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The Intuitive Case for <b>β</b>‐blockers in Patients with ESRD

2012· editorial· en· W1515697916 on OpenAlexaff
Rory McQuillan, Christopher T. Chan

Bibliographic record

VenueSeminars in Dialysis · 2012
Typeeditorial
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineIntensive care medicine

Abstract

fetched live from OpenAlex

Sudden cardiac death (SCD) is common in dialysis patients accounting for up to 25% of all-cause mortality. Unlike in the general population, occlusive coronary artery disease is implicated in a minority of these deaths. Activation of the sympathetic nervous system is prevalent in the dialysis population and may underlie this high rate of SCD. β-blockers reduce SCD in the general population and, given their mode of action, β-blockers would seem to be an ideal class of agents to prevent SCD in dialysis patients. In this review, we will explore the etiology of SCD in dialysis patients and discuss the evidence supporting the use of β-blockers in patients with ESRD. We will also examine potential impediments to the use β-blocker in the dialysis population and outline directions for future trials in this area.

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)0.014
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: Editorial
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0020.001
Research integrity0.0110.017
Insufficient payload (model declined to judge)0.0050.004

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 head0.003
GPT teacher head0.246
Teacher spread0.242 · 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

Citations6
Published2012
Admission routes1
Has abstractyes

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