B - 105 ICANS, CAR-T, and Cognition: a Case Study
Bibliographic record
Abstract
Abstract Objective Immune effector cell-associated neurotoxicity syndrome (ICANS), an autoimmune delirious condition, affects 37.5% to 77% of individuals during or after chimeric antigen receptor T-cell (CAR-T) treatment for hematologic cancers (Grant et al., 2022). Initial clinical response varies widely but may include apraxia, aphasia, disorientation, and hallucinations (Möhn et al., 2022). Recent research indicates complete symptom resolution in most patients a month post-ICANS onset (Sales et al., 2023). However, a self-report study suggested more than 1 in 3 report persisting cognitive sequelae 1–5 years post-ICANS onset (Rurak et al., 2020). This discrepancy may be due to subtle changes missed by the Montreal Cognitive Objective Assessment (Sales et al., 2023; Möhn et al., 2022). The current case report investigates neurobehavioral outcome post-ICANS via comprehensive neuropsychological assessment. Method Two weeks post-CAR-T therapy, a 53-year-old male exhibited abrupt onset facial palsy and cognitive slowing prompting hospitalization. His wife reported new-onset apathy, atypical behaviors exacerbation (e.g., licking plate), and cognitive lapses (e.g., short-term memory, slowing, repeating questions) with little insight. Neuroimaging revealed supratentorial white matter hyperintensities plus calvarium and R skull base enhancing lesion regression. Results Neuropsychological assessment 10-months post-ICANS revealed subtle executive inefficiencies with family reports of improved yet ongoing social disinhibition and apathy. Conclusions This is the first comprehensive neuropsychological assessment of a patient who developed ICANS post-CAR-T therapy. Neuropsychologists should be aware of delayed cognitive sequelae possibility of this advancing treatment option. Future studies will be useful for patient/family preparation.
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.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".