See the published version of this preprint at BMC Cardiovascular Disorders.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
Research article
Larisa G Tereshchenko
Oregon Health and Science University
Corresponding Author
ORCiD: https://orcid.org/0000-0002-6976-1313
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background—The risk of sudden cardiac death (SCD) is known to be dynamic. However, an accuracy of a dynamic SCD prediction is unknown. We aimed to measure dynamic predictive accuracy of ECG biomarkers of SCD and competing non-SCD. Methods—Atherosclerosis Risk In Community study participants with analyzable ECGs in sinus rhythm were included (n=15,716; 55% female, 73% white, age 54.2±5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity and traditional ECG metrics were measured. Adjudicated SCD was the primary outcome; non-SCD was competing outcome. Time-dependent area under the (receiver operating characteristic) curve (AUC) analysis was performed to assess prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years, using survival analysis framework. Reclassification improvement as compared to clinical risk factors (age, sex, race, diabetes, hypertension, coronary heart disease, stroke) was measured. Results—Over a median 24.4 y follow-up, there were 577 SCDs (incidence 1.76 (95%CI 1.63-1.91)/1,000 person-years), and 829 non-SCDs 2.55 (95%CI 2.37-2.71). Short-term, spatial ventricular gradient (SVG) elevation predicted SCD (AUC 0.706; 95%CI 0.526-0.886), but not a non-SCD. Short-term, upward and more likely forward–directed SVG vector predicted SCD, whereas backward-directed SVG predicted non-SCD. Within the first 3 months after ECG recording, only SVG azimuth improved reclassification of the risk beyond clinical risk factors (18% SCD events reclassified up). Long-term, backward–directed SVG predicted both SCD and non-SCD. Conclusion—Short-term predictors of SCD, non-SCD, and biomarkers of long-term SCD risk differed, reflecting differences in transient vs. persistent SCD substrates.
Keywords
Electrocardiography, sudden cardiac death, vectorcardiography, dynamic prediction, global electrical heterogeneity
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
This is a list of supplementary files associated with this preprint. Click to download.
Loading...
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Cardiovascular Disorders.
No community comments so far
Editorial decision: Accept
On 23 Oct, 2019
Editor assigned
On 21 Oct, 2019
Submission checks complete
On 20 Oct, 2019
Editor invited
On 20 Oct, 2019
No comments provided
Editorial decision: Minor revision
On 18 Oct, 2019
Editor assigned
On 16 Oct, 2019
Submission checks complete
On 15 Oct, 2019
Editor invited
On 15 Oct, 2019
Version 1
Posted 19 Jun, 2019
No comments provided
Editorial decision: Major revision
On 07 Oct, 2019
Review #2 received
Received 30 Sep, 2019
Reviewer #2 agreed
On 26 Jul, 2019
Review #1 received
Received 25 Jun, 2019
Reviewer #1 agreed
On 21 Jun, 2019
Reviewers invited
Invitations sent on 20 Jun, 2019
Submission checks complete
On 18 Jun, 2019
Editor invited
On 10 Jun, 2019
Editor assigned
On 10 Jun, 2019
First submitted
On 07 Jun, 2019
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cardiac & Cardiovascular Systems
Learn more about our company.
A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
See the published version of this preprint at BMC Cardiovascular Disorders.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Larisa G Tereshchenko
Oregon Health and Science University
Corresponding Author
ORCiD: https://orcid.org/0000-0002-6976-1313
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Cardiovascular Disorders.
No community comments so far
Editorial decision: Accept
On 23 Oct, 2019
Editor assigned
On 21 Oct, 2019
Submission checks complete
On 20 Oct, 2019
Editor invited
On 20 Oct, 2019
No comments provided
Editorial decision: Minor revision
On 18 Oct, 2019
Editor assigned
On 16 Oct, 2019
Submission checks complete
On 15 Oct, 2019
Editor invited
On 15 Oct, 2019
Version 1
Posted 19 Jun, 2019
No comments provided
Editorial decision: Major revision
On 07 Oct, 2019
Review #2 received
Received 30 Sep, 2019
Reviewer #2 agreed
On 26 Jul, 2019
Review #1 received
Received 25 Jun, 2019
Reviewer #1 agreed
On 21 Jun, 2019
Reviewers invited
Invitations sent on 20 Jun, 2019
Submission checks complete
On 18 Jun, 2019
Editor invited
On 10 Jun, 2019
Editor assigned
On 10 Jun, 2019
First submitted
On 07 Jun, 2019
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cardiac & Cardiovascular Systems
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BMC Cardiovascular Disorders.
Background—The risk of sudden cardiac death (SCD) is known to be dynamic. However, an accuracy of a dynamic SCD prediction is unknown. We aimed to measure dynamic predictive accuracy of ECG biomarkers of SCD and competing non-SCD. Methods—Atherosclerosis Risk In Community study participants with analyzable ECGs in sinus rhythm were included (n=15,716; 55% female, 73% white, age 54.2±5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity and traditional ECG metrics were measured. Adjudicated SCD was the primary outcome; non-SCD was competing outcome. Time-dependent area under the (receiver operating characteristic) curve (AUC) analysis was performed to assess prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years, using survival analysis framework. Reclassification improvement as compared to clinical risk factors (age, sex, race, diabetes, hypertension, coronary heart disease, stroke) was measured. Results—Over a median 24.4 y follow-up, there were 577 SCDs (incidence 1.76 (95%CI 1.63-1.91)/1,000 person-years), and 829 non-SCDs 2.55 (95%CI 2.37-2.71). Short-term, spatial ventricular gradient (SVG) elevation predicted SCD (AUC 0.706; 95%CI 0.526-0.886), but not a non-SCD. Short-term, upward and more likely forward–directed SVG vector predicted SCD, whereas backward-directed SVG predicted non-SCD. Within the first 3 months after ECG recording, only SVG azimuth improved reclassification of the risk beyond clinical risk factors (18% SCD events reclassified up). Long-term, backward–directed SVG predicted both SCD and non-SCD. Conclusion—Short-term predictors of SCD, non-SCD, and biomarkers of long-term SCD risk differed, reflecting differences in transient vs. persistent SCD substrates.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
This is a list of supplementary files associated with this preprint. Click to download.
Loading...