Sex Differences in Computed Tomography Coronary Stenosis Severity Versus Flow Impairment and Impact on Revascularization, Clinical Events and Health Care Costs: A FORECAST Substudy
Bibliographic record
Abstract
Background The impact of sex‐related differences in coronary atheroma and flow impairment severity on clinical events and costs remains unclear. Methods and Results This is a secondary analysis of patients with stable coronary artery disease who underwent both coronary computed tomography angiography and fractional flow reserve derived from computed tomography as part of the FORECAST (Fractional Flow Reserve Derived From Computed Tomography Coronary Angiography in the Assessment and Management of Stable Chest Pain) trial, investigating (1) the relationship between coronary stenosis severity on coronary computed tomography angiography and fractional flow reserve derived from computed tomography FFR CT by sex and (2) the association with revascularization, resource usage, and adverse clinical events. A total of 212 patients (64 female participants [32.1%]) and 1245 vessels were included. There was no significant sex difference in the frequencies of significant coronary artery disease (38.2% of women versus 51.3% of men; P =0.073), but female participants had significantly less coronary flow impairment, according to the presence of at least 1 fractional flow reserve derived from computed tomography≤0.8 (47.0% versus 71.5%; P =0.008). Female subjects underwent fewer revascularization procedures (23.5% versus 42.3%; P =0.014), less coronary artery bypass graft surgery (2.9% versus 13.1%; P =0.025) and were less likely to be on statin treatment (72.0% versus 84.7%; P =0.022) by 9‐month follow‐up. This resulted in lower overall health care costs for female participants compared with male counterparts (median total cost, £1276 versus £2051; P =0.014). In multivariable Cox analysis the presence of significant coronary artery disease (hazard ratio [ HR], 2.91; 95% CI , 1.30–6.51) and having a positive fractional flow reserve derived from computed tomography ( HR, 4.11; 95% CI, 1.15–14.69) were independent predictors of major adverse cardiovascular events at 9 months, whereas sex was not statistically significant ( p =0.13). Conclusions There are significant sex differences in the anatomico‐functional assessment of coronary artery disease leading to differences in clinical management, costs, and adverse events.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".