Objective: Previous studies have provided inconclusive results on the association between depression and stroke risk, and the potential modifying effect of comorbid insomnia on this association remains unclear. Our study aimed to clarify the independent roles of depression and insomnia as risk factors for stroke and to investigate the possibility of an interaction effect between these two conditions on stroke incidence. Methods: We used data from the Korean Genome and Epidemiology Study. The primary exposure was depression, measured by the Beck Depression Inventory. The secondary exposure was insomnia. The main outcome was the occurrence of stroke observed in biennial follow-up surveys. Cox proportional regression analysis was performed to estimate the effects of depression and insomnia on stroke incidence. We also conducted interaction analysis to investigate the interaction between depression and insomnia on stroke incidence. Results: During 16 years of follow-up involving 3,301 individuals, we documented 172 cases of new-onset stroke (4.3 cases per 1,000 person-years). Cox proportional logistic regression analysis showed that severe depression significantly increased the risk of stroke (hazard ratio [HR]: 2.06, 95% confidence interval [CI]: 1.13–3.75), whereas mild and moderate depression did not increase this risk. Interaction analysis demonstrated that stroke risk was increased with only moderate (HR: 2.04, 95% CI: 1.04–4.00) and severe (HR: 3.01, 95% CI: 1.43–6.31) depression among individuals without insomnia. Conclusion Although general depression does not significantly increase stroke risk, moderate-to-severe depression may increase this risk, particularly in individuals without insomnia.

Objective: Previous studies have provided inconclusive results on the association between depression and stroke risk, and the potential modifying effect of comorbid insomnia on this association remains unclear. Our study aimed to clarify the independent roles of depression and insomnia as risk factors for stroke and to investigate the possibility of an interaction effect between these two conditions on stroke incidence. Methods: We used data from the Korean Genome and Epidemiology Study. The primary exposure was depression, measured by the Beck Depression Inventory. The secondary exposure was insomnia. The main outcome was the occurrence of stroke observed in biennial follow-up surveys. Cox proportional regression analysis was performed to estimate the effects of depression and insomnia on stroke incidence. We also conducted interaction analysis to investigate the interaction between depression and insomnia on stroke incidence. Results: During 16 years of follow-up involving 3,301 individuals, we documented 172 cases of new-onset stroke (4.3 cases per 1,000 person-years). Cox proportional logistic regression analysis showed that severe depression significantly increased the risk of stroke (hazard ratio [HR]: 2.06, 95% confidence interval [CI]: 1.13–3.75), whereas mild and moderate depression did not increase this risk. Interaction analysis demonstrated that stroke risk was increased with only moderate (HR: 2.04, 95% CI: 1.04–4.00) and severe (HR: 3.01, 95% CI: 1.43–6.31) depression among individuals without insomnia. Conclusion Although general depression does not significantly increase stroke risk, moderate-to-severe depression may increase this risk, particularly in individuals without insomnia.

Objective: Previous studies have provided inconclusive results on the association between depression and stroke risk, and the potential modifying effect of comorbid insomnia on this association remains unclear. Our study aimed to clarify the independent roles of depression and insomnia as risk factors for stroke and to investigate the possibility of an interaction effect between these two conditions on stroke incidence. Methods: We used data from the Korean Genome and Epidemiology Study. The primary exposure was depression, measured by the Beck Depression Inventory. The secondary exposure was insomnia. The main outcome was the occurrence of stroke observed in biennial follow-up surveys. Cox proportional regression analysis was performed to estimate the effects of depression and insomnia on stroke incidence. We also conducted interaction analysis to investigate the interaction between depression and insomnia on stroke incidence. Results: During 16 years of follow-up involving 3,301 individuals, we documented 172 cases of new-onset stroke (4.3 cases per 1,000 person-years). Cox proportional logistic regression analysis showed that severe depression significantly increased the risk of stroke (hazard ratio [HR]: 2.06, 95% confidence interval [CI]: 1.13–3.75), whereas mild and moderate depression did not increase this risk. Interaction analysis demonstrated that stroke risk was increased with only moderate (HR: 2.04, 95% CI: 1.04–4.00) and severe (HR: 3.01, 95% CI: 1.43–6.31) depression among individuals without insomnia. Conclusion Although general depression does not significantly increase stroke risk, moderate-to-severe depression may increase this risk, particularly in individuals without insomnia.

