Relevance of Motion Artifacts in Planning Computed Tomography on Outcomes After Transcatheter Aortic Valve Implantation
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
BackgroundMotion artifacts in planning computed tomography (CT) for transcatheter aortic valve implantation (TAVI) can potentially skew measurements required for procedural planning. Whether such artifacts may affect safety or efficacy has not been studied.MethodsWe conducted a retrospective analysis of 852 consecutive patients (mean age, 82 years; 47% women) undergoing TAVI-planning CT at a tertiary care center. Two independent observers divided CTs according to the presence of motion artifacts at the annulus level (Motion vs. Normal group). Endpoints included surrogate markers for inappropriate valve selection: annular rupture, valve embolization or misplacement, need for a new permanent pacemaker, paravalvular leak (PVL), postprocedural transvalvular gradient, all-cause death.ResultsForty-six (5.4%) patients presented motion artifacts on TAVI-planning CT (Motion group). These patients had more preexisting heart failure, moderate-severe mitral regurgitation, and atrial fibrillation. Interobserver variability of annular measurement (Normal vs. Motion group) did not differ for mean annular diameter but was significantly different for perimeter and area. Presence of motion artifacts on planning CT did not affect the prevalence of PVL (≥moderate PVL 0% vs. 2.5% p = 0.5), mean transvalvular gradient (6±3 mmHg vs 7±5 mmHg, p = 0.1), or the need for additional valve implantation (0% vs. 2.8%, p = 0.6). One annular rupture occurred (Normal group). Pacemaker implantation, procedural duration, hospital stay, 30-day outcomes, and all-cause mortality did not differ between the groups.ConclusionsMotion artifacts on planning CT were found in about 5% of patients. Measurements for valve selection were possible without the need for repeat CT, with mean diameter-derived annulus measurement being the most accurate. Motion artifacts were not associated with worse outcomes.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.000 | 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