Hypoparathyroidism in Pregnancy and Lactation: Current Approach to Diagnosis and Management
Bibliographic record
Abstract
BACKGROUND: Hypoparathyroidism is an uncommon endocrine disorder. During pregnancy, multiple changes occur in the calcium-regulating hormones, which may affect the requirements of calcium and active vitamin D during pregnancy in patients with hypoparathyroidism. Close monitoring of serum calcium during pregnancy and lactation is ideal in order to optimize maternal and fetal outcomes. In this review, we describe calcium homeostasis during pregnancy in euparathyroid individuals and also review the diagnosis and management of hypoparathyroidism during pregnancy and lactation. METHODS: We searched the MEDLINE, CINAHL, EMBASE, and Google scholar databases from 1 January 1990 to 31 December 2020. Case reports, case series, book chapters, and clinical guidelines were included in this review. CONCLUSIONS: During pregnancy, rises in 1,25-dihydroxyvitamin D (1,25-(OH)2-D3) and PTH-related peptide result in suppression of PTH and enhanced calcium absorption from the bowel. In individuals with hypoparathyroidism, the requirements for calcium and active vitamin D may decrease. Close monitoring of serum calcium is advised in women with hypoparathyroidism with adjustment of the doses of calcium and active vitamin D to ensure that serum calcium is maintained in the low-normal to mid-normal reference range. Hyper- and hypocalcemia should be avoided in order to reduce the maternal and fetal complications of hypoparathyroidism during pregnancy and lactation. Standard of care therapy consisting of elemental calcium, active vitamin D, and vitamin D is safe during pregnancy.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".