123 Patient Perspectives Regarding Ethics of Neuromodulators in the Treatment of Persistent Postoperative Neuropathic Pain
Bibliographic record
Abstract
INTRODUCTION: The aim of this study is to better understand patients' perspectives of persistent postoperative neuropathic pain (PPNP) and assess perceptions of the ethical issues surrounding implantation of neuromodulators, such as spinal cord stimulators (SCS), to treat PPNP in medically refractory patients. METHODS: Semistructured face-to-face interviews were conducted with patients from the neurosurgery clinics at Toronto Western Hospital. Interviews were audio recorded, transcribed, and subjected to thematic analysis using open and axial coding. RESULTS: The median age of the 18 study participants is 58 years and 44.4% (8/18) were female. The range of the duration of preoperative symptoms varied from 1 month to over 20 years, and was primarily back dominant (11/18). The median time since patients most recently underwent spinal surgery was 3 years. The majority of patients would be willing to have their surgeon reoperate on them if needed, citing a strong patient-physician relationship as the reason for this. Finally, nearly unanimously (17/18), patients did not perceive an ethical problem with a surgeon performing a structurally corrective spinal surgery and subsequently also implanting a SCS in the same patient that develops medically refractory PPNP. Broadly, patients cite trust in the surgeon and confidence in his or her competence as the most important factors in this perspective. CONCLUSION: The results of this work reveal that patients are comfortable with surgeons addressing their pain with all of the tools in their armamentarium, so long as they are well appraised of surgical risks and benefits and have open communication and trust in the physician-patient relationship.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".