46. Intraoperative Systolic Blood Pressure as a Significant Predictor of Postoperative Hematoma Following Facelift: Single Surgeon Experience of 118 Consecutive Facelifts
Bibliographic record
Abstract
PURPOSE: To evaluate the association of elevated or labile intraoperative systolic blood pressure on postoperative hematoma, using the senior author’s single surgeon experience of 118 consecutive facelifts. METHODS: A multivariate logistic regression was conducted using complete demographic, procedure-related, blood pressure-related, and outcomes-related data. One-way ANOVA and linear regression were used to assess for associations between a preoperative history of hypertension and elevated or labile intraoperative SBP. A Fisher’s Exact test was subsequently used to assess for specific intraoperative SBP measurement cut-offs significantly associated with postoperative hematoma. RESULTS: Multivariate logistic regression demonstrated no statistically significant patient- or procedure-related demographic predictors of postoperative hematoma. High preoperative SBP was not found to be a significant predictor of postoperative hematoma, although this approached statistical significance (p=0.05). In contrast, labile intraoperative SBP (maximum recorded intraopSBP - minimum recorded intraopSBP; p=0.026), as well as high immediate postoperative SBP (p=0.002), were both independent and statistically significant predictors of postoperative hematoma. Patients with a preoperative history of hypertension, and more specifically those with elevated SBP in the preoperative clinic, were more likely to demonstrate labile (p=0.007) or elevated (p=0.005) intraoperative SBP during surgery. Specifically, maximum recorded intraoperative SBP ≥155mmHg (p=0.045), as well as maximum intraoperative SBP fluctuations ≥80mmHg (p=0.036) were found to be significantly associated with hematoma. CONCLUSION: In contrast to hypertension that is aggressively treated and successfully controlled, hypertension that is difficult to control intraoperatively,may be a predictor of SBP that is difficult to control postoperatively, and thus a significant risk factor for postoperative hematoma following facelift.
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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 | 0.000 | 0.002 |
| 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".