High Pain Catastrophizing Scale predicts lower patient-reported outcome measures in the foot and ankle patient
Bibliographic record
Abstract
Abstract Background: A patient’s healthcare experience can be modulated by their understanding of their pre-operative disability along with their overall coping strategy. It is hypothesized that patient’s catastrophization and expectation on what they deem to be a successful surgery can affect their outcome. Methods: This current study prospectively assessed a consecutive cohort of patients undergoing foot and ankle reconstruction to describe the relationship between Pain Catastrophizing Scale (PCS) and patient-reported outcomes: SF-12 & FAOS. The PCS has a total score and three subcategories which are rumination, helplessness and magnification. Results: Forty-six patients were found to be eligible in the study with an average age of 54.7±14.4 years-old, a majority female (65%), a minority employed at the pre-operative visit (41%) and with an average BMI of 26.2±5.56. Looking at the FAOS Pain domain, it correlated significantly with the PCS Rumination and Helplessness subcategories. The FAOS Activity of Daily Living domain showed significant correlation with the PCS Rumination and Helplessness subcategories. The FAOS Quality of life domain was also statistically significant for the PCS Rumination and Helplessness subcategories. We found that the mental domain of the SF-12 had a statistically significant effect when compared to the Rumination (p=0.01) and Helplessness (p=0.001) subcategories.Conclusion: This study showed a significant association between an increase preoperative PCS and a worse one-year outcome looking at the FAOS domains. As such, in elective foot and ankle surgery, catastrophization should be screened for and potentially modulated pre-operatively to improve patient operative outcomes.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.004 | 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".