Objective: Previous studies have provided inconclusive results on the association between depression and stroke risk, and the potential modifying effect of comorbid insomnia on this association remains unclear. Our study aimed to clarify the independent roles of depression and insomnia as risk factors for stroke and to investigate the possibility of an interaction effect between these two conditions on stroke incidence. Methods: We used data from the Korean Genome and Epidemiology Study. The primary exposure was depression, measured by the Beck Depression Inventory. The secondary exposure was insomnia. The main outcome was the occurrence of stroke observed in biennial follow-up surveys. Cox proportional regression analysis was performed to estimate the effects of depression and insomnia on stroke incidence. We also conducted interaction analysis to investigate the interaction between depression and insomnia on stroke incidence. Results: During 16 years of follow-up involving 3,301 individuals, we documented 172 cases of new-onset stroke (4.3 cases per 1,000 person-years). Cox proportional logistic regression analysis showed that severe depression significantly increased the risk of stroke (hazard ratio [HR]: 2.06, 95% confidence interval [CI]: 1.13–3.75), whereas mild and moderate depression did not increase this risk. Interaction analysis demonstrated that stroke risk was increased with only moderate (HR: 2.04, 95% CI: 1.04–4.00) and severe (HR: 3.01, 95% CI: 1.43–6.31) depression among individuals without insomnia. Conclusion Although general depression does not significantly increase stroke risk, moderate-to-severe depression may increase this risk, particularly in individuals without insomnia.

Objective: Previous studies have provided inconclusive results on the association between depression and stroke risk, and the potential modifying effect of comorbid insomnia on this association remains unclear. Our study aimed to clarify the independent roles of depression and insomnia as risk factors for stroke and to investigate the possibility of an interaction effect between these two conditions on stroke incidence. Methods: We used data from the Korean Genome and Epidemiology Study. The primary exposure was depression, measured by the Beck Depression Inventory. The secondary exposure was insomnia. The main outcome was the occurrence of stroke observed in biennial follow-up surveys. Cox proportional regression analysis was performed to estimate the effects of depression and insomnia on stroke incidence. We also conducted interaction analysis to investigate the interaction between depression and insomnia on stroke incidence. Results: During 16 years of follow-up involving 3,301 individuals, we documented 172 cases of new-onset stroke (4.3 cases per 1,000 person-years). Cox proportional logistic regression analysis showed that severe depression significantly increased the risk of stroke (hazard ratio [HR]: 2.06, 95% confidence interval [CI]: 1.13–3.75), whereas mild and moderate depression did not increase this risk. Interaction analysis demonstrated that stroke risk was increased with only moderate (HR: 2.04, 95% CI: 1.04–4.00) and severe (HR: 3.01, 95% CI: 1.43–6.31) depression among individuals without insomnia. Conclusion Although general depression does not significantly increase stroke risk, moderate-to-severe depression may increase this risk, particularly in individuals without insomnia.

Purpose: As people living with cancer increase in the aging society, cancer-related emergency department (ED) visits are also increasing. This study aimed to investigate the epidemiologic characteristics of non-emergent cancer-related ED visits using a nationwide ED database. Materials and Methods: A cross-sectional study was conducted using the National Emergency Department Information System (NEDIS) database. All cancer-related ED visits between 2016 and 2020 were included. The study outcome was non-emergent ED visits, defined as patients triaged into non-emergent condition at both the time of arrival at ED and discharge from ED and were discharged without hospitalization. Results: Among 1185871 cancer-related ED visits over 5 years, 19.0% (n=225491) were classified as non-emergent visits. While abdominal pain and fever are the top chief complaints in both emergent and non-emergent visits, non-emergent visits had high proportions of abdomen distension (4.8%), ascite (2.4%), and pain in lower limb (2.0%) compared with emergent visits. The cancer types with a high proportion of non-emergent visits were thyroid (32.4%) and prostate cancer (30.4%). Adults compared with children or older adults, female, medical aid insurance, urban/rural ED, direct-in compared with transfer-in, and weekend visit were associated with high odds for non-emergent visits. Conclusion Approximately 20% of cancer-related ED visits may be potentially non-emergent. A significant number of non-emergent patients visited the ED due to cancer-related symptoms. To improve the quality of care for people living with cancer, the expansion of supportive care resources besides of ED, including active symptom control, is necessary.

Background: The objective of this study was to examine the effect of the coronavirus disease 2019 (COVID-19) outbreak on excess in-hospital mortality among patients who visited emergency departments (EDs) and to assess whether the excess mortality during the COVID-19 pandemic varies by community income level. Methods: This is a cross-sectional study using the National Emergency Department Information System (NEDIS) database in Korea. The study population was defined as patients who visited all 402 EDs with medical conditions other than injuries between January 27 and May 31, 2020 (after-COVID) and for the corresponding time period in 2019 (before-COVID). The primary outcome was in-hospital mortality. The main exposure was the COVID-19 outbreak, and the interaction variable was county per capita income tax. We calculated the risk-adjusted in-hospital mortality rates by COVID-19 outbreak, as well as the difference-in-difference of risk-adjusted rates between the before-COVID and after-COVID groups according to the county income tax using a multilevel linear regression model with the interaction term. Results: A total of 11,662,167 patients (6,765,717 in before-COVID and 4,896,450 in afterCOVID) were included in the study with a 1.6% crude in-hospital mortality rate. The riskadjusted mortality rate in the after-COVID group was higher than that in the before-COVID group (1.82% vs. 1.50%, difference: 0.31% [0.30 to 0.33]; adjusted odds ratio: 1.22 [1.18 to 1.25]). The excess in-hospital mortality rate of the after-COVID in the lowest quartile group of county income tax was significantly higher than that in the highest quartile group (difference-in-difference: 0.18% (0.14 to 0.23); P-for-interaction: < 0.01). Conclusion During the COVID-19 pandemic, there was excess in-hospital mortality among patients who visited EDs, and there were disparities in excess mortality depending on community socioeconomic positions.

