The Psychological Assessment of Candidates for Spinal Cord Stimulation for Chronic Pain Management
Bibliographic record
Abstract
It is known that, in spite of meeting appropriate clinical criteria for spinal cord stimulation (SCS) and having undergone flawless procedures, a significant number of patients who fail the therapy continues to exist. It is the purpose of this article to focus on the development of psychosocial indicators of success for SCS, if any. Referring to specialist literature authors present a review of what is known, what is not known, and what remains controversial on this topic. After reading this article we hope the reader will understand the importance of a psychological evaluation as part of the development of standards for identifying appropriate patients for this therapy. To improve treatment outcomes of SCS, seems to be essential to perform psychosocial evaluations on all persons clinically indicated for SCS to exclude those patients, who most probably, on a psychosocial level, will fail the procedure. To maximize treatment efficacy, authors believe spinal cord stimulation for chronic pain control must be part of a comprehensive program. An accurate preoperative psychosocial assessment and a course of psychological assistance both before and after therapy seems to be crucial for improving 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 | 0.001 | 0.006 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".