Personalized Risk Identification and Management for Arrhythmias and Heart Failure by ECG and MRI

NCT ID: NCT01353131

Last Updated: 2018-11-06

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 162 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2010-05-31
• Study Completion Date: 2016-10-31

Brief Summary

Prevention of myocardial functional deterioration and sudden cardiac death among individuals of intermediate risk remains one of the most elusive frontiers of contemporary medicine. While most of these individuals are known to have had contact with the medical system, they are frequently not considered to be at high risk until far advanced along one or multiple disease processes leading to irreversible myocardial loss and electric instability. The goal of this proposal is to determine the prognostic power of combining specific measures of ventricular architecture, myocardial structure and electrical function for the early identification of individuals at risk to develop ventricular arrhythmias and progressive myocardial failure leading to severe cardiovascular outcomes and death.

Detailed Description

During C-TRIP Stage 1 we refined a risk stratification algorithm based on the electronic analysis of 69,088 routine 12-lead ECGs performed in a large medical institution during a 6 month period by combining previously established indices of abnormal repolarization (wide QRS-T angle) with validated measures of myocardial damage (Selvester QRS score). Among patients considered at risk, 4.9% had perished 18 months later and among the survivors those > 70 years of age or with LV ejection fraction ≤ 35%, or at a high risk of dying within 3 years from cancer, end stage cardiac, pulmonary, renal, immunologic or neurologic diseases, were excluded using a simple and reproducible screening arborescence based on the digital medical record. From the pool of remaining at risk patients derived from the application of the same screening methods in three other similarly large academic institutions, a sample of 1100 individuals will be recruited for further risk stratification as participants of the C-TRIP Stage 2 prospective study. For C-TRIP Stage 2, patients will undergo detailed phenotypic studies including contrast-enhanced cardiac MRI, ECG Holter recordings at rest and during a 6 minute walk, signal averaged ECG and biomarkers of inflammation, myocardial ischemia and stress, as well as indices of collagen synthesis and turnover. Patients will be followed for 3 years for the development of a combined clinical outcome including mortality (all cause, cardiac and sudden cardiac death) and hospitalization for non-fatal myocardial infarction, acute coronary syndromes, ventricular arrhythmias and heart failure. From the combination of selected phenotypic markers of poor outcome, a risk score will be developed and used for the design of prophylactic strategies aimed at curbing premature sudden cardiac death and end-stage cardiac disease among patients currently classified as having intermediate levels of risk.

Conditions

Inpatients and Outpatients With Routine 12-lead ECG

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

ECG Screening

1000 patients with moderate to high risk determined by stratification algorithm based on the electronic analysis of 69,088 routine 12-lead ECGs performed in a large medical institution during a 6 month period by combining previously established indices of abnormal repolarization (wide QRS-T angle) with validated measures of myocardial damage (Selvester QRS score) excluding those \> 70 years of age or with LV ejection fraction ≤ 35%, or at a high risk of dying within 3 years from cancer, end stage cardiac, pulmonary, renal, immunologic or neurologic diseases excluded on clinical data obtained through medical record.

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

• general hospital population with routine 12-lead ECG with abnormal repolarization (wide QRS-T angle>100°) with validated measures of myocardial damage (Selvester QRS score>5)

Exclusion Criteria

• LVEF <35%
• age>70 years
• eGFR<45mL/min
• no ICD or PM
• no high risk of dying within 3 years from cancer, end stage cardiac, pulmonary, immunologic or neurologic diseases

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 70 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Johns Hopkins University

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Joao AC Lima, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

Johns Hopkins University

Locations

Division of Cardiology, Johns Hopkins University School of Medicine

Baltimore, Maryland, United States

Countries

United States

References

Mewton N, Strauss DG, Rizzi P, Verrier RL, Liu CY, Tereshchenko LG, Nearing B, Volpe GJ, Marchlinski FE, Moxley J, Killian T, Wu KC, Spooner P, Lima JA. Screening for Cardiac Magnetic Resonance Scar Features by 12-Lead ECG, in Patients with Preserved Ejection Fraction. Ann Noninvasive Electrocardiol. 2016 Jan;21(1):49-59. doi: 10.1111/anec.12264.

Reference Type: DERIVED

PMID: 26806840 (View on PubMed)

Murthy S, Rizzi P, Mewton N, Strauss DG, Liu CY, Volpe GJ, Marchlinski FE, Spooner P, Berger RD, Kellman P, Lima JA, Tereshchenko LG. Number of P-wave fragmentations on P-SAECG correlates with infiltrated atrial fat. Ann Noninvasive Electrocardiol. 2014 Mar;19(2):114-21. doi: 10.1111/anec.12084. Epub 2013 Sep 9.

Reference Type: DERIVED

PMID: 24620844 (View on PubMed)

Tereshchenko LG, Rizzi P, Mewton N, Volpe GJ, Murthy S, Strauss DG, Liu CY, Marchlinski FE, Spooner P, Berger RD, Kellman P, Lima JA. Infiltrated atrial fat characterizes underlying atrial fibrillation substrate in patients at risk as defined by the ARIC atrial fibrillation risk score. Int J Cardiol. 2014 Mar 1;172(1):196-201. doi: 10.1016/j.ijcard.2014.01.012. Epub 2014 Jan 22.

Reference Type: DERIVED

PMID: 24485635 (View on PubMed)

Other Identifiers

NA_00031964

Identifier Type: -

Identifier Source: org_study_id