Predicting changes in the status of patient-reported outcome measures after Birmingham Hip Resurfacing
Bibliographic record
Abstract
Aims It is not known whether change in patient-reported outcome measures (PROMs) over time can be predicted by factors present at surgery, or early follow-up. The aim of this study was to identify factors associated with changes in PROM status between two-year evaluation and medium-term follow-up. Patients and Methods Patients undergoing Birmingham Hip Resurfacing completed the Veteran’s Rand 36 (VR-36), modified Harris Hip Score (mHHS), Tegner Activity Score, and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) at two years and a minimum of three years. A change in score was assessed against minimal clinically important difference (MCID) and patient-acceptable symptom state (PASS) thresholds. Binary logistic regression was used to assess the relationship between patient factors and deterioration in PASS status between follow-ups. Results Overall, 18% of patients reported reductions in mHHS total score exceeding MCID, and 21% reported similar reductions for WOMAC function scores. Nonetheless, almost all patients remained above PASS thresholds for WOMAC function (98%) and mHHS (93%). Overall, 66% of patients with mHHS scores < PASS at two years reported scores > PASS at latest follow-up. Conversely, 6% of patients deteriorated from > PASS to < PASS between follow-ups. Multivariable modelling indicated body mass index (BMI) > 27 kg/m2, VR-36 Physical Component Score (PCS) < 51, VR-36 Mental Component Score (MCS) > 55, mHHS < 84 at two years, female sex, and bone graft use predicted these deteriorating patients with 79% accuracy and an area under the curve (AUC) of 0.84. Conclusion Due to largely acceptable results at a later follow-up, extensive monitoring of multiple PROMs is not recommended for Birmingham Hip Resurfacing patients unless they report borderline or unacceptable hip function at two years, are female, are overweight, or received a bone graft during surgery. Cite this article: Bone Joint J 2019;101-B:1431–1437.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".