Patient and observer scar assessment scores favour the late appearance of a transverse cervical incision over a vertical incision in patients undergoing carotid endarterectomy for stroke risk reduction
Bibliographic record
Abstract
BACKGROUND: Carotid endarterectomy (CEA) is a very common operation, but there is no agreement on the appropriate orientation of the surgical incision. METHODS: We retrospectively reviewed the charts of patients who had undergone CEA between Jul. 1, 2010, and Dec. 31, 2013. We contacted patients identified in the review to solicit participation in a clinical follow-up examination, during which the esthetic outcome of the scar was evaluated using the Patient and Observer Scar Assessment Scale (POSAS). RESULTS: During the study period 237 CEAs were performed. Nine patients refused the use of their personal health information in this study. There were no significant differences in the neurologic outcomes of patients based on the incision orientation (perioperative stroke and death 1.4% with transverse incision v. 0% with a vertical incision, p = 0.44). Fifty-two patients presented for follow-up examination. Thirty-three had a transverse incision and 19 had a vertical incision. Results of the POSAS significantly favoured the transverse incision (p = 0.03). Vertical incisions were more often associated with persistent, mild marginal mandibular nerve dysfunction (p = 0.04). CONCLUSION: Carotid endarterectomy performed through a transverse skin incision compared with a vertically oriented skin incision is associated with improved esthetic outcome, as measured by the POSAS, without an observed statistically significant difference in the risk of perioperative stroke or death between the 2 techniques.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".