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Record W3109565717 · doi:10.1093/ehjci/ehaa946.2686

Anticoagulation for mechanical aortic valve replacement: an international survey

2020· article· en· W3109565717 on OpenAlexaffabout
Saurabh Gupta, Emilie P. Belley‐Côté, Charlotte McEwen, Wenteng Hou, John W. Eikelboom, Richard Whitlock

Bibliographic record

VenueEuropean Heart Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsPopulation Health Research InstituteMcMaster University
Fundersnot available
KeywordsMedicineGuidelineAortic valveRandomized controlled trialAortic valve replacementMechanical valveSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Introduction Mechanical valves are preferred over biologic valves in younger patients because they are more durable but require long-term anticoagulation which increases the risk of bleeding. For patients with a mechanical aortic valve, the ACCP guidelines recommend a target INR of 2.5 (range 2.0–3.0) for all patients, whereas the ACC/AHA and ESC guidelines recommend a higher target for selected patients with additional risk factors for thromboembolism (TE). Data supporting the guideline recommendations are largely historical and of low quality. Purpose We surveyed physicians who manage anticoagulation for patient with mechanical heart valves to determine their usual practice, perceptions regarding guideline recommendations, and interest in participating in a randomized controlled trial (RCT) comparing lower with higher INR targets in patients with a mechanical aortic valve. Methods A 33-question web-based survey was sent to 75 cardiologists, cardiac surgeons and thrombosis specialists at centres in Canada and internationally (western Europe, South America, and the United States) who participated in previous anticoagulation trials led by investigators at McMaster University. Results Of the 55 respondents (73.3% response rate), 77.8% worked in academic teaching hospitals. Respondents had been in practice for a mean of 23.6 years; 40.9% followed AHA/ACC guidelines, 34.1% followed the ACCP guidelines and 22.7% followed the ESC guidelines. In patients with a mechanical aortic valve and no additional TE risk factors, 80% of respondents targeted an INR of 2.5 (range 2.0–3.0); among patients with additional TE risk factors, 48% targeted an INR of 2.5 (range 2.0–3.0) and 44% targeted an INR of 3.0 (range 2.5–3.5). With respect to guidelines: 57.1% of respondents agreed or strongly agreed that that the evidence for the guidelines was contemporary, 53.1% agreed or strongly agreed that the evidence was derived from patients with modern bi-leaflet mechanical valves, and 57.2% of respondents agreed or strongly agreed that the evidence was not of high quality. A majority of respondents (65.9%) reported that they would accept an increase in TE risk to reduce the risk of a major bleeding event; 86.4% are willing to randomize patients with a mechanical aortic valve to a target INR of 2.0 (range 1.5–2.5) if they had no risk factors for TE and 36.4% would randomize patients to a target INR of 2.0 with additional risk factors for TE. Conclusions Clinicians who participated in the survey followed different guidelines and employed different INR targets for patients with a mechanical aortic valve. A majority of respondents would be willing to randomize these patients to lower INR targets. Mechanical Aortic Valves and INR Targets Funding Acknowledgement Type of funding source: None

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)0.002
metaresearch head score (Gemma)0.005
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.242
GPT teacher head0.408
Teacher spread0.166 · 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
Published2020
Admission routes2
Has abstractyes

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