Chief Complaint at Admission Relates to Troponin Level and Mortality in Patients With Non-ACS Troponin Elevation
Bibliographic record
Abstract
BACKGROUND: Elevated level of troponin T (TnT) in the absence of acute coronary syndrome (ACS) can be caused by a number of conditions but the relevance of the chief complaint at admission for TnT level and prognosis has not been reported previously. The aim was to study whether TnT level differs among chief complaints or underlying causes in patients with non-ACS TnT elevation and if these factors predict mortality. METHODS: Patients admitted with TnT elevation were categorized as ACS or non-ACS and followed for 1 year. Statistical comparisons between different chief complaints and underlying causes were performed. RESULTS: Patients with non-ACS TnT elevation (n = 71) were less likely to present with chest pain compared to ACS (n = 50) (37% vs. 74%, P < 0.001) whereas dyspnea (25%), syncope/arrhythmia (14%) or other chief complaints (24%) were more common. Patients with dyspnea and other chief complaints had higher peak values of TnT compared to chest pain (P < 0.05). The most common peak occurred within 3 hours after admission for chest pain, dyspnea and other chief complaints whereas for arrhythmia it occurred after 3 - 9 hours (P < 0.01). A peak value > 15 hours after admission was only observed among dyspnea and other chief complaints. Mortality was higher in patients presenting with dyspnea (50%) or other causes (35%) compared to chest pain (8%) or syncope/arrhythmia (10%) (P < 0.05). Renal failure was the only underlying cause that predicted mortality. CONCLUSION: Among patients with non-ACS TnT elevation, patients presenting with dyspnea had higher TnT and higher 1-year mortality, whereas patients with chest pain were at lower risk.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".