Post-prandial analysis of fluctuations in the platelet count and platelet function in patients with the familial chylomicronemia syndrome
Bibliographic record
Abstract
BACKGROUND: /L) has been reported in patients with FCS, treated or not with volanesorsen, a second generation APOC3 anti-sense oligonucleotide. Chylomicrons are the lipoproteins delivering fat after a meal and FCS thus has a post-prandial origin. Platelet count and function have not been studied post-prandially in FCS. OBJECTIVE: To evaluate post-prandial fluctuations in the platelet count (PLC) and functional defects of hemostasis in FCS. METHODS: PLC, functional defects in hemostasis and hematologic variables were measured up-to 5 h after a meal in 6 homozygotes for FCS causing gene variants (HoLPL), 6 heterozygotes for LPL loss-of-function variants (HeLPL) and 7 normolipidemic controls. RESULTS: Hourly post-prandial PLC was significantly lower in HoLPL than in controls (P < 0.009). Compared to the other groups, the PLC tended to decrease rapidly (in the first hour) post-meal in HoLPL (P = 0.03) and remained lower than baseline 5-h post-meal (P = 0.02) whereas it tended to slightly increase in normolipidemic controls (P = 0.02). Platelet function was not affected by the prandial status. In HoLPL, post-prandial fluctuations in the PLC positively correlated with the lymphocyte count (P = 0.005) and negatively with neutrophil/lymphocyte ratio (NLR). CONCLUSION: The PLC decreases post-prandially in FCS (HoLPL), is not associated with changes in functional defects of hemostasis and correlates with the NLR, a marker of acute pancreatitis severity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".