The Agreement Between Self-Assessment and Clinician Assessment of Dry Eye Severity
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: The purpose of this analysis was to measure the degree of agreement between clinicians' assessment and subjects' self-assessment of dry eye severity in a cross-sectional, observational dry eye study. A secondary purpose was to identify the role of gender and age in that concordance. METHODS: In a cross-sectional observational study, 162 dry eye subjects and 48 controls were recruited from clinical databases of ICD-9 codes in 6 clinical sites. Before examination, subjects gave a global self-assessment of the severity of their dry eye from "none" to "extremely severe." After a clinical examination that included dry eye tests, the clinician discussed the subjects' symptoms and then gave global clinician assessment of dry eye from "none" to "severe." We measured the degree of agreement in these global measures. RESULTS: Although the correlation and agreement between clinician and self-assessment was significant (r = 0.720, P = 0.000; weighted K = 0.471; 95% CI = 0.395, 0.548; P = 0.000), the clinician assessment underestimated the severity in 40.9% of the subjects by at least 1 grade compared with the subjects' self-assessment. Over 54% of subjects over age 65 and 43% of the female subjects had their condition underestimated by the clinician (P < 0.05). CONCLUSIONS: Clinicians often relatively underestimated the severity of the subjects' self-assessment of dry eye in this clinical study, especially among the elderly and women. Eye care practitioners need better, more quantitative tools for the assessment of ocular surface symptoms to improve the concordance in severity assessment and to meet the needs of this symptomatic patient population by offering them appropriate treatments.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 it