Review: Statin use increases risk for diabetes
Bibliographic record
Abstract
ACP Journal Club15 June 2010Review: Statin use increases risk for diabetesJohn-Michael Gamble, BScPharm, MSc, Sumit R. Majumdar, MD, MPHJohn-Michael Gamble, BScPharm, MScUniversity of Alberta, Edmonton, Alberta, Canada (J.G., S.R.M.)Search for more papers by this author, Sumit R. Majumdar, MD, MPHUniversity of Alberta, Edmonton, Alberta, Canada (J.G., S.R.M.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-152-12-201006150-02007 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Source CitationSattar N, Preiss D, Murray HM, et al. Statins and risk of incident diabetes: a collaborative meta-analysis of randomised statin trials. Lancet. 2010;375:735-42. https://pubmed.ncbi.nlm.nih.gov/20167359Clinical Impact RatingsGIM/FP/GP: Cardiology: Endocrinology: References1 Baigent C, Keech A, Kearney PM, et al. Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90, 056 participants in 14 randomised trials of statins. Lancet. 2005;366:1267-78. [PMID: 16214597] Google Scholar Author, Article, and Disclosure InformationAuthors: John-Michael Gamble, BScPharm, MSc; Sumit R. Majumdar, MD, MPHAffiliations: University of Alberta, Edmonton, Alberta, Canada (J.G., S.R.M.)This article was published at Annals.org on 1 June 2010. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics 15 June 2010Volume 152, Issue 12Page: JC6-7KeywordsDeath ratesDiabetes preventionEndocrinologyHypertensionMyocardial infarctionNumber needed to harmOdds ratioRisk managementStatinsType 2 diabetes ePublished: 15 June 2010 Issue Published: 15 June 2010 Copyright & PermissionsCopyright © 2010 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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".