Evaluierung der NEF-Fehl- und Übergabeeinsätze im Raum Innsbruck

Die Anaesthesiologie - Die Qualität eines Rettungssystems zeichnet sich auch durch den effizienten Einsatz seiner personellen und Fahrzeugressourcen aus. So können im berechtigten Fall...     

Internet of things-based health monitoring system for early detection of cardiovascular events during COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) has currently caused the mortality of millions of people around the world. Aside from the direct mortality from the COVID-19, the indirect effects of the pandemic have also led to an increase in the mortality rate of other non-COVID patients. Evidence indicates that novel COVID-19 pandemic has caused an inflation in acute cardiovascular mortality, which did not relate to COVID-19 infection. It has in fact increased the risk of death in cardiovascular disease (CVD) patients. For this purpose, it is dramatically inevitable to monitor CVD patients’ vital signs and to detect abnormal events before the occurrence of any critical conditions resulted in death. Internet of things (IoT) and health monitoring sensors have improved the medical care systems by enabling latency-sensitive surveillance and computing of large amounts of patients’ data. The major challenge being faced currently in this problem is its limited scalability and late detection of cardiovascular events in IoT-based computing environments. To this end, this paper proposes a novel framework to early detection of cardiovascular events based on a deep learning architecture in IoT environments. Experimental results showed that the proposed method was able to detect cardiovascular events with better performance (95.30% average sensitivity and 95.94% mean prediction values).     

Riesgo de recurrencia tras retirada de la anticoagulación en pacientes con enfermedad tromboembólica venosa no provocada: validación externa del nomograma de Viena y del modelo predictivo DASH

IntroductionScales for predicting venous thromboembolism (VTE) recurrence are useful for deciding the duration of the anticoagulant treatment. Although there are several scales, the most appropriate for our setting has not been identified. For this reason, we aimed to validate the DASH prediction score and the Vienna nomogram at 12 months.MethodsThis was a retrospective study of unselected consecutive VTE patients seen between 2006 and 2014. We compared the ability of the DASH score and the Vienna nomogram to predict recurrences of VTE. The validation was performed by stratifying patients as low-risk or high-risk, according to each scale (discrimination) and comparing the observed recurrence with the expected rate (calibration).ResultsOf 353 patients evaluated, 195 were analyzed, with an average age of 53.5 ± 19 years. There were 21 recurrences in 1 year (10.8%, 95% CI: 6.8%-16%). According to the DASH score, 42% were classified as low risk, and the rate of VTE recurrence in this group was 4.9% (95% CI: 1.3%-12%) vs. the high-risk group that was 15% (95% CI: 9%-23%) (p <.05). According to the Vienna nomogram, 30% were classified as low risk, and the rate of VTE recurrence in the low risk group vs. the high risk group was 4.2% (95% CI:0.5%-14%) vs. 16.2% (95% CI: 9.9%-24.4%) (p <.05).ConclusionsOur study validates the DASH score and the Vienna nomogram in our population. The DASH prediction score may be the most advisable, both because of its simplicity and its ability to identify more low-risk patients than the Vienna nomogram (42% vs. 30%).     

HLA markers in familial Lichen Sclerosus

Background: Lichen sclerosus (LS) has been identified with increased frequency in families,often associated with HLA markers, mainly DQ7. A genetic co‐etiology seems likely in this setting. Moreover, there is an association of LS with autoimmune disorders, such as the presence of anti‐thyroid peroxidase autoantibodies (anti‐TPO), a hallmark of autoimmune thyroid diseases. Patients and Methods: In 3 families affected by LS, we verified their HLA markers, and identified previously undiagnosed cases of LS and autoimmune disorders. 30 individuals were examined with history, skin biopsy, HLA class I and II typing by PCR‐SSP, and measurement of anti‐TPO, free thyroxine and thyroidstimulating hormones (TSH) levels. Results: There were 8 cases of LS, 50 % of them anti‐TPO+. Autoimmune disorders were found in 40 % (total) and in 87.5 % of those affected. Most common HLA markers were B*15, B*57, CW*03, CW*07, CW*18, DRB1*04, DRB1*07, DRB4*. The three latter have been previously associated with LS. Conclusion: New cases of LS and autoimmune disorders can be detected in first degree relatives of patients with LS. The presence of anti‐TPO antibodies strongly suggests autoimmune thyroiditis. There is intra‐familial association between the haplotype HLA‐B*15 ‐DRB1*04 ‐DRB4* and anti‐TPO,emphasizing their link with thyroiditis. New familial approaches might help to make clear the pathogenesis of LS and its association with autoimmune diseases.