Is a Pattern of Increasing Biomarker Concentrations Important for Long-Term Risk Stratification in Acute Coronary Syndrome Patients Presenting Early after the Onset of Symptoms?
Bibliographic record
Abstract
BACKGROUND: Guidelines for treatment of acute coronary syndrome (ACS) recommend observing a rise or fall in cardiac troponin (cTn) concentrations for assessing acute injury. It is unknown whether a rising pattern presages a more adverse long-term prognosis than elevations that do not change. The present study assessed whether a rising pattern of cardiac biomarkers was more prognostic than simple elevations. METHODS: We measured N-terminal pro-brain natriuretic peptide (NT-proBNP) (Roche), cTnT (Roche) and cTnI (Beckman Coulter) in 212 ACS patients. These biomarkers were measured in coincident EDTA and heparin plasma samples available from at least 2 different time points, an early first specimen obtained a median of 2 hours after onset of symptoms, interquartile range (IQR) 2-4 hours, and a later second specimen obtained at 9 hours, IQR 9-9 hours. The cTn concentration in the second specimen was used to classify myocardial necrosis (cTnI >0.04 ug/L; cTnT >0.01 ug/L). Outcomes [death, myocardial infarction (MI), heart failure (HF)] were obtained >8 years after the initial presentation. For patients with myocardial necrosis and a cTn concentration ratio (second/first measured concentrations) > or =1.00, the concentration ratios and the absolute concentrations in the second specimen were used to assess prognosis after 4 years. RESULTS: In myocardial necrosis, the relative change (cTn2/cTn1) was greater for cTnI than for cTnT (P <0.01), whereas the relative change in NT-proBNP was the same regardless of which troponin was used to classify necrosis (P = 0.71). The concentration ratio for cTnI, cTnT, and NT-proBNP was not useful for risk stratification (i.e., death/MI/HF; P > or =0.15). CONCLUSIONS: A rise in cardiac troponin or NT-proBNP concentration in ACS patients presenting early after onset of pain is not helpful for long-term prognosis.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".