Complications of Browlift Techniques: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: There is ongoing debate over which surgical technique is the safest for brow elevation. OBJECTIVES: The authors outline complication rates for a variety of open and endoscopic browlift techniques based on the results of a literature review. METHODS: The following databases were searched to capture relevant studies: MEDLINE, EMBASE, CINAHL, LILACS, Web of Science, Cochrane Libraries, controlled-trials.com, and clinicaltrials.gov. Eighty-two studies met the inclusion criteria. Assuming between-study heterogeneity due to the limitations and biases inherent to case series, a random-effects model was used to calculate weighted proportions. Pooled weighted proportions with 95% confidence intervals were determined. RESULTS: All open and endoscopic procedures are associated with a variety of complications. Unacceptable scarring and paresthesia are the most common complications among all surgical browlifts. For anterior hairline incision with subcutaneous dissection, alopecia occurred in 8.5% of patients, paresthesia in 5.4%, unacceptable scarring in 2.1%, and skin necrosis in 1.8%. For coronal incision with subgaleal dissection, unacceptable scarring occurred in 3.6% of patients, hematoma in 0.5%, and infection in 0.2%. Endoscopic techniques with subperiosteal dissection had the highest complication rates: 6.2% for paresthesia, 3.6% for asymmetry, 3.0% for alopecia, and 2.7% for lagophthalmos. CONCLUSIONS: Although complication rates vary with respect to incision site and plane of dissection, endoscopic techniques are associated with a larger variety of complications than open approaches. The findings should be interpreted with caution due to the limitations inherent to a case series. A well-designed comparative study is needed to evaluate the "true" rate of complications among the various browlift 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 | 0.009 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".