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BACKGROUND AND OBJECTIVE: Chronic respiratory diseases in children deteriorate their daily life due to dyspnea and reduced lung function. We aimed to evaluate the feasibility of home-based pulmonary rehabilitation in pediatric chronic respiratory diseases. METHODS: This prospective, single-arm, cohort study included children with chronic lung disease. They were instructed to perform home-based pulmonary rehabilitation 30 min/session, three sessions/week for three months. Pulmonary function test (PFT) using spirometry, respiratory muscle strength (RMT), cardiopulmonary exercise test (CPET), 6 min walk test (6MWT), dyspnea questionnaires, speech evaluation, and pediatric quality of life inventory (PedsQL) were assessed pre- and post-pulmonary rehabilitation. Compliance and satisfaction of the program were also evaluated. RESULTS: Twenty children (mean age: 11.2 ± 3.1 years) with chronic respiratory diseases without cardiopulmonary instability participated. The overall compliance was 71.1% with no related adverse events. After pulmonary rehabilitation, forced expiratory volume in one second (FEV1), peak expiratory flow (PEF), RMT, 6MWT, dyspnea questionnaire, speech rate, and PedsQL (child) significantly improved (p < 0.05), particularly better in the FEV1 < 60% group than in the FEV1 ≥ 60% group and in the high-compliance group (compliance ≥ 50%) than in the low-compliance group (compliance < 50%). CONCLUSIONS: Home-based pulmonary rehabilitation for children with chronic lung disease was feasible with high compliance and effective in terms of objective functions, subjective dyspnea symptom, and quality of life.
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BACKGROUND/AIMS: Sedation has become a standard practice for patients undergoing gastrointestinal (GI) endoscopy. However, considering the serious cardiopulmonary adverse events associated with sedatives, it is important to identify patients at high risk. Machine learning can generate reasonable prediction for a wide range of medical conditions. This study aimed to evaluate the risk factors associated with sedation during GI endoscopy and develop a predictive model for hypoxia during endoscopy under sedation. METHODS: This prospective observational study enrolled 446 patients who underwent sedative endoscopy at the Korea University Ansan Hospital. Clinical data were used as predictor variables to construct predictive models using the random forest method that is a machine learning algorithm. RESULTS: Seventy-two of the 446 patients (16.1%) experienced life-threatening hypoxia requiring immediate medical intervention. Patients who developed hypoxia had higher body weight, body mass index (BMI), neck circumference, and Mallampati scores. Propofol alone and higher initial and total dose of propofol were significantly associated with hypoxia during sedative endoscopy. Among these variables, high BMI, neck circumference, and Mallampati score were independent risk factors for hypoxia. The area under the receiver operating characteristic curve for the random forest-based predictive model for hypoxia during sedative endoscopy was 0.82 (95% confidence interval, 0.79-0.86) and displayed a moderate discriminatory power. CONCLUSIONS: High BMI, neck circumference, and Mallampati score were independently associated with hypoxia during sedative endoscopy. We constructed a model with acceptable performance for predicting hypoxia during sedative endoscopy.
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BACKGROUND: The increased expression of the nicotinic acetylcholine receptor (nAChR) in muscle denervation is thought to be associated with electrophysiological acetylcholine supersensitivity after nerve injury. Hence, we investigated the utility of the 18F-ASEM alpha7-nAChR targeting radiotracer as a new diagnostic method by visualizing skeletal muscle denervation in mouse models of sciatic nerve injury. METHODS: Ten-week-old C57BL/6 male mice were utilized. The mice were anesthetized, and the left sciatic nerve was resected after splitting the gluteal muscle. One week (n = 11) and three weeks (n = 6) after the denervation, 18F-ASEM positron emission tomography/magnetic resonance imaging (PET/MRI) was acquired. Maximum standardized uptake values (SUVmax) of the tibialis anterior muscle were measured for the denervated side and the control side. Autoradiographic evaluation was performed to measure the mean counts of the denervated and control tibialis anterior muscles at one week. In addition, immunohistochemistry was used to identify alpha7-nAChR-positive areas in denervated and control tibialis anterior muscles at one week (n = 6). Furthermore, a blocking study was conducted with methyllycaconitine (MLA, n = 5). RESULTS: 18F-ASEM PET/MRI showed significantly increased 18F-ASEM uptake in the denervated tibialis anterior muscle relative to the control side one week and three weeks post-denervation. SUVmax of the denervated muscles at one week and three weeks showed significantly higher uptake than the control (P = 0.0033 and 0.0277, respectively). The relative uptake by autoradiography for the denervated muscle was significantly higher than in the control, and immunohistochemistry revealed significantly greater alpha7-nAChR expression in the denervated muscle (P = 0.0277). In addition, the blocking study showed no significant 18F-ASEM uptake in the denervated side when compared to the control (P = 0.0796). CONCLUSIONS: Our results suggest that nAChR imaging with 18F-ASEM has potential as a noninvasive diagnostic method for peripheral nervous system disorders.
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PURPOSE: Vestibular schwannoma is a benign tumor originating from Schwann cells surrounding the eighth cranial nerve and can cause hearing loss, tinnitus, balance problems, and facial nerve disorders. Because of the slow growth of the tumor, predicting the hearing function of patients with vestibular schwannoma's is important to obtain information that would be useful for deciding the treatment modality. This study aimed to analyze the association between magnetic resonance imaging features and hearing status using a new radiomics technique. METHODS: We retrospectively analyzed 115 magnetic resonance images and hearing results from 73 patients with vestibular schwannoma. A total of 70 radiomics features from each tumor volume were calculated using T1-weighted magnetic resonance imaging. Radiomics features were classified as histogram-based, shape-based, texture-based, and filter-based. The least absolute shrinkage and selection operator method was used to select the radiomics features among the 70 features that best predicted the hearing test. To ensure the stability of the selected features, the least absolute shrinkage and selection operator method was repeated 10 times. Finally, features set five or more times were selected as radiomics signatures. RESULTS: The radiomics signatures selected using the least absolute shrinkage and selection operator method were: minimum, variance, maximum 3D diameter, size zone variance, log skewness, skewness slope, and kurtosis slope. In random forest, the mean performance was 0.66 (0.63-0.77), and the most important feature was Log skewness. CONCLUSIONS: Newly developed radiomics features are associated with hearing status in patients with vestibular schwannoma and could provide information when deciding the treatment modality.