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Record W2396422857

Treating the right patient at the right time: access to care in non-ST segment elevation acute coronary syndromes.

2005· article· en· W2396422857 on OpenAlexaffabout
Blair J. O’Neill, James M. Brophy, Carroll S. Simpson, M M Sholdice, Marit Knutson, David B. Ross, H. Ross, Jonas Röttger, Kevin Glasgow

Bibliographic record

VenuePubMed · 2005
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineGynecologyHumanities
DOInot available

Abstract

fetched live from OpenAlex

In 2004, the Canadian Cardiovascular Society formed an Access to Care Working Group with a mandate to use the best science and information available to establish reasonable triage categories and safe wait times for common cardiovascular services and procedures through a series of commentaries. The present commentary discusses the rationale for access benchmarks for urgent cardiac catheterization and revascularization, including hospital transfer in the setting of non-ST elevation acute coronary syndromes. The literature on standards of care, wait times, wait list management and clinical trials was reviewed. A survey of all cardiac catheterization directors in Canada was performed to develop an inventory of current practices in identifying and triaging patients. The Working Group recommended the following medically acceptable wait times for access to diagnostic catheterization and revascularization in patients presenting with acute coronary syndromes: for diagnostic catheterization and percutaneous coronary intervention, the target should be 24 h to 48 h for high-risk, three to five days for intermediate-risk and five to seven days for low-risk patients; for coronary artery bypass graft surgery, the target should be three to five days for high-risk, two to three weeks for intermediate-risk and six weeks for low-risk patients. All stakeholders must affirm the appropriateness of these standards and work continuously to achieve them. However, some questions remain around what are the best clinical risk markers to delineate the triage categories and the utility of clinical risk scores to assist clinicians in triaging patients for invasive therapies.

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)0.013
metaresearch head score (Gemma)0.106
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.336
Threshold uncertainty score0.669

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.106
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0050.007
Scholarly communication0.0040.005
Open science0.0030.002
Research integrity0.0180.019
Insufficient payload (model declined to judge)0.0060.001

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 head0.017
GPT teacher head0.286
Teacher spread0.269 · 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

Citations11
Published2005
Admission routes2
Has abstractyes

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