Association between pulmonary artery pulsatility and mortality after implantation of left ventricular assist device.

AIMS: Right ventricular failure after left ventricular assist device (LVAD) implantation is a major concern that remains challenging to predict. We sought to investigate the relationship between preoperative pulmonary artery pulsatility index (PAPi) and mortality after LVAD implantation. METHODS AND RESULTS: A retrospective analysis of the ASSIST-ICD multicentre registry allowed the assessment of PAPi before LVAD according to the formula [(systolic pulmonary artery pressure - diastolic pulmonary artery pressure)/central venous pressure]. The primary endpoint was survival at 3 months, according to the threshold value of PAPi determined by the receiver operating characteristic (ROC) curve. A multivariate analysis including demographic, echographic, haemodynamic, and biological variables was performed to identify predictive factors for 2 year mortality. One hundred seventeen patients were included from 2007 to 2021. The mean age was 58.45 years (±13.16), with 15.4% of women (sex ratio 5.5). A total of 53.4% were implanted as bridge to transplant and 43.1% as destination therapy. Post-operative right ventricular failure was observed in 57 patients (48.7%), with no significant difference between survivors and non-survivors at 1 month (odds ratio 1.59, P = 0.30). The median PAPi for the whole study population was 2.83 [interquartile range 1.63-4.69]. The threshold value of PAPi determined by the ROC curve was 2.84. Patients with PAPi ≥ 2.84 had a higher survival rate at 3 months [PAPi < 2.84: 58.1% [46.3-72.8%] vs. PAPi ≥ 2.84: 89.1% [81.1-97.7%], hazard ratio (HR) 0.08 [0.02-0.28], P < 0.01], with no significant difference after 3 months (HR 0.67 [0.17-2.67], P = 0.57). Other predictors of 2 year mortality were systemic hypertension (HR 4.22 [1.49-11.97], P < 0.01) and diabetes mellitus (HR 4.90 [1.83-13.14], P < 0.01). LVAD implantation as bridge to transplant (HR 0.18 [0.04-0.74], P = 0.02) and heart transplantation (HR 0.02 [0.00-0.18], P < 0.01) were associated with a higher survival rate at 2 years. CONCLUSIONS: Preoperative PAPi < 2.84 was associated with a higher risk of early mortality after LVAD implantation without impacting 2 year outcomes among survivors.

Transcatheter pulmonary valve replacement after pulmonary homograft dysfunction.

Pulmonary homograft dysfunction is challenging to treat in patients with a previous Ross procedure, and results in significant morbidity and mortality in case of reoperation. We report the case of a patient with early severe pulmonary homograft stenosis 18 months after a Ross procedure and successful management using transcatheter pulmonary valve replacement.

Should the Vasoactive Inotropic Score be a Determinant for Early Initiation of VA ECMO in Postcardiotomy Cardiogenic Shock?

OBJECTIVES: The authors investigated the role of early venoarterial extracorporeal membrane oxygenation (VA ECMO) implantation in patients with postcardiotomy cardiogenic shock (PCS) on mortality and morbidity when integrating vasoactive-inotropic score (VIS) and type of catecholamine support. DESIGN: A retrospective, multicenter, observational study with propensity-weight matching. SETTING: Four university-affiliated intensive care units. PARTICIPANTS: Patients with PCS in the operating room. INTERVENTIONS: Early VA ECMO support. MEASUREMENTS AND MAIN RESULTS: Of 2,742 patients screened during the study period, 424 (16%) patients were treated with inotropic drugs, and 75 (3%) patients were supported by VA ECMO in the operating room. Patients supported by VA ECMO had a higher use of vasopressor and inotropic drugs, with a higher VIS score. After propensity matching (integrating VIS and catecholamines type), mortality (56% v 20%, p < 0.001) and morbidity (cardiac, renal, transfusion) were higher in patients supported by VA ECMO than in a matched control group. CONCLUSIONS: When matching integrated the pre-ECMO VIS and the type of catecholamines, VA ECMO remained associated with high mortality and morbidity, suggesting that VIS alone should not be used as a main determinant of VA ECMO implantation.

