Dutch Oncology COVID-19 consortium:Outcome of COVID-19 in patients with cancer in a nationwide cohort study

Aim of the study: Patients with cancer might have an increased risk for severe outcome of coronavirus disease 2019 (COVID-19). To identify risk factors associated with a worse outcome of COVID-19, a nationwide registry was developed for patients with cancer and COVID-19. Methods: This observational cohort study has been designed as a quality of care registry and is executed by the Dutch Oncology COVID-19 Consortium (DOCC), a nationwide collaboration of oncology physicians in the Netherlands. A questionnaire has been developed to collect pseudonymised patient data on patients' characteristics, cancer diagnosis and treatment. All patients with COVID-19 and a cancer diagnosis or treatment in the past 5 years are eligible. Results: Between March 27th and May 4th, 442 patients were registered. For this first analysis, 351 patients were included of whom 114 patients died. In multivariable analyses, age ≥65 years (p < 0.001), male gender (p = 0.035), prior or other malignancy (p = 0.045) and active diagnosis of haematological malignancy (p = 0.046) or lung cancer (p = 0.003) were independent risk factors for a fatal outcome of COVID-19. In a subgroup analysis of patients with active malignancy, the risk for a fatal outcome was mainly determined by tumour type (haematological malignancy or lung cancer) and age (≥65 years). Conclusion: The findings in this registry indicate that patients with a haematological malignancy or lung cancer have an increased risk of a worse outcome of COVID-19. During the ongoing COVID-19 pandemic, these vulnerable patients should avoid exposure to severe acute respiratory syndrome coronavirus 2, whereas treatment adjustments and prioritising vaccination, when available, should also be considered

Let's You Do That: Enquiries into the Cognitive Burdens of Dialogue

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Modularity and the processing of closed-class words

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On the throughput efficiency of greedy maximal scheduling in wireless ad hoc networks

Due to its low complexity, Greedy Maximal Scheduling (GMS), also known as Longest Queue First (LQF), has been studied extensively for wireless networks. However, GMS can result in degraded throughput performance in general wireless networks. In this thesis, we derive performance bounds of GMS for wireless networks under the general k-hop interference model. In particular, we prove that GMS achieves 100% throughput in all networks with eight nodes or less, under the two-hop interference model. Further, the obtained performance bounds improve upon previous results for larger networks up to a certain size. We also provide a simple proof to show that GMS can be implemented using only local neighborhood information in networks of any size

The HCRC Map Task corpus

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Shared Responsibility in Dialogue: Attending to the Interlocutor's Knowledge and the Interlocutor's Problems

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