Upper Eyelid Static Surgical Approaches for the Treatment of Facial Palsy-Induced Lagophthalmos: A Systematic Review
Bibliographic record
Abstract
Background: Incomplete eyelid closure and lagophthalmos due to facial nerve palsy are significant functional and aesthetic concerns often requiring surgical correction. The aim of this systematic review is to quantitatively assess the efficacy, safety, and patient satisfaction associated with gold or platinum weight implantation, autologous fat grafting (lipofilling), and müllerectomy. Methods: A systematic review was performed following PRISMA guidelines, searching PubMed, Embase, Cochrane Library, Web of Science, and Scopus up to March 2025. Studies included clinical data on surgical correction for incomplete eyelid closure in facial palsy, reporting functional, anatomical, and satisfaction outcomes. Quality was assessed using the Newcastle–Ottawa Scale (NOS) and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system. Results: Twenty-six studies including a total of 1205 patients were included. Gold/platinum weight implantation achieved complete or near-complete eyelid closure in 83–92% of cases, with a reduction in lagophthalmos to <1 mm. Complication rates ranged from 5–15% (mainly extrusion/migration), and patient satisfaction averaged 7.9/10. Lipofilling showed persistent benefit in 77% of cases, with 9–20% requiring repeat procedures and 10–12% experiencing minor complications. Müllerectomy yielded symptomatic improvement or resolution in 92% of cases, with a mean lagophthalmos reduction of 1.18 mm. Conclusions: Gold or platinum weight implantation provides the most reliable improvement for severe upper eyelid dysfunction in facial palsy. Lipofilling is a viable autologous alternative, while müllerectomy is effective in selected cases. Further prospective comparative trials are needed to refine surgical selection and optimize outcomes.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".