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Objective: We investigated the characteristics of vertigo and dizziness developing in children during the coronavirus disease 2019 (COVID-19) pandemic. Materials and Methods: A total of 56 children aged 2–15 years old (median 12 years) with dizziness seen during the five-year period from April 2017 to March 2022 participated in this study. We performed examinations of the equilibrium function for the diagnosis. In particular, we compared the differences in the distribution of the diagnosis prior to and during the COVID-19 pandemic. Results: In both periods, the most common diagnoses were orthostatic dysregulation (OD), psychogenic vertigo, Meniere's disease, benign paroxysmal vertigo, and migrainous vertigo. The patients diagnosed as having vertigo and dizziness during COVID-19 pandemic were significantly older. Furthermore, the main causes were obviously biased towards OD during the pandemic period. Discussion and Conclusion: The prevalence of OD was about 5% in elementary school students and about 10% in junior high school students. We consider that the prolonged lockdown measures to prevent the spread of COVID-19, including school attendance restrictions, during the pandemic produced chronic stress in children, which increased the potential risk of development of OD. © 2023 Authors. All rights reserved.
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Given the recent advances in wireless communication technology, all things are being connected to networks, and it is expected that various new and novel applications will be created. The diversification in applications will yield various requirements for wireless communication. We believe that autonomous robot services will be popular after COVID, and the management, monitoring, and operation of the mobility robots requires highly reliable wireless links. In this paper, we propose a wireless link quality prediction system that uses camera images. The proposal generates a prediction model for each camera and combines the output of the models using weights calculated by the outputs of reliability models. By providing separate prediction models for each camera, the prediction system easily handles new additional cameras and drops the cameras found to have low reliability. Indoor experiments show that the proposed prediction scheme outperforms the prediction method that uses all camera images as input features without regard to their reliability. © 2022 IEEE.
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Background: Data on thrombosis and current real-world management strategies for anticoagulation therapy are important for an optimal management of patients with coronavirus disease 2019 (COVID-19) Methods: The CLOT-COVID Study (thrombosis and antiCoaguLatiOn Therapy in patients with COVID-19 in Japan Study) was a retrospective, multicenter cohort study enrolling consecutive hospitalized patients with COVID-19 among 16 centers in Japan from April 2021 to September 2021. Also subanalysis is performed for D-dimer at the admission and influence of sex with adjustment confounders with multivariable logistic regression model. Result(s): Among 2894 patients with COVID-19, 1245 (43%) received pharmacological thromboprophylaxis. The proportion of pharmacological thromboprophylaxis increased according to the severity of the COVID-19 in9.8% with mild COVID-19, 61% with moderate COVID-19, and 97% with severe COVID-19. During the hospitalization, 38 patients (1.3%)and 126 (4.4%) underwent ultrasound examinations for the lower extremities and contrastenhanced computed tomography examinations, respectively, and 55 (1.9%) developed thrombosis, mostly venous thromboembolism(71%). The incidence of thrombosis increased according to the severity of the COVID-19 in 0.2% with mild COVID-19, 1.4%withmoderate COVID-19, and 9.5%with severe COVID-19. Major bleeding occurred in 57 patients (2.0%) and 158 (5.5%) died, and 81% of them were due to respiratory failure from COVID-19 pneumonia. The higher D-dimer levels in the 3rd tertile (>=1.1 mug/mL) in 2,771 patients who had D-dimer levels measured at admission. were independently associated with a higher risk of VTE during hospitalization (adjusted odds ratio 4.83 [95% confidence interval 1.93-12.11;P<0.001];reference=1st tertile).Men had more severe status of the COVID-19 at admission compared with women (Mild: 57% versus 66%, Moderate: 34% versus 29%, and Severe: 9.1% versus 5.7%, P < 0.001). During the hospitalization, men more often developed thrombosis than women (2.5% [95%CI, 1.9-3.3%] versus 0.8% [95%CI, 0.4- 1.6%], P = 0.001). Men had numerically higher incidences of thrombosis than women in all subgroups of the worst severity of COVID-19during the hospitalization (Mild: 0.3% versus 0.0%, Moderate: 1.6% versus 1.0%, and Severe: 11.1% versus 4.3%) Conclusion(s): In the large-scale observational study, pharmacological thromboprophylaxis for hospitalized patients was common especially in patients with severe COVID-19. The overall incidence of thrombosis was substantially low with an increased incidence according to the severity of the COVID-19 in Japan. In contrast to previous studies outside Japan, the risk of thrombosis in Japanese patients with COVID-19 may be relatively low, and racial differences may have to be considered. In subanalysis higher D-dimer levels at admission were associated with a higher risk of VTE events during hospitalization. Men had more severe status of the COVID-19 than women, and the risk of development of thrombosis was higher in men compared with women.
