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Postprandial Hypertriglyceridaemia Revisited in the Era of Non-Fasting Lipid Profile Testing: A 2019 Expert Panel Statement, Narrative Review

2019· review· en· W4210992022 on OpenAlexaff
Genovefa Kolovou, Gerald F. Watts, Dimitri P. Mikhailidis, Pablo Pérez‐Martínez, Samia Mora, Helen Bilianou, George Panotopoulos, Niki Katsiki, Teik Chye Ooi, José López‐Miranda, Anne Tybjærg‐Hansen, Nikolaοs Tentolouris, Børge G. Nordestgaard

Bibliographic record

VenueCurrent Vascular Pharmacology · 2019
Typereview
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersNational Heart, Lung, and Blood Institute
KeywordsPostprandialMedicineInternal medicineTriglycerideHypertriglyceridemiaDiabetes mellitusEndocrinologyObesityMetabolic syndromeType 2 Diabetes MellitusCholesterol

Abstract

fetched live from OpenAlex

Postprandial hypertriglyceridaemia, defined as an increase in plasma triglyceride-containing lipoproteins following a fat meal, is a potential risk predictor of atherosclerotic cardiovascular disease and other chronic diseases. Several non-modifiable factors (genetics, age, sex and menopausal status) and lifestyle factors (diet, physical activity, smoking status, obesity, alcohol and medication use) may influence postprandial hypertriglyceridaemia. This narrative review considers the studies published over the last decade that evaluated postprandial hypertriglyceridaemia. Additionally, the genetic determinants of postprandial plasma triglyceride levels, the types of meals for studying postprandial triglyceride response, and underlying conditions (e.g. familial dyslipidaemias, diabetes mellitus, metabolic syndrome, non-alcoholic fatty liver and chronic kidney disease) that are associated with postprandial hypertriglyceridaemia are reviewed; therapeutic aspects are also considered.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.002

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.

Opus teacher head0.107
GPT teacher head0.405
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations23
Published2019
Admission routes1
Has abstractyes

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