Monophasic demyelination reduces brain growth in children
Bibliographic record
Abstract
<h3>Objective:</h3> To investigate how monophasic acquired demyelinating syndromes (ADS) affect age-expected brain growth over time. <h3>Methods:</h3> We analyzed 83 pediatric patients imaged serially from initial demyelinating attack: 18 with acute disseminated encephalomyelitis (ADEM) and 65 with other monophasic ADS presentations (monoADS). We further subdivided the monoADS group by the presence (n = 33; monoADSlesion) or absence (n = 32; monoADSnolesion) of T2 lesions involving the brain at onset. We used normative data to compare brain volumes and calculate age- and sex-specific <i>z</i> scores, and used mixed-effect models to investigate their relationship with time from demyelinating illness. <h3>Results:</h3> Children with monophasic demyelination (ADEM, non-ADEM with brain lesions, and those without brain involvement) demonstrated reduced age-expected brain growth on serial images, driven by reduced age-expected white matter growth. Cortical gray matter volumes were not reduced at onset but demonstrated reduced age-expected growth afterwards in all groups. Brain volumes differed from age- and sex-expected values to the greatest extent in children with ADEM. All patient groups failed to recover age-expected brain growth trajectories. <h3>Conclusions:</h3> Brain volume, and more importantly age-expected brain growth, is negatively affected by acquired demyelination, even in the absence of chronicity, implicating factors other than active inflammation as operative in this process.
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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 | 0.002 |
| 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".