Neurocognitive functioning in preschool-age children with type 1 diabetes mellitus
Bibliographic record
Abstract
Neurocognitive functioning may be compromised in children with type 1 diabetes mellitus (T1DM). The factor most consistently implicated in the long-term neurocognitive functioning of children with T1DM is age of onset. The pediatric literature suggests that glycemic extremes may have an effect on the neurocognitive functioning of children, but findings are mixed. The purpose of this study was to compare the neurocognitive functioning of young children with T1DM diagnosed before 6 yr of age and healthy children (i.e., without chronic illness). Additionally, in the children with T1DM, we examined the relationship between their neurocognitive functioning and glycemic control. Sixty-eight (36 with T1DM and 32 without chronic illness) preschool-age children (M age = 4.4 yr ) were recruited and administered a battery of instruments to measure cognitive, language, and fine motor skills. Children with T1DM performed similar to the healthy controls and both groups' skills fell in the average range. Among children with diabetes, poor glycemic control [higher hemoglobin A1c (HbA1c)] was related to lower general cognitive abilities (r = -0.44,p < 0.04), slower fine motor speed (r = -0.64,p < 0.02), and lower receptive language scores (r = -0.39,p < 0.04). Such findings indicate that young children with T1DM already demonstrate some negative neurocognitive effects in association with chronic hyperglycemia.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".