Impact of religious fasting on ocular dryness: objective and subjective assessment
Bibliographic record
Abstract
Background Certain religions require long hours of fasting, abstaining from fluid intake for durations extending up to 16 h. Lack of fluid intake may alter multiple physiological parameters, which can influence the ocular system. In this prospective study, we evaluated the effect of prolonged fasting on dry eye disease using both objective and subjective measures. Methods We included patients who fasted for at least 12 h a day for at least 2 weeks, including the testing day, and retested them at least 1 week after the fasting period had ended with no fasting on the testing day. At each visit, Non-Invasive Keratograph Break up time (NIKBUT) and Tear meniscus height (TM) were measured using the Oculus Keratograph 5 M. Ocular Surface Disease Index (OSDI) was evaluated at each timepoint to assess dryness symptoms subjectively. Results This study included a total of 40 patients. NIKBUT values during the fasting times were higher than during the non-fasting times; however, the difference was statistically non-significant. There were no significant differences in TM and OSDI measurements between non-fasting and fasting periods (p > 0.05). Lubricating eyedrop use was significantly lower in fasting patients. Conclusion Our study showed that prolonged fasting, including complete abstinence from fluid intake, did not lead to significant dryness, neither subjectively nor objectively. During fasting, patients used significantly fewer lubricating drops compared to non-fasting periods.
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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 | 0.002 |
| 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) | 0.001 | 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".