Electronic cigarette (e-cigarette) or vaping product use-associated lung injury (EVALI) has emerged as a social issue as e-cigarette use is rapidly increasing worldwide and is related to many deaths in the United States. To our knowledge, this is the first case report of EVALI in South Korea of a 24-year-old man with acute respiratory symptoms and a history of e-cigarette use. Chest CT revealed diffuse bilateral ground-glass opacities with subpleural sparing, airspace consolidation, and centrilobular micronodules as typical patterns of EVALI with organizing pneumonia and diffuse alveolar damage. Infection was excluded with meticulous laboratory examinations, and the patients’ illnesses were not attributed to other causes. EVALI was diagnosed by meeting the diagnostic criteria with consistent clinico-radiologic findings through a multidisciplinary approach. Radiologists should have good knowledge of EVALI radiologic findings and play a cardinal role in the proper diagnosis and management of EVALI.

Background/Aims: This study aimed to investigate the possibility of in situ diagnosis of Helicobacter pylori (H. pylori) infection during endoscopic examination. The predictive infection value was estimated using the endoscopic Kyoto scoring system (EKSS), and specific endoscopic findings were evaluated for diagnosing H. pylori infection in H. pylori naïve patients and those with a eradication history. Materials and Methods: A total of 836 patients with H. pylori infection were analyzed. The state of the infection was predicted using the EKSS and specific endoscopic findings. Results: Patients were classified into two groups: the H. pylori naïve group and the group with a the bacterial eradication history. The area under the curve (AUC) on receiver operating characteristics analysis was 0.90 for EKSS in H. pylori naïve patients and 0.83 for the other group patients. For patients with open type atrophy and/or intestinal metaplasia, EKSS (24.4%; 95% CI, 12.4~0.3%) and regular arrangement of collecting venules (RAC) (46.3%; 95% CI, 30.7~62.9%) showed low specificities. Mucosal swelling (66.2%; 95% CI, 62.5~69.7%) and sticky mucus (80.5%; 95% CI, 74.8~85.2%) presented relatively high positive predictive values for H. pylori infection in naïve patients, whereas reflux esophagitis, hematin, red streak, and duodenitis exhibited high negative predictive values in patients with a H. pylori eradication history (98.0%; 95% CI, 96.4~99.1%). Conclusions EKSS and RAC are excellent tools for predicting H. pylori infection. However, they have a limited role in patients with open type atrophy and/or intestinal metaplasia. Specific endoscopic findings could help predict the infection state.

Background/Aims: This study examined the clinical features and prognosis of patients with mucinous gastric carcinoma (MGC), non-mucinous gastric carcinoma (NMGC), and signet ring cell gastric carcinoma (SRC). Methods: A retrospective cohort study was performed, enrolling 65 patients with MGC from January 2007 to December 2016.During the same period, 1,814 patients with histologically proven gastric cancers underwent curative or palliative operations. One hundred and ninety-five NMGC patients were selected as the 1:3 age- and sex-matched control groups. In addition, 200 SRC patients were identified. This study evaluated the demographic features of the patients, pathologic features of the tumor, and the predictive factors, such as the recurrence-free survival and overall survival. Results: The recurrence rates were significantly high in MGC than in NMGC or SRC (both p<0.01). The proportion of early gastric cancer was lower in the MGC group than in the other groups (p<0.01). In addition, metastatic lymph nodes were found more frequently in the MGC group (p<0.01), and the proportion of initial pT4, M1 stage, was highest in the MGC group. The recurrence-free survival and overall survival in the MGC group were significantly lower than those in the NMGC or SRC. Subgroup analysis showed that patients with the same American Joint Committee on Cancer (AJCC) stage of each cancer group showed a similar prognosis. Conclusions MGC frequently presents an advanced stage with an unfavorable prognosis compared to NMGC or SRC. On the other hand, MGC of the same AJCC stage had a similar prognosis to NMGC and SRC.