Comparative Evaluation of Two Paclitaxel-Coated Stents in an Experimental Setting.

INTRODUCTION: Unlike paclitaxel-coated balloons, pre-clinical data comparing different paclitaxel-coated stents (PCSs) are weak. The study objective was to compare the features of the 2 main PCSs: Eluvia® (Boston Scientific, Marlborough, MA) versus ZilverPTX® (Cook Medical, Bloomington, IN). METHOD: Analysis was carried out on 12 pigs divided into 2 groups: Eluvia® (n=6) and ZilverPTX® (n=6). The pigs received the PCS corresponding to their group in each external iliac artery and were paired one by one, to examine 6 different post-implantation timepoints: after 30 minutes, 6 hours, 24 hours, 3 days, 7 days, and 14 days. The paclitaxel concentration measurements and the histological analysis were carried out under blind testing on the plasma, arterial, lymph node, and muscle samples. A linear regression model and Wilcoxon Mann-Whitney test were used to study the variables. RESULTS: The plasma paclitaxel rate decrease over 24 hours after PCS implantation was significantly different between the two groups, expressed by the correlation coefficient 0.19 (0.14-0.23; p<0.001) with an undetectable concentration at the 10th hour for Eluvia® versus 3 days for ZilverPTX®. Significantly higher paclitaxel concentrations with ZilverPTX® PCS were observed in muscle samples at each timepoint: extensor digitorum brevis 3.2 (1.17-5.23; p=0.005), biceps femoris 4.27 (2.27-6.26; p<0.001), semi-tendinosus 3.79 (1.85-5.73; p=0.001), tibialis anterior 3.0 (1.37-4.64; p=0.001), and in the femoral nodes 2.27±1.74 ng/g versus 0.14±0.13 ng/g (p<0.001). Histological analysis revealed a trend for more marked intimal inflammation in the arteries stented with ZilverPTX® (p=0.063), especially after the 7th and 14th days. CONCLUSION: Such a difference in the concentration of paclitaxel in the plasma, muscles, and lymph nodes between the two stents was higher than expected based on differences in device design. The clinical consequences of these results remain to be elucidated, particularly regarding the concerning presence of paclitaxel in muscles and adjacent lymph nodes. CLINICAL IMPACT: This experimental study compares 2 paclitaxel-coated stents. It demonstrates that differences in stent designs and drug features (coatings and concentrations) translate into differences in terms of concentrations of paclitaxel in the plasma, muscles, and lymph nodes. Our results favor the Eluvia® stent over the ZilverPTX® stent, although more studies are required to confirm this conclusion.

Tracking of Blood Vessels Motion from 4D-flow MRI Data.

This paper presents a novel approach to track objects from 4D-flow MRI data. A salient feature of the proposed method is that it fully exploits the geometrical and dynamical nature of the information provided by this imaging modality. The underlying idea consists in formulating the tracking problem as a data assimilation problem, in which both position and velocity observations are extracted from the 4D-flow MRI data series. Optimal state estimation is then performed in a sequential fashion via Kalman filtering. The capabilities of the method are extensively assessed in a numerical study involving synthetic and clinical data.

Computer-aided shape features extraction and regression models for predicting the ascending aortic aneurysm growth rate.

