Global Consensus on the Management of Limbal Stem Cell Deficiency
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: In recent decades, the medical and surgical treatment of limbal stem cell deficiency (LSCD) has evolved significantly through the incorporation of innovative pharmacological strategies, surgical techniques, bioengineering, and cell therapy. With such a wide variety of options, there is a need to establish a global consensus on the preferred approaches for the medical and surgical treatment of LSCD. METHODS: An international LSCD Working Group was established by the Cornea Society in 2012 and divided into subcommittees. Four face-to-face meetings, frequent email discussions, and teleconferences were conducted since then to reach agreement on a strategic plan and methods after a comprehensive literature search. A writing group drafted the current study. RESULTS: A consensus in the medical and surgical management of LSCD was reached by the Working Group. Optimization of the ocular surface by eyelid and conjunctival reconstruction, antiinflammatory therapy, dry eye and meibomian gland dysfunction treatment, minimization of ocular surface toxicity from medications, topical medications that promote epithelialization, and use of a scleral lens is considered essential before surgical treatment of LSCD. Depending on the laterality, cause, and stage of LSCD, surgical strategies including conjunctival epitheliectomy, amniotic membrane transplantation, transplantation of limbal stem cells using different techniques and sources (allogeneic vs. autologous vs. ex vivo-cultivated), transplantation of oral mucosal epithelium, and keratoprosthesis can be performed as treatment. A stepwise flowchart for use in treatment decision-making was established. CONCLUSIONS: This global consensus provides an up-to-date and comprehensive framework for the management of LSCD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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