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Background: Azvudine (FNC) is a promising treatment candidate for managing coronavirus disease 2019 (COVID-19). However, drug interactions with azvudine have been poorly studied, especially with no reported cases of azvudine with anticoagulants such as warfarin and rivaroxaban. Case summary: The patient was diagnosed with lower limb venous thrombosis and took warfarin regularly. The international normalized ratio (INR) was stable (2.0-3.0). However, the INR increased to 7.52 after administering azvudine. The patient had no other factors justifying this change. This increase in INR occurred again with the administration of azvudine in combination with rivaroxaban, and the INR increased to 18.91. After azvudine administration was stopped, the INR did not increase when rivaroxaban was used alone. Conclusion: Azvudine, warfarin, and rivaroxaban might have previously unidentified drug interactions that increased the INR. Therefore, the INR must be closely monitored when they are concomitantly administered in COVID-19 patients.
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With the popularity of portable positioning devices, crowd-sourced trajectory data have attracted widespread attention, and led to many research breakthroughs in the field of road network extraction. However, it is still a challenging task to detect the road networks of old downtown areas with complex network layouts from high noise, low frequency, and uneven distribution trajectories. Therefore, this paper focuses on the old downtown area and provides a novel intersection-first approach to generate road networks based on low quality, crowd-sourced vehicle trajectories. For intersection detection, virtual representative points with distance constraints are detected, and the clustering by fast search and find of density peaks (CFDP) algorithm is introduced to overcome low frequency features of trajectories, and improve the positioning accuracy of intersections. For link extraction, an identification strategy based on the Delaunay triangulation network is developed to quickly filter out false links between large-scale intersections. In order to alleviate the curse of sparse and uneven data distribution, an adaptive link-fitting scheme, considering feature differences, is further designed to derive link centerlines. The experiment results show that the method proposed in this paper preforms remarkably better in both intersection detection and road network generation for old downtown areas.
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Purpose: We hypothesized that increased level of serum ß2-microglobulin (ß2M) is an independent factor associated with higher mortality in hospitalized patients with exacerbated chronic obstructive pulmonary disease (COPD). Patients and Methods: We retrospectively analyzed 488 hospitalized patients with exacerbated COPD as the first diagnosis at Beijing Chao-Yang hospital, P. R. China between December 31st, 2012 and December 28th, 2017. Concentrations of serum ß2M and other clinical indexes were measured or collected on admission, and all patients were followed up to 90 days. The relationship between ß2M and 30- and 90-day all-cause mortality was explored by Cox regression analysis adjusted for age, C-reactive protein values, N-terminal pro-brain natriuretic peptide/100, respiratory failure [RF, defined as partial arterial oxygen pressure (PaO2) <60 mmHg on room air or PaO2 over the fraction of inspired oxygen (PaO2/FiO2) < 300], eosinopenia, consolidation, and acidaemia. Results: Median concentrations of ß2M were significantly higher in non-survivals compared to survivals within 30 days (4.11 mg/L (IQR 3.10-6.60) vs 2.79mg/L (IQR 2.13-3.76), P < 0.001) and 90 days (3.79 mg/L (IQR 2.61-6.69) vs 2.79 mg/L (IQR 2.13-3.73), P < 0.001). Serum levels of ß2M were correlated with 30-day and 90-day mortality in overall exacerbated COPD patients, with hazard ratios (HRs) of 1.09 (95% CI 1.04-1.14, P = 0.001) and 1.09 (95% CI 1.05-1.14, P < 0.001). In exacerbated COPD patients without RF and with RF, the HRs were 1.06 (95% CI 0.995-1.137, P = 0.069) and 1.14 (95% CI 1.02-1.27, P = 0.021) for 30-day mortality, 1.09 (95% CI 1.02-1.15, P = 0.010) and 1.14 (95% CI 1.03-1.26, P = 0.014) for 90-day mortality, respectively. Conclusion: Our data showed that concentrations of serum ß2M were associated with an increased risk of mortality, suggesting that ß2M might be a valuable predictor of poor prognosis for hospitalized patients with exacerbated COPD.