Angiotensin-Converting Enzyme Inhibitors after Acute Myocardial Infarction
Bibliographic record
Abstract
Letters4 January 2005Angiotensin-Converting Enzyme Inhibitors after Acute Myocardial InfarctionLouise Pilote, MD, MPH, PhD and Michal Abrahamowicz, PhDLouise Pilote, MD, MPH, PhDFrom Montreal General Hospital, Montreal, Quebec H3G 1A4, Canada.Search for more papers by this author and Michal Abrahamowicz, PhDFrom Montreal General Hospital, Montreal, Quebec H3G 1A4, Canada.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-142-1-200501040-00020 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail IN RESPONSE:We thank Dr. Jorde for his letter, although we take issue with several points. We disagree that our study was “no more than hypothesis-generating” because of its design and limitations. Pharmacoepidemiologic studies allow the assessment of the effect of medications in real-life situations, in contrast to the highly selected samples of clinical trials. However, they are prone to biases because of confounding by indication. State-of-the-art statistical analyses can compensate for these limitations. Since it is unlikely that ACE inhibitors will ever be compared head-to-head in a clinical trial, our findings should alert physicians that all ACE inhibitors do ...References1. Hennessy S, Kimmel SE. Is improved survival a class effect of angiotensin-converting enzyme inhibitors? [Editorial]. Ann Intern Med. 2004;141:157-8. [PMID: 15262673] LinkGoogle Scholar2. Yusuf S, Sleight P, Pogue J, Bosch J, Davies R, Dagenais G. Effects of an angiotensin-converting-enzyme inhibitor, ramipril, on cardiovascular events in high-risk patients. The Heart Outcomes Prevention Evaluation Study Investigators. N Engl J Med. 2000;342:145-53. [PMID: 10639539] CrossrefMedlineGoogle Scholar3. Effect of ramipril on mortality and morbidity of survivors of acute myocardial infarction with clinical evidence of heart failure. The Acute Infarction Ramipril Efficacy (AIRE) Study Investigators. Lancet. 1993;342:821-8. [PMID: 8104270] MedlineGoogle Scholar4. 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 Scholar Author, Article, and Disclosure InformationAuthors: Louise Pilote, MD, MPH, PhD; Michal Abrahamowicz, PhDAffiliations: From Montreal General Hospital, Montreal, Quebec H3G 1A4, Canada. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoMortality Rates in Elderly Patients Who Take Different Angiotensin-Converting Enzyme Inhibitors after Acute Myocardial Infarction: A Class Effect? Louise Pilote , Michal Abrahamowicz , Eric Rodrigues , Mark J. Eisenberg , and Elham Rahme Is Improved Survival a Class Effect of Angiotensin-Converting Enzyme Inhibitors? Sean Hennessy and Stephen E. Kimmel Angiotensin-Converting Enzyme Inhibitors after Acute Myocardial Infarction Ulrich Jorde Angiotensin-Converting Enzyme Inhibitors after Acute Myocardial Infarction Heather L. Horton Metrics Cited byA population-based analysis of the class effect of β-blockers after myocardial infarction 4 January 2005Volume 142, Issue 1Page: 78-79KeywordsACE inhibitorsClinical trialsCongestive heart failureHeartInfarctionLongitudinal studiesMortalityMyocardial infarctionRisk managementStatins ePublished: 4 January 2005 Issue Published: 4 January 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 | 0.002 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.007 |
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".