Extreme dislocation of the cervical spine-case report.

We present the case of rare extreme dislocation of subaxial cervical spine, which was challenging regarding type and time of surgery. A 22-year-old patient was injured in a traffic accident, from very beginning with signs of spinal shock. Severe traumatic C6/C7 dislocation with resulting transection of the spinal cord was diagnosed with MDCT imaging. The main dilemmas regarding the surgical treatment of this injury referred to the timing of surgery and the choice of surgical approach. We decided to perform posterior surgery at first stage. Postoperative her condition get worsening and on the 16th postoperative day came to the fatal outcome. Despite all the available protocols, in our case, the decision had to be made on the basis of individual multidisciplinary assessment, bearing in mind the mechanism of the injury and the clinical presentation of the injured patient.

The mortality of COVID-19 in CML patients from 2020 until 2022: results from the EPICOVIDEHA survey.

Since the beginning of the COVID-19 pandemic, there has been an overall improvement in patient mortality. However, haematological malignancy patients continue to experience significant impacts from COVID-19, including high rates of hospitalization, intensive care unit (ICU) admissions, and mortality. In comparison to other haematological malignancy patients, individuals with chronic myeloid leukemia (CML) generally have better prognosis. This study, conducted using a large haematological malignancy patient database (EPICOVIDEHA), demonstrated that the majority of CML patients experienced mild infections. The decline in severe and critical infections over the years can largely be attributed to the widespread administration of vaccinations and the positive response they elicited. Notably, the mortality rate among CML patients was low and exhibited a downward trend in subsequent years. Importantly, our analysis provided confirmation of the effectiveness of vaccinations in CML patients.

Invasive fungal disease in COVID-19 patients: a single-center prospective observational study.

Background: Invasive fungal diseases (IFDs) are caused by fungal infections that manifest as serious secondary infections in patients with COVID-19. The increased morbidity and mortality rates are most frequently observed in patients with COVID-19-associated pulmonary aspergillosis (CAPA) and COVID-19-associated candidiasis (CAC). CAPA is the most frequently encountered infection with an incidence rate of 0.7-7.7%, while CAC is a less common and less studied fungal infection in COVID-19 patients. Materials and methods: The present article is a prospective observational single-center study that was conducted between 1 September 2021 and 24 December 2021, involving 6,335 patients who were admitted to COVID Hospital "Batajnica," University Clinical Center of Serbia, Belgrade. Results: Of the 6,335 patients hospitalized during the four-month period of the study, 120 patients (1.86%) who had a proven diagnosis of IFD were included in the study. These patients were divided into two groups: CAPA patients (n = 63) and CAC patients (n = 56); however, one of the 120 patients was diagnosed with Cryptoccocus neoformans infection. The mean age of the study population was 65.7 ± 13.9 years, and 78 (65.5%) of them were men. The patients were identified to have the following non-malignant comorbidities: arterial hypertension in 62 (52.1%) patients, diabetes mellitus in 34 (28.65), pre-existing lung damage similar to that observed in COPD and asthma in 20 (16.8%), and chronic renal insufficiency in 13 (10.9%) patients. The hematological malignancies were found to be the most prevalent malignancies and were identified in 20 (16.8%) patients, particularly in CAPA patients [11 (17.5%); p < 0.041]. Fiberoptic bronchoscopy with bronchoalveolar lavage fluid (BALF) and microscopic examination confirmed the presence of fungal infections in 17 (14.3%) patients. Serology testing was also performed in the majority of cases. Antibodies against Aspergillus spp. and Candida spp. were predominantly found in CAPA patients (p < 0.001). The patients were also tested for the presence of (1-3)-ß-D glucan (p < 0.019), galactomannan, and mannan in the specimens. Blood cultures were found to be positive in 45 (37.8%) patients, mostly in CAC patients. Mechanical ventilation was applied in 41 (34.5%) patients, while a non-invasive technique, such as continuous positive airway pressure (CPAP) or high-flow nasal cannula (HFNC), was used in 20 (16.8%) patients. The following antifungals were administered: echinocandins in 42 (35.3%), voriconazole in 30 (25.2%), and fluconazole in 27 (22.7%) patients. Most of the patients received systemic corticosteroids (mainly methylprednisolone), while 11 (9.16%) received favipiravir, 32 (26.67%) remdesivir, 8 (6.67%) casirivimab/imdevimab, and 5 (4.16%) sotrovimab. The outcome was lethal in 76 (63.9%) patients, predominantly CAC patients (p < 0.001). Conclusion: Invasive fungal disease is a severe complication associated with COVID-19 and accounts for increased mortality in these patients. Early identification and appropriate treatment may provide a favorable outcome.

A collection of public transport network data sets for 25 cities.

Various public transport (PT) agencies publish their route and timetable information with the General Transit Feed Specification (GTFS) as the standard open format. Timetable data are commonly used for PT passenger routing. They can also be used for studying the structure and organization of PT networks, as well as the accessibility and the level of service these networks provide. However, using raw GTFS data is challenging as researchers need to understand the details of the GTFS data format, make sure that the data contain all relevant modes of public transport, and have no errors. To lower the barrier for using GTFS data in research, we publish a curated collection of 25 cities' public transport networks in multiple easy-to-use formats including network edge lists, temporal network event lists, SQLite databases, GeoJSON files, and the GTFS data format. This collection promotes the study of how PT is organized across the globe, and also provides a testbed for developing tools for PT network analysis and PT routing algorithms.

Engineering Social Justice into Traffic Control for Self-Driving Vehicles?

The convergence of computing, sensing, and communication technology will soon permit large-scale deployment of self-driving vehicles. This will in turn permit a radical transformation of traffic control technology. This paper makes a case for the importance of addressing questions of social justice in this transformation, and sketches a preliminary framework for doing so. We explain how new forms of traffic control technology have potential implications for several dimensions of social justice, including safety, sustainability, privacy, efficiency, and equal access. Our central focus is on efficiency and equal access as desiderata for traffic control design. We explain the limitations of conventional traffic control in meeting these desiderata, and sketch a preliminary vision for a next-generation traffic control tailored to address better the demands of social justice. One component of this vision is cooperative, hierarchically distributed self-organization among vehicles. Another component of this vision is a priority system enabling selection of priority levels by the user for each vehicle trip in the network, based on the supporting structure of non-monetary credits.