Immediate Kangaroo Mother Care for Sick Newborns: Quality Improvement Implementation and Feasibility Study
Bibliographic record
Abstract
BACKGROUND: A systematic separation of late preterm and/or sick newborns from their mothers and families continues to occur in most neonatal units around the world. OBJECTIVE: The aim of this study was to implement immediate kangaroo mother care for sick newborns from birth. METHODS: This study comprised preterm newborns at ≥34 weeks of gestational age and weighing ≥1800 g, term newborns with noninvasive ventilation, and newborns at ≥34 weeks of gestational age and weighing ≥1800 g with congenital anomalies that did not require urgent medical or surgical attention. Newborns were excluded in cases of advanced resuscitation or at medical discretion. The newborns in this study were maintained skin-to-skin for 120 minutes, preferably with the mother, and then transferred skin-to-skin to their destination unit. RESULTS: In this study, 60 newborns were included. The median time for immediate kangaroo mother care was 120 minutes for all newborns; 100% of the time was spent with the mother, even when respiratory support was required. Immediate kangaroo mother care was interrupted for 13 of the 60 newborns, and this was more frequent in newborns with heart disease (9/13, 69%), with the main cause being the neonatologist's concern. No causes of separation were related to maternal issues, hypoglycemia, or temperature instability, and no incidents such as hypothermia were observed during kangaroo mother care, either at birth or during transport. CONCLUSIONS: Kangaroo mother care during the first 120 minutes of life in late premature or sick newborns is a safe and feasible practice.
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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 | 0.026 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".