Dong Hyun Choi

Approximately 16 percent of patients with submucosally invasive colorectal carcinoma and risk factors benefited from subsequent surgery. Tumor budding was the most significant factor for lymph node metastasis. Observation would be appropriate for patients without risk factors after endoscopic resection.

PURPOSE: The anastomotic leakage rate after rectal resection has been reported to be approximately 2.5-21 percent, but most results were associated with open surgery. The aim of this study was to identify risk factors and their relationship to the experience of the surgeon for anastomotic leakage after laparoscopic rectal resection. METHODS: Between March 2003 and December 2008, 156 patients underwent a laparoscopic rectal resection without a diverting ileostomy. The patients' characteristics, t

A striking decrease in pediatric ED visits was observed during the COVID-19 outbreak, the scale which was associated with the stringency of government policies. Changes in the number and characteristics of children visiting the ED should be considered to facilitate the effective operation of EDs during the pandemic.

Exposure to microgravity affects human physiology in various ways, and astronauts frequently report skin-related problems. Skin rash and irritation are frequent complaints during space missions, and skin thinning has also been reported after returning to Earth. However, spaceflight missions for studying the physiological changes in microgravity are impractical. Thus, we used a previously developed 3D clinostat to simulate a microgravity environment and investigate whether physiological changes o

Prediction of bacteremia is a clinically important but challenging task. An artificial intelligence (AI) model has the potential to facilitate early bacteremia prediction, aiding emergency department (ED) physicians in making timely decisions and reducing unnecessary medical costs. In this study, we developed and externally validated a Bayesian neural network-based AI bacteremia prediction model (AI-BPM). We also evaluated its impact on physician predictive performance considering both AI and ph

Choi, Dong Hyun M.D.; Park, Ji Won M.D.; Kim, Byung Nyun M.D.; Han, Kyung Su M.D.; Hong, Chang Won M.D.; Sohn, Dae Kyung M.D.; Lim, Seok-Byung M.D.; Choi, Hyo Seong M.D.; Jeong, Seung-Yong M.D. Author Information

Importance: The association between low socioeconomic position (SEP) and poor survival after out-of-hospital cardiac arrest (OHCA) has not been thoroughly investigated. Objectives: To evaluate the association between individual SEP and survival after OHCA and to identify any mediating pathways using structural equation modeling (SEM). Design, Setting, and Participants: This is a retrospective cohort study that used data collected from January 2013 to December 2019. Participants were adults with

<b>Background:</b> The objective of this study was to develop and validate machine learning models for data entry error detection in a national out-of-hospital cardiac arrest (OHCA) prehospital patient care report database.<b>Methods:</b> Adult OHCAs of presumed cardiac etiology were included. Data entry errors were defined as discrepancies between the coded data and the free-text note documenting the intervention or event; for example, information that was recorded as "absent" in the coded data

This is the first nationwide epidemiologic study of pediatric sports-related TBI in Korea. The ratios of TBI, intracranial injury and admission were highest in bicycle and street sports. Prevention strategies for pediatric sports-related TBI can be developed according to sports types.

Background: Traumatic brain injury (TBI) is one of the leading causes of pediatric disability that results in many emergency department visits. The risk of TBI is high while playing sports. The aim of this study was to examine the demographics and clinical characteristics of sports-related TBI. Methods: We performed a multicenter observational study using the Emergency Department–Based Injury In-Depth Surveillance database in Korea. Patients aged 5 to 18 years old, who sustained unintentional, s

Locally deployable LLMs, trained to extract core injury-related information from free-text ED clinical notes, demonstrated good performance. Generative LLMs can serve as versatile solutions for various injury-related information extraction tasks.