Background/Aims: This study examined the clinical features and prognosis of patients with mucinous gastric carcinoma (MGC), non-mucinous gastric carcinoma (NMGC), and signet ring cell gastric carcinoma (SRC). Methods: A retrospective cohort study was performed, enrolling 65 patients with MGC from January 2007 to December 2016.During the same period, 1,814 patients with histologically proven gastric cancers underwent curative or palliative operations. One hundred and ninety-five NMGC patients were selected as the 1:3 age- and sex-matched control groups. In addition, 200 SRC patients were identified. This study evaluated the demographic features of the patients, pathologic features of the tumor, and the predictive factors, such as the recurrence-free survival and overall survival. Results: The recurrence rates were significantly high in MGC than in NMGC or SRC (both p<0.01). The proportion of early gastric cancer was lower in the MGC group than in the other groups (p<0.01). In addition, metastatic lymph nodes were found more frequently in the MGC group (p<0.01), and the proportion of initial pT4, M1 stage, was highest in the MGC group. The recurrence-free survival and overall survival in the MGC group were significantly lower than those in the NMGC or SRC. Subgroup analysis showed that patients with the same American Joint Committee on Cancer (AJCC) stage of each cancer group showed a similar prognosis. Conclusions MGC frequently presents an advanced stage with an unfavorable prognosis compared to NMGC or SRC. On the other hand, MGC of the same AJCC stage had a similar prognosis to NMGC and SRC.

Background: Despite their effectiveness, coronavirus disease 2019 (COVID-19) vaccines have been associated with adverse effects, underscoring the importance of continuous surveillance to ensure vaccine safety and effective management of public health. Herein, the characteristics and risk factors of vaccine-related adverse events (AEs) were identified to gain an in-depth understanding of vaccine safety by investigating the impact of the vaccination dose on changes in post-vaccination AEs. Methods: Herein, a linked database of COVID-19 vaccination records from the Korea Disease Control and Prevention Agency, AE reports from the COVID-19 Vaccination Management System, and healthcare claims from the National Health Insurance Service, targeting ≥ 5-year-old individuals, was utilized (study duration = February 26, 2021, to January 31, 2023).The frequency and severity of reported post-vaccination AEs were evaluated. Furthermore, we specifically explored AEs in relation to the cumulative dosage of vaccines administered while evaluating associated risk factors. Results: During the observation period, 42,804,523 individuals completed the COVID-19 vaccination series, with 365,900 reporting AEs, with headache, muscle pain, and fever being the most frequently reported. Notably, the AE reports were approximately twice as high for women than for men, which was further exacerbated following both doses. Analysis by age group revealed that AE reports were lower among children, adolescents, and older adults than in the middleaged cohort (age = 50–64 years), with higher reports observed for 18–49-year-old individuals.Additionally, a higher risk of reporting was identified among individuals with lower socioeconomic status compared with those of middle socioeconomic status. Excluding dementia, the risk of reporting AEs was high in individuals with underlying diseases compared with those without, for instance, the risk of reporting AEs following two-dose vaccinations was approximately twice as high in individuals with chronic obstructive pulmonary disease and asthma. Conclusion These findings indicate that women, younger people, those with a lower socioeconomic status, and those with underlying health conditions reported a higher incidence of AEs following COVID-19 vaccinations. This emphasizes the need for continued monitoring to ensure safe vaccination and address vaccine-related anxiety and fear, especially within the aforementioned groups.

