Assessing heart risks in patients with left bundle branch block using echocardiography
Prediction of Heart-failure and Mortality by Echocardiographic Parameters and Machine Learning in Individuals With Left Bundle Branch Block
University Hospital of North Norway · NCT04293471
This study is trying to see if new heart imaging techniques can help doctors figure out the risks for patients with left bundle branch block and identify who might benefit from a specific heart treatment.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 2000 (estimated) |
| Ages | 18 Years to 100 Years |
| Sex | All |
| Sponsor | University Hospital of North Norway (other) |
| Locations | 1 site (Tromsø, Troms) |
| Trial ID | NCT04293471 on ClinicalTrials.gov |
What this trial studies
This observational study focuses on patients with left bundle branch block (LBBB), a condition that can lead to heart failure and increased mortality. By utilizing machine learning techniques, the study aims to identify echocardiographic parameters and ECG characteristics that can help in developing individual risk assessments for these patients. The research will explore how new echocardiographic measures, particularly strain imaging and regional myocardial work, can provide insights into the effects of LBBB on heart function. The ultimate goal is to better define which patients may benefit from cardiac resynchronization therapy (CRT).
Who should consider this trial
Good fit: Ideal candidates for this study are patients with left bundle branch block who have specific echocardiographic findings and may have previously undergone cardiac resynchronization therapy.
Not a fit: Patients with typical right bundle branch block or those with non-cardiovascular comorbidities that significantly reduce life expectancy may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could lead to improved risk stratification and treatment outcomes for patients with left bundle branch block.
How similar studies have performed: Other studies have shown promise in using echocardiographic parameters and machine learning for risk assessment in cardiac conditions, suggesting a potential for success in this approach.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * QRS complex \>130 ms and R-wave duration in * V6 \>70 ms * ventricular pacing\>50% * Previously implanted cardiac resynchronisation therapy (CRT) Exclusion Criteria: * Typical right bundle branch block. * No ability to give informed consent, * non-cardiovascular co-mobidities with reduced life-expectancy \< 1 year * patients with complex congenital heart disease.
Where this trial is running
Tromsø, Troms
- University Hospital North Norway — Tromsø, Troms, Norway (RECRUITING)
Study contacts
- Principal investigator: Assami Rösner, MD,PhD — University Hospital North Norway
- Study coordinator: Assami Rösner, MD,PhD
- Email: assami.rosner@unn.no
- Phone: 04795990071
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions: Left Bundle-Branch Block, Left bundle branch block, strain-imaging, myocardial work assessment, machine learning