Comparison of Patients With Familial Chylomicronemia Syndrome and Multifactorial Chylomicronemia Syndrome
Bibliographic record
Abstract
CONTEXT: Patients with rare familial chylomicronemia syndrome (FCS) and relatively common multifactorial chylomicronemia syndrome (MCS) both express severe hypertriglyceridemia, defined as plasma triglyceride concentration ≥10 mmol/L (≥885 mg/dL). Clinically there can be confusion between the 2 conditions. OBJECTIVE: To compare clinical and biochemical phenotypes in patients with genotypically characterized FCS and MCS. METHODS: We performed targeted sequencing of DNA from 193 patients with severe hypertriglyceridemia, classified them as having either FCS or MCS, and compared clinical and biochemical characteristics. RESULTS: Patients with FCS were significantly younger than patients with MCS (31.4 ± 16.7 vs 51.0 ± 11.3 years; P = .003), with earlier age at symptom onset (15.0 ± 15.8 vs 37.8 ± 8.8 years; P = .00066), lower body mass index (23.3 ± 3.1 vs 30.7 ± 5.0 kg/m2; P = .000016), and higher prevalence of pancreatitis events (81.8% vs 35.2%; P = .003). Furthermore, patients with FCS had a higher ratio of triglyceride to total cholesterol (ie, 4.18 ± 0.92 vs 1.08 ± 0.51; P < .0001) and lower plasma apolipoprotein B (ie, 0.56 ± 0.15 vs 1.02 ± 0.43 g/L; P < .0001) than patients with MCS. Patients with MCS with heterozygous pathogenic variants had a relatively more severe clinical presentation than other MCS genetic subgroups. CONCLUSION: Patients with FCS have notable phenotypic differences from patients with MCS, although there is overlap. While genetic analysis of patients with persistent severe hypertriglyceridemia can definitively diagnose FCS, 8.8% of patients with MCS with sustained refractory hypertriglyceridemia behave functionally as if they have FCS, which should influence their eligibility for novel therapies for severe hypertriglyceridemia.
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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 | 0.002 |
| 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 | 0.001 | 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".