Background: Despite their effectiveness, coronavirus disease 2019 (COVID-19) vaccines have been associated with adverse effects, underscoring the importance of continuous surveillance to ensure vaccine safety and effective management of public health. Herein, the characteristics and risk factors of vaccine-related adverse events (AEs) were identified to gain an in-depth understanding of vaccine safety by investigating the impact of the vaccination dose on changes in post-vaccination AEs. Methods: Herein, a linked database of COVID-19 vaccination records from the Korea Disease Control and Prevention Agency, AE reports from the COVID-19 Vaccination Management System, and healthcare claims from the National Health Insurance Service, targeting ≥ 5-year-old individuals, was utilized (study duration = February 26, 2021, to January 31, 2023).The frequency and severity of reported post-vaccination AEs were evaluated. Furthermore, we specifically explored AEs in relation to the cumulative dosage of vaccines administered while evaluating associated risk factors. Results: During the observation period, 42,804,523 individuals completed the COVID-19 vaccination series, with 365,900 reporting AEs, with headache, muscle pain, and fever being the most frequently reported. Notably, the AE reports were approximately twice as high for women than for men, which was further exacerbated following both doses. Analysis by age group revealed that AE reports were lower among children, adolescents, and older adults than in the middleaged cohort (age = 50–64 years), with higher reports observed for 18–49-year-old individuals.Additionally, a higher risk of reporting was identified among individuals with lower socioeconomic status compared with those of middle socioeconomic status. Excluding dementia, the risk of reporting AEs was high in individuals with underlying diseases compared with those without, for instance, the risk of reporting AEs following two-dose vaccinations was approximately twice as high in individuals with chronic obstructive pulmonary disease and asthma. Conclusion These findings indicate that women, younger people, those with a lower socioeconomic status, and those with underlying health conditions reported a higher incidence of AEs following COVID-19 vaccinations. This emphasizes the need for continued monitoring to ensure safe vaccination and address vaccine-related anxiety and fear, especially within the aforementioned groups.

Background: Despite their effectiveness, coronavirus disease 2019 (COVID-19) vaccines have been associated with adverse effects, underscoring the importance of continuous surveillance to ensure vaccine safety and effective management of public health. Herein, the characteristics and risk factors of vaccine-related adverse events (AEs) were identified to gain an in-depth understanding of vaccine safety by investigating the impact of the vaccination dose on changes in post-vaccination AEs. Methods: Herein, a linked database of COVID-19 vaccination records from the Korea Disease Control and Prevention Agency, AE reports from the COVID-19 Vaccination Management System, and healthcare claims from the National Health Insurance Service, targeting ≥ 5-year-old individuals, was utilized (study duration = February 26, 2021, to January 31, 2023).The frequency and severity of reported post-vaccination AEs were evaluated. Furthermore, we specifically explored AEs in relation to the cumulative dosage of vaccines administered while evaluating associated risk factors. Results: During the observation period, 42,804,523 individuals completed the COVID-19 vaccination series, with 365,900 reporting AEs, with headache, muscle pain, and fever being the most frequently reported. Notably, the AE reports were approximately twice as high for women than for men, which was further exacerbated following both doses. Analysis by age group revealed that AE reports were lower among children, adolescents, and older adults than in the middleaged cohort (age = 50–64 years), with higher reports observed for 18–49-year-old individuals.Additionally, a higher risk of reporting was identified among individuals with lower socioeconomic status compared with those of middle socioeconomic status. Excluding dementia, the risk of reporting AEs was high in individuals with underlying diseases compared with those without, for instance, the risk of reporting AEs following two-dose vaccinations was approximately twice as high in individuals with chronic obstructive pulmonary disease and asthma. Conclusion These findings indicate that women, younger people, those with a lower socioeconomic status, and those with underlying health conditions reported a higher incidence of AEs following COVID-19 vaccinations. This emphasizes the need for continued monitoring to ensure safe vaccination and address vaccine-related anxiety and fear, especially within the aforementioned groups.