OBJECTIVE: ascending aortic aneurysm growth prediction is still challenging in clinics. In this study, we evaluate and compare the ability of local and global shape features to predict the ascending aortic aneurysm growth. MATERIAL AND METHODS: 70 patients with aneurysm, for which two 3D acquisitions were available, are included. Following segmentation, three local shape features are computed: (1) the ratio between maximum diameter and length of the ascending aorta centerline, (2) the ratio between the length of external and internal lines on the ascending aorta and (3) the tortuosity of the ascending tract. By exploiting longitudinal data, the aneurysm growth rate is derived. Using radial basis function mesh morphing, iso-topological surface meshes are created. Statistical shape analysis is performed through unsupervised principal component analysis (PCA) and supervised partial least squares (PLS). Two types of global shape features are identified: three PCA-derived and three PLS-based shape modes. Three regression models are set for growth prediction: two based on gaussian support vector machine using local and PCA-derived global shape features; the third is a PLS linear regression model based on the related global shape features. The prediction results are assessed and the aortic shapes most prone to growth are identified. RESULTS: the prediction root mean square error from leave-one-out cross-validation is: 0.112 mm/month, 0.083 mm/month and 0.066 mm/month for local, PCA-based and PLS-derived shape features, respectively. Aneurysms close to the root with a large initial diameter report faster growth. CONCLUSION: global shape features might provide an important contribution for predicting the aneurysm growth.

Segmentation of 4D Flow MRI: Comparison between 3D Deep Learning and Velocity-Based Level Sets.

A thoracic aortic aneurysm is an abnormal dilatation of the aorta that can progress and lead to rupture. The decision to conduct surgery is made by considering the maximum diameter, but it is now well known that this metric alone is not completely reliable. The advent of 4D flow magnetic resonance imaging has allowed for the calculation of new biomarkers for the study of aortic diseases, such as wall shear stress. However, the calculation of these biomarkers requires the precise segmentation of the aorta during all phases of the cardiac cycle. The objective of this work was to compare two different methods for automatically segmenting the thoracic aorta in the systolic phase using 4D flow MRI. The first method is based on a level set framework and uses the velocity field in addition to 3D phase contrast magnetic resonance imaging. The second method is a U-Net-like approach that is only applied to magnitude images from 4D flow MRI. The used dataset was composed of 36 exams from different patients, with ground truth data for the systolic phase of the cardiac cycle. The comparison was performed based on selected metrics, such as the Dice similarity coefficient (DSC) and Hausdorf distance (HD), for the whole aorta and also three aortic regions. Wall shear stress was also assessed and the maximum wall shear stress values were used for comparison. The U-Net-based approach provided statistically better results for the 3D segmentation of the aorta, with a DSC of 0.92 ± 0.02 vs. 0.86 ± 0.5 and an HD of 21.49 ± 24.8 mm vs. 35.79 ± 31.33 mm for the whole aorta. The absolute difference between the wall shear stress and ground truth slightly favored the level set method, but not significantly (0.754 ± 1.07 Pa vs. 0.737 ± 0.79 Pa). The results showed that the deep learning-based method should be considered for the segmentation of all time steps in order to evaluate biomarkers based on 4D flow MRI.

Calibration of the Mechanical Boundary Conditions for a Patient-Specific Thoracic Aorta Model Including the Heart Motion Effect.

OBJECTIVE: We propose a procedure for calibrating 4 parameters governing the mechanical boundary conditions (BCs) of a thoracic aorta (TA) model derived from one patient with ascending aortic aneurysm. The BCs reproduce the visco-elastic structural support provided by the soft tissue and the spine and allow for the inclusion of the heart motion effect. METHODS: We first segment the TA from magnetic resonance imaging (MRI) angiography and derive the heart motion by tracking the aortic annulus from cine-MRI. A rigid-wall fluid-dynamic simulation is performed to derive the time-varying wall pressure field. We build the finite element model considering patient-specific material properties and imposing the derived pressure field and the motion at the annulus boundary. The calibration, which involves the zero-pressure state computation, is based on purely structural simulations. After obtaining the vessel boundaries from the cine-MRI sequences, an iterative procedure is performed to minimize the distance between them and the corresponding boundaries derived from the deformed structural model. A strongly-coupled fluid-structure interaction (FSI) analysis is finally performed with the tuned parameters and compared to the purely structural simulation. RESULTS AND CONCLUSION: The calibration with structural simulations allows to reduce maximum and mean distances between image-derived and simulation-derived boundaries from 8.64 mm to 6.37 mm and from 2.24 mm to 1.83 mm, respectively. The maximum root mean square error between the deformed structural and FSI surface meshes is 0.19 mm. This procedure may prove crucial for increasing the model fidelity in replicating the real aortic root kinematics.

