• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.41 no.1
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• pp.52-56
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• 2015

Clinical features of masticator-space abscess (MSA) are very similar to those of parotitis or temporomandibular disorder (TMD), making early differential diagnosis difficult. Local causes of MSA include nerve block anesthesia, infection after tooth extraction, and trauma to the temporomandibular joint (TMJ); the systemic cause is immunodeficiency. Odontogenic causes account for most etiologies, but there are also unusual causes of MSA. A 66-year-old male patient visited the emergency room (ER) presenting with left-side TMJ pain three days after receiving an acupressure massage. He was tentatively diagnosed with conventional post-trauma TMD and discharged with medication. However, the patient returned to the ER with increased pain. At this time, his TMD diagnosis was confirmed. He made a third visit to the ER during which facial computed tomographic (CT) images were taken. CT readings identified an abscess or hematoma in the left masticator space. After hospitalizing the patient, needle aspiration confirmed pus in the infratemporal and temporal fossa. Antibiotics were administered, and the abscess was drained through an incision made by the attending physician. The patient's symptoms decreased, and he was discharged.

• Clinical and Experimental Pediatrics
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• v.59 no.1
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• pp.24-29
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• 2016

Purpose: Mumps meningitis is a common complication of mumps infection; however, information on mumps meningitis in the postvaccine era is limited. The purpose of the present study was to determine factors associated with mumps meningitis and to discuss the effect of vaccination on this disease. Methods: We retrospectively reviewed patients younger than 19 years with mumps, diagnosed at a university hospital in Korea between 2003 and 2013. Patients were divided into groups with and without meningitis, and the clinical features of the 2 groups were compared. Results: The study enrolled 119 patients: 19 patients with meningitis and 100 patients without. Univariate analysis showed that older age (median: 15 years vs. 9.5 years, respectively), a longer interval from last vaccination (median: 10.2 years vs. 4.8 years, respectively), and febrile presentation (94.7% vs. 31.0%, respectively) were significantly associated with mumps meningitis. Sex, number of vaccination doses, bilateral parotitis, and the presence of complications other than meningitis did not differ between the 2 groups. In multivariate logistic regression analysis, age (odds ratio, 1.38; 95% confidence interval, 1.01-1.89; P=0.04) and fever (odds ratio, 30.46; 95% confidence interval, 3.27-283.61; P<0.01) remained independent factors for mumps meningitis. Conclusion: Clinicians in the postvaccine era should be aware of the possibility of mumps meningitis in febrile cases of mumps in adolescents, regardless of the number of vaccination doses. To establish the role of vaccination in mumps meningitis, further studies will be necessary.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.139-148
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• 2020

Infectious diseases have long plagued mankind, and predicting and preventing them has been a big challenge for mankind. For this reasen, various studies have been conducted so far to predict infectious diseases. Most of the early studies relied on epidemiological data from the Centers for Disease Control and Prevention (CDC), and the problem was that the data provided by the CDC was updated only once a week, making it difficult to predict the number of real-time disease outbreaks. However, with the emergence of various Internet media due to the recent development of IT technology, studies have been conducted to predict the occurrence of infectious diseases through web data, and most of the studies we have researched have been using single Web data to predict diseases. However, disease forecasting through a single Web data has the disadvantage of having difficulty collecting large amounts of learning data and making accurate predictions through models for recent outbreaks such as "COVID-19". Thus, we would like to demonstrate through experiments that models that use multiple Web data to predict the occurrence of infectious diseases through LSTM models are more accurate than those that use single Web data and suggest models suitable for predicting infectious diseases. In this experiment, we predicted the occurrence of "Malaria" and "Epidemic-parotitis" using a single web data model and the model we propose. A total of 104 weeks of NEWS, SNS, and search query data were collected, of which 75 weeks were used as learning data and 29 weeks were used as verification data. In the experiment we predicted verification data using our proposed model and single web data, Pearson correlation coefficient for the predicted results of our proposed model showed the highest similarity at 0.94, 0.86, and RMSE was also the lowest at 0.19, 0.07.