Angiotensin-Converting Enzyme Inhibitors and Angiotensin-Receptor Blockers in Chronic Heart Failure
Bibliographic record
Abstract
Letters1 March 2005Angiotensin-Converting Enzyme Inhibitors and Angiotensin-Receptor Blockers in Chronic Heart FailureLoren D. Regier, BSP, BA and Brent Jensen, BSPLoren D. Regier, BSP, BAFrom Saskatoon City Hospital, Saskatoon, Saskatchewan S7K 0M7, Canada.Search for more papers by this author and Brent Jensen, BSPFrom Saskatoon City Hospital, Saskatoon, Saskatchewan S7K 0M7, Canada.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-142-5-200503010-00019 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail TO THE EDITOR:Lee and colleagues' meta-analysis on ARBs (1) appears to have missed 2 points that could be important for optimizing patient outcomes. First, in the post-MI setting, the target dosage for valsartan in the VALIANT trial was 160 mg twice daily (2), much higher than the dosage of 80 mg twice daily reported by Lee and colleagues in their Table. The captopril dosage was 50 mg 3 times daily. (Mean dosages at 1 year were 247 mg/d in the valsartan group and 117 mg/d in the captopril group, both clearly above the “target” dosages reported in the meta-analysis.) ...References1. Lee VC, Rhew DC, Dylan M, Badamgarav E, Braunstein GD, Weingarten SR. Meta-analysis: angiotensin-receptor blockers in chronic heart failure and high-risk acute myocardial infarction. Ann Intern Med. 2004;141:693-704. [PMID: 15520426] LinkGoogle Scholar2. Pfeffer MA, McMurray JJ, Velazquez EJ, Rouleau JL, Kober L, Maggioni AP, et al. Valsartan, captopril, or both in myocardial infarction complicated by heart failure, left ventricular dysfunction, or both. N Engl J Med. 2003;349:1893-906. [PMID: 14610160] CrossrefMedlineGoogle Scholar3. Dickstein K, Kjekshus J. Effects of losartan and captopril on mortality and morbidity in high-risk patients after acute myocardial infarction: the OPTIMAAL randomised trial. Optimal Trial in Myocardial Infarction with Angiotensin II Antagonist Losartan. Lancet. 2002;360:752-60. [PMID: 12241832] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAuthors: Loren D. Regier, BSP, BA; Brent Jensen, BSPAffiliations: From Saskatoon City Hospital, Saskatoon, Saskatchewan S7K 0M7, Canada. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoMeta-Analysis: Angiotensin-Receptor Blockers in Chronic Heart Failure and High-Risk Acute Myocardial Infarction Victor C. Lee , David C. Rhew , Michelle Dylan , Enkhe Badamgarav , Glenn D. Braunstein , and Scott R. Weingarten Angiotensin-Converting Enzyme Inhibitors and Angiotensin-Receptor Blockers in Chronic Heart Failure Victor C. Lee , David C. Rhew , and Glenn D. Braunstein Angiotensin-Converting Enzyme Inhibitors and Angiotensin-Receptor Blockers in Chronic Heart Failure Mark B. McClellan , Jerod M. Loeb , Carolyn M. Clancy , Gary S. Francis , Alice K. Jacobs , Kenneth W. Kizer , Margaret E. O'Kane , and Michael J. Wolk Angiotensin-Converting Enzyme Inhibitors and Angiotensin-Receptor Blockers in Chronic Heart Failure Michael J. Peeters and James P. Tsikouris Metrics 1 March 2005Volume 142, Issue 5Page: 388KeywordsACE inhibitorsAdverse eventsAngiotensin converting enzyme inhibitorHeart failure ePublished: 1 March 2005 Issue Published: 1 March 2005 Copyright & PermissionsCopyright © 2005 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.036 | 0.005 |
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".