Neurocognitive Dysfunction in Hematopoietic Cell Transplant Recipients: Expert Review from the Late Effects and Quality of Life Working Committee of the Center for International Blood and Marrow Transplant Research and Complications and Quality of Life Working Party of the European Society for Blood and Marrow Transplantation
Bibliographic record
Abstract
Hematopoietic cell transplantation (HCT) is a potentially curative treatment for children and adults with malignant and nonmalignant diseases. Despite increasing survival rates, long-term morbidity after HCT is substantial. Neurocognitive dysfunction is a serious cause of morbidity, yet little is known about neurocognitive dysfunction after HCT. To address this gap, collaborative efforts of the Center for International Blood and Marrow Transplant Research and the European Society for Blood and Marrow Transplantation undertook an expert review of neurocognitive dysfunction after HCT. In this review we define what constitutes neurocognitive dysfunction, characterize its risk factors and sequelae, describe tools and methods to assess neurocognitive function in HCT recipients, and discuss possible interventions for HCT patients with this condition. This review aims to help clinicians understand the scope of this health-related problem, highlight its impact on well-being of survivors, and help determine factors that may improve identification of patients at risk for declines in cognitive functioning after HCT. In particular, we review strategies for preventing and treating neurocognitive dysfunction in HCT patients. Finally, we highlight the need for well-designed studies to develop and test interventions aimed at preventing and improving neurocognitive dysfunction and its sequelae after HCT.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".