Custom total knee arthroplasty combined with personalised alignment grants 94% patient satisfaction at minimum follow‐up of 2 years
Bibliographic record
Abstract
PURPOSE: The purpose was to report detailed patient-reported outcome measures (PROMs) and satisfaction rates for computed tomography (CT)-based custom TKA at minimum follow-up of 2 years. The hypothesis was that custom TKA combined with 'personalised alignment' would yield equivalent or better PROMs compared to values reported in systematic reviews and meta-analyses on off-the-shelf (OTS) TKA. METHODS: Of an initial cohort of 150 custom TKAs, four died (unrelated to surgery), one required a revision, and five refused participation, leaving 140 patients for analysis. Patients completed pre- and post-operative PROMs (Oxford Knee Score (OKS), Forgotten Joint Score (FJS), Knee injury and Osteoarthritis Outcome Score (KOOS), Western Ontario and McMaster osteoarthritis index (WOMAC)) as well as overall level of satisfaction. Proportions that attained a patient acceptable symptom state (PASS) were calculated for OKS and FJS. Clinical findings were compared to the average scores reported for PROMs in recent systematic reviews and/or meta-analyses on OTS TKA. Descriptive statistics were used to summarise the clinical findings as means, standard deviations (SD) and ranges, or numbers and percentages. RESULTS: At mean follow-up 33.5 ± 4.5 months, 94% (135/143) were either satisfied or very satisfied. Proportions that achieved PASS were 89% for OKS (120/135), and 85% for FJS (118/139). Median OKS, WOMAC and KOOS Symptoms and Pain scores were all within the 4th quartile of medians reported in systematic reviews and/or meta-analyses. CONCLUSIONS: At a minimum follow-up of two years following custom TKA combined with 'personalised alignment', 94% of patients were either satisfied or very satisfied, and the PASS criteria were achieved in 89% for OKS and 85% for FJS, all of which compare favourably to published outcomes of OTS TKA. Direct comparisons to the literature may not be appropriate, however, considering the heterogeneity of patient demographics and alignment techniques. Randomised controlled trials with sufficient statistical power are needed to corroborate these findings and generalise them to unselected TKA patients. LEVEL OF EVIDENCE: IV, retrospective cohort study.
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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 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".