Does the temperature of an artificial tear affect its comfort?
Bibliographic record
Abstract
BACKGROUND: Refrigerated eye-drops have been advocated in cases of ocular allergies to provide a soothing effect upon instillation. This notion continues to be promoted by practitioners for artificial tears (AT) in the management of dry eye (DE) with little support in the literature. To further substantiate claims of a soothing effect of cold eye-drops, the aim of this study was to determine if refrigeration of an AT enhanced the subjective comfort upon instillation. METHODS: Participants with mild to moderate DE participated in an open label contralateral study of two weeks duration. Each participant instilled Systane Ultra (Alcon Laboratories) in the morning (between 6.00-10.00 hours) and in the evening (between 18.00-22.00 hours). Participants were asked to report the subjective comfort immediately after both of these instillations, on a scale from 1 (poor) to 10 (excellent). This was done for ambient (aAT) and refrigerated (rAT) drops. An in vitro study evaluated if there were any changes in eye-drop pH and osmolarity with refrigeration. RESULTS: Participants (n = 18, three male, 15 female, age 22-28 years, average 24.4 ± 1.6) reported mean comfort scores (± standard deviation) of 7.8 ± 0.9 and 7.6 ± 1.4, for the aAT and the rAT, respectively. Mean comfort scores (± standard deviation) for morning and evening, were 7.7 ± 1.2 and 7.8 ± 1.1, respectively. A non-parametric Friedman test of differences among repeated measures was conducted and rendered a chi-squared value of 3.74, which was not statistically significant (p = 0.29). The pH remained stable at 8.0 and the osmolality did not vary significantly with refrigeration. CONCLUSION: There is no advantage, with respect to patient perceived comfort, in refrigerating the Systane Ultra (Alcon Laboratories) AT for mild to moderate DE.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".