Impact of ALLHAT publication on antihypertensive prescribing patterns in Regione Emilia-Romagna, Italy
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Studies from the US and Canada observed changes in antihypertensive prescribing patterns in accordance with Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) study findings immediately after the study's publication, but little is known about the impact of ALLHAT in Italy. The objective of this study was to examine antihypertensive prescribing patterns in Regione Emilia-Romagna (RER), Italy, following the publication of the ALLHAT main results. METHODS: We conducted a time series analysis using automated pharmacy data of approximately 4 million RER residents between 1 January 2000 and 31 December 2003. We computed monthly relative percentages of prescriptions for all antihypertensive medications and separately for all new antihypertensives defined as no recorded antihypertensive use in the previous year. A stepwise auto-regressive forecasting model based on data prior to the ALLHAT publication was used to estimate predicted relative percentages for the 12 months following the ALLHAT publication. Observed and predicted values were compared. RESULTS AND DISCUSSION: Use of thiazide-type diuretics showed a general increasing trend over the study period, but the difference between the observed and predicted values reached statistical significance only for new prescriptions in October 2003 (3.71% vs. 2.32%; P = 0.0170). The relative percentage of new angiotensin-converting enzyme inhibitor and angiotensin receptor blocker (ACE/ARB) prescriptions was higher than predicted for the months May to August 2003 (P < 0.05), but no significant differences were observed for total ACE/ARB prescriptions. Modest changes in patterns of prescribing of calcium channel blockers and alpha-blockers were observed. CONCLUSION: We found little evidence that the ALLHAT study had an impact on antihypertensive prescribing patterns in RER in the year following their publication.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".