Epidemiology and longitudinal course of chylomicronemia: Insights from NHANES and a large health care system
Bibliographic record
Abstract
BACKGROUND: Chylomicronemia is characterized by fasting triglyceride (TG) ≥1000 mg/dL; its longitudinal course is not well studied. METHODS: Using National Health and Nutrition Examination Survey (NHANES) data (1999-2018; n = 21,998), we determined chylomicronemia prevalence and temporal trend. Using Mayo Clinic data (4,524,506 TG measurements for 1,294,044 individuals), we studied the longitudinal course and ascertained persistent chylomicronemia (PC), defined as TG ≥1000 mg/dL in more than half the measurements for individuals with ≥3 measurements. We used logistic regression to assess factors associated with PC. RESULTS: In NHANES, the prevalence of chylomicronemia was 0.20% overall, with higher prevalence in men (0.32%) and Hispanics (0.33%). Chylomicronemia prevalence declined from 0.34% in 1999-2004 to 0.11% in 2013-2018, while lipid-lowering pharmacotherapy use in chylomicronemia patients increased from 5.3% to 51.9%. In the Mayo Clinic data, 5618 individuals (0.43%) had at least 1 episode of chylomicronemia. Of these, 8.8% (390 of 4443 with ≥3 measurements) met the operational definition for PC. In individuals with TG <150 mg/dL, 1.3% had a diagnosis of acute pancreatitis, and 0.6% had chronic pancreatitis. Respective figures for individuals with nonpersistent chylomicronemia were 12.5% and 5.1%, and for individuals with PC were 26.2% and 11.5%. Younger age, Hispanic ethnicity, prior pancreatitis, and higher TG levels were associated with PC. CONCLUSION: In the US, 1 in ∼500 adults has chylomicronemia and 1 in ∼5500 has PC. Individuals with PC have high occurrence of acute and chronic pancreatitis and may need more effective treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".