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] 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] 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] 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
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
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 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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, 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".