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Perioperative Myocardial Infarction in Patients Undergoing Noncardiac Surgery

2011· article· en· W2089799908 on OpenAlexaffabout
P.J. Devereaux, Gordon Guyatt, Salim Yusuf

Bibliographic record

VenueAnnals of Internal Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsHamilton General Hospital
Fundersnot available
KeywordsPerioperativeMedicineMyocardial infarctionBlockadeGeneral hospitalStroke (engine)General surgerySurgeryInternal medicine

Abstract

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Letters4 October 2011Perioperative Myocardial Infarction in Patients Undergoing Noncardiac SurgeryP.J. Devereaux, MD, PhD, Gordon Guyatt, MD, MSc, and Salim Yusuf, MBBS, DPhilP.J. Devereaux, MD, PhDFrom Hamilton General Hospital, Hamilton, Ontario L8L 2X2, Canada; McMaster University, Hamilton, Ontario L8N 3Z5, Canada; and Hamilton General Hospital, Hamilton, Ontario L8L 2X2, Canada.Search for more papers by this author, Gordon Guyatt, MD, MScFrom Hamilton General Hospital, Hamilton, Ontario L8L 2X2, Canada; McMaster University, Hamilton, Ontario L8N 3Z5, Canada; and Hamilton General Hospital, Hamilton, Ontario L8L 2X2, Canada.Search for more papers by this author, and Salim Yusuf, MBBS, DPhilFrom Hamilton General Hospital, Hamilton, Ontario L8L 2X2, Canada; McMaster University, Hamilton, Ontario L8N 3Z5, Canada; and Hamilton General Hospital, Hamilton, Ontario L8L 2X2, Canada.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-155-7-201110040-00015 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail IN RESPONSE:Dr. Potyk states that we did not comment on the effects of perioperative β-blockade. On the basis of all the β-blocker trials in patients undergoing noncardiac surgery, there is strong evidence that β-blockade prevents perioperative MI. Contrary to Dr. Potyk's statement, perioperative β-blockade probably increases the risk for death and almost certainly increases the risk for stroke (1, 2). Our interpretation of these data is that controlling the sympathetic system in the perioperative setting is beneficial, but we need to find a way to do it safely and practically.Dr. Potyk believes that it is not necessary to ...References1. Devereaux PJ, Yang H, Yusuf S, Guyatt G, Leslie K, Villar JC, et al; POISE Study Group. Effects of extended-release metoprolol succinate in patients undergoing non-cardiac surgery (POISE trial): a randomised controlled trial. Lancet. 2008;371:1839-47. [PMID: 18479744] CrossrefMedlineGoogle Scholar2. Bangalore S, Wetterslev J, Pranesh S, Sawhney S, Gluud C, Messerli FH. Perioperative beta blockers in patients having non-cardiac surgery: a meta-analysis. Lancet. 2008;372:1962-76. [PMID: 19012955] CrossrefMedlineGoogle Scholar3. Levy M, Heels-Ansdell D, Hiralal R, Bhandari M, Guyatt G, Yusuf S, et al. Prognostic value of troponin and creatine kinase muscle and brain isoenzyme measurement after noncardiac surgery: a systematic review and meta-analysis. Anesthesiology. 2011;114:796-806. [PMID: 21336095] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAuthors: P.J. Devereaux, MD, PhD; Gordon Guyatt, MD, MSc; Salim Yusuf, MBBS, DPhilAffiliations: From Hamilton General Hospital, Hamilton, Ontario L8L 2X2, Canada; McMaster University, Hamilton, Ontario L8N 3Z5, Canada; and Hamilton General Hospital, Hamilton, Ontario L8L 2X2, Canada.Note: Drs, Devereaux, Guyatt, and Yusuf are responding on behalf of the POISE investigators.Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M10-2129. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoCharacteristics and Short-Term Prognosis of Perioperative Myocardial Infarction in Patients Undergoing Noncardiac Surgery P.J. Devereaux , Denis Xavier , Janice Pogue , Gordon Guyatt , Alben Sigamani , Ignacio Garutti , Kate Leslie , Purnima Rao-Melacini , Sue Chrolavicius , Homer Yang , Colin MacDonald , Alvaro Avezum , Luc Lanthier , Weijiang Hu , and Salim Yusuf , on behalf of the POISE (PeriOperative ISchemic Evaluation) InvestigatorsPerioperative Myocardial Infarction in Patients Undergoing Noncardiac Surgery Darryl Potyk Metrics 4 October 2011Volume 155, Issue 7Page: 477-478KeywordsAdjusted odds ratioDeath ratesDecision makingDisclosureMortalityMyocardial infarctionStatinsStrokeSurgeryTroponin ePublished: 4 October 2011 Issue Published: 4 October 2011 Copyright & PermissionsCopyright © 2011 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...

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

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.058
GPT teacher head0.309
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2011
Admission routes2
Has abstractyes

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