Evaluation of treatment efficacy in a large regional pain clinic
Bibliographic record
Abstract
Although it is generally accepted that pain clinics are efficacious, we seek to evaluate the outcome of medical treatments given in a large outpatient pain clinic in terms of clinically relevant change. Treatments include drug therapy, nerve blockade, surgery, nerve stimulation and relaxation. Pain intensity, disability, depression and anxiety are measured at presentation and discharge. The psychometric questionnaires used are: Oswestry Disability Inventory (GDI), Modified Zung Self-rating Depression Scale (m-ZSDS), Speilberger StateTrait Anxiety Inventory (STAI-S), and McGill Pain Questionnaire (MPQ-PRI-T). Pain intensity is also measured using a visual analogue scale (VAS). 2348 patients entered the study. A sub-group of 739 patients (36.4%) treated to discharge, were analysed for outcome. 24.6% (n = 525) of these patients have a 50% or greater fall in pain severity scores. Comparisons of group means indicate that pain severity and disability are reduced after treatment but depression and anxiety are not. For patients with improvement of pain, there is an associated improvement in disability and depression. Many patients attending the clinic do not receive good pain relief. The low rates of success will persist until chronic pain conditions are better understood and classified, and clinicians can predict which patients may be improved.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".