Background: Artificial intelligence (AI) has emerged as a transformative technology in healthcare, with its integration into cardiac surgery offering significant advancements in precision, efficiency, and patient outcomes. However, a comprehensive understanding of AI’s applications, benefits, challenges, and future directions in cardiac surgery is needed to inform its safe and effective implementation. Methods: A systematic review was conducted following PRISMA guidelines. Literature searches were performed in PubMed, Scopus, Cochrane Library, Google Scholar, and Web of Science, covering publications from January 2000 to November 2024. Studies focusing on AI applications in cardiac surgery, including risk stratification, surgical planning, intraoperative guidance, and postoperative management, were included. Data extraction and quality assessment were conducted using standardized tools, and findings were synthesized narratively. Results: A total of 121 studies were included in this review. AI demonstrated superior predictive capabilities in risk stratification, with machine learning models outperforming traditional scoring systems in mortality and complication prediction. Robotic-assisted systems enhanced surgical precision and minimized trauma, while computer vision and augmented cognition improved intraoperative guidance. Postoperative AI applications showed potential in predicting complications, supporting patient monitoring, and reducing healthcare costs. However, challenges such as data quality, validation, ethical considerations, and integration into clinical workflows remain significant barriers to widespread adoption. Conclusions: AI has the potential to revolutionize cardiac surgery by enhancing decision making, surgical accuracy, and patient outcomes. Addressing limitations related to data quality, bias, validation, and regulatory frameworks is essential for its safe and effective implementation. Future research should focus on interdisciplinary collaboration, robust testing, and the development of ethical and transparent AI systems to ensure equitable and sustainable advancements in cardiac surgery.

Background: Artificial intelligence (AI) is rapidly transforming thoracic surgery by enhancing diagnostic accuracy, surgical precision, intraoperative guidance, and postoperative management. AI-driven technologies, including machine learning (ML), deep learning, computer vision, and robotic-assisted surgery, have the potential to optimize clinical workflows and improve patient outcomes. However, challenges such as data integration, ethical concerns, and regulatory barriers must be addressed to ensure AI’s safe and effective implementation. This review aims to analyze the current applications, benefits, limitations, and future directions of AI in thoracic surgery. Methods: This review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive literature search was performed using PubMed, Scopus, Web of Science, and Cochrane Library for studies published up to January 2025. Relevant articles were selected based on predefined inclusion and exclusion criteria, focusing on AI applications in thoracic surgery, including diagnostics, robotic-assisted surgery, intraoperative guidance, and postoperative care. A risk of bias assessment was conducted using the Cochrane Risk of Bias Tool and ROBINS-I for non-randomized studies. Results: Out of 279 identified studies, 36 met the inclusion criteria for qualitative synthesis, highlighting AI’s growing role in diagnostic accuracy, surgical precision, intraoperative guidance, and postoperative care in thoracic surgery. AI-driven imaging analysis and radiomics have improved pulmonary nodule detection, lung cancer classification, and lymph node metastasis prediction, while robotic-assisted thoracic surgery (RATS) has enhanced surgical accuracy, reduced operative times, and improved recovery rates. Intraoperatively, AI-powered image-guided navigation, augmented reality (AR), and real-time decision-support systems have optimized surgical planning and safety. Postoperatively, AI-driven predictive models and wearable monitoring devices have enabled early complication detection and improved patient follow-up. However, challenges remain, including algorithmic biases, a lack of multicenter validation, high implementation costs, and ethical concerns regarding data security and clinical accountability. Despite these limitations, AI has shown significant potential to enhance surgical outcomes, requiring further research and standardized validation for widespread adoption. Conclusions: AI is poised to revolutionize thoracic surgery by enhancing decision-making, improving patient outcomes, and optimizing surgical workflows. However, widespread adoption requires addressing key limitations through multicenter validation studies, standardized AI frameworks, and ethical AI governance. Future research should focus on digital twin technology, federated learning, and explainable AI (XAI) to improve AI interpretability, reliability, and accessibility. With continued advancements and responsible integration, AI will play a pivotal role in shaping the next generation of precision thoracic surgery.

