Pharmacovigilance in hospice/palliative care: Net effect of amitriptyline or nortriptyline on neuropathic pain: UTS/IMPACCT Rapid programme international consecutive cohort
Bibliographic record
Abstract
Background: Real-world effectiveness of interventions in palliative care need to be systematically quantified to inform patient/clinical decisions. Neuropathic pain is prevalent and difficult to palliate. Tricyclic antidepressants have an established role for some neuropathic pain aetiologies, but this is less clear in palliative care. Aim: To describe the real-world use and outcomes from amitriptyline or nortriptyline for neuropathic pain in palliative care. Design: An international, prospective, consecutive cohort post-marketing/phase IV/pharmacovigilance/quality improvement study of palliative care patients with neuropathic pain where the treating clinician had already made the decision to use a tricyclic antidepressant. Data were entered at set times: baseline, and days 7 and 14. Likert scales graded benefits and harms. Setting/participants: Twenty-one sites (inpatient, outpatient, community) participated in six countries between June 2016 and March 2019. Patients had clinician-diagnosed neuropathic pain. Results: One hundred and fifty patients were prescribed amitriptyline (110) or nortriptyline (40) of whom: 85% had cancer; mean age 73.2 years (SD 12.3); mean 0–4 scores for neuropathic pain at baseline were 1.8 (SD 1.0). By day 14, doses of amitriptyline were 57 mg (SD 21) and nortriptyline (48 mg (SD 21). Fifty-two (34.7%) patients had pain improvement by day 14 (amitriptyline (45/110 (43.3%); nortriptyline (7/40 (18.9%)). Thirty-nine (27.7%) had new harms; (amitriptyline 29/104 (27.9%); nortriptyline 10/37 (27.0%); dizziness ( n = 23), dry mouth ( n = 20), constipation ( n = 14), urinary retention ( n = 10)). Benefits without harms occurred (amitriptyline (26/104 (25.0%); nortriptyline (4/37 (10.8%)). Conclusions: Benefits favoured amitriptyline while harms were similar for both medications.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".