Complication Rates After Left- Versus Right-Sided Carotid Endarterectomy
Bibliographic record
Abstract
BACKGROUND: Studies suggest that the side of carotid endarterectomy (CE) may influence the rate of postoperative complications. We sought to clarify this by (1) analysis of individual-level data from 3 large studies and (2) systematic review and meta-analysis of additional published descriptions of outcomes by side. METHODS AND RESULTS: The Western Canada Carotid Endarterectomy (WCCE) study (n=3164) was analyzed for outcomes by side along with data from the North American Symptomatic Carotid Endarterectomy Trial (NASCET; n=1415), and the ASA [Acetylsalicylic Acid] in Carotid Endarterectomy Trial (ACE; n=2469). Pooled analysis of individual-level data from these three studies allowed calculation of rate ratios for stroke or death by side. Medline and EMBASE were searched to identify additional studies reporting CE outcomes by side, and an overall risk ratio for outcomes by side was determined with fixed-effects meta-analysis. The WCCE in-hospital stroke or death rates for left and right-sided CE were 3.72% and 3.07%, respectively (P=0.27). A pooled analysis of the NASCET and ACE trials also revealed higher stroke or death rates for left-sided CE (5.39% versus 2.96%; P<0.001). The corresponding risk-adjusted rate ratios for stroke or death for left- versus right-sided surgery were 1.22 (95% CI, 0.83 to 1.77) for WCCE and 1.82 (1.32 to 2.50) for the pooled NASCET and ACE trials. Systematic review of the literature identified 2 additional studies. Meta-analysis of all 5 available studies yielded a corresponding pooled rate ratio for stroke or death of 1.36 (1.18 to 1.56). CONCLUSIONS: Left-sided CE is consistently associated with higher postoperative adverse event rates. Research into potential mechanisms is required to explain and address this finding.
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 | 0.017 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.011 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".