Biomechanical properties of 3D printable material usable for synthetic personalized healthy human aorta.

With the development of three-dimensional (3D) printing, 3D-printed products have been widely used in medical fields, such as plastic surgery, orthopedics, dentistry, etc. In cardiovascular research, 3D-printed models are becoming more realistic in shape. However, from a biomechanical point of view, only a few studies have explored printable materials that can represent the properties of the human aorta. This study focuses on 3D-printed materials that might simulate the stiffness of human aortic tissue. First, the biomechanical properties of a healthy human aorta were defined and used as reference. The main objective of this study was to identify 3D printable materials that possess similar properties to the human aorta. Three synthetic materials, NinjaFlex (Fenner Inc., Manheim, USA), FilasticTM (Filastic Inc., Jardim Paulistano, Brazil), and RGD450+TangoPlus (Stratasys Ltd.©, Rehovot, Israel), were printed in different thicknesses. Uniaxial and biaxial tensile tests were performed to compute several biomechanical properties, such as thickness, stress, strain, and stiffness. We found that with the mixed material RGD450+TangoPlus, it was possible to achieve a similar stiffness to healthy human aorta. Moreover, the 50-shore-hardness RGD450+TangoPlus had similar thickness and stiffness to the human aorta.

Long-term oncological results in penile cancer treated by inguinal lymphadenectomy.

PURPOSE: In 95% of cases, penile cancer is a squamous cell carcinoma whose specificity is lymphatic spread with the inguinal lymph nodes as the first relay route. Inguinal lymph node dissection is a primordial part of the treatment. The objective was to assess the oncological results of inguinal lymph node dissection in penile cancer at our centre. METHODS: We retrospectively included all patients having undergone inguinal lymph node dissection at our centre between 1 January 2004 and 1 January 2020 for the treatment of penile cancer. Patients for whom lymphadenopathy was palliative were excluded. Depending on indications, the procedures consisted in either dynamic sentinel node biopsy, modified lymphadenectomy or radical lymphadenectomy. All cancers were reclassified using the 2016 TNM classification system. Survival was analysed according to the Kaplan-Meier method. RESULTS: 242 inguinal lymph node dissections were performed in 122 patients. There were 71 pN0 (58%), 9 pN1 (7%), 4 pN2 (3%) and 38 pN3 (31%). Mean follow-up was 51 ± 45 months. The 3-year recurrence-free survival rate was 76% in pN0 patients and 17% in pN3 patients. The 5-year specific and overall survival rates were, respectively, 82% and 73% for pN0 stages, and 14% and 17% for pN3 stages. Extracapsular extension on an inguinal lymphadenopathy appeared as a highly negative prognostic factor. CONCLUSION: Inguinal lymph node dissection is essential in the treatment of penile cancer. Recurrence-free, specific and overall survival are closely linked to the lymph node stage. Extracapsular extension and pelvic lymph node invasion are highly negative prognostic factors.

[Results of the management of kidney cancer with extension into the inferior vena cava: A retrospective, single-center, observational study]. / Résultats de la prise en charge des cancers du rein avec extension dans la veine cave inférieure : étude observationnelle rétrospective monocentrique.

OBJECTIVES: The aim of our study was to evaluate the morbidity and mortality, as well as the oncogical results of patients who had undergone surgical procedure for a kidney cancer with thrombus extension into the inferior vena cava. MATERIALS AND METHODS: Between January 2004 and April 2020, 57 patients were operated by enlarged nephrectomy with thrombectomy for kidney cancer with thrombus extension in the inferior vena cava. Twelve patients (21%) with the use of cardiopulmonary bypass because the thrombus was upper than the sus-hepatic veins. Twenty-three patients (40.4%) were metastatic at diagnosis. RESULTS: Perioperative mortality was 10.5%, without difference according to surgical technique. Morbidity during hospitalization was 58%, without difference according to surgical technique. Median follow-up was 40.8±40.1months. Overall survival at 2 and 5years was 60% and 28%, respectively. At 5years, the principal prognostic factor was the metastatic status at diagnosis, in multivariate analysis (OR: 0.15, P=0.03). Progression free survival mean was 28.2±40.2months. Progression free survival at 2 and 5years was 28% and 18%, respectively. All the patients who were metastatic at diagnosis had a recurrence in an average time of 5.7months (median of 3months). Thirteen percent of patients can be considered cured at the end of the study. CONCLUSION: Morbidity and mortality of this surgery remain important. The metastatic status at diagnosis has appeared to be the principal prognostic factor on the survival of these patients. LEVEL OF EVIDENCE: Level 4: retrospective study.

