The fate of the distal aorta after repair of acute type A aortic dissection

ObjectivesThe residual aorta’s behavior after repair of acute type A dissection is incompletely understood. We analyzed segmental growth rates, distal reoperation, and factors influencing long-term survival.MethodsOne hundred seventy-nine consecutive patients (70% male; mean age, 60 years) with acute type A dissection underwent aggressive resection of the intimal tear and open distal anastomosis (1986-2003). Hospital mortality was 13.4%. Survivors had serial computed tomographic scans: digitization yielded distal segmental dimensions. Segment-specific average rates of enlargement and factors influencing faster growth were analyzed. Distal reoperations and patient survival were examined.ResultsEighty-nine (57%) patients had imaging data sufficient for growth rate calculations. The median diameters after repair were as follows: aortic arch, 3.6 cm; descending aorta, 3.7 cm; and abdominal aorta, 3.2 cm. Subsequent growth rates were 0.8, 1.0, and 0.8 mm/y, respectively. Initial size of greater than 4 cm (P = .005) and initial diameter of less than 4 cm with a patent false lumen (P = .004) predicted greater growth in the descending aorta, and male sex (P = .05) significantly affected growth in the abdominal aorta. No significant factors were found for the aortic arch. There were 25 distal aortic reoperations (16 patients), and risk of reoperation was 16% at 10 years. Risk factors reducing long-term survival after repair of acute type A dissection included age (P < .0001), new neurological deficit at presentation (P = .04), absence of preoperative thrombus in the false lumen of the ascending aorta (P = .03), and a patent distal false lumen postoperatively (P = .06) but not distal reoperation.ConclusionsGrowth of the distal aorta after repair of acute type A dissection is typically slow and linear. Distal reoperation is uncommon, and late risk of death is approximately twice that of a healthy population

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Exploitation of textural and morphological image features in Sentinel-2A data for slum mapping

In this paper we use image texture and morphological profiles for mapping slums in Sentinel-2A imagery. Varying sizes of the respective spatial descriptors (GLCM, differential morphological profiles) are tested for classification using a random forest classifier. Results are interpreted based on pixel-based and patch-based accuracy assessment. Best classification results have been reached at the pixel-based level with a kappa of 81.65 for the combined feature set with both GLCM and DMP. At the patch level, the analyses show that higher accuracies are reached with large kernel sizes and detection is better for large slum areas

Outcome after severe multiple trauma: a retrospective analysis

Background Aim of this study was to evaluate prognosis of severely injured patients. Methods All severely injured patients with an Injury Severity Score (ISS) ≥ 50 were identified in a 6-year-period between 2000 and 2005 in German Level 1 Trauma Center Murnau. Data was evaluated from German Trauma Registry and Polytrauma Outcome Chart of the German Society for Trauma Surgery and a personal interview to assess working ability and disability and are presented as average. Results 88 out of 1435 evaluated patients after severe polytrauma demonstrated an ISS ≥ 50 (6.5%), among them 23% women and 77% men. 66 patients (75%) had an ISS of 50-60, 14 (16%) 61-70, and 8 (9%) ≥ 70. In 27% of patients trauma was caused by motor bike accidents. 3.6 body regions were involved. Patients had to be operated 5.3 times and were treated 23 days in the ICU and stayed 73 days in hospital. Mortality rate was 36% and rate of multi-organ failure 28%. 15% of patients demonstrated severe senso-motoric dysfunction as well as residues of severe head injury. 25% recovered well or at least moderately. 29 out of 56 survivors answered the POLO-chart. A personal interview was performed with 13 patients. The state of health was at least moderate in 72% of patients. In 48% interpersonal problems and in 41% severe pain was observed. In 57% of patients problems with working ability regarding duration, as well as quantitative and qualitative performance were observed. Symptoms of post-traumatic stress disorder were found in 41%. The more distal the lesions were located (foot/ankle) the more functional disability affected daily life. In only 15%, working ability was not impaired. 8 out of 13 interviewed patients demonstrated complete work disability. Conclusions Even severely injured patients after multiple trauma have a good prognosis. The ISS is an established tool to assess severity and prognosis of trauma, whereas prediction of clinical outcome cannot be deducted from this score