Intracardiac echocardiographically guided permanent pacemaker implantation is a feasible imaging tool with comparable procedural efficacy and safety

Background

Amongst cardiovascular interventions, pacemaker implantation procedure is one of the most hazardous in terms of radiation exposure due to its proximity and unprotected radiation exposure. In order to reduce radiation hazards, alternative imaging tool to guide pacemaker implantation should be sought. The aim of this study is to investigate the feasibility, efficacy, and safety of intracardiac echocardiographically (ICE) guided pacemaker implantation.

Methods

We retrospectively investigated pacemaker implantation with ICE guidance. ICE catheter was placed in right atrium (RA). Right ventricular (RV) lead was placed in RV apex within home view (low RA, 2-4 O'clock). Then RA lead was placed in RA appendage within mid RA 1-2 O'clock view. Fluoroscopy was used only for verifying lead redundancy (2 or 3 second duration before pocket closure). Other procedure steps were similarly performed as in conventional fluoroscopic method. Radiation dosage, patient safety, total procedure time, and lead parameters were assessed and compared.

Results

From June 2013 to March 2021, a total of 270 patients underwent pacemaker implantation either with ICE or with fluoroscopy. Amongst them, ICE guided implantation was attempted in 35 patients. In order to exclude potential bias caused by the operator's learning curve, we excluded early 5 cases out of ICE group. Radiation exposure was markedly decreased within ICE group (2.3±4.4 Gy cm2 in ICE group vs. 27.2±50.5 Gy cm2 in fluoroscopy group, P<0.001). The total procedure time and complication rate showed no significant difference between groups. In ICE group, atrial lead parameters were better than those of fluoroscopy group (impedance 454±57 Ω vs. 533±125 Ω, P<0.001).

Conclusion

In 30 patients with ICE guided pacemaker implantation, radiation exposure was markedly decreased without any trade-offs in terms of patients' safety and procedural success. Furthermore, operation team members' physical stress reduction also might be potentially guaranteed.

Funding Acknowledgement

Type of funding sources: None.

Net clinical benefit of NOAC in Korean atrial fibrillation patients with low to intermediate stroke risk

Background

The balance of stroke risk reduction and potential hemorrhagic risk associated with anti-thrombotic treatment (ATT) remain unclear in Korean atrial fibrillation (AF) patients with low to intermediate stroke risk, defined as non-gender CHA2DS2-VASc score 0–1.

Purpose

The net clinical benefit (NCB) analysis of ATT may be helpful to guide stroke prevention strategy in AF patients with non-gender CHA2DS2-VASc score 0–1.

Methods

This Korean multi-center cohort study retrospectively evaluated the clinical outcomes with single antiplatelet (SAPT), vitamin K antagonist (VKA), and non-vitamin K antagonist oral anticoagulant (NOAC) in non-gender CHA2DS2-VASc score 0–1 and further stratified by biomarker-based ABCD score (Age [≥60 years], B-type natriuretic peptide [BNP] or N-terminal pro-BNP [≥300 pg/ml], Creatinine clearance [<50 ml/min/1.73 m2], and Dimension of the left atrium [≥45 mm]). The primary outcome was the NCB of ATT including thromboembolic and major bleeding events.

Results

We included 2465 patients (56.2±9.5 years; female, 665 [27.0%]) followed-up for 4.0±2.8 years, of whom 661 (26.8%) were treated with SAPT; 423 (17.2%) with VKA; and 1040 (42.2%) with NOAC. In comparison with no treatment, only NOAC demonstrated a positive tendency for stroke prevention (NOAC, NCB 0.47, 95% confidence interval [CI] −0.40 to 2.10; SAPT, NCB −0.31, 95% CI −1.48 to 1.40; and VKA, NCB −1.26, 95% CI −2.97 to 0.67). With detailed risk stratification with ABCD score, NOAC showed a significant NCB for stroke prevention compared with SAPT and VKA (SAPT vs. NOAC, NCB 1.6, 95% CI 0.26–3.50; VKA vs. NOAC, NCB 1.96, 95% CI 0.47–4.16) in patients with ABCD score ≥1. ATT failed to show NCB in patients with truly low stroke risk defined as ABCD score=0.