Assessment of shape-based features ability to predict the ascending aortic aneurysm growth.

The current guidelines for the ascending aortic aneurysm (AsAA) treatment recommend surgery mainly according to the maximum diameter assessment. This criterion has already proven to be often inefficient in identifying patients at high risk of aneurysm growth and rupture. In this study, we propose a method to compute a set of local shape features that, in addition to the maximum diameter D, are intended to improve the classification performances for the ascending aortic aneurysm growth risk assessment. Apart from D, these are the ratio DCR between D and the length of the ascending aorta centerline, the ratio EILR between the length of the external and the internal lines and the tortuosity T. 50 patients with two 3D acquisitions at least 6 months apart were segmented and the growth rate (GR) with the shape features related to the first exam computed. The correlation between them has been investigated. After, the dataset was divided into two classes according to the growth rate value. We used six different classifiers with input data exclusively from the first exam to predict the class to which each patient belonged. A first classification was performed using only D and a second with all the shape features together. The performances have been evaluated by computing accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUROC) and positive (negative) likelihood ratio LHR+ (LHR-). A positive correlation was observed between growth rate and DCR (r = 0.511, p = 1.3e-4) and between GR and EILR (r = 0.472, p = 2.7e-4). Overall, the classifiers based on the four metrics outperformed the same ones based only on D. Among the diameter-based classifiers, k-nearest neighbours (KNN) reported the best accuracy (86%), sensitivity (55.6%), AUROC (0.74), LHR+ (7.62) and LHR- (0.48). Concerning the classifiers based on the four shape features, we obtained the best accuracy (94%), sensitivity (66.7%), specificity (100%), AUROC (0.94), LHR+ (+∞) and LHR- (0.33) with support vector machine (SVM). This demonstrates how automatic shape features detection combined with risk classification criteria could be crucial in planning the follow-up of patients with ascending aortic aneurysm and in predicting the possible dangerous progression of the disease.

Optimal Timing of Coronary Artery Bypass Grafting in Haemodynamically Stable Patients after Myocardial Infarction.

During the acute phase of myocardial infarction, the culprit artery must be revascularized quickly with angioplasty. Surgery then completes the procedure in a second stage. If emergency surgery is performed, the resulting death rate is high; 15-20% of patients are operated on within the first 48 h after the myocardial infarction. The timing of surgical revascularization and the patient's preoperative state influence the mortality rate. We aimed to evaluate the impact of surgery delay on morbimortality. Between 2007 and 2017, a retrospective monocentric study was conducted including 477 haemodynamically stable patients after myocardial infarction who underwent an urgent coronary bypass. Three groups were described, depending on the timing of the surgery: during the first 4 days (Group 1, n = 111, 23%), 5 to 10 days (Group 2, n = 242, 51%) and after 11 days (Group 3, n = 124, 26%). The overall thirty-day mortality was 7.1% (n = 34). The death rate was significantly higher in Group 1 (n = 16; 14% vs. n = 10; 4.0% vs. n = 8; 6%, p < 0.01). The mortality risk factors identified were age (OR: 1.08; CI 95%: 1.04-1.12; p < 0.001), peripheral arteriopathy (OR: 3.31; CI 95%: 1.16-9.43; p = 0.024), preoperative renal failure (OR: 6.39; CI 95%: 2.49-15.6; p < 0.001) and preoperative ischemic recurrence (OR: 3.47; CI 95%: 1.59-7.48; p < 0.01). Ninety-two patients presented with preoperative ischemic recurrence (19%), with no difference between the groups. The optimal timing for the surgical revascularization of MI seems to be after Day 4 in stable patients. However, timing is not the only factor influencing the death rate: the patient's health condition and disease severity must be considered in the individual management strategy.

