Course of Pregnancies and Occurrence of Acute Pancreatitis in Women With Chylomicronemia
Bibliographic record
Abstract
OBJECTIVE: Chylomicronemia is characterized by extreme hypertriglyceridemia (triglyceride values >10 mmol/L). It may be caused by a biallelic combination of a pathogenic variant [familial chylomicronemia syndrome (FCS)] or by genetic susceptibility combined with comorbidities and environmental factors [multifactorial chylomicronemia syndrome (MCS)]. Acute pancreatitis (AP) is the most serious complication of chylomicronemia. In the general population, the prevalence of AP during pregnancy is estimated to be <0.35%. As triglyceride levels significantly increase during pregnancy, it may affect the course of pregnancy and further increase the risk of AP in women with chylomicronemia. METHODS: One hundred sixteen pregnancies involving 49 European and North American women with a history of chylomicronemia (20 FCS, 29 MCS) were retrospectively reviewed. The occurrence of AP, the course of pregnancy, fetal development, and delivery were evaluated. RESULTS: Forty-two percent of FCS and 10% of MCS women experienced at least 1 AP episode during pregnancy (P = .01). Compared to MCS, women with FCS presented a higher percentage of pregnancies with AP (17% vs 5%, P = .02). Among all reviewed pregnancy-related AP, 56% occurred in primigravida FCS women compared to 0% in MCS. Premature deliveries were elevated in both groups, although they were more frequent in FCS (56%) vs MCS (19%) (P = .01). The percentages of miscarriages (11.8% vs 10.7%) and fetal failure to thrive (5.9% vs 9.2%) were not significantly different between the 2 cohorts. CONCLUSION: In this study, pregnant women with chylomicronemia had a 30-fold (MCS) to 120-fold (FCS) higher occurrence of AP compared to the general population. Chylomicronemia per se does not seem to influence fetal development.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".