Physical Growth and Current Health Status of Infants Who Were of Extremely Low Birth Weight and Controls at Adolescence
Bibliographic record
Abstract
OBJECTIVES: To compare the physical growth, current health status, and utilization of health care resources by extremely low birth weight (ELBW) and control (C) adolescents and to look at changes over time. METHODS: A longitudinal regional cohort study was conducted. Growth measures were converted to z scores on the National Center for Health Statistics growth curves. Information regarding current health status/health care utilization was obtained by parental interviews. RESULTS: A total of 154 (91%) of 169 ELBW survivors between 12 and 16 years and 125 (86%) of 145 controls participated. Neurosensory impairments were present in 28% of ELBW survivors and 2% of control participants. Mean z scores for both height and weight were below 0 for ELBW survivors (weight: -0.35; height: -0.55) compared with control participants (weight: 0.40; height: 0.28). However, among ELBW survivors, significant catch-up growth occurred in both parameters between age 8 and adolescence but remained stable among control participants. ELBW survivors had a higher prevalence of visual problems (57% vs 21%), seizures (7% vs 1%), developmental delay (26% vs 1%), learning disabilities (34% vs 10%), and hyperactivity (9% vs 2%) and used more specialists and community resources than did control participants. CONCLUSIONS: Although physical growth continues to be compromised and substantial morbidity remains among ELBW survivors at adolescence, there seems to be some catch-up growth, a reduction in the prevalence of acute health problems, and a decrease in the utilization of medical resources.
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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 | 0.000 |
| 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) | 0.001 | 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".