Review: In renal impairment, apixaban reduces, or does not increase, bleeding compared with other anticoagulants
Bibliographic record
Abstract
ACP Journal Club21 April 2015Review: In renal impairment, apixaban reduces, or does not increase, bleeding compared with other anticoagulantsChristine M. Ribic, MD, MSc, FRCPC, Catherine M. Clase, MB, BChir, MSc, FRCPCChristine M. Ribic, MD, MSc, FRCPCMcMaster University, Hamilton, Ontario, Canada (C.M.R., C.M.C.)Search for more papers by this author, Catherine M. Clase, MB, BChir, MSc, FRCPCMcMaster University, Hamilton, Ontario, Canada (C.M.R., C.M.C.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/ACPJC-2015-162-8-003 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Source CitationPathak R, Pandit A, Karmacharya P, et al. Meta-analysis on risk of bleeding with apixaban in patients with renal impairment. Am J Cardiol. 2015;115:323-7. https://pubmed.ncbi.nlm.nih.gov/25527282Clinical Impact RatingsGIM/FP/GP: Cardiology: Hematology: Nephrology: References1. Connolly SJ, Ezekowitz MD, Yusuf S, et al; RE-LY Steering Committee and Investigators. Dabigatran versus warfarin in patients with atrial fibrillation. N Engl J Med. 2009;361:1139-51. [PMID: 19717844] Google Scholar2. Hernandez I, Baik SH, Piñera A, Zhang Y. Risk of bleeding with dabigatran in atrial fibrillation. JAMA Intern Med. 2015;175:18-24. [PMID: 25365537] Google Scholar3. Jun M, James MT, Manns BJ, et al; Alberta Kidney Disease Network. The association between kidney function and major bleeding in older adults with atrial fibrillation starting warfarin treatment: population based observational study. BMJ. 2015;350:h246. [PMID: 25647223] Google Scholar4. Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney International Supplements. 2013;3:1−150. Google Scholar Author, Article, and Disclosure InformationAffiliations: McMaster University, Hamilton, Ontario, Canada (C.M.R., C.M.C.)This article was published at Annals.org on 7 April 2015. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics Cited ByClinical Application and Pharmacodynamic Monitoring of Apixaban in a Patient with End-Stage Renal Disease Requiring Chronic Hemodialysis 21 April 2015Volume 162, Issue 8Page: JC3KeywordsAcute renal failureAnticoagulantsCreatinineDrugsHemorrhageKidneysResearch designSafety ePublished: 21 April 2015 Issue Published: 21 April 2015 CopyrightCopyright © 2015 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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 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".