Purpose: This study aimed to provide the basic data needed to estimate future urologist supply and demand by applying various statistical models related to healthcare utilization. Materials and Methods: Data from multiple sources, including the Yearbook of Health and Welfare Statistics, Korean Hospital Association, Korean Medical Association, and the Korean Urological Association, were used for supply estimation. Demand estimation incorporated data on both clinical and non-clinical urologists, along with future population estimates. In-and-out moves and demographic methods were employed for supply estimation, while the Bureau of Health Professions model was utilized for demand estimation. Supply estimation assumptions included fixed resident quotas, age-specific death rates, migration rates, and retirement age considerations. Demand estimation assumptions included combining clinical and nonclinical urologist demands, adjusting population size for age-related healthcare usage variations. Urologist productivity was determined by adjusting productivity levels to 100%, 90%, and 80% of the base year based on actual clinical practice volumes. Results: Estimations of both demand and supply consistently indicate an oversupply of urologists until 2025, followed by an expected shortage by 2035 owing to increased deaths and retirements attributed to the aging urologist population. This shortage becomes more pronounced when employing more reliable models, such as logit or ARIMA (autoregressive integrated moving average), underscoring the growing need for urologists in the future. Conclusions All estimation models estimated an oversupply of urologists until 2025, transitioning to a deficit due to reduced supply thereafter. However, considering potential unaccounted factors, greater effort is needed for accurate predictions and corresponding measures.

Purpose: This study compared 3D-T1 high resolution isovolumetric examination (3DTHRIVE) multiplanar reconstruction (MPR) imaging of shoulder magnetic resonance arthrography (MRA) with conventional MR images and validated the diagnostic agreements of isovolumetric MRA with and without compressed sensing (CS). Materials and Methods: Seventy-three patients who underwent shoulder MRA, including image sets of conventional 2D fast spin echo (FSE) sequences and isotropic 3D-THRIVE sequences with and without CS, were evaluated. The CS acceleration factor was set to 1.5.In the first session, MPR images on the 3D-THRIVE sequence with CS were analyzed using current standard 2D FSE sequences in the axial, oblique-coronal, and oblique-sagittal planes. In the second session, 3D-THRIVE sequences with and without CS were compared with respect to image quality and degree of artifacts. Overall image quality scores and artifacts for conventional 2D images and 3D-THRIVE MPR with CS were analyzed using a paired t-test. The diagnostic agreement for pathological lesions of the shoulder in 3DTHRIVE with and without CS was evaluated using intraclass correlation coefficients. Results: CS in the isotropic 3D-THRIVE showed a reduction in scanning time from 104 s (non-CS) to 81 s (CS). The diagnostic agreement between 2D FSE and 3D-THRIVE for shoulder tendon pathologies was excellent for subscapularis, supraspinatus, infraspinatus, and biceps tendons. The inter-rater agreements were excellent, and CS-3D-THRIVE demonstrated excellent diagnostic agreement for certain tendon pathologies compared with 3D-THRIVE without CS. Conclusion CS-accelerated isotropic 3D-THRIVE shoulder MRA can provide diagnostically acceptable images of tendon pathology with a reduced scan time. Shoulder MRI using 3D-THRIVE with CS may replace standard 2D FSE sequences in patients who require rapid imaging.

Recently, interest in machine learning (ML) has increased as the application fields have expanded significantly. Although ML methods excel in many fields, establishing an ML pipeline requires considerable time and human resources. Automated ML (AutoML) tools offer a solution by automating repetitive tasks, such as data preprocessing, model selection, hyperparameter optimization, and prediction analysis. This review introduces the use of AutoML tools for general research, including clinical studies. In particular, it outlines a simple approach that is accessible to beginners using the R programming language (R Foundation for Statistical Computing). In addition, the practical code and output results for binary classification are provided to facilitate direct application by clinical researchers in future studies.

