Trends in Opioid use for Chronic Neuropathic Pain: a Survey of Patients Pursuing Enrollment in Clinical Trials
Bibliographic record
Abstract
PURPOSE: Clinical trials suggest that opioids relieve neuropathic pain and decrease pain‐related disability. We conducted a pilot study of current prescribing trends and patients’ attitudes towards opioids for neuropathic pain. METHODS: A patient questionnaire was completed by individuals pursuing enrollment in neuropathic pain clinical trials at our facility. RESULTS: Of 154 patients with diabetic neuropathy (55.2%), postherpetic neuralgia (29.9%), idiopathic peripheral neuropathy (9.7%) and other neuropathies (5.2%), 73.4% complained of inadequate pain control, the mean pain duration was 4.7 (SD = 4.4) yr and the mean pain intensity (0–10) was 7.7 (SD = 2.3). In this group, 40.9% had never tried opioids and 24.7% had never tried any opioids, tricyclic antidepressants or anticonvulsants. Only 9.7% were receiving long‐acting opioids or “around the clock” dosing whereas 25.3% were receiving opioids on an “as needed” basis. Opioids combined with tricyclic antidepressants and/or anticonvulsants were used in 11.0%. Fear of addiction and adverse effects were expressed by 31.8% and 46.8% respectively. CONCLUSION: These data suggest that barriers to opioid therapy for neuropathic pain include patients’, and possibly physicians’, fears of addiction and adverse effects, which are exaggerated in light of current evidence. The merits of continuous treatment with sustained‐release opioids, “as needed” dosing with short‐acting preparations, or combining opioids with other agents are discussed, Continued research and communication between health professionals, law enforcement officials and legislators is vital in order to facilitate appropriate opioid use which has a minimal negative impact on the public yet optimally benefits individuals who suffer from disabling neuropathic pain.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".