Correlations among trends in cardiovascular mortality, hypertensive nephrosclerosis and antihypertensive medication prescriptions in North America
Bibliographic record
Abstract
The National Health and Nutrition Surveys (NHANES) prepared for the National Heart, Lung and Blood Institute have demonstrated a dramatic decline in both age-adjusted mortality rates from coronary heart disease and stroke since the early 1970s. Concurrently, there has been a steady and dramatic increase in the prevalence of end-stage renal failure requiring renal replacement therapy (all modalities of dialysis and renal transplantation) and the incidence of end-stage renal failure attributed to hypertensive nephrosclerosis reported by the United States Renal Data System (USRDS) and by the Canadian Organ Replacement Registry (CORR) since the early 1980s. Antihypertensive medication prescribing practices of physicians have evolved since the 1980s and through the 1990s, with interesting changes in reported antihypertensive medication prescription behaviours of physicians which correlate to changes in the incidence of hypertensive end-stage renal disease. The rate of increase in the incidence of end-stage renal disease attributed to hypertensive nephrosclerosis has attenuated in the latter half of the 1990s. Possible explanations for this trend as reflected by physician prescribing behaviours, particularly an increase in the use of calcium channel blockers, angiotensin receptor blockers and angiotensin converting enzyme inhibitors compared to a plateau in reliance upon beta-blockers and diuretics, are discussed.
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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 | 0.002 |
| 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".