Effects of blinking exercises on palpebral fissure height and tear film parameters
Bibliographic record
Abstract
PURPOSE: Blinking is an involuntary movement essential for ocular surface health and visual comfort. While blinking exercises in patients with dry eye have been shown to improve symptoms, increase non-invasive tear film breakup time (NIBUT), and decrease incomplete blink rate (IBR), no studies have quantified improvements in eyelid opening. This study evaluated the effects of blinking exercises on palpebral fissure height (PFH), subjective symptoms, and tear film-related parameters. METHODS: Participants were randomly assigned to a "blinking exercise group" that performed blinking exercises after instilling artificial tear drops five times daily for three days or control group that only used artificial tear drops. Standard Patient Evaluation of Eye Dryness (SPEED) and Visual Analog Scale (VAS) scores were recorded for dryness, eye strain, ocular discomfort, blurred vision, foreign body sensation, dullness, and difficulty in opening the eyelids. The pre- and post-study measurements included lipid layer thickness, PFH, blink interval, IBR, tear meniscus height, NIBUT, fluorescein staining, and fluorescein breakup time (FBUT). RESULTS: Among 100 participants (28 males, 72 females, mean age 38.4 ± 7.4 years), 52 were in the blinking exercise group and 48 were in the control group. The blinking exercise group showed significant improvements in SPEED (P < 0.001), VAS scores for eye strain and discomfort (P = 0.003, 0.007), enlarged PFH (P < 0.001), prolonged NIBUT and FBUT (P < 0.001), and reduced IBR (P < 0.001) compared to the controls. CONCLUSIONS: Blinking exercises improved PFH, incomplete blinking, tear film stability, and subjective symptoms in patients with dry eye.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".