Human Milk Biomarkers of Secretory Activation in Breast Pump-Dependent Mothers of Premature Infants
Bibliographic record
Abstract
OBJECTIVE: Mothers of premature infants confront barriers to coming to volume (CTV; ≥500 mL/day mother's own milk [MOM] by postpartum day 14), a strong predictor of continued MOM provision at neonatal intensive care unit (NICU) discharge. We sought to determine concentrations of secretory activation biomarkers (MOM sodium, total protein, lactose, and citrate) during the first 14 postpartum days and to describe relationships among these biomarkers, pumped MOM volume, CTV, and pumping frequency. STUDY DESIGN: This descriptive observational study collected serial MOM samples, pumped MOM volume, and pumping frequency during the first 14 postpartum days in 16 breast pump-dependent mothers who delivered <33 weeks gestation. Daily biomarker concentrations were compared to published normal values for mothers of term infants. Relationships among biomarkers, pumped MOM volume, and pumping frequency were determined. RESULTS: On postpartum day 5, only 40% of MOM samples revealed normal concentrations of all four biomarkers, and normalcy was not maintained throughout the first 14 days. All eight mothers (50%) who achieved CTV had normal concentrations for four biomarkers at 5.4 ± 3.5 days postpartum and had more cumulative pumping sessions by day 5 (p = 0.03). A dose-response relationship between number of normal biomarkers and pumped MOM volume was demonstrated for postpartum days 3 (p = 0.01) and 5 (p = 0.04). CONCLUSION: Secretory activation is delayed in mothers who deliver prematurely and is closely tied to CTV, MOM volume, and pumping frequency. MOM biomarkers hold promise as objective research outcome measures and for point-of-care testing to identify and proactively manage mothers at risk for compromised lactation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".