Low pre-albumin but not thiamine predicts cognitive deficits in adolescents post-Fontan and healthy controls
Bibliographic record
Abstract
BACKGROUND: Low pre-albumin, body mass index, and thiamine levels have been associated with poor nutritional status and cognitive/memory deficits in adult heart failure patients. However, the relationship of these nutritional/dietary intake biomarkers to cognition has not been assessed in adolescents post-Fontan procedure and healthy controls. METHODS: This is a cross-sectional study. Adolescents (14-21 years of age) post-Fontan completion were recruited from paediatric cardiology clinics and controls from the community. The Montreal Cognitive Assessment was administered (normal ≥ 26), and blood draw (thiamine [normal 70-110 nmol/L] and pre-albumin levels [adolescent normal 23-45 mg/dL]) and the Thiamine Food Frequency Questionnaire were completed by all participants. RESULTS: Seventy subjects, 40 post-Fontan (mean age 16 ± 1.6, female 51%, Hispanic 44%, hypoplastic left heart syndrome 26%) and 30 controls (mean age 16.8 ± 1.9, female 52%, Hispanic 66%), were participated. Post-Fontan group had lower median total cognitive scores (23 versus 29, p < 0.001), pre-albumin levels (23 versus 27, p = 0.013), and body mass index (20 versus 24, p = 0.027) than controls. Post-Fontan group had higher thiamine levels than controls (127 versus 103, p = 0.033). Lower pre-albumin levels (< 23) and underweight body mass index were associated with abnormal total cognitive scores (p = 0.030). Low pre-albumin level (p = .038) was an independent predictor of worse cognition. CONCLUSION: Lower pre-albumin was an independent predictor for worse cognition in adolescents post-Fontan. Lower pre-albumin levels may reflect chronic liver changes or protein-losing enteropathy seen in Fontan physiology. These findings highlight the possibility for nutrition-induced cognitive changes.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".