Conclusion

Korean AF cohort with low to intermediate stroke risk indicates that, in comparison with no ATT, only ATT with NOAC showed marginal NCB. With further risk stratification by ABCD score, NOAC showed significant advantages over other ATTs (VKA or SAPT) in patients with ABCD ≥1.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Korean Disease Control and Prevention Agency

External validation of the biomarker based ABCD score in atrial fibrillation patients with a non gender CHA2DS2 VASc score 0 to 1, A Korean multicenter retrospective cohort

Background

Patients with low to intermediate risk atrial fibrillation (AF), defined as non-gender CHA2DS2-VASc score of 0–1, are still at risk of stroke. This study verified the usefulness of ABCD score (Age [≥60 years], B-type natriuretic peptide [BNP] or N-terminal pro-BNP [≥300 pg/ml], Creatinine clearance [<50 ml/min/1.73 m2], and Dimension of the left atrium [≥45 mm]) for stroke risk stratification in non-gender CHA2DS2-VASc score 0–1.

Methods

This multi-center cohort study retrospectively analyzed AF patients with non-gender CHA2DS2-VASc score 0–1. The primary endpoint was the incidence of stroke with or without anti-thrombotic treatment (ATT). An ABCD score was also validated.

Results

Overall, 2694 patients (56.3±9.5 years; female, 726 [26.9%]) were followed-up for 4.0±2.8 years. The overall stroke rate was 0.84/100 person-years (P-Y), stratified as follows: 0.46/100P-Y for an ABCD score 0; 1.02/100P-Y for an ABCD score≥1. The ABCD score was superior to the non-gender CHA2DS2-VASc score in stroke risk stratification (C-index=0.618, P=0.015; net reclassification improvement=0.576, P=0.040; integrated differential improvement=0.033, P=0.066). ATT was prescribed in 2353 patients (86.5%), and the stroke rate was significantly lower in patients receiving non-vitamin K antagonist oral anticoagulant (NOAC) therapy and an ABCD score≥1 than in those without ATT (0.44/100P-Y versus 1.55/100 P-Y; hazard ratio=0.26, 95% confidence interval 0.11–0.63, P=0.003).

Conclusion

The biomarker-based ABCD score demonstrated improved stroke risk stratification in AF patients with non-gender CHA2DS2-VASc score 0–1. Furthermore, NOAC with an ABCD score≥1 was associated with significantly lower stroke rate in AF patients with a non-gender CHA2DS2-VASc score 0–1.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Korean Disease Control and Prevention Agency

Machine Learning-Aided Chronic Kidney Disease Diagnosis Based on Ultrasound Imaging Integrated with Computer-Extracted Measurable Features

Although ultrasound plays an important role in the diagnosis of chronic kidney disease (CKD), image interpretation requires extensive training. High operator variability and limited image quality control of ultrasound images have made the application of computer-aided diagnosis (CAD) challenging. This study assessed the effect of integrating computer-extracted measurable features with the convolutional neural network (CNN) on the ultrasound image CAD accuracy of CKD. Ultrasound images from patients who visited Severance Hospital and Gangnam Severance Hospital in South Korea between 2011 and 2018 were used. A Mask regional CNN model was used for organ segmentation and measurable feature extraction. Data on kidney length and kidney-to-liver echogenicity ratio were extracted. The ResNet18 model classified kidney ultrasound images into CKD and non-CKD. Experiments were conducted with and without the input of the measurable feature data. The performance of each model was evaluated using the area under the receiver operating characteristic curve (AUROC). A total of 909 patients (mean age, 51.4 ± 19.3 years; 414 [49.5%] men and 495 [54.5%] women) were included in the study. The average AUROC from the model trained using ultrasound images achieved a level of 0.81. Image training with the integration of automatically extracted kidney length and echogenicity features revealed an improved average AUROC of 0.88. This value further increased to 0.91 when the clinical information of underlying diabetes was also included in the model trained with CNN and measurable features. The automated step-wise machine learning-aided model segmented, measured, and classified the kidney ultrasound images with high performance. The integration of computer-extracted measurable features into the machine learning model may improve CKD classification.