Appropriateness of Questionnaires for the Diagnosis and Monitoring Treatment of Dry Eye Disease
Bibliographic record
Abstract
Objectives: If questionnaires contributing to the diagnosis of dry eye disease are to be recommended as alternatives to existing questionnaires, they must be comparable, with similar repeatability and treatment sensitivity. Comparability was thus examined for three common dry eye questionnaires along with identifying the individual questions that most strongly predicted overall scores. Methods: Anonymised data (n = 329) collected via the Ocular Surface Disease Index (OSDI), 5-item Dry Eye Questionnaire (DEQ-5) and Symptom Assessment in Dry Eye (SANDE) questionnaires (including responses to individual questions) from consenting patients were drawn from real-world dry eye clinics/registries in the United Kingdom, Australia and New Zealand; at follow-up, normalised changes were evaluated in 54 of these patients. Treatment data were also analysed from a 6-month, randomised controlled trial assessing artificial tear supplement treatments with 43 responders and 13 non-responders to treatment identified. The questions extracted from the OSDI which form the abbreviated 6-item OSDI were also analysed. Results: The agreement between the questionnaires ranged from r = 0.577 to 0.754 (all p < 0.001). For the OSDI, three questions accounted for 89.1% of the variability in the total score. The correlation between the OSDI and OSDI-6 was r = 0.939, p < 0.001. For the DEQ-5, two questions accounted for 88.5% of the variance in the total score. Normalised treatment changes were also only moderately correlated between the questionnaires (r = 0.441 to 0.595, p < 0.01). For non-responders, variability was 7.4% with both OSDI and OSDI-6, 9.7% with DEQ-5, 12.1% with SANDE-frequency and 11.9% with SANDE-severity scale. For responders, improvement with drops was detected with a 19.1% change in OSDI, 20.2% in OSDI-6, 20.9% in DEQ-5, and 27.5%/23.6% in SANDE-frequency/severity scales. Conclusions: Existing commonly used dry eye questionnaire scores do not show high levels of correlation. The OSDI was the least variable of the questionnaires and while displaying a slightly lower treatment effect than either the DEQ or SANDE, it was more sensitive to detection of a treatment effect. The quicker-to-complete OSDI-6 exhibited essentially the same outcome as the OSDI, with similar variability and treatment sensitivity.
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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 | 0.212 | 0.335 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".