Does right thoracotomy increase the risk of mitral valve reoperation?

ObjectiveThe study objective was to determine whether a right thoracotomy approach increases the risk of mitral valve reoperation.MethodsBetween January of 1993 and January of 2004, 2469 patients with mitral valve disease underwent 2570 reoperations (1508 replacements, 1062 repairs). The approach was median sternotomy in 2444 patients, right thoracotomy in 80 patients, and other in 46 patients. Multivariable logistic regression was used to identify factors associated with median sternotomy versus right thoracotomy, mitral valve repair versus replacement, hospital death, and stroke. Factors favoring median sternotomy (P < .03) included coronary artery bypass grafting (30% vs 2%), aortic valve replacement (39% vs 2%), tricuspid valve repair (27% vs 13%), fewer previous cardiac operations, more recent reoperation, and no prior left internal thoracic artery graft. These factors were used to construct a propensity score for risk-adjusting outcomes.ResultsHospital mortality was 6.7% (163/2444) for the median sternotomy approach and 6.3% (5/80) for the thoracotomy approach (P = .9). Risk factors (P < .04) included earlier surgery date, higher New York Heart Association class, emergency operation, multiple reoperations, and mitral valve replacement. Stroke occurred in 66 patients (2.7%) who underwent a median sternotomy and in 6 patients (7.5%) who underwent a thoracotomy (P = .006). Mitral valve replacement (vs repair) was more common in those receiving a thoracotomy (P < .04).ConclusionsCompared with median sternotomy, right thoracotomy is associated with a higher occurrence of stroke and less frequent mitral valve repair. Specific strategies for conducting the operation should be used to reduce the risk of stroke when right thoracotomy is used for mitral valve reoperation. In most instances, repeat median sternotomy, with its better exposure and greater latitude for concomitant procedures, is preferred

Automation in human-machine networks: how increasing machine agency affects human agency

© 2018, Springer International Publishing AG. Efficient human-machine networks require productive interaction between human and machine actors. In this study, we address how a strengthening of machine agency, for example through increasing levels of automation, affect the human actors of the networks. Findings from case studies within air traffic management, emergency management, and crowd evacuation are presented, shedding light on how automation may strengthen the agency of human actors in the network through responsibility sharing and task allocation, and serve as a needed prerequisite of innovation and change

Maritime Navigation: Characterizing Collaboration in a High-Speed Craft Navigation Activity

acceptedVersio

Similar Biochemical Signatures and Prion Protein Genotypes in Atypical Scrapie and Nor98 Cases, France and Norway

Similarities raise questions regarding the origin of these recently described cases

Investigating older adults’ preferences for functions within a human-machine interface designed for fully autonomous vehicles

© Springer International Publishing AG, part of Springer Nature 2018. Compared to traditional cars, where the driver has most of their attention allocated on the road and on driving tasks, in fully autonomous vehicles it is likely that the user would not need to intervene with driving related functions meaning that there will be little need for HMIs to have features and functionality relating to these factors. However, there will be an opportunity for a range of other interactions with the user. As such, designers and researchers need to have an understanding of what is actually needed or expected and how to balance the type of functionality they make available. Also, in HMI design, the design principles need to be considered in relation to a range of user characteristics, such as age, and sensory, cognitive and physical ability and other impairments. In this study, we proposed an HMI specially designed for connected autonomous vehicles with a focus on older adults. We examined older adults’ preferences of CAV HMI functions, and, the degree to which individual differences (e.g., personality, attitude towards computers, trust in technology, cognitive functioning) correlate with preferences for these functions. Thirty-one participants (M age = 67.52, SD = 7.29), took part in the study. They had to interact with the HMI and rate its functions based on the importance and likelihood of using them. Results suggest that participants prefer adaptive HMIs, with journey planner capabilities. As expected, as it is a CAV HMI, the Information and Entertainment functions are also preferred. Individual differences have limited relationship with HMI preferences