3283Long-term prognostic value of non-invasive fractional flow reserve derived from coronary CT angiography (FFRct)
Bibliographic record
Abstract
Background: The long-term prognostic value of CT-derived fractional flow reserve (FFRct) compared to CT coronary angiography (CTA) and the independent relationship of its numeric value with clinical outcomes is not known. Objectives: 1) To determine the long-term prognostic value of FFRct in predicting death, non-fatal myocardial infarction and revascularisation when compared with CTA alone, and 2) to describe the relationship of the numeric value of FFRct with clinical outcomes. Methods: This is a subanalysis of NXT (HeartFlowNXT: HeartFlow Analysis of Coronary Blood Flow Using Coronary CT Angiography), a prospective, multicentre study with suspected stable coronary artery disease (CAD) who underwent CTA, FFRct, invasive coronary angiography and FFR. Of the 310 patients with an accepted CTA by FFRct core laboratory, outcome data was available in 206 (age 64±9.5, 64% male). We compared the predictive value of an abnormal FFRct (defined as ≤0.8) with the presence of significant stenosis on CTA (>50% site read stenosis) for composite primary endpoint of death, nonfatal myocardial infarction and revascularization. In addition, we assessed its relationship with each 0.05-unit strata decrease in FFRct adjusted for clinical and CTA features.
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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 | 0.004 |
| 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 | 0.000 | 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".