Transition to Neonatal Follow-up Programs
Bibliographic record
Abstract
Neonatal follow-up (NFU) programs provide health services for infants at high risk for developmental problems after they transition home from the neonatal intensive care unit (NICU). The purpose of the study was to assess current patterns of NFU attendance and explore time points when mothers and infants withdrew from NFU programs during the infant's first year of life. The study was conducted in 3 Canadian tertiary-level NICUs that referred to 2 affiliated, regional NFU programs. A total of 357 mothers and 400 infants were consecutively recruited during NICU hospitalization. Attendance at NFU programs was tracked at each of the 3 scheduled appointments from existing NFU databases. Attendance at NFU decreased over time from 84% at the first appointment to 74% by 12 months, with the highest withdrawal from NFU after NICU discharge, followed by withdrawal after the first NFU appointment. Nonattendance at NFU results in less access to required services and underreporting of the developmental outcomes of these infants. Given these findings, mothers should be screened earlier in the NICU to identify those at greatest risk of not attending NFU. Strategies should be implemented to address potential barriers and provide effective transition and access to the NFU program.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".