Pretransplantation Cognitive Dysfunction in Advanced-Age Hematologic Cancers: Predictors and Associated Outcomes
Bibliographic record
Abstract
Patients presenting for treatment of hematologic cancers may be at increased risk for cognitive dysfunction before allogeneic hematopoietic stem cell transplantation (HSCT) due to advanced age, previous chemotherapy treatment, deconditioning, and fatigue. Cognitive dysfunction may affect treatment decision making, ability to recall or follow post-HSCT treatment recommendations and overall survival (OS). A total of 448 patients admitted for HSCT between 2011 and 2014 were administered the Montreal Cognitive Assessment (MoCA) by occupational therapists during admission before transplantation, and 260 were reassessed following transplantation and before discharge. We examined select predictor variables, including age, Karnofsky Performance Status, sex, disease type, psychotropic medications, and select outcome variables, including OS, and nonrelapse mortality (NRM). Before transplantation, 36.4% of patients met criteria for cognitive dysfunction. Age was found to be a significant predictor, along with disease type (myelodysplastic syndrome [MDS], myeloproliferative disorder [MPD]). No significant association was found between cognitive dysfunction and OS or NRM. Longitudinal analysis from pretransplantation to post-transplantation indicated significant decline following HSCT. Notably, one-third of the study cohort showed cognitive dysfunction at hospital discharge. A significant proportion of HSCT candidates present with cognitive dysfunction, with older patients and those diagnosed with MDS and MPD at greatest risk in this cohort. Attention to cognitive dysfunction before transplantation may alert the treatment team to high-risk cases that require increased oversight, inclusion by caregivers, and referral to occupational therapy at discharge. Longitudinal follow-up studies are needed to clarify the specific effect of HSCT on cognitive dysfunction and the impact of cognitive dysfunction on transplantation outcomes.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".