Dietary intakes in pregnant women with previous bariatric surgery
Bibliographic record
Abstract
Abstract Purpose: To 1) compare dietary intakes of pregnant women with previous bariatric surgery with the Dietary reference intakes (DRIs); 2); compare their dietary intakes as well as their diet quality with a control group of pregnant women with no history of bariatric surgery. Methods: Twenty-eight (28) pregnant women with previous surgery (sleeve gastrectomy, n=7 and biliopancreatic diversion with duodenal switch, n=21) were matched for pre-pregnancy body mass index with 28 pregnant women with no history of surgery. In at least one trimester, participants completed a minimum of 2 Web-based 24-h dietary recalls from which energy, macro- and micronutrient intakes as well as the Canadian Healthy Eating Index (C-HEI) were derived. Results: No differences were observed for energy intake between groups. All women had protein intakes within the recommended range, but most women with previous surgery had carbohydrate (67 %) and dietary fiber intakes (98 %) below recommendations. In both groups, mean total fat, saturated fatty acids, free sugars and sodium intakes were above recommendations, as opposed to mean vitamin D, folic acid and iron dietary intakes below recommendations for most women. Compared with the control group, pregnant women with previous bariatric surgery had lower overall C-HEI scores. Conclusion: These results suggest that pregnant women with previous bariatric surgery would benefit from a nutritional follow-up throughout their pregnancy.Level of evidenceLevel III: Evidence obtained from well-designed cohort or case-control analytic studies
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".