Familial Chylomicronemia Syndrome
Bibliographic record
Abstract
Familial Chylomicronemia Syndrome is a severe and very rare metabolic disease characterized by chylomicronemia associated with recurrent episodes of abdominal pain and/or pancreatitis. The worldwide estimate is that Familial Chylomicronemia Syndrome occurs in one for every 500,000 to 1,000,000 people. It often manifests in childhood or adolescence and has been described in all ethnicities, with higher prevalence in some geographic areas, such as Quebec, due to the founder effect. Male patient, 40 years old, accountant, married, father of two daughters (1 and 4 years). Since the age of four, he knows how to have very high triglyceride values by warning from the laboratory. Genetic analysis confirmed deficiency of lipoprotein lipase. Pediatricians recommended the dietary and exercise lifestyle. As a teenager, he had pancreatitis when triglyceride levels reached 5,000 mg/dL. The patient does not present cardiovascular risk factors. We were wanted about three years ago when a second sister with the same condition died. It is noteworthy that his parents are first cousins. After therapeutic trials, little benefit was noticed. In association with the direction of hematology, we began to prescribe weekly and later biweekly dialysis. Since the emergence of volanesorsena, we have been prescribing it. Although its use in this patient is recent, six months, the results showed an important and significant reduction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".