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Abstract 4360016: Anatomical Stroke Topography Predicts Ventricular and Atrial Ectopic Burden

2025· article· en· W4415791180 on OpenAlexaff
Jayant Seth, Simon W. Rabkin

Bibliographic record

VenueCirculation · 2025
Typearticle
Languageen
FieldMedicine
TopicECG Monitoring and Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsStroke (engine)Middle cerebral arteryBasal (medicine)EtiologyIncidence (geometry)Posterior cerebral artery

Abstract

fetched live from OpenAlex

Introduction: Stroke-related autonomic dysregulation can trigger cardiac arrhythmias, but impact of stroke localization on ectopic burden is uncertain. Goals/Aims: Identify stroke locations associated with PVC/PAC burden to guide post-stroke cardiac monitoring. Methods: We retrospectively screened 150 consecutive adults admitted to a University Hospital stroke service for stroke (2023–2025). Inclusion criteria were radiologically confirmed stroke, 24-hour Holter monitoring, and no pre-existing arrhythmia and were met ( n=103). Stroke topography was classified by: (1) vascular territory (anterior cerebral artery [ACA], middle cerebral artery [MCA], posterior cerebral artery [PCA], multifocal, brainstem), (2) neuro-anatomical region (frontal, temporal, parietal, occipital, basal ganglia, insula, cerebellum), and (3) hemisphere (left, right, bilateral). Stroke etiology (ischemic vs hemorrhagic) was analyzed. Negative-binomial models, validated by deviance and Pearson residuals, quantified associations between stroke location and ectopic counts, adjusting for age, sex, hypertension, and left ventricular function. Results: Mean age was 70.8 years; 54.9% were male, 62.1% had hypertension. Arrhythmias occurred in 11.7% patients. The following results are significant (p < 0.05): Vascular territory: PVC burden showed no significant differences across vascular territories. PAC burden was higher in ACA strokes than MCA (12.5-fold). PAC burden was higher in MCA strokes than PCA (8.3-fold). Neuro-anatomical region: PVC burden was elevated in basal ganglia, cerebellum, and brainstem compared to frontal, temporal, parietal, and occipital lobes. PAC burden was lowest in frontal lobe, with incidence rate ratios (IRR) of 0.17 vs temporal, 0.03 vs basal ganglia, and 0.01 vs cerebellum. Frontal lobe had the lowest PACs. Hemisphere: PVC burden was higher in left-sided strokes compared to right (IRR=1.98) and bilateral strokes (IRR=12.33), and higher in right-sided strokes compared to bilateral strokes (IRR=6.22). PAC burden was higher in left- versus right-sided strokes (IRR 13.69) and lower in right- versus bilateral strokes (IRR 0.04). Stroke etiology: Ischemic and hemorrhagic strokes showed no difference in PVC or PAC burden. Conclusions: Ectopic activity post-stroke varies by lesion site, with higher burden in ACA territory, basal ganglia, and left hemisphere strokes. Anatomical stroke topography identities patients with a more urgent need for cardiac arrhythmia monitoring.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.277

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.266
Teacher spread0.257 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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