Systolic Blood Pressure Less Than 120 mmHg is a Safe and Effective Method to Minimize Bleeding After Facelift Surgery: A Review of 502 Consecutive Cases
Bibliographic record
Abstract
BACKGROUND: Hematoma is the most common complication after facelift surgery. Hypertension is the major risk factor for hematoma following facelift. Measures taken to reduce systolic blood pressure perioperatively significantly reduce the risk of hematoma. There is evidence that treating systolic blood pressure of 140 mmHg or above reduces hematoma; there were no studies to date in which systolic blood pressures below 120 mmHg had been evaluated. OBJECTIVES: To assess the safety and efficacy of maintaining systolic blood pressures of 120 mmHg or less postoperatively to reduce hematoma after facelift. METHODS: A retrospective chart review of a single surgeon's series of facelift procedures from January 2004 to July 2018 was undertaken. Implementation of a more stringent perioperative blood pressure protocol (maintaining a systolic blood pressure of less than 120 mmHg postoperatively) was initiated in January of 2013, dividing patients into 2 groups. RESULTS: A total of 502 consecutive patients who underwent a facelift by F.N. were included in the study. A total of 319 patients underwent a facelift before 2013, and a total of 183 patients underwent a facelift in 2013 or later. Overall, a total of 13 hematomas occurred during the entire 15-year study period (2.59%), of which 12 occurred before the implementation of a strict blood pressure regimen (3.76%), and only 1 occurred after the new protocol (0.5%). There were no adverse events related to the lower blood pressure. CONCLUSIONS: Treating systolic blood pressure greater than 120 mmHg postoperatively is a safe and effective method for reducing the risk of hematoma after 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".