Purpose: This study investigated the factors influencing smartphone overdependence in university students using an ecological model and descriptive research. Methods: Data were collected from 482 students at 13 universities in the six regions in South Korea from October 20, 2020, to March 25, 2021. Data analysis involved descriptive statistics, the chi-square test, the independent samples t-test, analysis of variance, and hierarchical multiple regression. Results: The significant ecological factors influencing smartphone overdependence included self-awareness of smartphone overdependence (β=.33, p<.001), autonomy (β=–.25, p<.001), average daily smartphone usage time (β=.18, p<.001), gender (β=.15, p=.001), college year (β=.15, p=.020), forming relationships with others as a motivation for smartphone use (β=–.15, p=.008), friend support (β=.14, p=.006), and age (β=–.12, p=.047). The model explained 34.9% of the variance. Conclusion The study emphasized the role of personal and interpersonal factors, in smartphone overdependence among university students. Tailored intervention strategies are necessary to address smartphone overdependence, considering the unique characteristics of students’ environments. A significant aspect of this study is that it provides an explanation of the multidimensional factors contributing to smartphone overdependence among university students, including intrapersonal, interpersonal, and environmental influences.

Background: Barriers to treatment with intravenous thrombolysis (IVT) for patients with acute ischemic stroke (AIS) in South Korea remain incompletely characterized. We analyze a nationwide prospective cohort to determine patient-level features associated with delayed presentation and non-treatment of potential IVT-eligible patients. Methods: We identified consecutive patients with AIS from 01/2011 to 08/2023 from a multicenter and prospective acute stroke registry in Korea. Patients were defined as IVT candidates if they presented within 4.5 hours from the last known well, had no lab evidence of coagulopathy, and had National Institute of Health Stroke Scale (NIHSS) ≥ 4. Multivariable generalized linear mixed regression models were used to investigate the associations between their characteristics and the IVT candidates or the use of IVT among the candidates. Results: Among 84,103 AIS patients, 41.0% were female, with a mean age of 69 ± 13 years and presentation NIHSS of 4 [interquartile range, 1–8]. Out of these patients, 13,757 (16.4%) were eligible for IVT, of whom 8,179 (59.5%) received IVT. Female sex (adjusted risk ratio [RR], 0.90; 95% confidence interval [CI], 0.86–0.94) and lower years of education (adjusted RR, 0.90; 95% CI, 0.84–0.97 for 0–3 years, compared to ≥ 13 years) were associated with a decreased likelihood of presenting as eligible for IVT after AIS; meanwhile, young age (adjusted RR, 1.12; 95% CI, 1.01–1.24 for ≤ 44 years, compared to 75–84 years) was associated with an increased likelihood of being an IVT candidate. Among those who were eligible for IVT, only age was significantly associated with the use of IVT (adjusted RR, 1.09; 95% CI, 1.03–1.16 for age 65–74 and adjusted RR, 0.83; 95% CI, 0.76–0.90 for ≥ 85 years, respectively). Conclusion Most patients with AIS present outside IVT eligibility in South Korea, and only 60% of eligible patients were ultimately treated. We identified increased age, female sex and lower education as key features on which to focus interventions for improving IVT utilization.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Objective: : Korea’s healthcare system and policy promotes early, actively stroke treatment to improve prognosis. This study represents stroke epidemiology and outcomes in Korea. Methods: : This study investigated data from the Acute Stroke Assessment Registry. The registry collects data from over 220 hospitals nationwide, focusing on quality stroke service management. Data analysis included patient demographics, stroke severity assessment, and discharge prognosis measurement using standardized scales. Results: : Eighty-six thousand five hundred sixty-eight acute stroke patients were collected with demographic and clinical characteristics during 18 months from 2016, 2018, and between 2020 to 2021, focusing on acute subarachnoid hemorrhage (SAH), acute intracerebral hemorrhage (ICH), and acute ischemic stroke. Of these 86568 patients, 8.3% was SAH, 16.3% ICH, and 74.9% ischemic stroke. Trends showed decreasing SAH and increasing ICH cases over the years. 68.3% stroke patients had the clear onset time. 49.6% stroke patients arrived within 4.5 hours of symptom onset, with more patients treated at general hospitals. Good functional outcomes at discharge was obtained with 58.3% of acute stroke patients, 55.9% of SAH patients, 34.6% of ICH patients, and 63.8% of ischemic stroke patients. Conclusion : The results showed that ischemic stroke was the most common subtype, followed by ICH and SAH. Prognosis differed among subtypes, with favorable outcomes more common in ischemic stroke and SAH compared to ICH.

Purpose: This study investigated the factors influencing smartphone overdependence in university students using an ecological model and descriptive research. Methods: Data were collected from 482 students at 13 universities in the six regions in South Korea from October 20, 2020, to March 25, 2021. Data analysis involved descriptive statistics, the chi-square test, the independent samples t-test, analysis of variance, and hierarchical multiple regression. Results: The significant ecological factors influencing smartphone overdependence included self-awareness of smartphone overdependence (β=.33, p<.001), autonomy (β=–.25, p<.001), average daily smartphone usage time (β=.18, p<.001), gender (β=.15, p=.001), college year (β=.15, p=.020), forming relationships with others as a motivation for smartphone use (β=–.15, p=.008), friend support (β=.14, p=.006), and age (β=–.12, p=.047). The model explained 34.9% of the variance. Conclusion The study emphasized the role of personal and interpersonal factors, in smartphone overdependence among university students. Tailored intervention strategies are necessary to address smartphone overdependence, considering the unique characteristics of students’ environments. A significant aspect of this study is that it provides an explanation of the multidimensional factors contributing to smartphone overdependence among university students, including intrapersonal, interpersonal, and environmental influences.

