Cardiac Troponin Testing in Patients with COVID-19: A Strategy for Testing and Reporting Results
Bibliographic record
Abstract
BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged late in 2019 causing COVID-19 (coronavirus disease-2019) may adversely affect the cardiovascular system. Publications from Asia, Europe, and North America have identified cardiac troponin as an important prognostic indicator for patients hospitalized with COVID-19. We recognized from publications within the first 6 months of the pandemic that there has been much uncertainty on the reporting, interpretation, and pathophysiology of an increased cardiac troponin concentration in this setting. CONTENT: The purpose of this mini-review is: a) to review the pathophysiology of SARS-CoV-2 and the cardiovascular system, b) to overview the strengths and weaknesses of selected studies evaluating cardiac troponin in patients with COVID-19, and c) to recommend testing strategies in the acute period, in the convalescence period and in long-term care for patients who have become ill with COVID-19. SUMMARY: This review provides important educational information and identifies gaps in understanding the role of cardiac troponin and COVID-19. Future, properly designed studies will hopefully provide the much-needed evidence on the path forward in testing cardiac troponin in patients with COVID-19.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.254 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".