Background: The objective of this study was to examine the effect of the coronavirus disease 2019 (COVID-19) outbreak on excess in-hospital mortality among patients who visited emergency departments (EDs) and to assess whether the excess mortality during the COVID-19 pandemic varies by community income level. Methods: This is a cross-sectional study using the National Emergency Department Information System (NEDIS) database in Korea. The study population was defined as patients who visited all 402 EDs with medical conditions other than injuries between January 27 and May 31, 2020 (after-COVID) and for the corresponding time period in 2019 (before-COVID). The primary outcome was in-hospital mortality. The main exposure was the COVID-19 outbreak, and the interaction variable was county per capita income tax. We calculated the risk-adjusted in-hospital mortality rates by COVID-19 outbreak, as well as the difference-in-difference of risk-adjusted rates between the before-COVID and after-COVID groups according to the county income tax using a multilevel linear regression model with the interaction term. Results: A total of 11,662,167 patients (6,765,717 in before-COVID and 4,896,450 in afterCOVID) were included in the study with a 1.6% crude in-hospital mortality rate. The riskadjusted mortality rate in the after-COVID group was higher than that in the before-COVID group (1.82% vs. 1.50%, difference: 0.31% [0.30 to 0.33]; adjusted odds ratio: 1.22 [1.18 to 1.25]). The excess in-hospital mortality rate of the after-COVID in the lowest quartile group of county income tax was significantly higher than that in the highest quartile group (difference-in-difference: 0.18% (0.14 to 0.23); P-for-interaction: < 0.01). Conclusion During the COVID-19 pandemic, there was excess in-hospital mortality among patients who visited EDs, and there were disparities in excess mortality depending on community socioeconomic positions.

Purpose: There has been no report of sex-specific, pediatric age-adjusted shock index (PASI) for pediatric trauma patients in previous studies. We aimed to determine the association between the PASI and in-hospital mortality of pediatric trauma patients and whether this association differs depending on sex. Materials and Methods: This is a prospective, multinational, and multicenter cohort study using the Pan-Asian Trauma Outcome Study (PATOS) registry in the Asia-Pacific region, conducted in pediatric patients who visited the participating hospitals. The main exposure of our study was abnormal (elevated) PASI measured in an emergency department. The main outcome was in-hospital mortality. We performed a multivariable logistic regression analysis to estimate the association between abnormal PASI and study outcomes after adjusting for potential confounders. An interaction analysis between PASI and sex was also conducted. Results: Of 6280 pediatric trauma patients, 10.9% (686) of the patients had abnormal PASI. In multivariable logistic regression analysis, abnormal PASI was significantly associated with increased in-hospital mortality [adjusted odds ratios (aOR), 1.74; 95% confidence interval (CI), 1.13–2.47]. Abnormal PASI had interaction effects with sex for in-hospital mortality (aOR, 1.86; 95% CI, 1.19–2.91 and aOR, 1.38; 95% CI, 0.58–2.99 for male and female, respectively) (p<0.01). Conclusion Abnormal PASI is associated with increased in-hospital mortality in pediatric trauma patients. The prediction power of PASI for in-hospital mortality was maintained only in male patients.

Purpose: Sleep apnea (SA) is a risk factor for coronary artery disease (CAD), and SA and CAD increase the incidence of sudden cardiac arrest (SCA). This study aimed to investigate the effect of SA on the incidence of SCA and explore the effect of varying degrees of SA with or without CAD on the incidence of SCA. Materials and Methods: This prospective multi-center, case-control study was performed using the phase II Cardiac Arrest Pursuit Trial with Unique Registry and Epidemiologic Surveillance (CAPTURES-II) database for SCA cases and community-based controls in Korea. The matching ratio of cases to controls was 1:1, and they were randomly matched within demographics, including age, sex, and residence. The primary variable was a history of SA, and the second variable was a history of CAD. We conducted a conditional logistic regression analysis to estimate the effect of SA and CAD on the SCA risk, and an interaction analysis between SA and CAD. Results: SA was associated with an increased risk of SCA [adjusted odds ratio (AOR) (95% confidence interval, CI): 1.54 (1.16–2.03)], and CAD was associated with an increased risk of SCA [AOR (95% CI): 3.94 (2.50–6.18)]. SA was a risk factor for SCA in patients without CAD [AOR (95% CI): 1.62 (1.21–2.17)], but not in patients with CAD [AOR (95% CI): 0.56 (0.20–1.53)]. Conclusion In the general population, SA is risk factor for SCA only in patients without CAD. Early medical intervention for SA, especially in populations without pre-existing CAD, may reduce the SCA risk.ClinicalTrials.gov (NCT03700203)