Global Consensus on Definition, Classification, Diagnosis, and Staging of Limbal Stem Cell Deficiency
Bibliographic record
Abstract
PURPOSE: Despite extensive knowledge gained over the last 3 decades regarding limbal stem cell deficiency (LSCD), the disease is not clearly defined, and there is lack of agreement on the diagnostic criteria, staging, and classification system among treating physicians and research scientists working on this field. There is therefore an unmet need to obtain global consensus on the definition, classification, diagnosis, and staging of LSCD. METHODS: A Limbal Stem Cell Working Group was first established by The Cornea Society in 2012. The Working Group was divided into subcommittees. Four face-to-face meetings, frequent email discussions, and teleconferences were conducted since then to obtain agreement on a strategic plan and methodology from all participants after a comprehensive literature search, and final agreement was reached on the definition, classification, diagnosis, and staging of LSCD. A writing group was formed to draft the current manuscript, which has been extensively revised to reflect the consensus of the Working Group. RESULTS: A consensus was reached on the definition, classification, diagnosis, and staging of LSCD. The clinical presentation and diagnostic criteria of LSCD were clarified, and a staging system of LSCD based on clinical presentation was established. CONCLUSIONS: This global consensus provides a comprehensive framework for the definition, classification, diagnosis, and staging of LSCD. The newly established criteria will aid in the correct diagnosis and formulation of an appropriate treatment for different stages of LSCD, which will facilitate a better understanding of the condition and help with clinical management, research, and clinical trials in this area.
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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 | 0.155 | 0.137 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.013 | 0.006 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.010 | 0.010 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".