Segmentation of the aorta in systolic phase from 4D flow MRI: multi-atlas vs. deep learning.

OBJECTIVE: In the management of the aortic aneurysm, 4D flow magnetic resonance Imaging provides valuable information for the computation of new biomarkers using computational fluid dynamics (CFD). However, accurate segmentation of the aorta is required. Thus, our objective is to evaluate the performance of two automatic segmentation methods on the calculation of aortic wall pressure. METHODS: Automatic segmentation of the aorta was performed with methods based on deep learning and multi-atlas using the systolic phase in the 4D flow MRI magnitude image of 36 patients. Using mesh morphing, isotopological meshes were generated, and CFD was performed to calculate the aortic wall pressure. Node-to-node comparisons of the pressure results were made to identify the most robust automatic method respect to the pressures obtained with a manually segmented model. RESULTS: Deep learning approach presented the best segmentation performance with a mean Dice similarity coefficient and a mean Hausdorff distance (HD) equal to 0.92+/- 0.02 and 21.02+/- 24.20 mm, respectively. At the global level HD is affected by the performance in the abdominal aorta. Locally, this distance decreases to 9.41+/- 3.45 and 5.82+/- 6.23 for the ascending and descending thoracic aorta, respectively. Moreover, with respect to the pressures from the manual segmentations, the differences in the pressures computed from deep learning were lower than those computed from multi-atlas method. CONCLUSION: To reduce biases in the calculation of aortic wall pressure, accurate segmentation is needed, particularly in regions with high blood flow velocities. Thus, the deep learning segmen-tation method should be preferred.

4D segmentation of the thoracic aorta from 4D flow MRI using deep learning.

BACKGROUND: 4D flow MRI allows the analysis of hemodynamic changes in the aorta caused by pathologies such as thoracic aortic aneurysms (TAA). For personalized management of TAA, new biomarkers are required to analyze the effect of fluid structure iteration which can be obtained from 4D flow MRI. However, the generation of these biomarkers requires prior 4D segmentation of the aorta. OBJECTIVE: To develop an automatic deep learning model to segment the aorta in 4D from 4D flow MRI. METHODS: Segmentation is addressed with a U-Net based segmentation model that treats each 4D flow MRI frame as an independent sample. Performance is measured with respect to Dice score (DS) and Hausdorff distance (HD). In addition, the maximum and minimum surface areas at the level of the ascending aorta are measured and compared with those obtained from cine-MRI. RESULTS: The segmentation performance was 0.90 ± 0.02 for the DS and the mean HD was 9.58 ± 4.36 mm. A correlation coefficient of r = 0.85 was obtained for the maximum surface and r = 0.86 for the minimum surface between the 4D flow MRI and cine-MRI. CONCLUSION: The proposed automatic approach of 4D aortic segmentation from 4D flow MRI seems to be accurate enough to contribute to the wider use of this imaging technique in the analysis of pathologies such as TAA.

Comparison of In-Vivo and Ex-Vivo Ascending Aorta Elastic Properties through Automatic Deep Learning Segmentation of Cine-MRI and Biomechanical Testing.

