5 research outputs found

    Analysis of the Swift Gamma-Ray Bursts duration

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    Two classes of gamma-ray bursts have been identified in the BATSE catalogs characterized by durations shorter and longer than about 2 seconds. There are, however, some indications for the existence of a third type of burst. Swift satellite detectors have different spectral sensitivity than pre-Swift ones for gamma-ray bursts. Therefore it is worth to reanalyze the durations and their distribution and also the classification of GRBs. Using The First BAT Catalog the maximum likelihood estimation was used to analyzed the duration distribution of GRBs. The three log-normal fit is significantly (99.54 % probability) better than the two for the duration distribution. Monte-Carlo simulations also confirm this probability (99.2 %).Comment: NANJING GAMMA-RAY BURST CONFERENCE 200

    Different satellites - different GRB redshift distributions?

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    The measured redshifts of gamma-ray bursts (GRBs), which were first detected by the Swift satellite, seem to be bigger on average than the redshifts of GRBs detected by other satellites. We analyzed the redshift distribution of GRBs triggered and observed by different satellites (Swift[1], HETE2[2], BeppoSax, Ulyssses). After considering the possible biases significant difference was found at the p = 95.70% level in the redshift distributions of GRBs measured by HETE and the Swift.Comment: 2008 NANJING GAMMA-RAY BURST CONFERENCE. AIP Conference Proceedings, Volume 1065, pp. 119-122 (2008

    Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

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    Background Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P < 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)
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