A163 DIETARY PATTERNS OF BREASTFEEDING POST-PARTUM MOTHERS WITH INFLAMMATORY BOWEL DISEASE AND THEIR ASSOCIATIONS ON INFANT GROWTH
Bibliographic record
Abstract
Abstract Background Inflammatory bowel disease (IBD), which includes Crohn’s disease (CD) and ulcerative colitis (UC) is characterized by chronic intestinal inflammation. Since IBD is often diagnosed in young adulthood, many people will have IBD at the time of pregnancy and breastfeeding. Chronic inflammation can cause severe nutritional deficiencies; however, it is unclear whether nutrient deficiencies during postpartum affect patients with IBD. Aims To investigate the dietary patterns of breastfeeding mothers with IBD and correlate their dietary patterns with their infant growth within the first 6 months. Methods A total of 21 mothers with IBD (9 CD and 12 UC) were recruited from the Preconception and Pregnancy IBD clinic at Mount Sinai. Inclusion criteria include females between 18-45 years olds with a diagnosis of CD or UC, who are at least 24 weeks gestational age, and females with multi-fetal gestation, co-morbid intestinal disease, or autoimmune comorbidities were excluded. Mothers completed a 3-day food diary and clinical disease activity scores at 1-month (1M) and 3-months (3M) postpartum, and self-filled questionnaires related to infant growth over a 6-month follow-up. Food and dietary patterns were analyzed using a food analysis software called ESHA based on age, gender, weight and height. Infant growth was compared to the World Health Organization’s growth curve Z-scores. Results About half (52% at 1M and 48% at 3M) of mothers with IBD met the protein recommendation. Over half (62% at 1M and 3M) met their total fat recommendation. However, most did not meet the carbohydrate (33% at 1M and 19% at 3M) and fiber (24% at 1M and 10% at 3M) recommendations. All infants included in the analysis were breastfed at 1M and 3M postpartum. Breastfed infants born to mothers who met their total fat recommendation had higher length measurements compared to those who did not at 6 months. Conclusions Our study findings show that breastfeeding mothers with IBD may not meet their recommended carbohydrate and fiber dietary intake, and that infants breastfed by mothers who do not meet their macronutrient dietary intake and lengths in the lower percentile range. Future research will delineate the specific nutrient composition in mothers’ breastmilk. Funding Agencies American College of Gastroenterology, University of Toronto, CAN-TAP-TALENT
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".