Evaluation of Prospective ECG-Triggered CT Scan as a Practical Alternative to Standard Retrospective ECG-Gated Scan for Pre-TAVI Patients
Bibliographic record
Abstract
Purpose: CT-TAVI is a critical component of pre-TAVI assessment. The conventional method, retrospective ECG-gated scan, covering a complete cardiac cycle, measures the annulus during optimal systolic phases. Recently, prospective ECG-triggered scans acquiring images at a specific interval of the cardiac cycle were evaluated, allowing faster acquisition and lower contrast doses. Moreover, these scans might be beneficial for elderly patients, reducing the need for breath-holding and easing cooperation requirements. Still, their impact on annular measurement and procedural success has yet to be fully evaluated. Methods: This retrospective, single-center study included 419 patients who underwent CT-TAVI scans, by either prospective or retrospective scanning methods. Baseline data and calculated surgical risk scores were collected, with propensity score matching performed, followed by univariate analysis, Cox regression, and multivariable regression analysis. Results: A total of 171 patient pairs were generated via propensity score matching, ensuring that both groups had similar distributions of age (81 ± 8 years), sex (55% males), and baseline comorbidities. The patients in the prospective ECG-triggered group were exposed to a smaller amount of contrast material (40.0 ± 12 mL vs. 70.0 ± 48 mL, p < 0.001) and radiation (4.4 ± 3.6 mSv vs. 8.0 ± 10.3 mSv, p < 0.001). The prospective ECG-triggered group had a smaller aortic annulus area and diameter (426.6 ± 121.0 mm2 vs. 469.1 ± 130.8 mm2, p = 0.006 and 23.3 ± 3.2 mm vs. 24.5 ± 3.6 mm, p = 0.004) but no excess paravalvular leak was observed. Multivariable analysis showed no significant differences in mortality and composite endpoints between the two groups after 23 months of follow-up. Conclusion: Prospective ECG-triggered, ultra-fast, low-dose, high-pitch scan protocol, used in selected patients offers comparable safety and clinical procedural outcomes along with time and contrast savings.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".