Evidence map›Paper›PMID 42296286›Full record

ArticleJournal of cardiovascular electrophysiology2026

Detection of Spatio-Temporal Dispersion Electrograms Using Complex Signal Identification-Labeled Abnormal Potential Areas in Patients With Persistent Atrial Fibrillation.

Kazuki Ito, Yoshihisa Naruse, Yuki Tokonami, Yutaro Kaneko, Makoto Sano, Yuichiro Maekawa

Abstract read
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Article in Journal of cardiovascular electrophysiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Kazuki ItoDepartment of Internal Medicine III, Division of Cardiology, Hamamatsu University School of Medicine, Handayama, Chuo-ku, Hamamatsu, Japan.
Yoshihisa NaruseDepartment of Internal Medicine III, Division of Cardiology, Hamamatsu University School of Medicine, Handayama, Chuo-ku, Hamamatsu, Japan.ORCID 0000-0001-9630-951X
Yuki TokonamiDepartment of Internal Medicine III, Division of Cardiology, Hamamatsu University School of Medicine, Handayama, Chuo-ku, Hamamatsu, Japan.
Yutaro KanekoDepartment of Internal Medicine III, Division of Cardiology, Hamamatsu University School of Medicine, Handayama, Chuo-ku, Hamamatsu, Japan.ORCID 0009-0003-7790-4200
Makoto SanoDepartment of Internal Medicine III, Division of Cardiology, Hamamatsu University School of Medicine, Handayama, Chuo-ku, Hamamatsu, Japan.
Yuichiro MaekawaDepartment of Internal Medicine III, Division of Cardiology, Hamamatsu University School of Medicine, Handayama, Chuo-ku, Hamamatsu, Japan.ORCID 0000-0001-7950-0339

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAblation targeting spatio-temporal dispersion electrograms (STDEs) in addition to pulmonary vein isolation (PVI) has been reported to reduce atrial fibrillation (AF) recurrence in patients with persistent AF.

backgroundHowever, STDE identification remains subjective. Complex Signal Identification (CSI), integrated into the CARTO 3 mapping system, automatically quantifies electrogram characteristics. We evaluated whether CSI parameters can accurately identify STDEs.

methodsWe retrospectively analyzed intracardiac electrogram points from five consecutive patients who underwent catheter ablation for persistent AF using the CARTO 3 version 8 mapping system (Biosense Webster, Diamond Bar, CA, USA) between October and December 2024 to evaluate the ability of CSI parameters to identify STDEs. STDEs were identified and marked by the operator using an OCTARAY catheter.

resultsA total of 4453 electrogram points obtained before ablation were analyzed. Among all CSI metrics, the fractionation score demonstrated the highest diagnostic accuracy. An optimal cutoff of 4.1 yielded an area under the curve (AUC) of 0.905 (95% CI: 0.892-0.918), with a sensitivity of 80.4%, specificity of 98.6%, positive predictive value of 94.1%, and negative predictive value of 93.1%. In contrast, complex duration (cutoff ≥ 50 ms), %cycle length (cutoff ≥ 15%), and complex onset (cutoff ≤ -32) showed AUCs of 0.613 (95% CI: 0.557-0.668), 0.599 (95% CI: 0.538-0.660), and 0.525 (95% CI: 0.461-0.589), respectively.

conclusionA CSI fractionation score cutoff of 4.1 identified STDEs with high accuracy, suggesting that CSI-guided mapping may serve as a practical tool for adjunctive ablation beyond PVI.

Indexed as

Action PotentialsAtrial FibrillationElectrophysiologic Techniques, CardiacHeart RateSignal Processing, Computer-AssistedAgedCatheter AblationFemaleHumansMaleMiddle AgedPredictive Value of TestsReproducibility of ResultsRetrospective StudiesTime FactorsTreatment OutcomeCARTO 3 version 8complex signal identificationpersistent atrial fibrillationspatio‐temporal dispersion electrograms

Identifiers

PMID42296286
PMCPMC13576592

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.