Use of the Dry Eye Questionnaire to Measure Symptoms of Ocular Irritation in Patients With Aqueous Tear Deficient Dry Eye
Bibliographic record
Abstract
PURPOSE: To demonstrate the ability of the Dry Eye Questionnaire (DEQ) to characterize the frequency of ocular surface symptoms and their diurnal intensity in patients with Sjögren's syndrome (SS), keratoconjunctivitis sicca (KCS), and age-matched controls. METHODS: One hundred patients with tear-deficient dry eye from Toronto Western Hospital were mailed the DEQ and the McMonnies' questionnaire (MQ). Age- and gender-matched controls were selected from an historical data set. The DEQ measured the habitual frequency, intensity, and impact of common ocular surface symptoms and asked questions about computer use, medications, and allergies. RESULTS: Sixty-two dry eye subjects responded; 30 with SS and 32 with KCS. Compared with controls, SS subjects consistently reported the highest frequency and intensity of symptoms, followed by non-KCS subjects. The intensity of symptoms was significantly greater in the evening than in the morning among SS subjects for all symptoms except dryness and light sensitivity (p < 0.05). Sixty percent of SS subjects reported the need to stop daily activities and close their eyes due to dryness, burning, and light sensitivity. CONCLUSIONS: Symptoms of ocular irritation were frequent and intense among SS and KCS subjects. These symptoms often increased in intensity over the day, suggesting that open-eye conditions affect the progression of symptoms. Measurement of symptom frequency and diurnal intensity by the DEQ provides a sensitive tool that may be useful in clinical treatment trials for 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".