The relationship of pain catastrophizing with postoperative patient-reported outcome measures in adults with pre-arthritic hip disease
Bibliographic record
Abstract
ABSTRACT The association between preoperative pain catastrophizing and postoperative patient-reported outcome measures of patients with pre-arthritic hip disease was evaluated. All patients scheduled for joint-preserving surgeries of the hip (JPSH) at our institution were approached. Patient demographics (age, sex, body mass index (BMI)), pain intensity (Numeric Pain Scale (NPS)) and pain catastrophizing (Pain Catastrophizing Scale (PCS)) were collected preoperatively. Patient function (12-Item International Hip Outcome Tool (iHot-12)) and physical and mental health (Patient-Reported Outcomes Measurement Information System (PROMIS-10) mental/physical) were collected preoperatively, three-month and one-year postoperatively. The analysis consisted of multivariate linear regression models fitted for continuous scores of outcome measures at three-month and one-year. Correlation between preoperative PCS and iHot-12 was assessed using the Pearson correlation coefficient. A total of 274 patients completed the PCS and were included in the multivariate linear regression models. Most patients were females (66.8%), mean age was 33 (SD 9), mean BMI was 26.5 (SD 5.8) and most were diagnosed with femoro-acetabular impingement (46.0%) and underwent arthroscopy (77.0%). There were statistically significant correlations between PCS and iHot-12 (preoperatively −0.615, P < 0.001; three-month −0.242, P = 0.002). Statistically significant associations were found for function (three-month PCS P = 0.046, age P = 0.014, NPS P = 0.043; one-year BMI P = 0.005, NPS P = 0.014), physical health (three-month BMI, P = 0.002, NPS P = 0.008; one-year BMI P = 0.002, NPS P = 0.013) and mental health (three-month BMI P = 0.047; one-year BMI P = 0.030). There is an association between function and preoperative pain catastrophizing in patients with pre-arthritic hip disease undergoing JPSH. When considering confounding variables, preoperative pain catastrophizing is associated with short-term recovery.
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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 | 0.001 | 0.007 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".