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Record W4315928475 · doi:10.1515/cclm-2022-1270

Cardiac troponin measurement at the point of care: educational recommendations on analytical and clinical aspects by the IFCC Committee on Clinical Applications of Cardiac Bio-Markers (IFCC C-CB)

2023· article· en· W4315928475 on OpenAlexafffund
Paul Collinson, Kristin M. Aakre, Amy K. Saenger, Ole Hammarsten, Allan S. Jaffe, Peter A. Kavsak, Torbjørn Omland, Jordi Ordonez-Lianos, Brad S. Karon, Fred S. Apple

Bibliographic record

VenueClinical Chemistry and Laboratory Medicine (CCLM) · 2023
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsMcMaster University
FundersAbbott DiagnosticsSiemens HealthineersMcMaster UniversityAmgenAstellas PharmaHennepin Healthcare Research InstituteSphingotec GmbHAbbott Laboratories
KeywordsPoint-of-care testingMedicineMedical laboratoryPoint of careTroponinCardiologyIntensive care medicineMedical physicsInternal medicinePathologyMyocardial infarction

Abstract

fetched live from OpenAlex

The International Federation of Clinical Chemistry and Laboarator Medicine (IFCC) Committee on Clinical Applications of Cardiac Bio-Markers (C-CB) has provided evidence-based educational resources to aid and improve the understanding of important analytical and clinical aspects of cardiac biomarkers. The present IFCC C-CB educational report focuses on recommendations for appropriate use, analytical performance, and gaps in clinical studies related to the use of cardiac troponin (cTn) by point of care (POC) measurement, often referred to as a point of care testing (POCT). The use of high-sensitivity (hs)-cTn POC devices in accelerated diagnostic protocols used in emergency departments or outpatient clinics investigating acute coronary syndrome has the potential for improved efficacy, reduction of length of stay and reduced costs in the health care system. POCT workflow integration includes location of the instrument, assignment of collection and testing responsibility to (non-lab) staff, instrument maintenance, in-service and recurrent training, quality control, proficiency assessments, discrepant result trapping, and troubleshooting and inventory management.

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.070
GPT teacher head0.422
Teacher spread0.352 · 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.

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

Citations36
Published2023
Admission routes2
Has abstractyes

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