Predicting cardiovascular events in out-of-hospital patients presenting with atypical chest pain and complete left bundle branch block: role of CTA and echocardiographic Global Longitudinal Strain
Bibliographic record
Abstract
Background Out-of-hospital patients presenting with atypical chest pain and complete left bundle branch block (LBBB) have to be stratified for the presence of coronary artery disease and the risk of developing heart failure (HF). We investigated the prognostic role of coronary CT-angiography (CTA) and echocardiographic global longitudinal strain (GLS) in those patients in a mid-term follow-up. Methods Out-of-hospital patients with LBBB underwent echocardiography and a 64-slice CT angiography were evaluated retrospectively. Development of HF or a cardiovascular death were the events scheduled. Results Seventy-eight patients (32 female; mean age: 66.0 ± 10.4 years were enrolled. During a follow-up of 33 months (IQR: 17-77), one patient (1.5%) experienced a cardiovascular death, 14 patients (17.9%) required urgent outpatient visits due to acute decompensated HF (12 hospitalizations). Echocardiography showed a slightly reduced left ventricular ejection fraction (LVEF) (50.0% ± 9.8%) and GLS within the normal range (-16.2% ± 4.1%). CTA analysis showed coronary stenosis > 50% in 28 patients (35.9%). A high Agatston score (> 100) was observed in 29.5%. Notably, 25 patients (32.1%) were diagnosed with left main coronary artery disease and 15 patients (16.7%) underwent revascularization during the follow up. Significant associations were observed between events and LVEF (P = 0.001), diastolic dysfunction grade ≥ 2 (P = 0.02), GLS (P < 0.001), multiple coronary stenosis (P = 0.04) and Agatston score (P = 0.05). Multivariate analysis confirmed the relationships with LVEF (R2 = 0.89, P < 0.001), diastolic dysfunction (R2 = 3.30, P = 0.04), GLS (R2 = 1.43, P < 0.001), and Agatston score (R2 = 1.01, P = 0.05). Conclusions In patients with complete LBBB, CTA and GLS identified those at a high risk of development HF.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| 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".