Brain MRI and cognitive function seven years after surviving an episode of severe acute malnutrition in a cohort of Malawian children
Bibliographic record
Abstract
OBJECTIVE: To assess differences in cognition functions and gross brain structure in children seven years after an episode of severe acute malnutrition (SAM), compared with other Malawian children. DESIGN: Prospective longitudinal cohort assessing school grade achieved and results of five computer-based (CANTAB) tests, covering three cognitive domains. A subset underwent brain MRI scans which were reviewed using a standardized checklist of gross abnormalities and compared with a reference population of Malawian children. SETTING: Blantyre, Malawi.ParticipantsChildren discharged from SAM treatment in 2006 and 2007 (n 320; median age 9·3 years) were compared with controls: siblings closest in age to the SAM survivors and age/sex-matched community children. RESULTS: SAM survivors were significantly more likely to be in a lower grade at school than controls (adjusted OR = 0·4; 95 % CI 0·3, 0·6; P < 0·0001) and had consistently poorer scores in all CANTAB cognitive tests. Adjusting for HIV and socio-economic status diminished statistically significant differences. There were no significant differences in odds of brain abnormalities and sinusitis between SAM survivors (n 49) and reference children (OR = 1·11; 95 % CI 0·61, 2·03; P = 0·73). CONCLUSIONS: Despite apparent preservation in gross brain structure, persistent impaired school achievement is likely to be detrimental to individual attainment and economic well-being. Understanding the multifactorial causes of lower school achievement is therefore needed to design interventions for SAM survivors to thrive in adulthood. The cognitive and potential economic implications of SAM need further emphasis to better advocate for SAM prevention and early treatment.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".