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Record W2883518120 · doi:10.1016/j.jfma.2018.06.002

2018 Guidelines of the Taiwan Society of Cardiology, Taiwan Society of Emergency Medicine and Taiwan Society of Cardiovascular Interventions for the management of non ST-segment elevation acute coronary syndrome

2018· article· en· W2883518120 on OpenAlexaboutno aff
Yi‐Heng Li, Yu-Chen Wang, Yi‐Chih Wang, Ju‐Chi Liu, Cheng‐Han Lee, Chun‐Chi Chen, Ching‐Lin Hsieh, Feng Yu Kuo, Wei‐Chun Huang, Shih‐Hsien Sung, Chiung-Zuan Chiu, Jung-Cheng Hsu, Shu-Long Jen, Juey‐Jen Hwang, Jiunn‐Lee Lin

Bibliographic record

VenueJournal of the Formosan Medical Association · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAcute coronary syndromeGuidelineInternal medicinePercutaneous coronary interventionRevascularizationCardiologyCanadian Cardiovascular SocietyPsychological interventionIntensive care medicineMyocardial infarctionAnginaPathology

Abstract

fetched live from OpenAlex

In Taiwan, the incidence of non-ST segment elevation acute coronary syndrome (NSTE-ACS) continues to increase in recent years. The purpose of this guideline is to help health care professionals in Taiwan to use adequate tests and treatments for management of NSTE-ACS. For rapid diagnosis, in addition to history and physical examination, 0/3 h rapid diagnosis protocol with high sensitivity cardiac troponin assay is recommended in this guideline. Dual antiplatelet and anticoagulation therapies are important parts in the initial treatment. Risk stratification should be performed to identify high risk patients for early coronary angiography. Through evaluation of the coronary anatomy and other clinical factors, the decision for coronary revascularization, either by percutaneous coronary intervention or coronary artery bypass grafting, should be decided by the heart team. The duration of dual antiplatelet therapy should be given for at least 12 months after discharge. Other secondary preventive medications are also recommended for long term use.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.063
GPT teacher head0.372
Teacher spread0.310 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations56
Published2018
Admission routes1
Has abstractyes

Explore more

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