MétaCan
Menu
Back to cohort
Record W4322618020 · doi:10.1714/3980.39627

Position paper ANMCO: Gestione dell’ipercolesterolemia nei pazienti con sindrome coronarica acuta

2023· article· en· W4322618020 on OpenAlexaff
Leonardo De Luca, Carmine Riccio, Alessandro Navazio, Serafina Valente, Manlio Cipriani, Marco Corda, Alfredo De Nardo, Giuseppina Maura Francese, Cosimo Napoletano, Emanuele Tizzani, Loris Roncon, Pasquale Caldarola, Michele Massimo Gulizia, Domenico Gabrielli, Fabrizio Oliva, Furio Colivicchi

Bibliographic record

VenueGiornale italiano di cardiologia · 2023
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsHealth Care Foundation
Fundersnot available
KeywordsMedicineAcute coronary syndromeInternal medicineCardiologyReimbursementCoronary heart diseaseIntensive care medicineLdl cholesterolRisk factorAdverse effectDiseaseCholesterolHealth careMyocardial infarction

Abstract

fetched live from OpenAlex

Patients suffering from acute coronary syndromes (ACS) present a high risk of recurrence and new adverse cardiovascular events after hospital discharge. Elevated plasma LDL-cholesterol (LDL-C) levels have been shown to be a causal factor for the development of coronary heart disease, and robust clinical evidence has documented that a decrease of LDL-C levels correlates linearly with a reduction in cardiovascular events. Recent studies have also demonstrated the safety and efficacy of an early and significant reduction in LDL-C levels in patients with ACS.In this position paper, ANMCO proposes a decision algorithm on early adoption of lipid-lowering strategies at hospital discharge and short-term follow-up of patients with ACS, in the light of the multiple evidence generated in recent years on the treatment of hypercholesterolemia and the available therapeutic options, considering current reimbursement criteria.

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)0.004
metaresearch head score (Gemma)0.011
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0090.004

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 head0.019
GPT teacher head0.262
Teacher spread0.243 · 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
GenreEditorial

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

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueGiornale italiano di cardiologiaSame topicLipoproteins and Cardiovascular HealthFrench-language works237,207