Background: Epinephrine (EPI) or norepinephrine (NOR) is widely used to treat cardiovascular collapse during lipid emulsion (LE) resuscitation for drug toxicity. However, the effect of LE on the vasoconstriction caused by EPI or NOR remains unknown. The purpose of this study was to examine the effect of an LE (Intralipid) on the vasoconstriction caused by EPI and NOR in isolated rat aorta. Methods: The effect of LE on the vasoconstriction caused by EPI or NOR in isolated rat aorta was examined. Additionally, the effect of LE on the calcium increase caused by EPI or NOR was investigated. The distribution constant (KD: lipid to aqueous phase) of EPI or NOR between a LE (1%) and an aqueous phase was determined. Results: LE (1 and 2%) did not significantly alter vasoconstriction caused by EPI or NOR in isolated endothelium-intact aorta. Moreover, the LE did not significantly alter the increased calcium level caused by EPI or NOR. The log KD of EPI in the LE (1%) was −0.71, −0.99, and −1.00 at 20, 50, and 100 mM ionic strength, respectively. The log KD of NOR in the LE (1%) was −1.22, −1.25, and −0.96 at 20, 50, and 100 mM ionic strength, respectively. Conclusions Taken together, the Intralipid emulsion did not alter vasoconstriction induced by EPI or NOR that seems to be due to the hydrophilicity of EPI or NOR, leading to sustained hemodynamic support produced by EPI or NOR used during LE resuscitation.

Methods: The ensemble AI model is designed and implemented by the Hadoop ecosystem with Kafka/NiFi, Spark/Hive, HUE, and ELK (Elasticsearch, Logstash, Kibana). Results The functional evaluation shows that the main function of this SAP architecture was operated successfully.DiscussionThe proposed model is confirmed to work well with safety mobility gateways to provide some safety applications.

Since the era of evidence-based medicine, it has become a matter of course to use statistics to create objective evidence in clinical research. As an extension of this, it has become essential in clinical research to calculate the correct sample size to demonstrate a clinically significant difference before starting the study.Also, because sample size calculation methods vary from study design to study design, there is no formula for sample size calculation that applies to all designs. It is very important for us to understand this. In this review, each sample size calculation method suitable for various study designs was introduced using the R program (R Foundation for Statistical Computing). In order for clinical researchers to directly utilize it according to future research, we presented practice codes, output results, and interpretation of results for each situation.

Objectives: This study was conducted to develop a generalizable annotation tool for bilingual complex clinical text annotation, which led to the design and development of a clinical text annotation tool, ANNO. Methods: We designed ANNO to enable human annotators to support the annotation of information in clinical documents efficiently and accurately. First, annotations for different classes (word or phrase types) can be tagged according to the type of word using the dictionary function. In addition, it is possible to evaluate and reconcile differences by comparing annotation results between human annotators. Moreover, if the regular expression set for each class is updated during annotation, it is automatically reflected in the new document. The regular expression set created by human annotators is designed such that a word tagged once is automatically labeled in new documents. Results: Because ANNO is a Docker-based web application, users can use it freely without being subjected to dependency issues. Human annotators can share their annotation markups as regular expression sets with a dictionary structure, and they can cross-check their annotated corpora with each other. The dictionary-based regular expression sharing function, cross-check function for each annotator, and standardized input (Microsoft Excel) and output (extensible markup language [XML]) formats are the main features of ANNO. Conclusions With the growing need for massively annotated clinical data to support the development of machine learning models, we expect ANNO to be helpful to many researchers.

Objective: To elucidate whether clinical features and the weighted genetic risk score (wGRS) were associated with the presence of lupus nephritis (LN). Methods: We retrospectively divided patients with systemic lupus erythematosus (SLE, n=1,078) into biopsy-proven LN (n=507) and non-LN groups (non-LN, n=571). Baseline clinical features, serologic markers, and the wGRS were collected. The wGRS was calculated from 112 non-human leukocyte antigen (non-HLA) loci and HLA-DRβ1 amino acid haplotypes for SLE. Associations among clinical features, wGRS, and the presence of LN were identified. Results: In the multivariate analysis, patients with LN were younger at diagnosis (odds ratio [OR]=0.97, p＜0.001), had more pleuritis (OR=2.44, p＜0.001) and pericarditis (OR=1.62, p=0.029), had a higher detection rate of anti-double stranded deoxyribonucleic acid (anti-dsDNA antibodies, OR=2.22, p＜0.001), anti-Smith antibodies (anti-Sm antibodies, OR=1.70, p=0.002), low level of complement (OR=1.37, p=0.043) and absence of antiphospholipid antibodies (aPL antibodies, OR=1.60, p=0.002), and had higher wGRS (OR=1.16, p=0.012). Mediation analysis suggested that anti-Sm antibodies and low complement could be mediators in the relationship between high wGRS and the presence of LN. Conclusion Onset age, pleuritis, pericarditis, several serologic markers, and wGRS were associated with the presence of LN. Anti-Sm antibodies and low complement appeared to mediate the indirect relationship between wGRS and the presence of LN.

