The potential savings of using thiazides as the first choice antihypertensive drug: cost-minimisation analysis
Bibliographic record
Abstract
BACKGROUND: All clinical practice guidelines recommend thiazides as a first-choice drug for the management of uncomplicated hypertension. Thiazides are also the lowest priced antihypertensive drugs. Despite this, the use of thiazides is much lower than that of other drug-classes. We wanted to estimate the potential for savings if thiazides were used as the first choice drug for the management of uncomplicated hypertension. METHODS: For six countries (Canada, France, Germany, Norway, the UK and the US) we estimated the number of people that are being treated for hypertension, and the proportion of them that are suitable candidates for thiazide-therapy. By comparing this estimate with thiazide prescribing, we calculated the number of people that could switch from more expensive medication to thiazides. This enabled us to estimate the potential drug-cost savings. The analysis was based on findings from epidemiological studies and drug trials, and data on sales and prescribing provided by IMS for the year 2000. RESULTS: For Canada, France, Germany, Norway, the UK and the US the estimated potential annual savings were US13.8 million dollars, US37.4 million dollars, US72.2 million dollars, US10.7 million dollars, US119.7 million dollars and US433.6 million dollars, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.000 | 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".