Spectrum and Management of Hypertriglyceridemia Among Children in Clinical Practice
Bibliographic record
Abstract
OBJECTIVES: The prevalence and identification of hypertriglyceridemia in youths will likely will increase in the future as a consequence of childhood obesity and increased screening for dyslipidemias. We sought to review our clinical experience with hypertriglyceridemia, evaluate factors associated with increased triglyceride levels, and review treatment options to provide guidance for management. METHODS: Clinical review of data for all patients who had > or =1 elevated triglyceride level (>4 mmol/L [>350 mg/dL]) while being monitored in a specialized lipid disorders clinic was performed. RESULTS: The study population consisted of 76 patients with 761 clinic visits. Hypertriglyceridemia was secondary to lifestyle factors for 13 patients. The rest had primary hypertriglyceridemia, with 32 patients having familial combined hypertriglyceridemia and hypercholesterolemia (type II), 25 patients having primary hypertriglyceridemia (type IV), 4 patients having familial lipase deficiency (type I), and 2 patients having hyperlipoproteinemia E2/E2 phenotype (type III). Triglyceride levels were highest in type I and III hypertriglyceridemia (>10 mmol/L [>900 mg/dL]), followed by type IV and adiposity-related hypertriglyceridemia (>4 mmol/L [>350 mg/dL]) and finally type II familial combined hypertriglyceridemia and hypercholesterolemia (>2 mmol/L [>180 mg/dL]). A total of 34 patients received 37 trials of drug therapy as part of triglyceride level management (bile acid-binding resins, n = 12; fibrates, n = 19; statins, n = 6). Triglyceride levels were found to decrease over time with the use of fibrates, to increase with the use of bile acid-binding resins, and not to change with the use of statins. CONCLUSIONS: Lifestyle modifications remain the primary therapeutic avenue for the management of pediatric hypertriglyceridemia. We propose an algorithm for the management of this heterogeneous population to guide clinicians in their treatment decisions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".