Psychological Characteristics, Female Sex, and Opioid Use Predict Acute Postoperative Pain in Patients Surgically Treated for Thumb Base Osteoarthritis: A Cohort Study
Bibliographic record
Abstract
BACKGROUND: It is unclear which factors predict acute postoperative pain in patients surgically treated for thumb base osteoarthritis. The authors investigated the influence of type of surgery, preoperative sociodemographics, preoperative patient-reported outcome measures, psychological characteristics, and postoperative opioid use on acute postoperative pain 24 hours postoperatively following surgery for thumb carpometacarpal osteoarthritis. In addition, preoperative and acute postoperative pain were compared. METHODS: In this prospective cohort study, 215 patients surgically treated for thumb carpometacarpal osteoarthritis were included. Data were collected in 16 clinics for hand surgery and therapy in The Netherlands. Hierarchical regression was used to identify whether type of surgery, preoperative sociodemographics, preoperative patient-reported outcome measures, psychological characteristics (including treatment credibility and expectations, illness perception, pain catastrophizing, anxiety, and depression), and postoperative opioid use predicted acute postoperative pain 24 hours postoperatively, measured using the Numeric Pain Rating Scale (range, 0 to 10). RESULTS: Female sex, opioid use, higher preoperative satisfaction with hand, and higher self-reported consequences and coherence predicted greater postoperative pain, with 31 percent explained variance in the final model including psychological factors. Mean postoperative Numeric Pain Rating Scale score was lower (5.1 ± 2.4) than preoperative pain, measured using visual analogue scales (during the past week, 6.7 ± 1.7; physical load, 7.5 ± 1.7) and the Michigan Hand Outcomes Questionnaire (6.4 ± 1.4; p < 0.001). CONCLUSIONS: Psychological factors, female sex, and opioid use enhance the prediction of acute postoperative pain beyond surgery type, preoperative sociodemographics, and patient-reported outcome measures. Female sex and opioid use were the strongest predictors, even after controlling for psychological factors. Future studies may investigate sex-based approaches and patient education for reducing acute postoperative pain. CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, II.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".