The Most Recent Oncologic Emergency: What Emergency Physicians Need to Know About the Potential Complications of Immune Checkpoint Inhibitors
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
Immune checkpoint inhibitors targeting cytotoxic T-lymphocyte associated protein 4 (CTLA-4) and programmable cell death protein 1 (PD-1)/PD-L1 have shown antitumor activity in cancers such as melanoma, non-small cell lung cancer, renal cell carcinoma, and urothelial cancer. Certain checkpoint inhibitors have been approved for use in Canada, and are becoming a mainstay in the treatment of melanoma and other malignancies. These drugs have a unique side effect profile and are known to cause immune-related adverse events (irAEs). These adverse events often appear to originate from an infectious etiology, when in fact they result from the enhanced immune response caused by immune checkpoint therapy. IrAEs are primarily treated with corticosteroids, which suppress the overactive immune response that is secondary to the treatment. IrAEs can occur in any organ system, but adverse events in the skin, gastrointestinal, endocrine, and pulmonary systems are among the most common. As an emergency physician, one must be familiar with these drugs and their adverse events in order to identify patients presenting with irAE and treat them accordingly. This paper provides a brief introduction to immune checkpoint inhibitors, discusses the most common irAEs relevant to emergency physicians, and gives suggestions on how to manage patients presenting to the emergency department (ED) suffering from irAEs.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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