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Cardiac Pacing Device Therapy for Atrial Dysrhythmias

2004· review· en· W2047110775 on OpenAlexaff
Marleen Irwin

Bibliographic record

VenueAACN Clinical Issues Advanced Practice in Acute & Critical Care · 2004
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsGrey Nuns Community Hospital
Fundersnot available
KeywordsMedicineAtrial fibrillationBradycardiaCardiologyInternal medicineHeart failurePopulationIntensive care medicineHeart rateBlood pressure

Abstract

fetched live from OpenAlex

Atrial fibrillation (AF) is the most common dysrhythmia in North America. Paroxysmal or persistent AF affects an estimated 2.8 million individuals, causes significant morbidity, and is associated with 1 billion dollars in healthcare costs each year in the United States. An aging population, the prevalence of hypertension, and the emergence of heart failure as the final common pathway of heart disease finds us in an age where the incidence of AF is ever increasing and the management challenges are indeed an expanding clinical problem. Although guidelines for selection of the appropriate pacing mode have been published, device therapy for the control of AF and paroxysmal AF is an emerging clinical management strategy. In 2001 The American College of Cardiology (ACC)/American Heart Association (AHA) published a document to revise the 1998 guidelines for device therapy, and even now these guidelines require elucidation and inclusion for the use of cardiac pacing device therapy for the control of atrial dysrhythmia. Choosing a complex system, in particular for the patient with persistent and symptomatic atrial dysrhythmia, is a most intricate challenge for the healthcare professional and the healthcare system. Rate dependent effects on refractoriness, reduction of ectopy, remodeling of the substrate, and prevention of pauses have been described as the potential mechanisms responsible for the rhythmic control effect attributed to atrial pacing. However, while permanent cardiac pacing is required for patients with symptomatic bradycardia with atrioventricular block and AF, the concept of pacing for the primary prevention of AF is novel. Pacing algorithms, single site, biatrial, and dual-site atrial pacing and site-specific pacing have all been studied as substrate modulators to prevent recurrent atrial dysrhythmia.A dilemma exists surrounding the primary approach for the control of symptomatic AF with rapid ventricular response. The question remains: should it be to maintain the sinus rhythm or to control the ventricular response rate to the AF and anticoagulate? Variations in the population studied, differences in the pacing algorithms and protocols, and a lack of definitive end points account for the variable results of the studies completed thus far. With the current data available, it appears that for individuals with sinus node dysfunction and paroxysmal AF in combination with a bradyarrhythmia indication for pacing, suppression algorithms may play an additive role with full atrial pacing in the management and reduction of episodes and burden of paroxysmal AF. The goal of these therapies is to reduce the symptoms and hopefully decrease the healthcare costs associated with paroxysmal and persistent AF with uncontrolled ventricular response.

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)0.002
metaresearch head score (Gemma)0.040
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.040
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
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 head0.252
GPT teacher head0.602
Teacher spread0.350 · 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.

Study designOther design
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

Citations3
Published2004
Admission routes1
Has abstractyes

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