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Background: IgA nephropathy (IgAN) flairs with gross hematuria after COVID-19 vaccination have been recently reported as adverse events of immunization, but no study to date has examined the incidence and clinical course of IgAN patients with gross hematuria following vaccination. Method(s): A single-center retrospective observational study included 301 patients with biopsy-proven IgAN and followed-up for more than 6 months with therapeutic intervention and received at least one dose of COVID-19 vaccination. We examined from medical records the incidence of gross hematuria following vaccination and also evaluated the clinical course of eGFR, spot urine protein/Cr ratio (UPCR), urinary erythrocyte count (URBC) /hpf among IgAN patients with gross hematuria following COVID-19 vaccination. Result(s): We identified 7 (3.0 %) patients with gross hematuria following COVID-19 vaccination. 6 patients were female. The median age was 42 (range, 33 to 48). Median time to develop gross hematuria after vaccination was 1 (range, 0 to 4) day and gross hematuria resolved within 3 (range, 1 to 7) days. 6 patients presented gross hematuria after the second dose. Mean baseline eGFR and UPCR before vaccination were 73.7 (IQR, 61.3 to 86.0) ml/min/1.73m2 and 0.23 (range, 0.01 to 0.70) g/g Cr, respectively, and median grade of hematuria was URBC 10-19/hpf. With mean follow up of 238.7 (range, 184 to 282) days after the onset of gross hematuria, 4 patients were introduced steroid therapy. Within one month after the onset of gross hematuria, mean eGFR decreased -13 (range, -29.2 to -5.2) % and UPCR increased +0.70 (range, +0.02 to + 2.59) g/gCr from baseline, and median grade of hematuria increased to URBC 50- 99/hpf as compared to baseline. At 6 months, mean eGFR and UPCR improved to 73.9 (IQR, 60.2 to 88.0) ml/min/1.73m2 and 0.30 (range, 0.06 to 0.74) g/g Cr, respectively, and median grade of hematuria decreased to URBC 5-9/hpf. Conclusion(s): Our study revealed the incidence of gross hematuria following vaccination in IgAN patients and also suggested that eGFR, proteinuria and hematuria may transiently worsen but improve almost to baseline with appropriate therapeutic intervention or careful follow-up.
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The global outbreak of the Coronavirus 2019 (COVID-19) has overloaded worldwide healthcare systems. Computer-aided diagnosis for COVID-19 fast detection and patient triage is becoming critical. This paper proposes a novel self-knowledge distillation based self-supervised learning method for COVID-19 detection from chest X-ray images. Our method can use self-knowledge of images based on similarities of their visual features for self-supervised learning. Experimental results show that our method achieved an HM score of 0.988, an AUC of 0.999, and an accuracy of 0.957 on the largest open COVID-19 chest X-ray dataset. © 2022 IEEE
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Introduction: It is known that the number of patients with end-stage renal failure in ASEAN countries will certainly increase in the near future. However, many of these patients cannot receive good quality hemodialysis (HD) or any HD at all, resulting in death. The HD skill in Japan is top level expertise throughout the world. Therefore, the staff of the Department of Nephrology and Hemodialysis Unit of National Center for Global Health and Medicine (NCGM) have set forth to instruct the HD staff and physicians of some HD facilities, first in Malaysia, on our good technique and method of HD, in collaboration with Tsukuba International University and other HD-related companies of Japan. This project was a part of “Projects for global growth of medical technologies, systems and services through human resource development” funded by the Ministry of Health, Labour and Welfare. Methods: 1) The staff of the Department of Nephrology and HD Unit of NCGM with the collaborators visited HD facilities in Malaysia, surveyed their level and HD technique, and instructed the staff on our HD method and technique. 2) We invited the staff of the National Kidney Foundation of Malaysia (NKF) and other staff of HD facilities to visit Japan to inspect the HD method at NCGM, Tsukuba International University and a few other exemplary HD facilities in Tokyo. Further, we discussed the differences in HD method and technique between Japan and Malaysia. 3) We proposed that the system of clinical engineers (CE) working in HD facilities, which has been successfully established in Japan, should be established to improve the skill of HD in Malaysia. 4) We produced online videos on the sophisticated HD management and practice to show staff of HD facilities in Malaysia, as we could not directly instruct them due to the COVID-19 pandemic in the recent 2 years. Results: 1) We visited various HD facilities, small and large, in Malaysia 5 times in 2016, 2017 and 2018. We not only surveyed the level and technique of HD but also gave lectures on the Japanese method of HD. 2) We invited the primary staff of NKF as well as nurses and medical staff of the HD facilities, that we visited, to come to Japan. The staff who visited Japan directly observed and inspected the method and setting of HD at NCGM, Tsukuba International University and a few other HD facilities in Tokyo. The visitors could visualize and understand the Japanese method of HD in the clinical setting, and they had good discussion with the Japanese participants. 3) We proposed to the president of NKF and other experienced nephrologists in Malaysia that it is reasonable to establish the system of CE to develop high-level HD. We also presented the necessity of CE in Malaysia at the 34th Congress of the Malaysian Society of Nephrology, 2018. 4) We produced 2 sets of videos showing lessons on dialysis machines and electrical safety, and more than 40 Malaysian staff from HD facilities of a private clinic and a university hospital viewed them. Now we are newly preparing videos on other themes which can be viewed by more HD staff working in Malaysia on demand. Conclusions: We could successfully start the spread of higher-level HD in Malaysia. We are considering appropriate strategy to further improve the technical level of HD in Malaysia via online teaching methods. Conflict of interest Potential conflict of interest: This project was funded by the Ministry of Health, Labour and Welfare.
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In this paper, we propose a method for analyzing social trends related to the coronavirus disease (COVID-19) pandemic by using social media data. The proposed method reveals that there is a correlation between tweets posted by users in Twitter and the number of infected people in a certain period. Specifically, the proposed method extracts tweet features based on the relationship between the contents and keywords of tweets. Compared to the previous approaches which focus only on the number of tweets, the proposed method can capture more richer information. Therefore, high correlation between the tweet features and the number of infected people can be obtained. For analyzing the tweets related to COVID-19, the proposed method consider not the number of tweets but the contents of the tweets. This is the main contribution of this paper. We verify the effectiveness of the proposed method through experiments on real-world datasets. © 2021 IEEE.