Endothelial function predicts 5-year adverse outcome in patients hospitalized in an emergency department chest pain unit
Bibliographic record
Abstract
BACKGROUND: Although endothelial function is a marker for cardiovascular risk, endothelial dysfunction assessment is not routinely used in daily clinical practice. A growing challenge has emerged in identifying patients prone to cardiovascular events. We aim to investigate whether abnormal endothelial function may be associated with adverse 5-year outcomes in patients presenting to a chest pain unit (CPU). METHODS: Following endothelial function testing using EndoPAT 2000 in 300 consecutive patients without a history of coronary artery disease, patients underwent coronary computerized tomographic angiography (CCTA) or single-photon emission computed tomography according to availability. RESULTS: Mean 10-year Framingham risk score (FRS) was 6.6 ± 5.9%; mean 10-year atherosclerotic cardiovascular disease (ASCVD) risk was 7.1 ± 7.2%; median reactive hyperemia index (RHI) as a measure of an endothelial function 2.0 and mean was 2.0 ± 0.4. During a 5-year follow-up, the 30 patients who developed major adverse cardiovascular events (MACE), including all-cause mortality, nonfatal myocardial infarction, hospitalization for heart failure or angina pectoris, stroke, coronary artery bypass grafting, and percutaneous coronary interventions, had higher 10-year FRS (9.6 ± 7.8 vs. 6.3 ± 5.6%; P = 0.032), higher 10-year ASCVD risk (10.4 ± 9.2 vs. 6.7 ± 6.9%; P = 0.042), lower baseline RHI (1.6 ± 0.5 vs. 2.1 ± 0.4; P < 0.001) and a greater degree of coronary atherosclerotic lesions (53 vs. 3%, P < 0.001) on CCTA compared with patients without MACE. Multivariate analysis demonstrated that RHI below the median was an independent predictor of 5-year MACE (odds ratio 5.567, 95% confidence interval 1.955-15.853; P = 0.001). CONCLUSION: Our findings suggest that noninvasive endothelial function testing may contribute to clinical efficacy in triaging patients in the CPU and in predicting 5-year MACE. CLINICAL TRIALSGOV IDENTIFIER: NCT01618123.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".