Aberrant opioid use behaviour in advanced cancer
Bibliographic record
Abstract
OBJECTIVES: To evaluate the presence of aberrant behaviour in a consecutive sample of patients with advanced cancer treated with opioids in a country like Italy, with its peculiar attitudes towards the use opioids. The second objective was to detect the real misuse of opioids in clinical practice. METHODS: Prospective observational study in two palliative care units in Italy in a period of 6 months. At admission the Edmonton Symptom Assessment Scale, the Memorial Delirium Assessment Scale, Brief Pain Inventory (BPI) and the Hospital Anxiety Depression Scale were measured. For detecting the risk of aberrant opioid use, the Screener and Opioid Assessment for Patients With Pain (SOAAP), the Opioid Risk Tool (ORT), the Cut Down-Annoyed-Guilty-Eye Opener (CAGE) questionnaire adapted to include drug use (CAGE-AID) were used. Aberrant behaviours displayed at follow-up within 1 month were recorded. RESULTS: One-hundred and thirteen patients with advanced cancer were examined. About 35% of patients were SOAPP positive. There was correlation between SOAPP, CAGE-AID and ORT. SOAPP was independently associated with a lower Karnofsky level, pain intensity, poor well-being, BPI pain at the moment. No patient displayed aberrant behaviours, despite having a moderate-high risk. CONCLUSIONS: Despite a high percentage of patients showed a high risk of aberrant behaviours, no patient displayed clinical aberrant behaviours after 1 month-follow-up. This does not exempt from continuous monitoring for patients who are at risk.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".