Customary practices in the monitoring of dry eye disease in Sjogren's syndrome
Bibliographic record
Abstract
Diagnostic testing for dry eye disease (DED) in Sjogren's syndrome (SS) is well described. Little is published about monitoring this systemic autoimmune DED. We analyzed the SS related DED tests used in North American optometric practices and compared academic settings to private practice settings. A retrospective chart review of 123 SS charts from 6 optometric practices in North America was conducted. Testing done during the first examination following a SS diagnosis was recorded on Research Electronic Data Capture (REDCap) database. The complete data file was reviewed and testing type and methodology were compared. Symptoms of DED (98.4% of charts),meibomian gland dysfunction (76.4% of charts), corneal staining with fluorescein (75.6% of charts) and anterior blepharitis (73.2% of charts) were the most frequently recorded variables. Clinicians used different methodologies to measure and grade these variables. Private practitioners were more likely to use symptom questionnaires and grading scales and to describe anterior blepharitis. Academic settings were more likely to record TBUT and tear meniscus height. The monitoring of DED in SS is not uniform in optometric offices across North America. Creating accepted standards of testing will improve the ability of clinicians and researchers to communicate and understand the course of DED in SS. Las pruebas diagnósticas para la enfermedad del ojo seco en el síndrome de Sjogren (SS) están bien descritas. Se ha publicado poco acerca de la supervisión de este síndrome del ojo seco autoinmune sistémico. Analizamos el SS relacionado con las pruebas de ojo seco en las prácticas optométricas de Norte América, y comparamos los centros académicos con los centros de práctica privada. Se realizó una revisión retrospectiva de 123 historias clínicas de SS procedentes de 6 centros optométricos de Norte América. Las pruebas realizadas durante el primer examen, tras el diagnóstico de SS, se registraron en la base de datos Research Electronic Data Capture (REDCap). Se revisó el archivo de datos completo y se compararon el tipo de prueba y la metodología. Las variables más frecuentemente registradas fueron los síntomas de ojo seco (98,4% de las historias), disfunción de la glándula de Meibomio (76,4%), tinción corneal con fluoresceína (75,6%), y blefaritis anterior (73,2%). Los clínicos utilizaron diferentes metodologías para medir y clasificar dichas variables. Los facultativos privados tendieron a utilizar con mayor frecuencia los cuestionarios de síntomas y las escalas de clasificación, y a describir la blefaritis anterior. Los centros académicos tendieron a registrar con mayor frecuencia TBUT y la altura del menisco lagrimal. La supervisión del ojo seco en el SS no es uniforme en los centros optométricos de Norte América. La creación de estándares de pruebas aceptados mejoraría la capacidad de comunicar y comprender el curso del ojo seco en el SS por parte de clínicos e investigadores.
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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 | 0.012 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".