Bilateral tension pneumothorax caused by an abrupt increase in airway pressure during cervical spine surgery in the prone position -A case report-

Elevated peak inspiratory airway pressure (PIP) can occur during general anesthesia and is usually easily rectified. In rare circumstances it can lead to potentially fatal conditions such as tension pneumothorax. We report on a 77-year-old male patient admitted for a cervical laminoplasty. The preoperative chest radiograph showed normal findings and there was no medical history of allergy or underlying airway inflammation. Anesthesia induction and maintenance progressed uneventfully. However, 5 minutes after prophylactic antibiotic administration, PIP suddenly increased and blood pressure dropped. The operation was abandoned and the patient was moved to a supine position to perform chest radiography. Cardiac arrest occurred, and cardiopulmonary resuscitation was performed. The radiograph showed bilateral tension pneumothorax. Needle aspiration was immediately performed, and chest tubes were inserted. Ventilation rapidly improved and the vital signs normalized. The patient was discharged without sequelae on postoperative day 36

Spinal epidural hematoma related to an epidural catheter in a cardiac surgery patient -A case report-

The addition of thoracic epidural anesthesia to general anesthesia during cardiac surgery may have a beneficial effect on clinical outcome. However, epidural catheter insertion in a patient anticoagulated with heparin may increase the risk of epidural hematoma. We report a case of epidural hematoma in a 55-year-old male patient who had a thoracic epidural placed under general anesthesia preceding uneventful mitral valve replacement and tricuspid valve annular plasty. During the immediate postoperative period and first postoperative day, prothrombin time (PT) and activate partial thromboplastin time (aPTT) were mildly prolonged. On the first postoperative day, he complained of motor weakness of the lower limbs and back pain. An immediate MRI of the spine was performed and it revealed an epidural hematoma at the T5-6 level. Rapid surgical decompression resulted in a recovery of his neurological abnormalities to near normal levels. Management and preventing strategies of epidural hematoma are discussed

A Case of Granular Cell Tumor of the Trachea

A 20-year-old man presented to our outpatient clinic with hemoptysis, cough, and pleuritic chest pain. His chest radiograph and pulmonary function tests (PFT) were normal. A bronchoscopy showed a small yellowish patch with a regular surface. A direct bronchoscopic biopsy was performed. The pathologic findings showed a benign granular cell tumor. The respiratory symptoms resolved after biopsying the tumor. On follow.up, there were no signs of recurrence of the granular cell tumor after a period of 24 months

Predicting factors of present hepatitis C virus infection among patients positive for the hepatitis C virus antibody

Background/AimsTo identify the predicting factors of present hepatitis C virus (HCV) infection among patients with positivity for antibodies to HCV (anti-HCV).MethodsWe analyzed patients who showed positive enzyme immunoassay (EIA) results and performed an HCV RNA test as a confirmatory test at Kyung Hee University Hospital at Gangdong from June 2006 to July 2012. The features distinguishing the groups with positive and negative HCV RNA results were reviewed.ResultsIn total, 490 patients were included. The results of the HCV RNA test were positive and negative in 228 and 262 patients, respectively. The index value of anti-HCV, mean age, platelet counts, total bilirubin, prothrombin time international normalized ratio, albumin and alanine transaminase (ALT) levels differed significantly between the two groups. On multivariable analysis, an index value of anti-HCV >10 [odds ratio (OR)=397.27, P40 IU/L (OR=3.64, P=0.001), and albumin <3.8 g/dL (OR=2.66, P=0.014) were related to present HCV infection.ConclusionsAlthough EIA is not a quantitative test, considering the anti-HCV titer with ALT and albumin levels may be helpful in predicting present of HCV infection

Stroke awareness decreases prehospital delay after acute ischemic stroke in korea

