Right Atrial Collision Time (RACT): a novel marker of propensity for typical atrial flutter
Bibliographic record
Abstract
Abstract Background The risk of typical atrial flutter (AFL) is increased by factors that increase right atrial (RA) size or cause scarring to reduce conduction velocity. These characteristics ensure the macro re-entrant wave front does not meet its refractory tail. The time taken to traverse the circuit would take account of both of these characteristics (being equal to distance divided by velocity), and may provide a superior marker of propensity to develop AFL. Purpose To investigate right atrial collision time (RACT) as a marker of typical AFL. Methods This single centre, prospective study recruited consecutive typical AFL ablation cases that were in sinus rhythm. Controls were consecutive cases other than atrial fibrillation and >50 years of age. Exclusion criteria for both groups were a prior ablation in the RA and class I and III antiarrhythmics. While pacing the coronary sinus ostium at 600 ms, a local activation time map was created to locate the latest collision point on the anterolateral wall, excluding the RA appendage (Figure 1). This RACT approximates half a revolution. Results The AFL group's (n=34) mean RACT was 132.5±15.06 vs 98.7±12.23ms in the controls (n=40) (p<0.01). No significant difference was observed for age (mean 65.6 vs 62.6 (p=0.18)), male (68.8% vs 60% (p=0.59)), body surface area (mean 2.1 vs 2.03 m2 (p=0.24)). The RACT also proved to be a superior marker than the echocardiographic measurement of right atrial area in an apical four chamber view (mean 17.8 vs 16.3 cm2 (p=0.21).A ROC curve indicated an AUC of 0.97 (95% CI: 0.93–1.0, p<0.01). A RACT cut-off of 120 ms had a specificity of 99% and a sensitivity of 75%. Conclusion RACT is a novel and promising marker of propensity for typical AFL. The ability to predict AFL would be of significant clinical value given the risk of stroke and frequent need for ablation. Funding Acknowledgement Type of funding source: None
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".