Changes in Energy Metabolism from Prepregnancy to Postpartum: A Case Report
Bibliographic record
Abstract
PURPOSE: Energy metabolism is at the core of maintaining healthy body weights. Likewise, the assessment of energy needs is essential for providing adequate dietary advice. We explored differences in energy metabolism of a primigravid woman (age: 30 years) at 1 month prepregnancy ("baseline"), during pregnancy (33 weeks), and at 3 and 9 months postpartum. Measured versus estimated energy expenditure were compared using equations commonly used in clinical practice. METHODS: Energy metabolism was measured using a state-of-the-art whole body calorimetry unit (WBCU). Body composition (dual-energy X-ray absorptiometry), energy intake (3-day food records), physical activity (Baecke questionnaire), and breastmilk volume/breastfeeding energy expenditure (24-hours of infant test-retest weighing) were assessed. RESULTS: This case report is the first to assess energy expenditure in 3 different stages of a woman's life (prepregnancy, pregnancy, and postpartum) using WBCU. We noticed that weight and energy needs returned to prepregnancy values at 9 months postpartum, although a pattern of altered body composition emerged (higher fat/lean ratio) without changes in physical activity and energy intake. For this woman, current recommendations for energy overestimated actual needs by 350 kcal/day (9 months postpartum). CONCLUSION: It is likely that more accurate approaches are needed to estimate energy needs during and postpregnancy, with targeted interventions to optimize body composition.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".