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Performance of Ambulatory Electrocardiographic Data for Prediction of Stroke and Heart Failure Events.

Publication ,  Journal Article
Schwennesen, HT; Li, Z; Hammill, BG; Clark, AG; Pokorney, S; Hytopoulos, E; Turakhia, MP; Cambra, J; Piccini, JP
Published in: JACC Adv
November 2024

BACKGROUND: Despite clear associations between arrhythmia burden and cardiovascular risk, clinical risk scores that predict cardiovascular events do not incorporate individual-level arrhythmia characteristics from long-term continuous monitoring (LTCM). OBJECTIVES: This study evaluated the performance of risk models that use data from LTCM and patient claims for prediction of heart failure (HF) and ischemic stroke. METHODS: We retrospectively analyzed features extracted from up to 14 days of LTCM electrocardiogram (ECG) data linked to patient-level claims data for 320,974 Medicare beneficiaries who underwent ZioXT ambulatory monitoring. We created predictive models for HF hospitalization, stroke hospitalization, and new-onset HF within 1 year using LASSO Cox regression for variable selection among ambulatory ECG variables and components of the CHA2DS2-VASc score. RESULTS: A model that included components of the CHA2DS2-VASc and all ambulatory ECG variables had greater discrimination for HF hospitalization (C-statistic 0.85, 95% CI: 0.84-0.86) than the CHA2DS2-VASc (C-statistic 0.73, 95% CI: 0.72-0.74), but performed similarly to the CHA2DS2-VASc for prediction of stroke hospitalization (C-statistic 0.75 [95% CI: 0.74-0.77] vs 0.71 [95% CI: 0.70-0.72], respectively). Atrial fibrillation was associated with greater risk in the most predictive models (HF hospitalization, HR: 1.53 [95% CI: 1.35-1.72]; stroke hospitalization, HR: 1.58 [95% CI: 1.30-1.93]), and premature ventricular couplets were associated with greater risk of HF hospitalization (HR: 1.54, 95% CI: 1.43-1.65). CONCLUSIONS: The CHA2DS2-VASc performed modestly for prediction of stroke and HF events; predictive ability improved significantly with addition of LTCM ECG covariates. The presence of atrial fibrillation and ventricular ectopy on 14-day LTCM were strongly associated with HF events.

Duke Scholars

Published In

JACC Adv

DOI

EISSN

2772-963X

Publication Date

November 2024

Volume

3

Issue

11

Start / End Page

101340

Location

United States
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Schwennesen, H. T., Li, Z., Hammill, B. G., Clark, A. G., Pokorney, S., Hytopoulos, E., … Piccini, J. P. (2024). Performance of Ambulatory Electrocardiographic Data for Prediction of Stroke and Heart Failure Events. JACC Adv, 3(11), 101340. https://doi.org/10.1016/j.jacadv.2024.101340
Schwennesen, Hannah T., Zhen Li, Bradley G. Hammill, Amy G. Clark, Sean Pokorney, Evangelos Hytopoulos, Mintu P. Turakhia, Justin Cambra, and Jonathan P. Piccini. “Performance of Ambulatory Electrocardiographic Data for Prediction of Stroke and Heart Failure Events.JACC Adv 3, no. 11 (November 2024): 101340. https://doi.org/10.1016/j.jacadv.2024.101340.
Schwennesen HT, Li Z, Hammill BG, Clark AG, Pokorney S, Hytopoulos E, et al. Performance of Ambulatory Electrocardiographic Data for Prediction of Stroke and Heart Failure Events. JACC Adv. 2024 Nov;3(11):101340.
Schwennesen, Hannah T., et al. “Performance of Ambulatory Electrocardiographic Data for Prediction of Stroke and Heart Failure Events.JACC Adv, vol. 3, no. 11, Nov. 2024, p. 101340. Pubmed, doi:10.1016/j.jacadv.2024.101340.
Schwennesen HT, Li Z, Hammill BG, Clark AG, Pokorney S, Hytopoulos E, Turakhia MP, Cambra J, Piccini JP. Performance of Ambulatory Electrocardiographic Data for Prediction of Stroke and Heart Failure Events. JACC Adv. 2024 Nov;3(11):101340.

Published In

JACC Adv

DOI

EISSN

2772-963X

Publication Date

November 2024

Volume

3

Issue

11

Start / End Page

101340

Location

United States