Background: Postoperative air leak (PAL) is a frequent and potentially serious complication following thoracic surgery, characterized by the persistent escape of air from the lung into the pleural space. It is associated with extended hospitalizations, increased morbidity, and elevated healthcare costs. Understanding the mechanisms, risk factors, and effective management strategies for PAL is crucial in improving surgical outcomes. Aim: This review seeks to synthesize all known data concerning PAL, including its etiology, risk factors, diagnostic approaches, and the range of available treatments from conservative measures to surgical interventions, with a special focus on the use of autologous plasma. Materials and Methods: A comprehensive literature search of databases such as PubMed, Cochrane Library, and Google Scholar was conducted for studies and reviews published on PAL following thoracic surgery. The selection criteria aimed to include articles that provided insights into the incidence, mechanisms, risk assessment, diagnostic methods, and treatment options for PAL. Special attention was given to studies detailing the use of autologous plasma in managing this complication. Results: PAL is influenced by a variety of patient-related, surgical, and perioperative factors. Diagnosis primarily relies on clinical observation and imaging, with severity assessments guiding management decisions. Conservative treatments, including chest tube management and physiotherapy, serve as the initial approach, while persistent leaks may necessitate surgical intervention. Autologous plasma has emerged as a promising treatment, offering a novel mechanism for enhancing pleural healing and reducing air leak duration, although evidence is still evolving. Conclusions: Effective management of PAL requires a multifaceted approach tailored to the individual patient’s needs and the specifics of their condition. Beyond the traditional treatment approaches, innovative treatment modalities offer the potential to improve outcomes for patients experiencing PAL after thoracic surgery. Further research is needed to optimize treatment protocols and integrate new therapies into clinical practice.

Background: Psychosocial factors such as anxiety, depression, and lack of social support are increasingly recognized as critical determinants of outcomes in cardiac surgery. Up to 32% of patients experience preoperative anxiety, and nearly 20% experience depression, both of which have been associated in observational studies with delayed recovery, increased complications, and higher mortality. Objective: This study aimed to review current evidence on psychosocial aspects of cardiac surgery and evaluate patient-centered care strategies that address these challenges. Methods: A narrative literature review was performed using PubMed, Scopus, and ScienceDirect, focusing on recently published studies. The search covered studies published between January 2009 and June 2024, yielding 76 eligible studies after screening and thematic synthesis. Search terms included patient-centered care, psychosocial factors, cardiac surgery, anxiety, depression, rehabilitation, and telemedicine. Eligible studies included randomized controlled trials, cohort studies, qualitative studies, and systematic reviews. Results: Key themes included preoperative psychological preparation, management of anxiety and depression, promotion of quality of life, effective communication strategies, and integration of psychosocial support into rehabilitation programs. Evidence shows that psychological and social interventions reduce reported pain by up to 33%, as reported in pooled randomized controlled trials and meta-analyses; shorten hospital stay; improve adherence to treatment; and enhance long-term quality of life. Emerging tools such as telemedicine and digital platforms further expand access to psychosocial care. Conclusions: Integrating psychosocial care into cardiac surgery is essential for achieving holistic outcomes. Patient-centered models that emphasize communication, shared decision-making, family involvement, and digital support improve not only survival but also recovery, well-being, and patient satisfaction. Redefining success in cardiac surgery requires attention to both clinical results and the broader human experience of illness and recovery.

Background: Resection of lung metastases with curative intention in selected patients is associated with prolonged survival. Laser–assisted resection of lung metastases results in complete resection of a high number of lung metastases, while preserving lung parenchyma. However, data concerning laser lung resections are scarce and contradictory. The aim of this study was to conduct a systematic review to evaluate the utility of laser-assisted pulmonary metastasectomy. Methods: An electronic search in MEDLINE (via PubMed), complemented by manual searches in article references, was conducted to identify eligible studies. Results: Fourteen studies with a total of 1196 patients were included in this metanalysis. Laser-assisted surgery (LAS) for lung metastases is a safe procedure with a postoperative morbidity up to 24.2% and almost zero mortality. LAS resulted in the resection of a high number of lung metastases with reduction of the lung parenchyma loss in comparison with conventional resection methods. Survival was similar between LAS and conventional resections. Conclusion: LAS allows radical lung-parenchyma saving resection of a high number of lung metastases with similar survival to conventional methods.