Cognitive and educational outcomes in early adulthood for infants weighing 1000 grams or less at birth
Bibliographic record
Abstract
AIM: To assess the intelligence quotient (IQ) and academic achievement in early adulthood of a cohort of extremely-low-birthweight (ELBW 1000 g) subjects. METHODS: All 82 ELBW survivors consecutively born in or referred to a single tertiary center in 1976-1981 were traced at a mean age of 18 y. Three disabled children had died. Fifty-nine subjects (75%) had their IQ tested and 69 (87%) responded to a questionnaire. They were compared to 44 term, normal birthweight (NBW) matched controls. Outcome measures were: IQ (Wechsler Adult Intelligence Scale) and educational outcome. The main outcome variables were compared between groups and analyzed for neonatal and demographic data and in the ELBW group for childhood data. RESULTS: There was a strong relationship (r2=0.55, p<0.0001) between childhood and adult IQ for the 41 ELBW subjects tested at both ages (6.1+/-1.3 and 18.4+/-1.9 y). Differences were significant between ELBW and NBW groups: in mean full-scale IQ (94+/-12 vs 108+/-14), verbal IQ (93+/-12 vs 106+/-14) and performance IQ (97+/-14 vs 109+/-16) (p<0.0001). Differences between ELBW and NBW groups in prevalence of IQ<85 (19 vs 2%, p=0.012), of schooling in a regular curriculum for age (36 vs 68%, p=0.0011), of requirement for special classes or schools (33 vs 9%, p=0.0032), and of obtainment of secondary school diploma for those 18 y or older (56 vs 85%, p=0.018) were largely due to fathers' socio-economic score. CONCLUSION: ELBW subjects had a mean adult IQ in the normal range; however, it was one standard deviation below that of NBW subjects and they had more school failures. Despite this, more than half of ELBW subjects aged 18 y or more had obtained their secondary school diploma.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".