Abstract 15634: Neurologic Impact of Carotid Stenosis in Cardiac Surgery, a Retrospective Study
Bibliographic record
Abstract
Context: The impact of carotid disease on the risk of stroke is not well established in patients undergoing surgery on cardiopulmonary bypass (CPB). The aim of this study is to evaluate the relationship between post-operative cerebrovascular events and the characteristics of concomitant carotid stenosis (CS) (degree, laterality and associated symptomatology) in patients undergoing cardiac surgery on CPB. Methodology: Single center retrospective cohort study with prospectively collected data including all patients undergoing cardiac surgery on CPB between January 2002 and February 2014. Data collected included patients’ pre-operative demographic characteristics, operative and post-operative variables, and were taken from a computerized database and patients’ charts. Univariate analysis and multivariate analysis with stepwise approach were performed. Results: Results were obtained for 19,918 patients who met the inclusion criteria. Of these, 474 (2.4%) had at least a unilateral CS ≥50%. By univariate analysis, patients with CS ≥50% had a higher risk of post-operative stroke and/or TIA than those with CS <50% (8.3% vs 2.4%, p<0.0001). In the group of patients with CS ≥50%, neither the laterality of the stenosis (p=0.75) nor the presence of CS-related symptoms (p=0.07) were significantly associated with post-operative stroke and/or TIA. By multivariate analysis, the presence of a ≥50% CS was identified as an independent risk factor for post-operative stroke and/or TIA [OR 2.84; CI95% (1.94-4.16)]. The relationship between the degree of CS (50-99%) and the neurological risk showed a trend toward significance: CS 80-99% vs CS 50-79% [OR 1.77; CI95% (0.81-3.85)], p=0.15. The risk of stroke and/or TIA was highest in the 80-99% CS group [OR 3.80; CI95% (2.14-6.73)]. Conclusion: The presence of a ≥ 50% CS is an independent risk factor for post-operative stroke and/or TIA. Regardless of the presence of preoperative CS-related symptoms, the clinically relevant risk of stroke and/or TIA was highest for CS of 80-99%. These results suggest that a decision to perform prophylactic carotid revascularization prior to cardiac surgery should not only be based on the presence of CS-related symptoms, but also on the severity of carotid stenosis.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".