• Journal of Cardiovascular Imaging
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• v.30 no.4
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• pp.292-304
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• 2022

BACKGROUND: Calcium is a determinant of paravalvular leakage (PVL) after transcatheter aortic valve implantation (TAVI). This is based on a fixed contrast attenuation value while X-ray attenuation is patient-dependent and without considering frame expansion and PVL location. We examined the role of calcium in (site-specific) PVL after TAVI using a patient-specific contrast attenuation coefficient combined with frame expansion. METHODS: 57 patients were included with baseline CT, post-TAVI transthoracic echocardiography and rotational angiography (R-angio). Calcium load was assessed using a patient-specific contrast attenuation coefficient. Baseline CT and post-TAVI R-angio were fused to assess frame expansion. PVL was assessed by a core lab. RESULTS: Overall, the highest calcium load was at the non-coronary-cusp-region (NCR, 436 mm³) vs. the right-coronary-cusp-region (RCR, 233 mm³) and the left-coronary-cusp-region (LCR, 244 mm³), p < 0.001. Calcium load was higher in patients with vs. without PVL (1,137 vs. 742 mm³, p = 0.012) and was an independent predictor of PVL (odds ratio, 4.83, p = 0.004). PVL was seen most often in the LCR (39% vs. 21% [RCR] and 19% [NCR]). The degree of frame expansion was 71% at the NCR, 70% at the RCR and 74% at the LCR without difference between patients with or without PVL. CONCLUSIONS: Calcium load was higher in patients with PVL and was an independent predictor of PVL. While calcium was predominantly seen at the NCR, PVL was most often at the LCR. These findings indicate that in addition to calcium, specific anatomic features play a role in PVL after TAVI.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.29-38
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• 2024

After Transcatheter Aortic Valve Replacement (TAVR), comprehensive management of complications, including the need for Permanent Pacemaker Implantation (PPI), is crucial, increasing the demand for accurate prediction models. Departing from traditional image-based methods, this study developed an optimal PPI prediction model based on ECG data using the XGBoost algorithm. Focusing on ECG signals like DeltaPR and DeltaQRS as key indicators, the model effectively identifies the correlation between conduction disorders and PPI needs, achieving superior performance with an AUC of 0.91. Validated using data from two hospitals, it demonstrated a high similarity rate of 95.28% in predicting PPI from ECG characteristics. This confirms the model's effective applicability across diverse hospital data, establishing a significant advancement in the development of reliable and practical PPI prediction models with reduced dependence on human intervention and costly medical imaging.

• Korean Journal of Radiology
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• v.21 no.11
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• pp.1230-1238
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• 2020

Objective: We aimed to assess the effects of remote ischemic pre-conditioning (RIPC) on the incidence of contrast-induced nephropathy (CIN) after an intravenous (IV) or intra-arterial injection of contrast medium (CM) in patient and control groups. Materials and Methods: This prospective, randomized, single-blinded, controlled trial included 26 patients who were hospitalized for the evaluation of the feasibility of transcatheter aortic valve implantation and underwent investigations including contrast-enhanced computed tomography (CT), with Mehran risk scores greater than or equal to six. All the patients underwent four cycles of five minute-blood pressure cuff inflation followed by five minutes of total deflation. In the RIPC group (n = 13), the cuff was inflated to 50 mm Hg above the patient's systolic blood pressure (SBP); in the control group (n = 13), it was inflated to 10 mm Hg below the patient's SBP. The primary endpoint was the occurrence of CIN. Additionally, variation in the serum levels of cystatin C was assessed. Results: One case of CIN was observed in the control group, whereas no cases were detected in the RIPC group (p = 0.48, analysis of 25 patients). Mean creatinine values at the baseline, 24 hours after injection of CM, and 48 hours after injection of CM were 88 ± 32 μmol/L, 91 ± 28 μmol/L and 82 ± 29 μmol/L, respectively (p = 0.73) in the RIPC group, whereas in the control group, they were 100 ± 36 μmol/L, 110 ± 36 μmol/L, and 105 ± 34 μmol/L, respectively (p = 0.78). Cystatin C values (median [Q1, Q3]) at the baseline, 24 hours after injection of CM, and 48 hours after injection of CM were 1.10 [1.08, 1.18] mg/L, 1.17 [0.97, 1.35] mg/L, and 1.12 [0.99, 1.24] mg/L, respectively (p = 0.88) in the RIPC group, whereas they were 1.11 [0.97, 1.28] mg/L, 1.13 [1.08, 1.25] mg/L, and 1.16 [1.03, 1.31] mg/L, respectively (p = 0.93), in the control group. Conclusion: The risk of CIN after an IV injection of CM is very low in patients with Mehran risk score greater than or equal to six and even in the patients who are unable to receive preventive hyperhydration. Hence, the Mehran risk score may not be an appropriate method for the estimation of the risk of CIN after IV CM injection.