Review: ACE inhibitors delay microalbuminuria in diabetes without nephropathy and reduce mortality in diabetic nephropathy
Bibliographic record
Abstract
Strippoli GF, Craig MC, Schena FP, et al . Role of blood pressure targets and specific antihypertensive agents used to prevent diabetic nephropathy and delay its progression. J Am Soc Nephrol 2006;17:S153–5. [OpenUrl][1][Abstract/FREE Full Text][2] Q Do antihypertensive agents prevent onset of microalbuminuria in patients with diabetes without nephropathy and delay progression in patients with diabetic nephropathy? Clinical impact ratings GP/FP/Primary care ★★★★★★☆ IM/Ambulatory care ★★★★★★☆ Nephrology ★★★★★★☆ Cardiology ★★★★★★☆ Endocrine ★★★★★☆☆ ### ![Graphic][3]</img>Data sources: Medline (1966 to September 2003), EMBASE/Excerpta Medica (1988 to September 2003), Cochrane Central Register of Controlled Trials (2004), reference lists, and authors in the field. ### ![Graphic][4]</img>Study selection and assessment: randomised controlled trials (RCTs) in any language comparing an antihypertensive agent with another antihypertensive agent or placebo in diabetic patients with and without nephropathy. 16 RCTs (n = 8570) in diabetic patients without nephropathy and 43 RCTs (n = 7545) in diabetic patients with nephropathy met the selection criteria. Quality assessment of individual studies was based on allocation concealment, intention to treat analysis, loss to follow up, and blinding. ### ![Graphic][5]</img>Outcomes: onset of microalbuminuria, all cause mortality, end stage renal disease … [1]: {openurl}?query=rft.jtitle%253DJournal%2Bof%2Bthe%2BAmerican%2BSociety%2Bof%2BNephrology%26rft.stitle%253DJ.%2BAm.%2BSoc.%2BNephrol.%26rft.issn%253D1046-6673%26rft.aulast%253DStrippoli%26rft.auinit1%253DG.%2BF.M.%26rft.volume%253D17%26rft.issue%253D4_suppl_2%26rft.spage%253DS153%26rft.epage%253DS155%26rft.atitle%253DRole%2Bof%2BBlood%2BPressure%2BTargets%2Band%2BSpecific%2BAntihypertensive%2BAgents%2BUsed%2Bto%2BPrevent%2BDiabetic%2BNephropathy%2Band%2BDelay%2BIts%2BProgression%26rft_id%253Dinfo%253Adoi%252F10.1681%252FASN.2005121337%26rft_id%253Dinfo%253Apmid%252F16565242%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=jnephrol&resid=17/4_suppl_2/S153&atom=%2Febmed%2F11%2F5%2F144.atom [3]: /embed/inline-graphic-1.gif [4]: /embed/inline-graphic-2.gif [5]: /embed/inline-graphic-3.gif
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".