Changes in left ventricular function after spontaneous coronary artery dissection
Bibliographic record
Abstract
BACKGROUND: Spontaneous healing of spontaneous coronary artery dissection (SCAD) and left ventricular ejection fraction (LVEF) recovery is frequently observed clinically. However, LVEF on presentation and follow-up imaging has not been described. HYPOTHESIS: We hypothesize that LV dysfunction improves at follow-up after initial SCAD presentation. METHODS: We included patients with nonatherosclerotic SCAD prospectively followed at Vancouver General Hospital, who had baseline assessment of LVEF and wall-motion abnormality (WMA) during their index presentation. A subset of these patients had repeat assessment of their ventricular function at follow-up. We compared the baseline LVEF and WMA with follow-up assessments and correlated to long-term cardiovascular outcomes. RESULTS: We included 277 SCAD patients who had baseline ventricular assessment performed. The average age was 52.4 ± 9.4 years, and 90.3% were female. All presented with myocardial infarction (24.2% STEMI, 75.8% NSTEMI). At baseline, the mean LVEF was 55.6% ± 9.1% and 72/277 (26.0%) had LVEF <50%. The presence of WMA was observed in 237/277 (85.6%) cases. Of 164 patients with repeat assessments, the baseline LVEF was 54.6% ± 9.2%, with improvement to 60.7% ± 7.2% at follow-up (P < 0.001). Baseline LVEF of <50% was observed in 29.9%, but only 6.7% had LVEF <50% at follow-up (P < 0.001). Baseline WMA was observed in 87.2% but decreased to 44.5% at follow-up (P < 0.001). Multivariable analysis showed that presentation with STEMI (odds ratio [OR]: 2.71, P = 0.001), troponin I >50 µg/L (OR: 1.02, P = 0.005), and SCAD involvement of the LAD (OR: 2.5, P = 0.002) were independent predictors of baseline LVEF <50%. CONCLUSIONS: In our large, prospectively followed SCAD cohort, the majority of patients presented with WMA and had relatively normal LVEF. Over half had subsequent normalization of WMA and LVEF on follow-up assessment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".