Neonatal follow-up programs in Canada: A national survey
Bibliographic record
Abstract
BACKGROUND: A 2006 Canadian survey showed a large variability in neonatal follow-up practices. In 2010, all 26 tertiary level Neonatal Follow-Up clinics joined the Canadian Neonatal Follow-Up Network (CNFUN) and agreed to implement a standardized assessment (including the Bayley Scales of Infant and Toddler Development-III (Bayley-III) at 18 months corrected age for children born < 29 weeks' gestation. It is unknown whether the variability in follow-up practices lessened as a result. OBJECTIVES: To describe the current status of neonatal follow-up services in Canada and changes over time. METHODS: A comprehensive online survey was sent to all tertiary level CNFUN Follow-up programs. Questions were based on previous survey results, current literature, and investigator expertise and consensus. RESULTS: Respondents included 23 of 26 (88%) CNFUN programs. All sites provide neurodevelopmental screening and referrals in a multidisciplinary setting with variations in staffing. CNFUN programs vary with most offering five to seven visits. Since 2006, assessments at 18 months CA increased from 84% to 91% of sites, Bayley-III use increased from 21% to 74% (P=0.001) and eligibility for follow-up was expanded for children with stroke, congenital diaphragmatic hernia and select anomalies detected in utero. Audit data is collected by > 80% of tertiary programs. CONCLUSION: Care became more consistent after CNFUN; 18-month assessments and Bayley-III use increased significantly. However, marked variability in follow-up practices persists.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".