L’hypertension chez les diabétiques de type 2: Mise à jour sur le traitement pharmacologique
Bibliographic record
Abstract
OBJECTIVE: To summarize the evidence for the need to improve pharmacologic management of hypertension in people with type 2 diabetes and to provide expert advice on how blood pressure (BP) treatment can be improved in primary care. SOURCES OF INFORMATION: Studies were obtained by performing a systematic review of the literature on hypertension and diabetes, from which management recommendations were developed, reviewed, and voted on by a group of experts selected by the Canadian Hypertension Education Program and the Canadian Diabetes Association; authors’ expert opinions on optimal pharmacologic management were also considered during this process. MAIN MESSAGE: The pathogenesis of hypertension in patients with diabetes is complex, involving a range of biological and environmental factors and genetic predisposition; as a result, hypertension in people with diabetes incurs higher associated risks and adverse events. Mortality and morbidity are heightened in diabetes patients who do not achieve BP control (ie, a target value of less than 130/80 mm Hg). Large randomized controlled trials and meta-analyses of randomized controlled trials have shown that reducing BP pharmacologically is single-handedly the most effective way to reduce rates of death and disability in patients with diabetes, particularly associated cardiovascular risks. Often, combinations of 2 or more drugs (diuretics, angiotensin-converting enzyme inhibitors, β-blockers, angiotensin receptor blockers, calcium channel blockers, spironolactone, etc) are required for pharmacotherapy to be effective, particularly for patients in whom BP is difficult to control. However, the health care costs associated with extensively lowering BP are substantially less than the costs associated with treating the complications that can be prevented by lowering BP. CONCLUSION: Detecting and managing hypertension in people with diabetes is one of the most effective measures to prevent adverse events, and pharmacotherapy is one of the most effective ways to maintain target BP levels in primary care.
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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 | 0.015 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".