Prospective examination of pain-related and psychological predictors of CRPS-like phenomena following total knee arthroplasty: a preliminary study
Bibliographic record
Abstract
We hypothesized that preoperative emotional distress and pain intensity would predict the occurrence of signs and symptoms of complex regional pain syndrome (CRPS) following total knee arthroplasty (TKA). Depression (Beck Depression Inventory, BDI), anxiety (State Trait Anxiety Inventory, STAI), pain (McGill Pain Questionnaire-Short Form, MPQ), and signs/symptoms meeting IASP criteria for CRPS were assessed preoperatively, and at 1-, 3-, and 6-months postoperatively in 77 patients undergoing TKA. The prevalence of subjects fulfilling CRPS criteria was 21.0% at 1 month, 13.0% at 3 months, and 12.7% at 6 months postoperative. Higher preoperative scores on the STAI predicted positive CRPS status at 1-month follow-up (P<0.05), with a similar non-significant trend for preoperative BDI scores (P<0.10). Diagnostic sensitivity for the STAI was good (0.73), with moderate specificity (0.56). Neither measure predicted CRPS at later follow-up (P>0.10). Greater preoperative pain intensity predicted positive CRPS status at 3-month (MPQ-Sensory and MPQ-Affective; P<0.01) and 6-month (MPQ-Sensory) follow-up (P<0.01), but not at 1-month (P>0.10). Diagnostic sensitivity was high (0.83-1.00), with moderate specificity (0.53-0.60). Post-TKA patients with CRPS were more depressed at 1-month follow-up (P<0.05) and more anxious at 6-month follow-up (P<0.05) than patients with ongoing non-CRPS pain (all other comparisons non-significant, P>0.10). Overall, results indicate that CRPS-like phenomena occur in a significant number of patients early post-TKA; however, it is not associated with significantly greater complaints of postoperative pain. There appears to be a modest utility for preoperative distress and pain in predicting CRPS signs and symptoms following TKA, although false positive rates are relatively high.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".