Ascending aortic aneurysm is a pathology that is important to be supervised and treated. During the years the aorta dilates, it becomes stiff, and its elastic properties decrease. In some cases, the aortic wall can rupture leading to aortic dissection with a high mortality rate. The main reference standard to measure when the patient needs to undertake surgery is the aortic diameter. However, the aortic diameter was shown not to be sufficient to predict aortic dissection, implying other characteristics should be considered. Therefore, the main objective of this work is to assess in-vivo the elastic properties of four different quadrants of the ascending aorta and compare the results with equivalent properties obtained ex-vivo. The database consists of 73 cine-MRI sequences of thoracic aorta acquired in axial orientation at the level of the pulmonary trunk. All the patients have dilated aorta and surgery is required. The exams were acquired just prior to surgery, each consisting of 30 slices on average across the cardiac cycle. Multiple deep learning architectures have been explored with different hyperparameters and settings to automatically segment the contour of the aorta on each image and then automatically calculate the aortic compliance. A semantic segmentation U-Net network outperforms the rest explored networks with a Dice score of 98.09% (±0.96%) and a Hausdorff distance of 4.88 mm (±1.70 mm). Local aortic compliance and local aortic wall strain were calculated from the segmented surfaces for each quadrant and then compared with elastic properties obtained ex-vivo. Good agreement was observed between Young's modulus and in-vivo strain. Our results suggest that the lateral and posterior quadrants are the stiffest. In contrast, the medial and anterior quadrants have the lowest aortic stiffness. The in-vivo stiffness tendency agrees with the values obtained ex-vivo. We can conclude that our automatic segmentation method is robust and compatible with clinical practice (thanks to a graphical user interface), while the in-vivo elastic properties are reliable and compatible with the ex-vivo ones.

A multicentre, propensity score matched analysis comparing a valve-sparing approach to valve replacement in aortic root aneurysm: Insight from the AVIATOR database.

OBJECTIVES: Our goal was to evaluate the outcome of valve-sparing root replacement (VSRR) and to compare the outcomes to those of patients having composite valve-graft conduit aortic root replacement (CVG-ARR) in a cohort of patients with aortic root aneurysm ± valve insufficiency, without valvular stenosis. Although valve-sparing procedures are preferable in young patients, there is a lack of comparative data in comparable patients. METHODS: The VSRR procedures were performed in 2005 patients, and 218 patients underwent a CVG-ARR procedure. Exclusion criteria included aortic dissection, endocarditis and valvular stenosis. Propensity score matching (3:1 ratio) was applied to compare VSRR (reimplantation 33% and remodelling 67%) and CVG-ARR. RESULTS: We matched 218 patients with CVG-ARR to 654 patients with VSRR (median age, 56.0; median follow-up was 4 years in both groups; interquartile range 1-5 years). Early mortality was 1.1% of those who had VSRR versus 2.3% in those who had CVG-ARR. Survival was 95.4% [95% confidence interval (CI) 94-97%] at 5 years in patients who had VSRR versus 85.4% (95% CI 82-92%) in those who had CVG-ARR; P = 0.002. Freedom from reintervention at 5 years was 96.8% (95% CI 95-98%) with VSRR and 95.4% (95% CI 91-99%) with CVG-ARR (P = 0.98). Additionally, there were more thromboembolic, endocarditis and bleeding events in the patients who had CVG-ARR (P = 0.02). CONCLUSIONS: This multicentre study shows excellent results after valve-sparing root replacement in patients with an ascending aortic aneurysm with or without valve insufficiency. Compared to composite valve-graft aortic root replacement, survival is better and valve-related events are fewer. Consequently, valve-sparing procedures should be considered whenever a durable repair is feasible. We advocate a valve-sparing strategy even in more complex cases when performed in experienced centres.

Morbidity and risk factors for complications of inguinal lymph node dissection in penile cancer.