Objective: To elucidate whether clinical features and the weighted genetic risk score (wGRS) were associated with the presence of lupus nephritis (LN). Methods: We retrospectively divided patients with systemic lupus erythematosus (SLE, n=1,078) into biopsy-proven LN (n=507) and non-LN groups (non-LN, n=571). Baseline clinical features, serologic markers, and the wGRS were collected. The wGRS was calculated from 112 non-human leukocyte antigen (non-HLA) loci and HLA-DRβ1 amino acid haplotypes for SLE. Associations among clinical features, wGRS, and the presence of LN were identified. Results: In the multivariate analysis, patients with LN were younger at diagnosis (odds ratio [OR]=0.97, p＜0.001), had more pleuritis (OR=2.44, p＜0.001) and pericarditis (OR=1.62, p=0.029), had a higher detection rate of anti-double stranded deoxyribonucleic acid (anti-dsDNA antibodies, OR=2.22, p＜0.001), anti-Smith antibodies (anti-Sm antibodies, OR=1.70, p=0.002), low level of complement (OR=1.37, p=0.043) and absence of antiphospholipid antibodies (aPL antibodies, OR=1.60, p=0.002), and had higher wGRS (OR=1.16, p=0.012). Mediation analysis suggested that anti-Sm antibodies and low complement could be mediators in the relationship between high wGRS and the presence of LN. Conclusion Onset age, pleuritis, pericarditis, several serologic markers, and wGRS were associated with the presence of LN. Anti-Sm antibodies and low complement appeared to mediate the indirect relationship between wGRS and the presence of LN.

Purpose: This study evaluated aggressive hyperbaric oxygen therapy (HBOT) by understanding various exposure routes of acute carbon monoxide (CO) poisoning, the risk factors causing acute cardiovascular, and neurological toxicity caused by poisoning. Methods: A retrospective study was conducted based on the medical records of 417 acute CO poisoning patients who visited the emergency care unit from March 2017 to August 2019. The exposure routes, HBOT performance, age, sex, medical history (hypertension, diabetes mellitus, ischemic heart disease, heart failure), intentionality, loss of consciousness (LOC), intake with alcohol or sedatives, and initial test results (carboxyhemoglobin (COHb), troponin- I, electrocardiography, echocardiography, brain MRI) were examined. Comparative analysis of the clinical information was conducted between the groups that showed acute cardiovascular toxicity and neurological toxicity, and groups that did not. Results: Among 417 patients diagnosed with acute CO poisoning, 201 cases (48.2%) were intentional, and charcoal briquette was the most common route (169 patients (40.5%)). Two hundred sixteen cases (51.8%) were accidental, and fire was the most common route (135 patients (32.4%)). The exposure route was more diverse with accidental poisoning. Three hundred ninety-nine patients were studied for acute cardiovascular toxicity, and 62 patients (15.5%) were confirmed to be positive. The result was statistically significant in intentionality, LOC, combined sedatives, initial COHb, HTN, and IHD. One hundred two patients were studied for acute neurological toxicity, which was observed in 26 patients (25.5%). The result was statistically significant in age and LOC. Conclusion Active HBOT should be performed to minimize damage to the major organs by identifying the various exposure routes of CO poisoning, risk factors for acute cardiovascular toxicity (intentionality, LOC, combined sedatives, initial COHb, HTN, IHD), and the risk factors for acute neurological toxicity (age, LOC).