Oculopharyngeal Muscular Dystrophy Ptosis, Mueller’s Muscle Involvement, and a Review of Management Over 34 Years
Bibliographic record
Abstract
PURPOSE: To review the management of the ptosis associated with oculopharyngeal muscular dystrophy (OPMD) from one author's experience over 34 years, demonstrate Mueller's muscle involvement in this disease, and how this impacts the preferred choice of surgery. METHODS: Retrospective, nonrandomized comparative case series. Forty patients with OPMD who underwent primary bilateral ptosis surgery through an anterior eyelid incision and had their Mueller's muscle biopsied (one side) and sent for histopathologic analysis were selected for chart review. The main outcome measure was the presence or absence of dystrophic changes in the biopsied Mueller's muscle. RESULTS: In 29/40 biopsies (72.5%), there were dystrophic changes and fatty infiltration of Mueller's muscle identified histopathologically. CONCLUSIONS: Mueller's muscle is involved in the dystrophic process more often than expected contributing to ptosis in the OPMD syndrome. A combined Mueller's-aponeurotic advancement is more effective at elevating the eyelid than simply advancing the aponeurosis when Mueller's is fatty infiltrated at the time of external levator advancement surgery in our experience. Management strategies for ptosis surgery in OPMD are reviewed. The age of onset, levator muscle function, previous ptosis repair, how debilitated the patient is with their disease process systemically, as well as the presence of other eye problems (e.g., dry eye, prior glaucoma filtering procedures, history of corneal surgery, laser refractive procedure) are important clinical considerations in patients with OPMD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".