Atrial thrombi detection prior to pulmonary vein isolation: Diagnostic accuracy of cardiac computed tomography versus transesophageal echocardiography
Bibliographic record
Abstract
BACKGROUND: Patients routinely undergo transesophageal echocardiography (TEE) prior to pulmonary vein isolation (PVI) in order to rule out the presence of intra-atrial thrombi. Cardiac computed tomography (CCT) is also routinely conducted prior to the procedure to determine cardiac anatomy. Although it has been demonstrated that CCT can also rule out intra-atrial thrombi, the use of CCT for thrombi detection is controversial. The primary objective was to determine the utility of CCT for detection of atrial thrombi as compared to TEE. METHODS: Patients who underwent PVI between 2010 and 2011 with CTs and TEEs complet-ed within 3 days of each other were retrospectively identified. TEE reports were analyzed, while CCTs were interpreted by a cardiologist specializing in CCTs. Severe spontaneous echo contrast or thrombus detected on TEE were considered positive, as were filling defects found on CCT. RESULTS: A total of 51 patients undergoing PVI (mean age 59.4 ± 9.5 years; 75% male; ejection fraction 60 ± 12%) had both TEE and CCT in timely fashion. By TEE, 0 left atrial ap-pendage (LAA) thrombi were identified with mild to moderate spontaneous echo contrast in 4 patients. By CCT, 2 definite LAA thrombi were identified and thrombi in 4 patients could not be ruled out. Specificity, positive predictive value, and negative predictive value for CCT were 88%, 0%, and 100%, respectively. CONCLUSIONS: CCT is an effective tool in ruling out atrial thrombi prior to PVI. TEE should be completed only if CCT is positive.
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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 | 0.003 | 0.017 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".