators across 22 sites prospectively implanted 843 subjects with currently available products (group A). Seventy-seven investigators across 48 sites prospectively implanted 2330 subjects with the ATTUNE Knee System; in which the first 10 subjects for each surgeon were the learning curve cases (group B, N = 611), and the later subjects were designated as group C (N = 1719). Surgical time, rates of intraoperative and early postoperative complications, and patient-reported outcome measures (PROMs) at a minimum of 1 year were compared. RESULTS: = .955 for group C vs group A). Intraoperative, early (<90 day) complication rates, and PROMs were similar for all groups. CONCLUSIONS: The new knee system learning curve was characterized by a slightly longer surgical time with no negative impact on complications or PROMs. LEVEL OF EVIDENCE: III.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".