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BACKGROUND: Left ventricular assist devices (LVAD) represent an important therapeutic option for patients progressing to end-stage heart failure. Women have been historically underrepresented in LVAD studies, and have been reported to have worse outcomes despite technological optimisation. We aimed to systematically explore the evidence on sex disparities in the use and outcomes of LVAD implantation. METHODS: A systematic database search with meta-analysis was conducted of comparative original articles of men versus women undergoing LVAD implantation, in EMBASE, MEDLINE, Cochrane database and Google Scholar, from inception to July 2022. Primary outcomes were stroke (haemorrhagic and ischaemic) and early/overall mortality. Secondary outcomes were LVAD thrombosis, right VAD implantation, major bleeding, kidney dysfunction, and device/driveline infection. RESULTS: Our search yielded 137 relevant studies, including 22 meeting the inclusion criteria with a total of 53 227 patients (24.2% women). Overall mortality was higher in women (odds ratio [OR] 1.35, 95% confidence interval [CI] 1.05-1.62, p = 0.02), as was overall stroke (OR 1.32, 95%CI 1.06-1.66, p = 0.01), including ischemic (OR 1.80, 95%CI 1.22-2.64, p = 0.003) and haemorrhagic (OR 1.72, 95%CI 1.09-2.70, p = 0.02). Women had more frequent right VAD implantation (OR 2.11, 95%CI 1.24-3.57, p = 0.006) and major bleeding (OR 1.40, 95%CI 1.06-1.85, p = 0.02). Kidney dysfunction, LVAD thrombosis, and device/driveline infections were comparable between sexes. CONCLUSIONS: Our analysis suggests that women face a greater risk of adverse events and mortality post-LVAD implantation. Although the mechanisms remain unclear, the difference in outcomes is thought to be multifactorial. Further research, that includes comprehensive pre-operative characteristics and post-operative outcomes, is encouraged.

BACKGROUND: This review aims to systematically evaluate the currently available evidence investigating the use of artificial intelligence (AI) and machine learning (ML) in the field of cardiac transplantation. Furthermore, based on the challenges identified we aim to provide a series of recommendations and a knowledge base for future research in the field of ML and heart transplantation. METHODS: A systematic database search was conducted of original articles that explored the use of ML and/or AI in heart transplantation in EMBASE, MEDLINE, Cochrane database, and Google Scholar, from inception to November 2021. RESULTS: Our search yielded 237 articles, of which 13 studies were included in this review, featuring 463 850 patients. Three main areas of application were identified: (1) ML for predictive modeling of heart transplantation mortality outcomes; (2) ML in graft failure outcomes; (3) ML to aid imaging in heart transplantation. The results of the included studies suggest that AI and ML are more accurate in predicting graft failure and mortality than traditional scoring systems and conventional regression analysis. Major predictors of graft failure and mortality identified in ML models were: length of hospital stay, immunosuppressive regimen, recipient's age, congenital heart disease, and organ ischemia time. Other potential benefits include analyzing initial lab investigations and imaging, assisting a patient with medication adherence, and creating positive behavioral changes to minimize further cardiovascular risk. CONCLUSION: ML demonstrated promising applications for improving heart transplantation outcomes and patient-centered care, nevertheless, there remain important limitations relating to implementing AI into everyday surgical practices.

Since the development of endoscopic vision in the late 1970s, the implementation of minimally invasive surgical methods has been rapidly progressing throughout a wide range of surgical disciplines, including cardiovascular surgery. The benefits of minimally invasive procedures including a reduction in operative trauma and postoperative morbidity, have been well-documented and compared to open-heart procedures, eventually becoming the preferred modality of treatment by many centers. Due to the cost ineffectiveness of the robotic systems for numerous institutions, new technologies have been developed to provide the advantages of robotic surgical systems at a lower price, thus making them more widely available. In this paper, we aimed to share our first experiences with Artisential® surgeon-powered robotic instruments and review their general advantages compared to conventional and robotic devices.

BACKGROUND: The use of left ventricular assist devices (LVAD) in patients with advance heart failure is still associated with an important risk of immune dysregulation and infections. The aim of this study was to determine whether extracorporeal blood purification using the CytoSorb device benefits patients after LVAD implantation in terms of complications and overall survival.MATERIALS AND METHODS: Between August 2010 and January 2020, 207 consecutive patients underwent LVAD implantation, of whom 72 underwent CytoSorb therapy and 135 did not. Overall survival, major adverse events, and laboratory parameters were compared between 112 propensity score-matched patients (CytoSorb: 72 patients; non-CytoSorb: 40 patients).RESULTS: WBC (p = .033), CRP (p = .001), and IL-6 (p < .001), significantly increased with LVAD implantation, while CytoSorb did not influence this response. In-hospital mortality and overall survival during follow-up were similar with CytoSorb. However, patients treated with CytoSorb were more likely to develop respiratory failure (54.2% vs. 30.0%, p = .024), need mechanical ventilation for longer than 6 days post-implant (50.0% vs. 27.5%, p = .035), and require tracheostomy during hospitalization (31.9% vs. 12.5%, p = .040). No other significant differences were observed with regard to major adverse events during follow-up.CONCLUSIONS: Overall, our results showed that CytoSorb might not convey a significant morbidity or mortality benefit for patients undergoing LVAD implantation.