Background Postviral olfactory loss after upper respiratory tract infection (URI) is not uncommon. However, its exact location and nature are not fully understood. Although it is likely to be caused by a direct damage of olfactory epithelium, a damage of the central pathway has also been suspected as its possible mechanism. This study will show basal metabolism in the brain of patients with postviral olfactory loss using fluorodeoxyglucose-positron emission tomography (FDG PET). Methods Nine patients with postviral olfactory dysfunction were enrolled. All of the patients had neither apparent sinusitis nor rhinitis. All of them recalled causative URI and temporal connection with development of their olfactory loss. After olfactory function tests using the butanol threshold test and smell identification test confirmed olfactory impairment, FDG PET studies were performed during a rest state. The cerebral metabolic abnormality was compared between the patients and age/gender-matched healthy controls using a voxel-wised analysis. Results In comparison with healthy controls, the patients showed a significant hypometabolism in the right piriform cortex and bilateral amygdala and parahippocampal areas where the olfactory neurons primarily project. Furthermore, hypometabolism was also shown in the bilateral insular cortices, medial and lateral temporal cortex where the olfactory information is integrated to produce the sensation. Increased metabolism was not found in any brain area. Conclusion This study showed that the postviral olfactory loss is likely to be associated with decreased metabolism in the specific brain regions where the olfactory information is received and integrated.
The oxidative stress in OSA was related to central obesity rather than intermittent hypoxia or respiratory disturbances. To control cardiovascular complications in OSA, weight reduction should be a component in the treatment strategy.
No studies for the role of adenotonsillar hypertrophy in development of dentofacial abnormalities have been performed in Asian pediatric population. Thus, we aimed to investigate the relationship between adenotonsillar hypertrophy and dentofacial abnormalities in Korean children. The present study included consecutive children who visited a pediatric clinic for sleep-disordered breathing due to habitual mouth breathing, snoring or sleep apnea. Their palatine tonsils and adenoids were graded by oropharyngeal endoscopy and lateral cephalometry. Anterior open bite, posterior crossbite, and Angle's class malocclusions were evaluated for dentofacial abnormality. The receiver-operating characteristic curve analysis was used to identify age cutoffs to predict dentofacial abnormality. A total of 1,083 children were included. The presence of adenotonsillar hypertrophy was significantly correlated with the prevalence of dentofacial abnormality [adjusted odds ratio = 4.587, 95% CI (2.747-7.658)] after adjusting age, sex, body mass index, allergy, and Korean version of obstructive sleep apnea-18 score. The cutoff age associated with dentofacial abnormality was 5.5 years (sensitivity = 75.5%, specificity = 67%) in the children with adenotonsillar hypertrophy and 6.5 years (sensitivity = 70.6%, specificity = 57%) in those without adenotonsillar hypertrophy. In conclusion, adenotonsillar hypertrophy may be a risk factor for dentofacial abnormalities in Korean children and early surgical intervention could be considered with regards to dentofacial abnormality.
Background Prevention and management of chronic diseases are the main goals of national health maintenance programs. Previously widely used screening tools, such as Health Risk Appraisal, are restricted in their achievement this goal due to their limitations, such as static characteristics, accessibility, and generalizability. Hypertension is one of the most important chronic diseases requiring management via the nationwide health maintenance program, and health care providers should inform patients about their risks of a complication caused by hypertension. Objective Our goal was to develop and compare machine learning models predicting high-risk vascular diseases for hypertensive patients so that they can manage their blood pressure based on their risk level. Methods We used a 12-year longitudinal dataset of the nationwide sample cohort, which contains the data of 514,866 patients and allows tracking of patients’ medical history across all health care providers in Korea (N=51,920). To ensure the generalizability of our models, we conducted an external validation using another national sample cohort dataset, comprising one million different patients, published by the National Health Insurance Service. From each dataset, we obtained the data of 74,535 and 59,738 patients with essential hypertension and developed machine learning models for predicting cardiovascular and cerebrovascular events. Six machine learning models were developed and compared for evaluating performances based on validation metrics. Results Machine learning algorithms enabled us to detect high-risk patients based on their medical history. The long short-term memory-based algorithm outperformed in the within test (F1-score=.772, external test F1-score=.613), and the random forest-based algorithm of risk prediction showed better performance over other machine learning algorithms concerning generalization (within test F1-score=.757, external test F1-score=.705). Concerning the number of features, in the within test, the long short-term memory-based algorithms outperformed regardless of the number of features. However, in the external test, the random forest-based algorithm was the best, irrespective of the number of features it encountered. Conclusions We developed and compared machine learning models predicting high-risk vascular diseases in hypertensive patients so that they may manage their blood pressure based on their risk level. By relying on the prediction model, a government can predict high-risk patients at the nationwide level and establish health care policies in advance.
ObjectivesAlthough adenotonsillar hypertrophy is the main cause of sleep-disordered breathing in children, surrounding anatomic factors, such as the width of the nasopharynx, can affect upper airway patency. However, there have been no reports of the association of nasopharyngeal width with sleep-disordered breathing in children. This study was undertaken to measure nasopharyngeal width in children undergoing adenotonsillectomy for sleep-disordered breathing and to investigate the clinical implications of this factor.MethodsThis was a retrospective study with a follow-up period of 1 year, performed at a tertiary referral center. We reviewed the operative records of children who underwent adenotonsillectomy at our center for symptoms of sleep-disordered breathing, such as snoring, apnea, and mouth breathing. The nasopharyngeal width was measured immediately before adenotonsillectomy, which was performed under general anesthesia with a microscopy-assisted mirror view. Adenotonsillar hypertrophy was graded on a four-point scale, and symptoms of sleep-disordered breathing were evaluated by using the Korean version of the Obstructive Sleep Apnea-18 questionnaire before and after surgery. The relationships between the average nasopharyngeal width and patient age and sex, adenotonsillar hypertrophy, and the Korean version of the Obstructive Sleep Apnea-18 score were analyzed.ResultsThe study included 549 children (343 boys) with a mean age of 6.0 years (range, 2 to 11 years). The average nasopharyngeal width was 11.9 mm (range, 7.0 to 18.0 mm) and increased with age (range, 11.2 to 13.3; β=0.264; P<0.001). At 1 year after surgery, children with a greater nasopharyngeal width at the time of surgery exhibited additional improvements in symptoms of obstruction relative to those at 1 month after surgery.ConclusionThe average nasopharyngeal width in children is approximately 11.9 mm and exhibits a slight increase with age. The width of the nasopharynx may be a factor associated with the degree of improvement in symptoms of sleep-disordered breathing after adenotonsillectomy.
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