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Record W2942748655 · doi:10.1016/j.ihj.2019.04.007

Lipoprotein(a): An underrecognized genetic risk factor for malignant coronary artery disease in young Indians

2019· review· en· W2942748655 on OpenAlexaff
Enas A. Enas, Basil Varkey, T. S. Dharmarajan, Guillaume Paré, Vinay K. Bahl

Bibliographic record

VenueIndian Heart Journal · 2019
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineCoronary artery diseaseDiabetes mellitusRisk factorInternal medicineLipoprotein(a)Myocardial infarctionCardiologyDiseaseLipoproteinCholesterolEndocrinology

Abstract

fetched live from OpenAlex

Malignant coronary artery disease (CAD) refers to a severe and extensive atherosclerotic process involving multiple coronary arteries in young individuals (aged <45 years in men and <50 years in women) with a low or no burden of established risk factors. Indians, in general, develop acute myocardial infarction (AMI) about 10 years earlier; AMI rates are threefold to fivefold higher in young Indians than in other populations. Although established CAD risk factors have a predictive value, they do not fully account for the excessive burden of CAD in young Indians. Lipoprotein(a) (Lp(a)) is increasingly recognized as the strongest known genetic risk factor for premature CAD, with high levels observed in Indians with malignant CAD. High Lp(a) levels confer a twofold to threefold risk of CAD-a risk similar to that of established risk factors, including diabetes. South Asians have the second highest Lp(a) levels and the highest risk of AMI from the elevated levels, more than double the risk observed in people of European descent. Approximately 25% of Indians and other South Asians have elevated Lp(a) levels (≥50 mg/dl), rendering Lp(a) a risk factor of great importance, similar to or surpassing diabetes. Lp(a) measurement is ready for clinical use and should be an essential part of all CAD research in Indians.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.341
Teacher spread0.277 · 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 teacher head, not a consensus.

Study designOther design
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

Citations67
Published2019
Admission routes1
Has abstractyes

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