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Record W4254827723 · doi:10.3410/f.736866539.793567220

Faculty Opinions recommendation of Causal Inference for Genetically Determined Levels of HDL (High-Density Lipoprotein) Cholesterol and Risk of Infectious Disease.

2019· dataset· en· W4254827723 on OpenAlexaboutno aff
Sergio Fazio

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2019
Typedataset
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsnot available
Fundersnot available
KeywordsHazard ratioMendelian randomizationProportional hazards modelMedicineInternal medicineTriglycerideLogistic regressionCholesterolSepsisHigh-density lipoproteinDemographyConfoundingBiologyGeneticsGenotypeConfidence intervalGenetic variants

Abstract

fetched live from OpenAlex

OBJECTIVE: HDL (high-density lipoprotein) cholesterol (HDL-C) and LDL (low-density lipoprotein) cholesterol (LDL-C) are inversely associated with infectious hospitalizations. Whether these represent causal relationships is unknown. Approach and Results: Adults of 40 to 69 years of age were recruited from across the United Kingdom between 2006 and 2010 and followed until March 31, 2016, as part of the UK Biobank. We determined HDL-C, LDL-C, and triglyceride polygenic scores for UK Biobank participants of British white ancestry (n=407 558). We examined the association of lipid levels and polygenic scores with infectious hospitalizations, antibiotic usage, and 28-day sepsis survival using Cox proportional hazards or logistic regression models. Measured levels of HDL-C and LDL-C were inversely associated with risk of infectious hospitalizations, while triglycerides displayed a positive association. A 1-mmol/L increase in genetically determined levels of HDL-C associated with a hazard ratio for infectious disease of 0.84 ([95% CI, 0.75-0.95]; P=0.004). Mendelian randomization using genetic variants associated with HDL-C as an instrumental variable was consistent with a causal relationship between elevated HDL-C and reduced risk of infectious hospitalizations (inverse weighted variance method, P=0.001). Furthermore, of 3222 participants who experienced an index episode of sepsis, there was a significant inverse association between continuous HDL-C polygenic score and 28-day mortality (adjusted hazard ratio, 0.37 [95% CI, 0.14-0.96] per 1 mmol/L increase; P=0.04). LDL-C and triglyceride polygenic scores were not significantly associated with hospitalization for infection, antibiotic use, or sepsis mortality.CONCLUSIONS: Our results provide causal inference for an inverse relationship between HDL-C, but not LDL-C or triglycerides, and risk of an infectious hospitalization. PMID: 31694394 Funding information This work was supported by: CIHR, Canada Medical Research Council, United Kingdom Grant ID: MC_QA137853 Medical Research Council, United Kingdom Grant ID: MC_PC_17228

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)0.028
metaresearch head score (Gemma)0.156
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.482
Threshold uncertainty score0.739

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.156
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0050.008
Science and technology studies0.0030.002
Scholarly communication0.0090.004
Open science0.0060.004
Research integrity0.0190.011
Insufficient payload (model declined to judge)0.4820.308

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 head0.031
GPT teacher head0.349
Teacher spread0.317 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2019
Admission routes1
Has abstractyes

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