Background: Despite their effectiveness, coronavirus disease 2019 (COVID-19) vaccines have been associated with adverse effects, underscoring the importance of continuous surveillance to ensure vaccine safety and effective management of public health. Herein, the characteristics and risk factors of vaccine-related adverse events (AEs) were identified to gain an in-depth understanding of vaccine safety by investigating the impact of the vaccination dose on changes in post-vaccination AEs. Methods: Herein, a linked database of COVID-19 vaccination records from the Korea Disease Control and Prevention Agency, AE reports from the COVID-19 Vaccination Management System, and healthcare claims from the National Health Insurance Service, targeting ≥ 5-year-old individuals, was utilized (study duration = February 26, 2021, to January 31, 2023).The frequency and severity of reported post-vaccination AEs were evaluated. Furthermore, we specifically explored AEs in relation to the cumulative dosage of vaccines administered while evaluating associated risk factors. Results: During the observation period, 42,804,523 individuals completed the COVID-19 vaccination series, with 365,900 reporting AEs, with headache, muscle pain, and fever being the most frequently reported. Notably, the AE reports were approximately twice as high for women than for men, which was further exacerbated following both doses. Analysis by age group revealed that AE reports were lower among children, adolescents, and older adults than in the middleaged cohort (age = 50–64 years), with higher reports observed for 18–49-year-old individuals.Additionally, a higher risk of reporting was identified among individuals with lower socioeconomic status compared with those of middle socioeconomic status. Excluding dementia, the risk of reporting AEs was high in individuals with underlying diseases compared with those without, for instance, the risk of reporting AEs following two-dose vaccinations was approximately twice as high in individuals with chronic obstructive pulmonary disease and asthma. Conclusion These findings indicate that women, younger people, those with a lower socioeconomic status, and those with underlying health conditions reported a higher incidence of AEs following COVID-19 vaccinations. This emphasizes the need for continued monitoring to ensure safe vaccination and address vaccine-related anxiety and fear, especially within the aforementioned groups.

Background: Vaccine safety surveillance is important because it is related to vaccine hesitancy, which affects vaccination rate. To increase confidence in vaccination, the active monitoring of vaccine adverse events is important. For effective active surveillance, we developed and verified a machine learning-based active surveillance system using national claim data. Methods: We used two databases, one from the Korea Disease Control and Prevention Agency, which contains flu vaccination records for the elderly, and another from the National Health Insurance Service, which contains the claim data of vaccinated people. We developed a casecrossover design based machine learning model to predict the health outcome of interest events (anaphylaxis and agranulocytosis) using a random forest. Feature importance values were evaluated to determine candidate associations with each outcome. We investigated the relationship of the features to each event via a literature review, comparison with the Side Effect Resource, and using the Local Interpretable Model-agnostic Explanation method. Results: The trained model predicted each health outcome of interest with a high accuracy (approximately 70%). We found literature supporting our results, and most of the important drug-related features were listed in the Side Effect Resource database as inducing the health outcome of interest. For anaphylaxis, flu vaccination ranked high in our feature importance analysis and had a positive association in Local Interpretable Model-Agnostic Explanation analysis. Although the feature importance of vaccination was lower for agranulocytosis, it also had a positive relationship in the Local Interpretable Model-Agnostic Explanation analysis. Conclusion We developed a machine learning-based active surveillance system for detecting possible factors that can induce adverse events using health claim and vaccination databases. The results of the study demonstrated a potentially useful application of two linked national health record databases. Our model can contribute to the establishment of a system for conducting active surveillance on vaccination.

Background: Vaccine safety surveillance is important because it is related to vaccine hesitancy, which affects vaccination rate. To increase confidence in vaccination, the active monitoring of vaccine adverse events is important. For effective active surveillance, we developed and verified a machine learning-based active surveillance system using national claim data. Methods: We used two databases, one from the Korea Disease Control and Prevention Agency, which contains flu vaccination records for the elderly, and another from the National Health Insurance Service, which contains the claim data of vaccinated people. We developed a casecrossover design based machine learning model to predict the health outcome of interest events (anaphylaxis and agranulocytosis) using a random forest. Feature importance values were evaluated to determine candidate associations with each outcome. We investigated the relationship of the features to each event via a literature review, comparison with the Side Effect Resource, and using the Local Interpretable Model-agnostic Explanation method. Results: The trained model predicted each health outcome of interest with a high accuracy (approximately 70%). We found literature supporting our results, and most of the important drug-related features were listed in the Side Effect Resource database as inducing the health outcome of interest. For anaphylaxis, flu vaccination ranked high in our feature importance analysis and had a positive association in Local Interpretable Model-Agnostic Explanation analysis. Although the feature importance of vaccination was lower for agranulocytosis, it also had a positive relationship in the Local Interpretable Model-Agnostic Explanation analysis. Conclusion We developed a machine learning-based active surveillance system for detecting possible factors that can induce adverse events using health claim and vaccination databases. The results of the study demonstrated a potentially useful application of two linked national health record databases. Our model can contribute to the establishment of a system for conducting active surveillance on vaccination.