Effect of Pregnancy on Bone Mineral Density in Healthy Women
Bibliographic record
Abstract
Despite numerous studies and case reports of changes in bone mineral density (BMD) during pregnancy, the postpartum, and lactation, controversy exists regarding the time course of BMD changes and recovery to baseline levels. The degree to which pregnancy affects BMD long-term remains unclear. Several influencing factors, including breast-feeding, length of amenorrhea after pregnancy, and parity, have been studied with respect to changes in BMD in healthy women. We conducted the first systematic review of its kind on this topic and evaluated the 23 identified citations according to the U.S. Preventive Services Task Force rating scale. Six studies qualified as Level II-2, 12 were Level II-3, and 5 were Level III. There seems to be good evidence that calcium is mobilized from the maternal skeleton to that of the developing fetus during pregnancy. However, the eventual return of BMD to prepregnancy values suggests that maternal bone loss may not be permanent. Results from the studies that specifically evaluated the effect of lactation on BMD were varied, ranging from a decrease in BMD to no change. Of the studies that evaluated the effect of parity on BMD, none found an association linking a greater number of pregnancies to greater decreases in BMD. Pregnancy-associated osteoporosis seems to be uncommon, based on the limited published reports. Overall, no long-term adverse clinical effects have been noted in healthy women who had at least one ongoing pregnancy, despite the good evidence that some bone loss does occur soon after delivery. Additional longitudinal studies need to be undertaken to provide more definitive information on the effects of pregnancy on BMD and risk of osteoporosis later in life.
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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 | 0.005 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".