Development of home‐based methods to defat human milk for infants with chylothorax: An experimental study
Bibliographic record
Abstract
BACKGROUND: Chylothorax is a postoperative complication for infants with congenital heart defects; with high nutrition risk. Defatted human milk is recommended; however, refrigerated centrifugation to process milk poses accessibility barriers for many hospitals and families at home. Creation of a simplified home-based defatted milk protocol allows infants with chylothorax to be provided the immunological benefits of human milk postoperatively. METHODS: Milk from 20 mothers was tested to compare refrigerated centrifugation as the standard defatting technique against gravity-based methods: syringe tip-down and gravy separator. Two timeframes, 24 h and 48 h, were tested to determine if additional time had a significant impact on fat reduction. The MIRIS human milk analyzer provided results for fat, true protein, carbohydrate, and energy content. One-way analysis of variance was used to determine a significant difference on fat content among methods. RESULTS: All methods had a significant reduction in fat content, with centrifugation having the largest mean decline from 3.4 to 0.5 g/100 ml (P < 0.0001). The second most effective method to defat milk was 48-h gravy separator with a mean decline to 0.7 g/100 ml (P < 0.0001). Postpartum age of milk impacted the degree of fat removal in all methods. True protein content remained the same as baseline in all methods. CONCLUSION: A simplified home-based gravity separation method over 48 h reduced human milk fat by 80%. This is the first protocol to defat human milk without use of the more resource-intensive centrifugation method, that shows significant fat reduction with easy-to-use and accessible equipment for management of infants with chylothorax.
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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 | 0.000 |
| 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".