Characteristics and outcomes of patients (pts) who developed immune-related adverse events (irAEs) with an initial presentation in the emergency department (ED).
Bibliographic record
Abstract
201 Background: Management of irAEs due to immune checkpoint inhibitors (ICIs) requires a high degree of suspicion, and management of severe irAEs require timely initiation of corticosteroids (CS). This can be challenging in the ED, where providers may not be aware of an individual pt’s cancer treatment or its toxicities. Methods: We performed a retrospective single-center chart review for pts treated with ICIs in 2018 and 2019 who subsequently presented to ED. New irAEs with first presentation in ED were analyzed and pt outcomes were recorded. Descriptive statistics compared this population to irAEs identified in outpatient setting, as well as rates of ED utilization in pts on doublet ICI (dICI). Results: Of 351 evaluable pts treated with an ICI, 129 (37%) had at least one presentation to ED. Seventeen pts had a first presentation of a new irAE. These pts had received a median 2 cycles of ICI prior to presentation (interquartile range [IQR] 1-3) Twelve of these pts presented with generalized fatigue or pain, twelve required admission, 4 were admitted to intensive care within 30 days, and two died. Toxicities included hypophysitis (5), arthritis (2), colitis (2), myocarditis (2), neuritis (2), pneumonitis (2), adrenalitis (1), hepatitis (1). Median admission was 8.5 days (IQR 2-32), and median time to corticosteroids was 30.5 hours (range 4-269). Grade 3 or higher toxicity was more frequent in the ED pts compared to the total ICI pt population (70.5% vs. 32.2%). Pts on dICI (n = 41) had a higher rate of ED utilization (n = 23, 56.1%) and ED visits were more likely to be for first presentation of a new irAE (n = 7, 30.4% of dICI ED visits) compared to single-agent ICI regimens. Conclusions: Pts with irAEs that first present at the ED often have generalized symptoms, prolonged hospitalizations, and can have long delays to initiation of CS. Development of a protocolized approach for pts on ICI at the point of care in the ED may improve identification of irAEs, ‘door-to-steroid’ time, and patient outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".