Neurocognitive Changes after Lung Transplantation
Bibliographic record
Abstract
RATIONALE: Neurocognitive impairments are associated with reduced quality of life and may adversely affect medical compliance, but their prevalence after lung transplantation has not been extensively studied. OBJECTIVES: To examine the frequency of neurocognitive impairment after lung transplantation and to examine perioperative factors affecting post-transplant neurocognitive function. MEASUREMENTS AND MAIN RESULTS: We performed serial assessments of neurocognitive function in a consecutive series of 47 subjects who received transplants between March 2013 and November 2013 (45% women; mean age, 53.5 ± 17.2 yr). Neurocognitive function was assessed using a composite measure including the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) total score and Trail Making Test parts A and B obtained before transplant, at hospital discharge, and 3 months after discharge. The presence of neurocognitive impairment was assessed using the Montreal Cognitive Assessment Battery (MoCA), and in-hospital delirium was assessed using the Confusion Assessment Method. Results demonstrated that neurocognitive performance initially worsened among non-cystic fibrosis patients and improved over follow-up (P = 0.002). Time effects were strongest on Trail Making Test part B (P < 0.001) and the RBANS (P = 0.054). Participants who exhibited delirium during their hospitalization showed poorer performance during follow-up assessments (P = 0.006). Examination of cognitive impairment rates demonstrated that 21 participants (45%) exhibited neurocognitive impairment (MoCA < 26) before lung transplant, whereas 27 (57%) participants exhibited impairment after transplantation, and 19 (57%) participants continued to neurocognitive impairment during a 3-month follow-up. CONCLUSIONS: Neurocognitive impairments are prevalent among lung transplant candidates and appear to worsen in some patients after transplant. Delirium during hospitalization is associated with worse neurocognitive function after transplant among patients without cystic fibrosis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".