BACKGROUND: Recent developments in surgical techniques and hospital care have led to improved outcomes following total anomalous pulmonary venous return (TAPVR) repair. However, the surgical repair of TAPVR remains associated with a high risk of mortality and need for reoperation. We conducted this retrospective study to evaluate mid-term outcomes following in situ TAPVR repair without total circulatory arrest (TCA), and to identify the risk factors associated with surgical outcomes. METHODS: We retrospectively reviewed 29 cases of surgical intervention for TAPVR conducted between April 2000 and July 2015. All patients were newborns or infants who underwent in situ TAPVR repair without TCA. RESULTS: Four anatomic subtypes of TAPVR were included in this study: supracardiac (20 cases, 69.0%), cardiac (4 cases, 13.8%), infracardiac (4 cases, 13.8%), and mixed (1 case, 3.4%). The median follow-up period for all patients was 42.9 months. Two (6.9%) early mortalities occurred, as well as 2 (6.9%) cases of postoperative pulmonary venous obstruction (PVO). Preoperative ventilator care (p=0.027) and preoperative PVO (p=0.002) were found to be independent risk factors for mortality. CONCLUSION: In situ repair of TAPVR without TCA was associated with encouraging mid-term outcomes. Preoperative ventilator care and preoperative PVO were found to be independent risk factors for mortality associated with TAPVR repair.
Follow-Up Studies ; Humans ; Infant ; Infant, Newborn ; Mortality ; Reoperation ; Retrospective Studies ; Risk Factors ; Scimitar Syndrome* ; Ventilators, Mechanical

PURPOSE: Adverse drug events (ADEs) are associated with high health and financial costs and have increased as more elderly patients treated with multiple medications emerge in an aging society. It has thus become challenging for physicians to identify drugs causing adverse events. This study proposes a novel approach that can improve clinical decision making with recommendations on ADE causative drugs based on patient information, drug information, and previous ADE cases. MATERIALS AND METHODS: We introduce a personalized and learning approach for detecting drugs with a specific adverse event, where recommendations tailored to each patient are generated using data mining techniques. Recommendations could be improved by learning the associations of patients and ADEs as more ADE cases are accumulated through iterations. After consulting the system-generated recommendations, a physician can alter prescriptions accordingly and report feedback, enabling the system to evolve with actual causal relationships. RESULTS: A prototype system is developed using ADE cases reported over 1.5 years and recommendations obtained from decision tree analysis are validated by physicians. Two representative cases demonstrate that the personalized recommendations could contribute to more prompt and accurate responses to ADEs. CONCLUSION: The current system where the information of individual drugs exists but is not organized in such a way that facilitates the extraction of relevant information together can be complemented with the proposed approach to enhance the treatment of patients with ADEs. Our illustrative results show the promise of the proposed system and further studies are expected to validate its performance with quantitative measures.
Aged ; Aging ; Clinical Decision-Making ; Complement System Proteins ; Data Mining ; Decision Trees ; Drug-Related Side Effects and Adverse Reactions ; Humans ; Learning* ; Prescriptions