64 Targeting Follow-Up Needs of Premature Survivors
Bibliographic record
Abstract
The objective was to analyze the neonatal morbidities and functional outcomes (using the preschool version of the Health Status Classification System (HSCS)) at 42 months age by 3 different neonatal follow-up recruitment criteria used in Canada (birth weight <801 grams, <1251 grams, <1501 grams) and control patients born in a 22 month period in 1996–97 in a population based sample in British Columbia. The HSCS captures domains typically addressed in neonatal follow-up programs. Results of a cross sectional survey were linked to Canadian Neonatal Network (CNN) data. Incidence of neonatal major morbidities (chronic lung disease, severe intraventricular hemorrhage, necrotising enterocolitis or retinopathy of prematurity) and functional outcomes measured by the HSCS were calculated for survivors in the 3 recruitment criteria above. The Cochran-Armitage Trend Test was used to assess linear trends for incremental groups (<801 g, 801–1250 g, 1250–1500 g and controls) and the effect of morbidities on the HSCS. All 329 subjects <1500 grams birth weight born were cared for in a NICU. The survey was completed by caregivers for 161 subjects. Nonrespondents did not differ significantly in neonatal morbidities or risk factors. 393 of 718 control subjects' caregivers completed the survey. The incidence of major morbidity was 75% <801 g, 40% <1251 g and 28.8% of <1501 g. One or more health problems on the HSCS (HSCS sum) was identified by 78.3% <801 g, 70.2% <1251 g, 68.3% <1501 g and 45% of controls. The greatest differences between groups (p<.001) were seen for vision, gross motor, fine motor, self care, learning, thinking and pain. Small differences were seen in speaking and general health and no differences in hearing, feelings and behaviour. There were statistically significant differences between incremental groups for major morbidities (p<0.0001) but not against HSCS sum (p=.16). Morbidity and HSCS were not significantly correlated for 2 of 3 recruitment groups. The incidence of major neonatal morbidities and most health issues as measured by the components of the HSCS decrease significantly with higher birth weight recruitment criteria but overall having at least one health issues was very common (68%) in <1501 g survivors. Together with evidence from the literature, these results can be used to design follow-up strategies to better target the needs of premature survivors.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".