Transcatheter Patent Ductus Arteriosus Closure in Premature Infants: Comparison of Echocardiogram and Angiogram Measurements.
Bassel Mohmmad NijresMohamed KhallafAdrianne Rahde BischoffKaitlin CarrUmang GuptaPatrick J McNamaraJimmy WindsorOsamah AldossPublished in: Pediatric cardiology (2024)
Transcatheter patent ductus arteriosus (PDA) closure (TCPC) utilizing transthoracic echocardiogram (TTE) as the sole imaging guide could simplify care. This single-center study compares PDA dimensions obtained from the TTE and angiogram images of patients who underwent attempted TCPC at Stead Family Children's Hospital from 10/01/2019 to 10/31/2020. Blinded investigators measured these dimensions solely for this study and had no impact on clinical care. Also, a hypothetical Piccolo device size was chosen based on the TTE dimensions and another on the angiographic dimensions, and then the correlation was analyzed. Sixty-two patients underwent TCPC attempts. TTE tends to overestimate the PDA narrowest dimension and underestimate the PDA length and aortic end dimension. Linear regression analysis revealed a weak correlation between the length and aortic diameter (R = 0.37 and 0.21, respectively). A modest correlation was observed for the smallest dimension without color Doppler (R = 0.57) and with color Doppler, which was utilized when needed (R = 0.6). Bland-Altman analysis revealed a smaller mean difference between the TTE and angiogram measurements of the narrowest diameter without color Doppler (0.4 mm) and with color Doppler (used as needed) (0.4 mm). However, the mean difference is larger for the aortic end (- 1.64 mm) and the length (- 1.73 mm). TTE accurately predicted the Piccolo device size in 43 (72%) patients and overestimated the size in 17 (28%) patients to the next size. Our findings should be verified with further studies, and additional development of protocols is needed to use TTE to guide TCPC without fluoroscopy.
Keyphrases
- end stage renal disease
- ejection fraction
- newly diagnosed
- healthcare
- prognostic factors
- palliative care
- aortic valve
- clinical trial
- emergency department
- machine learning
- heart failure
- patient reported outcomes
- coronary artery
- blood flow
- mass spectrometry
- convolutional neural network
- optical coherence tomography
- neural network
- health insurance