Emotional numbing and pain intensity predict the development of pain disability up to one year after lateral thoracotomy
Bibliographic record
Abstract
Little is known about the factors that predict the transition of acute, time limited pain to chronic pathological pain following postero-lateral thoracotomy. The aim of the present prospective, longitudinal study was to determine the extent to which (1) pre-operative pain intensity, pain disability, and post-traumatic stress symptoms (PTSS) predict post-thoracotomy pain disability 6 and 12 months later; and (2) if these variables, assessed at 6 months, predict 12 month pain disability. Fifty-four patients scheduled to undergo postero-lateral thoracotomy for intrathoracic malignancies were recruited before surgery and followed prospectively for one year. The incidence of chronic post-thoracotomy pain was 68.1% and 61.1% at the 6 and 12 month follow-ups, respectively. Multiple regression analyses showed that neither pre-operative factors nor acute movement-evoked post-operative pain predicted 6 or 12 month pain disability. However, concurrent pain intensity and emotional numbing, but not avoidance symptoms, made unique, significant contributions to the explanation of pain disability at each follow-up (total R(2)=76.3.0% and 63.9% at 6 and 12 months, respectively, both p<0.0009). The relative contribution of pain intensity decreased, while that of emotional numbing increased with time, indicating a progressive de-coupling of pain intensity and disability and a concomitant strengthening of the link between emotional numbing and disability. This suggests that pain may serve as a traumatic stressor which causes increased emotional numbing. The results also support recent suggestions that avoidance and emotional numbing constitute separate PTSS clusters. Further research is required to determine the source(s) of emotional numbing after postero-lateral thoracotomy and effective interventions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".