BACKGROUND: Delayed arrival at hospital is one of the major obstacles in enhancing the rate of thrombolysis therapy in patients with acute ischemic stroke. Our study aimed to investigate factors associated with prehospital delay after acute ischemic stroke in Korea. METHODS: A prospective, multicenter study was conducted at 14 tertiary hospitals in Korea from March 2009 to July 2009. We interviewed 500 consecutive patients with acute ischemic stroke who arrived within 48 hours. Univariate and multivariate analyses were performed to evaluate factors influencing prehospital delay. RESULTS: Among the 500 patients (median 67 years, 62% men), the median time interval from symptom onset to arrival was 474 minutes (interquartile range, 170-1313). Early arrival within 3 hours of symptom onset was significantly associated with the following factors: high National Institutes of Health Stroke Scale (NIHSS) score, previous stroke, atrial fibrillation, use of ambulance, knowledge about thrombolysis and awareness of the patient/bystander that the initial symptom was a stroke. Multivariable logistic regression analysis indicated that awareness of the patient/bystander that the initial symptom was a stroke (OR 4.438, 95% CI 2.669-7.381), knowledge about thrombolysis (OR 2.002, 95% CI 1.104-3.633) and use of ambulance (OR 1.961, 95% CI 1.176-3.270) were significantly associated with early arrival. CONCLUSIONS: In Korea, stroke awareness not only on the part of patients, but also of bystanders, had a great impact on early arrival at hospital. To increase the rate of thrombolysis therapy and the incidence of favorable outcomes, extensive general public education including how to recognize stroke symptoms would be important.ope

A Prediction Model of Incident Cardiovascular Disease in Patients with Sleep-Disordered Breathing

(1) Purpose: this study proposes a method of prediction of cardiovascular diseases (CVDs) that can develop within ten years in patients with sleep-disordered breathing (SDB). (2) Methods: For the design and evaluation of the algorithm, the Sleep Heart Health Study (SHHS) data from the 3367 participants were divided into a training set, validation set, and test set in the ratio of 5:3:2. From the data during a baseline period when patients did not have any CVD, we extracted 18 features from electrography (ECG) based on signal processing methods, 30 ECG features based on artificial intelligence (AI), ten clinical risk factors for CVD. We trained the model and evaluated it by using CVD outcomes result, monitored in follow-ups. The optimal feature vectors were selected through statistical analysis and support vector machine recursive feature elimination (SVM-RFE) of the extracted feature vectors. Features based on AI, a novel proposal from this study, showed excellent performance out of all selected feature vectors. In addition, new parameters based on AI were possibly meaningful predictors for CVD, when used in addition to the predictors for CVD that are already known. The selected features were used as inputs to the prediction model based on SVM for CVD, determining the development of CVD-free, coronary heart disease (CHD), heart failure (HF), or stroke within ten years. (3) Results: As a result, the respective recall and precision values were 82.9% and 87.5% for CVD-free; 71.9% and 63.8% for CVD; 57.2% and 55.4% for CHD; 52.6% and 40.8% for HF; 52.4% and 44.6% for stroke. The F1-score between CVD and CVD-free was 76.5%, and it was 59.1% in class four. (4) Conclusion: In conclusion, our results confirm the excellence of the prediction model for CVD in patients with SDB and verify the possibility of prediction within ten years of the CVDs that may occur in patients with SDB

Neural Network-Based Underwater Object Detection off the Coast of the Korean Peninsula

Recently, neural network-based deep learning techniques have been actively applied to detect underwater objects in sonar (sound navigation and ranging) images. However, unlike optical images, acquiring sonar images is extremely time- and cost-intensive, and therefore securing sonar data and conducting related research can be rather challenging. Here, a side-scan sonar was used to obtain sonar images to detect underwater objects off the coast of the Korean Peninsula. For the detection experiments, we used an underwater mock-up model with a similar size, shape, material, and acoustic characteristics to the target object that we wished to detect. We acquired various side-scan sonar images of the mock-up object against the background of mud, sand, and rock to account for the different characteristics of the coastal and seafloor environments of the Korean Peninsula. To construct a detection network suitable for the obtained sonar images from the experiment, the performance of five types of feature extraction networks and two types of optimizers was analyzed. From the analysis results, it was confirmed that performance was achieved when DarkNet-19 was used as the feature extraction network, and ADAM was applied as the optimizer. However, it is possible that there are feature extraction network and optimizer that are more suitable for our sonar images. Therefore, further research is needed. In addition, it is expected that the performance of the modified detection network can be more improved if additional images are obtained