Predicting Coarctation Severity with MRI
Author Information
Author(s): Muzzarelli Stefano, Meadows Jeffery J, Ordovas Karen Gomes, Hope Michael D, Higgins Charles B, Nielsen James C, Geva Tal, Meadows Alison Knauth
Primary Institution: University Hospital Basel
Hypothesis
Can a cardiovascular magnetic resonance (CMR) based tree algorithm predict coarctation transcatheter systolic pressure gradient > 20mmHg?
Conclusion
CMR derived minimal aortic cross-sectional area and heart rate-corrected flow deceleration time in the descending aorta can predict CoA gradient > 20 mmHg.
Supporting Evidence
- Severe CoA was present in 48 patients (60%).
- Indexed minimal aortic cross-sectional area and heart rate-corrected flow deceleration time were independent predictors of CoA gradient > 20mmHg.
- A clinical prediction tree combining these variables reached a sensitivity of 90% and specificity of 76%.
Takeaway
Doctors can use MRI measurements to help figure out if a patient has a serious heart condition called coarctation.
Methodology
Retrospective review of 79 patients who underwent CMR and cardiac catheterization, followed by logistic regression and recursive partitioning to develop a prediction tree.
Potential Biases
Potential bias due to retrospective nature and reliance on existing data.
Limitations
The algorithm was initially derived from a single institution and may not be generalizable without further validation.
Participant Demographics
Patients from two institutions: Children’s Hospital Boston (n=30) and UCSF (n=49).
Statistical Information
P-Value
p<0.01
Confidence Interval
95%-CI: 0.47-0.85 for aortic area; 95%-CI: 1.08-1.38 for flow deceleration time.
Statistical Significance
p<0.01
Digital Object Identifier (DOI)
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