Time‐trends in the prescribing of gastroprotective agents to primary care patients initiating low‐dose aspirin or non‐steroidal anti‐inflammatory drugs: a population‐based cohort study
Bibliographic record
Abstract
AIMS: Low-dose aspirin (LDA) and non-steroidal-anti-inflammatory drugs (NSAIDs) both increase the risk of upper gastrointestinal events (UGIEs). In the Netherlands, recommendations regarding the prescription of gastroprotective agents (GPAs) in LDA users were first issued in 2009 in the HARM-Wrestling consensus. National guidelines on gastroprotective strategies (GPSs) in NSAID users were issued in the first part of the preceding. The aim of the present study was to examine time-trends in GPSs in patients initiating LDA and those initiating NSAIDs between 2000 and 2012. METHODS: Within a large electronic primary healthcare database, two cohorts were selected: (i) patients newly prescribed LDA and (ii) patients newly prescribed NSAIDs between 2000 and 2012. Patients who had been prescribed a GPA in the previous six months were excluded. For both cohorts, patients' risk of a UGIE was classified as low, moderate or high, based on the HARM-Wrestling consensus, and the presence of an adequate GPSwas determined. RESULTS: A total of 37 578 patients were included in the LDA cohort and 352 025 patients in the NSAID cohort. In both cohorts, an increase in GPSs was observed over time, but prescription of GPAs was lower in the LDA cohort. By 2012, an adequate GPS was present in 31.8% of high-risk LDA initiators, vs. 48.0% of high-risk NSAID initiators. CONCLUSIONS: Despite a comparable risk of UGIEs, GPSs are prescribed less in high-risk LDA initiators than in high-risk NSAID initiators. For both groups of patients, there is still room for improvement in guideline adherence.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".