PURPOSE: To assess the morbidity of inguinal lymph node dissection (ILND) in penile cancer, then to compare this morbidity with that of ILND performed in the context of skin cancer treatment. METHODS: We retrospectively included all patients having undergone ILND between 1 January 2004 and 31 December 2019 in our centre's urology department in the context of treatment of penile cancer or skin cancer. Postoperative complications were reported in accordance with the Clavien-Dindo classification system. RESULTS: Two hundred forty-two ILNDs were performed in 122 patients with penile cancer and 56 ILNDs were performed in 56 patients with skin cancer. The most common early complication was postoperative fluid collection (lymphocele or haematoma), which complicated 44% of ILNDs overall and 60% of radical lymphadenectomies. The most common late complication was leg lymphoedema, found in up to 36% of radical lymphadenectomies. Major complications (grade ≥ III) were very rare (4% of radical lymphadenectomies). Radical lymphadenectomies resulted in significantly more cases of postoperative fluid collection, skin necrosis and dehiscence, as well as leg lymphoedema, than modified lymphadenectomy techniques. Two factors significantly increasing postoperative morbidity were demonstrated: ASA score = 3 (OR = 3.09) and operating time (OR = 1.01). CONCLUSION: ILNDs are morbid surgical procedures for which the indications must be well defined. However, the complications are almost exclusively minor, for a major oncological benefit.

Analysis of a multicenter registry on evaluation of transit-time flow in coronary artery disease surgery.

Objective: The Evaluation of Transit-Time Flow in Coronary Artery Disease Surgery (EFCAD) registry aims to assess the influence of transit-time flow measurement (TTFM) in daily practice. Methods: EFCAD is a prospective, multicenter study involving 9 centers performing TTFM during isolated coronary artery bypass grafting. Primary end point was occurrence and risk factors of major adverse cardiac events, including perioperative myocardial infarction, urgent postoperative coronary angiogram and/or revascularization, and hospital mortality. Secondary end points were rate of graft revision during surgery and factors affecting graft flow. We respected the limit values set by the experts: mean graft flow >15 mL/minute and pulsatility index ≤5. Results: Between May 2017 and March 2021, 1616 patients were registered in the EFCAD database. After review, 1414 were included for analyses. Of those, 1176 were eligible for primary end point analysis. Graft revision, mainly due to inadequate TTFM values, occurred in 2% (29 patients). The primary end point occurred in 46 (3.9%) patients, and it was related with left anterior descending artery graft flow ≤15 mL/minute (odds ratio, 3.64; P < .001). Graft flow was related with number of grafts (3 vs 1-2, ß = -1.6; 4-6 vs 1-2, ß = -4.1; P < .001; ß > 0 indicates higher flow), and graft origin (aorta vs Y, ß = 9.2; in situ left internal thoracic artery vs Y, ß = 3.2; in situ right internal thoracic artery vs Y, ß = 2.3; P < .001). Conclusions: Data from EFCAD study suggest that TTFM is reliable to evaluate graft flow, and acceptance of inadequate flow on left anterior descending artery anastomosis influence postoperative outcomes. In our opinion, TTFM assessment should be routinely used in coronary artery bypass procedures, even if interpretation depends on learning curves.

Determinants of Arterial Pressure of Oxygen and Carbon Dioxide in Patients Supported by Veno-Arterial ECMO.

Background: The present study aimed to assess the determinants of arterial partial pressure of oxygen (PaO2) and carbon dioxide (PaCO2) in the early phase of veno-arterial extracorporeal membrane oxygenation (VA ECMO) support. Even though the guidelines considered both the risks of hypoxemia and hyperoxemia during ECMO support, there are a lack of data concerning the patients supported by VA ECMO. Methods: This is a retrospective, monocentric, observational cohort study in a university-affiliated cardiac intensive care unit. Hemodynamic parameters, ECMO parameters, ventilator settings, and blood gas analyses were collected at several time points during the first 48 h of VA ECMO support. For each timepoint, the blood samples were drawn simultaneously from the right radial artery catheter, VA ECMO venous line (before the oxygenator), and from VA ECMO arterial line (after the oxygenator). Univariate followed by multivariate mixed-model analyses were performed for longitudinal data analyses. Results: Forty-five patients with femoro-femoral peripheral VA ECMO were included. In multivariate analysis, the patients' PaO2 was independently associated with QEC, FDO2, and time of measurement. The patients' PaCO2 was associated with the sweep rate flow and the PpreCO2. Conclusions: During acute VA ECMO support, the main determinants of patient oxygenation are determined by VA ECMO parameters.