Pellevé™ vs Lipiflow™ MGD-Related Dry Eye Treatment Study: The ThermaLid™ Procedure
Bibliographic record
Abstract
Objective: To assess the safety and efficacy of the Pellevé Wrinkle Treatment System as compared to LipiFlow, for treatment of dry eye syndrome due to meibomian gland dysfunction (MGD). Materials and Methods: In this split face, randomized study, ten patients who met specific criteria for inclusion were followed after treatment with the Pellevé Wrinkle Reduction System (what the authors have dubbed the "thermaLid Procedure") and a standard LipiFlow procedure performed the same day, with 1 and 3 months follow-up. Pre- and post- treatment MGD was assessed using a variety of subjective and objective measurements. Results: The function of the meibomian glands improved significantly from baseline to 3 months for both thermaLid and Lipiflow treated eyes, with no significant difference between them, as measured by MGE grading, wax plug scoring, Standard Patient Evaluation of Eye Dryness (SPEED) and Ocular Surface Disease Index (OSDI) scoring. A significant change in conjunctival staining was found after both treatments at the 1-month time point but not the 3-month time point. thermaLid but not Lipiflow treatment, significantly decreased MARX line measurements at 3-months. Lipiview, Non-Invasive Tear Breakup Time (NITBUT), corneal surface staining, Tear Osmolarity, and anesthetic Schirmer's testing did not show statistically significant improvement, nor differences between treatment modalities. Conclusions: thermaLid treatment of the eyelids appears to show efficacy similar to Lipiflow treatment in reducing symptoms, reducing wax plugging and improving the number of functioning MGs as well as reducing conjunctival staining in MGD related dry eye disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".