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Purpose: Laryngeal fracture is rare, but complications are frequent and severe. Controversy still exists in regards to its proper management. The aim of this study was to present the clinical findings and management of laryngeal fracture in Korea. Materials and Methods: We analyzed the medical records of 22 patients with laryngeal fracture at a tertiary care trauma center from 2000 to 2010 retrospectively. Results: In total, 22 patients (19 men and 3 woman) presented with laryngeal fractures caused by blunt (n=13) or penetrating (n=9) injury. Pain (68.1%), odynophagia (68.1%), hoarseness (18.1%), hemoptysis (13.6%), and subcutaneous emphysema (9%) were the common presenting symptoms and noncomminuted fracture was common. High velocity blunt trauma (mostly traffic accidents) patients had more extensive injury and poor voice outcomes. Penetrating trauma patients due to physical assault or suicide attempt demonstrated more frequently injuries on the left side. Conclusion: In driver-caused traffic accidents, where injuries in a wide area within the larynx occurred, poor voice results were seen, and these injuries required aggressive treatment. When endotracheal intubation was performed at experienced emergency centers with fiberoptic laryngoscopes, airway management was safely achieved. In addition, if the fractured laryngeal framework was corrected at appropriate times, voice results were good.
Penetrating neck injuries are potentially dangerous and require emergent management because of the presence of vital structures in the neck. Penetrating vascular trauma to zone I and III of the neck is potentially life-threatening. An accurate diagnosis and adequate surgical intervention are critical to the successful outcome of penetrating trauma in the neck. We experienced some cases with externally penetrating injuries in neck zone II in which the patients were confirmed to have the presence of large vessel injuries in neck zones I and III. Here we report on the endovascular stent techniques used in two cases to address penetrating carotid artery injuries and review the literature.
A novel location estimation method using IoT (Internet of Things) sensors to detect classified service areas in subway stations for smart station was presented in this paper. Using RSSI (Received Signal Strength Indicator) values of BLE (Bluetooth Low Energy) Beacons, virtual areas are divided electromagnetically according to specific service facilities for IoT service of smart station. The virtual service area is called Zone. MLP (Multi-Layer Perceptron) algorithm is applied to recognize the assigned Zone with the received RSSIs from multiple IoT sensors constructed in a real subway station. For verification of the proposed method, an experimental test was carried out in a real subway station environment. For recognition of 2 divided zones, 10 sensors were used with different transmitting power levels. From the test results, it was noticed that experimentally obtained zone recognition accuracy was 78.1% for a real subway station environment. The proposed zone-based location positioning method is expected to contribute to activation of user-centered real-time IoT services in smart stations. 본 논문에서는 향후 스마트스테이션 역사내 IoT (Internet of Things) 센서를 이용하여 특정 서비스 지역을 감지하는 위치 추정 방법을 제시하였다. IoT 센서로 사용된 BLE (Bluetooth Low Energy) 비콘의 수신신호강도 값으로부터 IoT 서비스의 시설에 따른 가상 영역을 분할하였다. 실제 지하철 역사 내에 구성된 여러 IoT 센서에서 수신 된 수신 신호강도 값들은 다층 퍼셉트론 알고리즘을 이용하여 할당 된 영역을 인식하게 된다. 제안 된 방법의 검증을 위해 실제 지하철 역사 환경에서 실험을 수행 하였다. 실제 지하철 역사 내 2 개의 분할 구역을 인식하기 위하여 10 개의 센서가 서로 다른 전송 전력 레벨로 사용되었다. 결과적으로 약 78.1%의 영역 인식 정확도를 확인 하였다. 제안된 서비스 영역 (Zone) 기반의 이용객 위치측위 방법이 향후 스마트스테이션에서 이용객 중심의 실시간 IoT 서비스 활성화에 기여할 것으로 기대된다.
In the field of computer vision, visual surveillance systems have recently become an important research topic. Growth in this area is being driven by both the increase in the availability of inexpensive computing devices and image sensors as well as the general inefficiency of manual surveillance and monitoring. In particular, the ultimate goal for many visual surveillance systems is to provide automatic activity recognition for events at a given site. A higher level of understanding of these activities requires certain lower-level computer vision tasks to be performed. So in this paper, we propose an intelligent activity recognition model that uses a structure learning method and a classification method. The structure learning method is provided as a K2-learning algorithm that generates Bayesian networks of causal relationships between sensors for a given activity. The statistical characteristics of the sensor values and the topological characteristics of the generated graphs are learned for each activity, and then a neural network is designed to classify the current activity according to the features extracted from the multiple sensor values that have been collected. Finally, the proposed method is implemented and tested by using PETS2013 benchmark data.
Diffuse alveolar hemorrhage (DAH) is an acute, life-threatening event. The blood-gas barrier must be very thin to allow gas exchange and is therefore subjected to high mechanical stresses when the capillary pressure rises. In general anesthesia, inhaled gases cause high mechanical stresses, and thus DAH occurs under certain conditions. We describe a case of inferred postoperative DAH. A 25-year-old man had an acute episode after undergoing a tonsillectomy for snoring. During surgery, no problems occurred and no marked bleeding was observed. After removal of the endotracheal tube, however, the patient had severe cough and hemoptysis. The patient was treated with an antihemorrhagic agent and antibiotics. He recovered after 1 week. Chronic snoring likely caused the alveolar damage in this patient and intubation led to DAH. The patient presented with a benign course that regressed spontaneously with medical intervention.
The malignant neoplasm of thyroglossal duct cyst (TGDC) is a rare tumor and is mostly revealed accidently in the course of histologic examinations after surgery. The most common histopathologic type is a papillary carcinoma. We experience a 25-year-old young woman of papillary carcinoma in thyroglossal duct cyst and the position of pyramidal lobe was unusual. She was treated by Sistrunk’s operation with total thyroidectomy. We report this case with a review of literature.
Background and Objectives:Hyper-responsivenes to nonspecific stimuli is a characteristic finding of all allergic diseases. It the whole mechanism has not been clearly established. We aimed to understand the role of inducible nitric oxide synthase (iNOS) expresion in nasal hyper-responsivenes of rhinosinusitis. Materials and Method:1) To develop a platelet activating factor (PAF)-induced rhinosinusitis rat model, 50 μl of 16 μg/ml PAF was applied into the nose of rats. At days 1, 3 and 5, the rats were killed. 2) μl of 10 μM capsaicin was applied intranasaly and the amount of microvascular leakage in the nasal mucosa was measured with Evans blue asay at days 1, 3 and 5 in the rhinosinusitis model and the control rats. 3) To examine the efect of iNOS, 75 mg/kg of aminoguanidine was pretreated systemicaly 1 hour before the application of capsaicin. 4) To localize the expresion of iNOS, immunohistochemical staining was performed using the avidin-biotin-peroxidase method with an anti-iNOS antibody. Results:Induction of rhino-ium, varied according to the time interval, were observed. A significant enhancement of microvascular leakage was clearly demon-strated by topicaly applied capsaicin, which was completely blocked by aminoguanidine, the iNOS inhibitor in the PAF-induced rhinosinusitis. The expression of iNOS was localized in the inflamatory cells infiltrated in the mucosa. Conclusion:The expression of iNOS in the inflamatory cells as well as epithelial damage related to eosinophil infiltration may cause nasal hyper-responsivenes. (Korean J Otolaryngol 203 ;46 :35-41)