Very severe hypertriglyceridemia complicating pediatric acute lymphoblastic leukemia treatment: a call for management guidelines
Bibliographic record
Abstract
OBJECTIVES: Severe and very severe hypertriglyceridemia although rare within the pediatric population occur more often among oncology patients, secondary to chemotherapeutic agents. Currently there exists minimal literature to guide management of severe hypertriglyceridemia among pediatric patients. Very-low-fat dietary restriction should be considered over nil per os (NPO) for initial management of severe hypertriglyceridemia in stable pediatric patients. Pediatricians caring for oncology patients must consider chylomicronemia as a potential etiology for presenting symptoms. Pediatric severe hypertriglyceridemia management guidelines are needed as pediatricians must currently rely on anecdotal experiences for management decisions. CASE PRESENTATION: Three children receiving treatment for acute lymphoblastic leukemia required hospitalization for very severe hypertriglyceridemia. Management varied among the cases but included: NPO or very-low-fat diet, insulin, intravenous fluids, fibrates, and omega-3 fatty acids. CONCLUSIONS: These cases suggest that pediatric severe hypertriglyceridemia management, in the absence of pancreatitis should allow a very-low-fat diet initially rather than NPO followed by pharmacologic therapies.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.020 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".