Trends in new prescription of gabapentinoids and of coprescription with opioids in the 4 nations of the UK, 1993–2017
Bibliographic record
Abstract
We explored potential differences in time trends of gabapentinoid prescription and of opioid coprescription between 1993 and 2017 in the 4 UK nations using the Clinical Practice Research Datalink, a UK primary care database. There were distinct trends in annual rates of new gabapentin and pregabalin prescriptions in Northern Ireland. The rate of new gabapentin prescriptions rapidly increased after 2010 and exceeded that of the other nations by 2017 (rate of 836 [95% confidence interval: 787-887] per 100 000 person-years). Additionally, the rate of new pregabalin prescriptions was higher during the entire study period, reaching a peak of 1139 (95% confidence interval: 1088-1193) per 100 000 person-years in 2010, 5-fold higher than the other nations. Findings in Northern Ireland may be partly attributable to the high burden of anxiety disorders, an indication for pregabalin. Further exploration of reasons for discrepancies in gabapentinoid prescribing between UK nations is warranted.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".