Diagnosing and Managing Uveitis Associated with Immune Checkpoint Inhibitors: A Review
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
This review aims to provide an understanding of the diagnostic and therapeutic challenges of uveitis associated with immune checkpoint inhibitors (ICI). In the wake of these molecules being increasingly employed as a treatment against different cancers, cases of uveitis post-ICI therapy have also been increasingly reported in the literature, warranting an extensive exploration of the clinical presentations, risk factors, and pathophysiological mechanisms of ICI-induced uveitis. This review further provides an understanding of the association between ICIs and uveitis, and assesses the efficacy of current diagnostic tools, underscoring the need for advanced techniques to enable early detection and accurate assessment. Further, it investigates the therapeutic strategies for ICI-related uveitis, weighing the benefits and limitations of existing treatment regimens, and discussing current challenges and emerging therapies in the context of their potential efficacy and side effects. Through an overview of the short-term and long-term outcomes, this article suggests recommendations and emphasizes the importance of multidisciplinary collaboration between ophthalmologists and oncologists. Finally, the review highlights promising avenues for future research and development in the field, potentially informing transformative approaches in the ocular assessment of patients under immunotherapy and the management of uveitis following ICI therapy.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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