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Record W4360605216 · doi:10.1515/cclm-2023-0028

Antibody-mediated interferences affecting cardiac troponin assays: recommendations from the IFCC Committee on Clinical Applications of Cardiac Biomarkers

2023· article· en· W4360605216 on OpenAlexaff
Ola Hammarsten, Janet Warner, Leo Lam, Peter A. Kavsak, Bertil Lindahl, Kristin M. Aakre, Paul Collinson, Allan S. Jaffe, Amy K. Saenger, Richard Body, Nicholas L. Mills, Torbjørn Omland, Jordi Ordóñez‐Llanos, Fred S. Apple

Bibliographic record

VenueClinical Chemistry and Laboratory Medicine (CCLM) · 2023
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsMcMaster University
FundersAbbott DiagnosticsAbbott VascularSiemens HealthineersSahlgrenska UniversitetssjukhusetBritish Heart FoundationAstellas PharmaCancerfonden
KeywordsMedicineClinical PracticeAntibodyAcute coronary syndromeIntensive care medicineMedical laboratoryTroponinCardiologyInternal medicinePathologyImmunologyMyocardial infarction

Abstract

fetched live from OpenAlex

The International Federation of Clinical Chemistry Committee on Clinical Applications of Cardiac Biomarkers (IFCC C-CB) provides educational documents to facilitate the interpretation and use of cardiac biomarkers in clinical laboratories and practice. Our aim is to improve the understanding of certain key analytical and clinical aspects of cardiac biomarkers and how these may interplay. Measurements of cardiac troponin (cTn) have a prominent place in the clinical work-up of patients with suspected acute coronary syndrome. It is therefore important that clinical laboratories know how to recognize and assess analytical issues. Two emerging analytical issues resulting in falsely high cTn concentrations, often several fold higher than the upper reference limit (URL), are antibody-mediated assay interference due to long-lived cTn-antibody complexes, called macrotroponin, and crosslinking antibodies that are frequently referred to as heterophilic antibodies. We provide an overview of antibody-mediated cTn assay interference and provide recommendations on how to confirm the interference and interpret the results.

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)0.006
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.267
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.077
GPT teacher head0.437
Teacher spread0.360 · 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

Citations46
Published2023
Admission routes1
Has abstractyes

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