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Record W3204602708 · doi:10.3390/diagnostics11101781

Sudden Cardiac Death in Systemic Sclerosis: Diagnostics to Assess Risk and Inform Management

2021· review· en· W3204602708 on OpenAlexaff
Laura Ross, E. Paratz, Murray Baron, André La Gerche, Mandana Nikpour

Bibliographic record

VenueDiagnostics · 2021
Typereview
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsMcGill UniversityJewish General Hospital
FundersNational Health and Medical Research CouncilRoyal Australasian College of PhysiciansPostcolonial Studies Association
KeywordsSudden cardiac deathMedicineDiseaseMyocarditisEpidemiologyIntensive care medicineCause of deathPopulationCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Cardiac disease is a leading cause of death in systemic sclerosis (SSc) and sudden cardiac death (SCD) is thought to occur more commonly in SSc than in the general population. Diffuse myocardial fibrosis, myocarditis and ischaemic heart disease are all prevalent in SSc and can be reasonably hypothesised to contribute to an increased risk of SCD. Despite this, SCD remains a relatively understudied area of SSc with little understood about SSc-specific risk factors and opportunities for primary prevention. In this review, we present an overview of the possible mechanisms of SCD in SSc and our current understanding of how each of these mechanisms may contribute to cardiac death. This review highlights the need for a future research agenda that addresses the underlying epidemiology of SCD in SSc and identifies opportunities for intervention to modify the disease course of heart disease in SSc.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.092
GPT teacher head0.337
Teacher spread0.245 · 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

Citations11
Published2021
Admission routes1
Has abstractyes

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