The length of the trachea varies and is relatively short in children, it is therefore difficult to determine the correct depth of tracheal tube placement. In 85 children, the tube was placed using one of the following methods: (i) after deliberate endobronchial intubation, withdrawal to the carina was confirmed by auscultation, and the tube was then withdrawn a further 2 cm (auscultation group); (ii) as above, except that withdrawal to the carina was confirmed by a decrease in peak inspiratory pressure (pressure group); (iii) the tube was placed with a 3.0-cm mark at the vocal cords (mark group). The mean (SD) distance from the tip of the tube to the carina was 1.91 (0.81) cm in the auscultation group, and 1.93 (0.67) cm in the pressure group. These were not significantly different (p > 0.05) from targeted distance of 2 cm. In the mark group, the tube was located 2.30 (0.98) cm above the carina in children younger than 36 months and was further from the carina [6.16 (1.0) cm] in older children. In 20% of patients initially randomly allocated to the mark group, the mark could not be visualised. In conclusion, the methods described above effectively achieve adequate tracheal tube depth in children.

The incidence of stomach cancer has been found to be gradually decreasing; however, it remains one of the most frequently occurring malignant cancers in Korea. According to statistics of 2017, stomach cancer is the top cancer in men and the fourth most important cancer in women, necessitating methods for its early detection and treatment. Considerable research in the field of bioinformatics has been conducted in cancer studies, and bioinformatics approaches might help develop methods and models for its early prediction. We aimed to develop a classification method based on deep learning and demonstrate its application to gene expression data obtained from patients with stomach cancer. Data of 60,483 genes from 334 patients with stomach cancer in The Cancer Genome Atlas were evaluated by principal component analysis, heatmaps, and the convolutional neural network (CNN) algorithm. We combined the RNA-seq gene expression data with clinical data, searched candidate genes, and analyzed them using the CNN deep learning algorithm. We performed learning using the sample type and vital status of patients with stomach cancer and verified the results. We obtained an accuracy of 95.96% for sample type and 50.51% for vital status. Despite overfitting owing to the limited number of patients, relatively accurate results for sample type were obtained. This approach can be used to predict the prognosis of stomach cancer, which has many types and underlying causes.

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Recently, large-scale bioinformatics and genomic data have been generated using advanced biotechnology methods, thus increasing the importance of analyzing such data. Numerous data mining methods have been developed to process genomic data in the field of bioinformatics. We extracted significant genes for the prognosis prediction of 1157 patients using gene expression data from patients with kidney cancer. We then proposed an end-to-end, cost-sensitive hybrid deep learning (COST-HDL) approach with a cost-sensitive loss function for classification tasks on imbalanced kidney cancer data. Here, we combined the deep symmetric auto encoder; the decoder is symmetric to the encoder in terms of layer structure, with reconstruction loss for non-linear feature extraction and neural network with balanced classification loss for prognosis prediction to address data imbalance problems. Combined clinical data from patients with kidney cancer and gene data were used to determine the optimal classification model and estimate classification accuracy by sample type, primary diagnosis, tumor stage, and vital status as risk factors representing the state of patients. Experimental results showed that the COST-HDL approach was more efficient with gene expression data for kidney cancer prognosis than other conventional machine learning and data mining techniques. These results could be applied to extract features from gene biomarkers for prognosis prediction of kidney cancer and prevention and early diagnosis.

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Publication lag is a determinant to journal efficiency that was not yet studied concerning Korean medical journals. To measure publication lag, we investigated the publication timestamps of 4,762 articles published by 10 Korean medical journals indexed in Scopus database, randomly selected from the KoreaMed Synapse since 2013. The total publication lag was 246.5 (Q1, Q3; 178.0, 347.0) days. The overall acceptance lag was 102.0 (65.0, 149.0) days. The overall lead lag was 123.0 (63.0, 236.0) days. The year of publication did not significantly affect the acceptance lag (P = 0.640), supposedly shortening it by about 1.4 (97.5% confidence interval [CI], −5.2 to 8.0) days/year, while the date affected the lead lag (P = 0.028), shortening it by about 12.9 (1.3 to 24.5) days/year. The Korean medical journals have reduced the total publication delay entirely by means of reducing the lead lag, not by reducing the acceptance lag.

Background: Although the intrathecal (IT) administration of midazolam has been reported to have analgesic effect in humans, it is not clear whether IT midazolam can prolong the duration of sensory block to T10 dermatome that is required block level for lower extremity surgery. The effect of 1 or 2 mg of IT midazolam added to bupivacaine on the duration of spinal anesthesia to T10 were examined in orthopedic patients.Methods: Sixty six adult patients were randomly allocated to receive 11 mg of intrathecal 0.5% hyperbaric bupivacaine alone (Group B, n = 22) or with 1 mg (Group BM-1, n = 22) or 2 mg (Group BM-2, n = 22) of midazolam. Both the patients and the observers were blinded to the drug solutions and patient groups. The onset and duration of sensory block to T10, BIS, OAA/S scale, hemodynamic variables, and side effects during the operation and recovery were compared among the groups.Results: The onset of sensory and motor block were not different among the groups. However, the duration of sensory block to T10 in the Group BM-2 was prolonged more 52.2, 42.2 minutes than the Group B and the Group BM-1, respectively. The BIS scale of the Group BM-2 tended to be lower than the Group B and the Group BM-1 but there were no statistical significance. The OAA/S scale were significantly higher in the Group BM-2 than the Group B and the Group BM-1 during operation. There were no differences in hemodynamic variables and side effects among the groups.Conclusions: Intrathecal addition of midazolam 2 mg to bupivacaine prolonged the duration of spinal block to T10 in orthopedic patients.

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