International Academy of Cardiology 18th World Congress on Heart Disease Annual Scientific Sessions 2013. Vancouver, B.C., Canada, July 26-29, 2013
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objectives \nWe assessed the feasibility of CartoSoundTM technology (Biosense \nWebster Inc, Diamond Bar, CA) to image the three-dimensional (3D) relationships of fibrotic binding sites between leads and the \ncardiovascular system during lead extraction. \nBackground \nFibrous adherences are the principal cause of permanent cardiac \npacing lead failed removal and complications, and are not directly \nvisualized by standard approach. \nMethods and Results \nSegments of real-time 2D ultrasound images were acquired using a 10-Fr 3D SoundStarTM catheter and integrated into the Carto mapping system to obtain 3D CartoSound anatomical maps of the superior vena cava, right atrium (RA), coronary sinus, right ventricle (RV), pacing leads, and fibrous tissue during lead removal. Lead extraction procedure was performed on 46 patients (38 men; mean age 73.7±10.5 years), and 90 leads (1.96 leads/patient) with a mean time from implant of 62.7±51.8 months. CartoSound was able to detect more binding sites in RA (17.4% vs. 4.3%, p=.04), and RV (43.5% vs. 21.7%, p=.04) compared to fluoroscopy. Mean fibrosis volume (mean 2.0±1.6 cm3) correlated positively with time from implant (r=.38, p<.05), and powered-sheaths use (r=.39, p<.05), and negatively with procedural success (r=-.37, p<.05). Mean CartoSound evaluation time was 4.9±2.3 min. When compared to standard approach, the CartoSound use was characterized by a significantly lower mean procedure time (99±35.5 min vs. 30.1±23.2 min, p=.001), and major complications (1.7% vs. 0%, p=.03). \nConclusions \nReal-time 3D fibrosis assessment using CartoSound anatomical mapping is feasible during lead extraction. Its role as a complementary surveillance tool to improve procedural outcomes requires extensive validation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it