Factors associated with the discontinuance of outpatient follow-up in neonatal units
Bibliographic record
Abstract
OBJECTIVES: to identify predisposing and enabling factors as well as the health needs associated with the discontinuance of outpatient follow-up of newborns who were hospitalized at neonatal intensive care unit. METHODS: cross-sectional study, using the behavioral model of health services use. The study was composed of 358 mothers and newborns referred to the outpatient follow-up after discharge. Characterization, perception of social support, postnatal depression, and attendance to appointments data were collected, analyzed by the R software (3.3.1). RESULTS: outpatient follow-up was discontinued by 31.28% of children in the first year after discharge. In multiple regression analysis, the chance of discontinuance was higher for newborns who used mechanical ventilation (OR = 1.68; 95%CI 1.04-2.72) and depended on technology (OR = 3.54; 95%CI 1.32-9.5). CONCLUSIONS: predisposing factors were associated with the discontinuance of follow-up; enabling factors and health needs did not present a significant association. Children with more complex health conditions require additional support to participate in follow-up programs, thus ensuring the continuity of care.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".