What does this research mean for the field?

An automated classification algorithm using the coefficient of variation of the atrial period and the number of points at the baseline can accurately classify atrial fibrillation types from intraatrial electrograms, with slight improvement when adding electrogram bandwidth. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

February 1, 2000Pacing and Clinical Electrophysiology

Automated Classification of Human Atrial Fibrillation From Intraatrial Electrograms

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Why the study?

Can an automated classification algorithm based on intraatrial electrogram parameters accurately classify atrial fibrillation types compared to expert visual inspection?

Population

160 atrial fibrillation strips from electrically induced and chronic patients, scored by an expert…

Comparison

Automated classification algorithm based on a… vs Visual inspection and scoring by an expert…

Design

Other

Authors

VBVincenzo BarbaroIstituto Superiore di Sanità PBP. BartoliniCenter for Devices and Radiological Health GCGiovanni CalcagniniElectrophysiology

Discussion

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Implication

May enable objective AF classification in EP labs; leaves open prospective validation before clinical adoption.

Structured PICO

Can an automated classification algorithm based on intraatrial electrogram parameters accurately classify atrial fibrillation types compared to expert visual inspection?

Population

160 atrial fibrillation (AF) strips (6 seconds long) from electrically induced (n = 13) and chronic (n = 10) patients, scored by an expert cardiologist as Type I, II, and III AF.

Intervention

Automated classification algorithm based on a minimum-distance (Mahalanobis distance) discriminant analysis using electrogram parameters (AP, CV, NO, EN, F-WIDTH, CWA, BW).

Comparator

Visual inspection and scoring by an expert cardiologist.

Outcome

Classification accuracy (sensitivity and specificity) of the automated algorithm compared to expert scoring.

An automated classification algorithm using two or three electrogram parameters can accurately classify atrial fibrillation types, matching expert visual inspection.

Cite This Study

Barbaro et al. (2000) studied this question.

synapsesocial.com/papers/6a1c13a3fc87fd06169d08b7 https://doi.org/10.1111/j.1540-8159.2000.tb00800.x

Topics

Atrial fibrillation Persistent AF management Anticoagulation in AF AF ablation outcomes

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Automated Classification of Human Atrial Fibrillation From Intraatrial Electrograms

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Topics

Automated Classification of Human Atrial Fibrillation From Intraatrial Electrograms

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Also Consider

Topics

Also Consider