Review: ACE inhibition or angiotensin receptor blockade: which should we use in diabetic patients?
Bibliographic record
Abstract
Blockade of the effects of angiotensin II (Ang II) by using an angiotensin-converting enzyme (ACE) inhibitor has been proven to be of value in Type 1 diabetic nephropathy and in non-diabetic renal disease. Evidence in favour of Ang II blockade in Type 2 diabetic patients with renal damage is still lacking for ACE inhibitors (ACE-Is), while recent data indicate that angiotensin receptor blockers (ARBs) could be the drugs of choice in this situation. On the other hand, renal damage from the onset of disease is accompanied by a very significant increment in global cardiovascular risk. This fact, as well as that of simultaneous renal and cardiovascular protection, have to be considered for drug selection. In this sense, ACE-Is have been shown to be the drugs of choice when secondary cardiovascular prevention is required, while the evidence in primary prevention in hypertensive patients has been shown with losartan in the Losartan Intervention For Endpoint reduction in hypertension (LIFE) study. All these facts led to the conclusion that both ACE-Is and ARBs can be considered when both renal and cardiovascular protection are aimed for in Type 2 diabetic patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".