Developmental Coordination Disorder in School-Aged Children Born Very Preterm and/or at Very Low Birth Weight: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: : To systematically review and synthesize the literature to document the association between infants born very preterm and/or very low birth weight (VLBW) and the presence of developmental coordination disorder (DCD) at school age. METHODS: : Seven databases were systematically searched. Studies were included if they examined very preterm (<32 weeks) and/or VLBW (<1500 g) infants to school age (age, 5-18 years), had a full-term and/or normal birth weight comparison group, and used a formal measure of motor impairment. Studies that included only infants who were small for gestational age or diagnosed with cerebral palsy were excluded. Two independent reviewers completed abstract and full-text screening, data extraction, and quality assessment of included studies. RESULTS: : Sixteen articles were included, with 7 studies incorporated into 2 meta-analyses using cutoff scores of either <5th or 5-15th percentile on the Movement Assessment Battery for Children. Both analyses showed a significant increase in the likelihood of DCD for children born very preterm and/or 1500 g or less, with odds ratios of 6.29 (95% confidence interval, 4.37-9.05, p < .00001) and 8.66 (95% confidence interval, 3.40-22.07, p < .00001) for <5th or 5-15th percentile scores, respectively. CONCLUSIONS: : Consistent across studies, DCD is more prevalent in the VLBW/very preterm population than full-term/normal birth weight control children and the general school-age population, with significantly greater odds of developing the disorder. Clinical practice should focus on early identification of and intervention for children with DCD, while research should focus on determining the mechanisms underlying DCD in the preterm population.
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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 | 0.008 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".