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Record W3158223130 · doi:10.15420/ecr.2020.42

Management of Dyslipidaemia in Real-world Clinical Practice: Rationale and Design of the VIPFARMA ISCP Project

2021· review· en· W3158223130 on OpenAlexaff
Ricardo López Santi, Felipe A. Martínez, Adrián Baranchuk, Álvaro Sosa Liprandi, Daniel Piskorz, Alberto Lorenzatti, J. C. Kaski

Bibliographic record

VenueEuropean Cardiology Review · 2021
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicinePharmacotherapyFamily medicineMedical prescriptionClinical PracticeInternal medicineNursing

Abstract

fetched live from OpenAlex

Dyslipidaemia plays a major role in the pathogenesis of atherosclerosis. Every year, scientific institutions publish cardiovascular prevention guidelines with updated goals and recommendations based on new evidence. However, medical barriers exist that make achieving these goals difficult and gaps between guidelines and best daily clinical practice still persist. The International Society of Cardiovascular Pharmacotherapy designed the Surveillance of Prescription Drugs in the Real World Project (VIPFARMA ISCP), a survey for physicians who manage lipid disorders in high-risk patients. Seven clusters of questions will be analysed comprising demographics, institution profile, access to continuing medical education, clinical practice profile, attitude regarding use of statins, knowledge regarding proprotein convertase subtilisin/kexin type 9 inhibitors and attitudes regarding medical decisions about triglycerides. The present study will be the first part of a larger programme and aims to shed light on barriers between lipid-lowering drug therapy recommendations in the 2019 European Society of Cardiology guidelines and clinical practice in different countries.

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)0.013
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.844
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.161
GPT teacher head0.445
Teacher spread0.284 · 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.

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

Citations2
Published2021
Admission routes1
Has abstractyes

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