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 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 | 0.000 | 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".