Background: Barriers to treatment with intravenous thrombolysis (IVT) for patients with acute ischemic stroke (AIS) in South Korea remain incompletely characterized. We analyze a nationwide prospective cohort to determine patient-level features associated with delayed presentation and non-treatment of potential IVT-eligible patients. Methods: We identified consecutive patients with AIS from 01/2011 to 08/2023 from a multicenter and prospective acute stroke registry in Korea. Patients were defined as IVT candidates if they presented within 4.5 hours from the last known well, had no lab evidence of coagulopathy, and had National Institute of Health Stroke Scale (NIHSS) ≥ 4. Multivariable generalized linear mixed regression models were used to investigate the associations between their characteristics and the IVT candidates or the use of IVT among the candidates. Results: Among 84,103 AIS patients, 41.0% were female, with a mean age of 69 ± 13 years and presentation NIHSS of 4 [interquartile range, 1–8]. Out of these patients, 13,757 (16.4%) were eligible for IVT, of whom 8,179 (59.5%) received IVT. Female sex (adjusted risk ratio [RR], 0.90; 95% confidence interval [CI], 0.86–0.94) and lower years of education (adjusted RR, 0.90; 95% CI, 0.84–0.97 for 0–3 years, compared to ≥ 13 years) were associated with a decreased likelihood of presenting as eligible for IVT after AIS; meanwhile, young age (adjusted RR, 1.12; 95% CI, 1.01–1.24 for ≤ 44 years, compared to 75–84 years) was associated with an increased likelihood of being an IVT candidate. Among those who were eligible for IVT, only age was significantly associated with the use of IVT (adjusted RR, 1.09; 95% CI, 1.03–1.16 for age 65–74 and adjusted RR, 0.83; 95% CI, 0.76–0.90 for ≥ 85 years, respectively). Conclusion Most patients with AIS present outside IVT eligibility in South Korea, and only 60% of eligible patients were ultimately treated. We identified increased age, female sex and lower education as key features on which to focus interventions for improving IVT utilization.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Objective: : Korea’s healthcare system and policy promotes early, actively stroke treatment to improve prognosis. This study represents stroke epidemiology and outcomes in Korea. Methods: : This study investigated data from the Acute Stroke Assessment Registry. The registry collects data from over 220 hospitals nationwide, focusing on quality stroke service management. Data analysis included patient demographics, stroke severity assessment, and discharge prognosis measurement using standardized scales. Results: : Eighty-six thousand five hundred sixty-eight acute stroke patients were collected with demographic and clinical characteristics during 18 months from 2016, 2018, and between 2020 to 2021, focusing on acute subarachnoid hemorrhage (SAH), acute intracerebral hemorrhage (ICH), and acute ischemic stroke. Of these 86568 patients, 8.3% was SAH, 16.3% ICH, and 74.9% ischemic stroke. Trends showed decreasing SAH and increasing ICH cases over the years. 68.3% stroke patients had the clear onset time. 49.6% stroke patients arrived within 4.5 hours of symptom onset, with more patients treated at general hospitals. Good functional outcomes at discharge was obtained with 58.3% of acute stroke patients, 55.9% of SAH patients, 34.6% of ICH patients, and 63.8% of ischemic stroke patients. Conclusion : The results showed that ischemic stroke was the most common subtype, followed by ICH and SAH. Prognosis differed among subtypes, with favorable outcomes more common in ischemic stroke and SAH compared to ICH.

Background: Insulin resistance (IR) is central to metabolic disorders and significantly influenced by diet. Studies on meal frequency (MF) and metabolic indicators have shown mixed results. This study explores the link between MF and IR in middle-aged and older adults. Methods: This prospective cohort study included 4,570 adults aged 40 to 69 years from the Korean Genome and Epidemiologic Study. MF were divided into two groups based on whether they consumed three or more, or fewer than three, meals daily. IR was evaluated using the homeostasis model assessment of insulin resistance (HOMA-IR); participants were classified as IR if their HOMA-IR value was ≥2.5. Multiple Cox proportional hazard regression analyses were conducted to examine the association between MF and the incidence of IR. Results: After adjusting for all variables, individuals in the MF ≥3 group showed a reduced incidence of IR compared to those in the MF <3 group (hazard ratio, 0.880; 95% confidence interval, 0.782 to 0.990). Additionally, subgroup analyses by sex, diabetes mellitus (DM), and body mass index (BMI) showed that this association persisted only in men, individuals without DM, and those with a BMI <25. Conclusion Our findings indicate that a higher MF among middle-aged and older adults is associated with a reduced incidence of IR. However, this association was maintained only in men, individuals without DM, and those without obesity.

Background: Studies on predictive markers of insulin resistance (IR) and elevated liver transaminases in children and adolescents are limited. We evaluated the predictive capabilities of the single-point insulin sensitivity estimator (SPISE) index, metabolic score for insulin resistance (METS-IR), homeostasis model assessment of insulin resistance (HOMA-IR), the triglyceride (TG)/ high-density lipoprotein cholesterol (HDL-C) ratio, and the triglyceride-glucose index (TyG) for IR and alanine aminotransferase (ALT) elevation in this population. Methods: Data from 1,593 participants aged 10 to 18 years were analyzed using a nationwide survey. Logistic regression analysis was performed with IR and ALT elevation as dependent variables. Receiver operating characteristic (ROC) curves were generated to assess predictive capability. Proportions of IR and ALT elevation were compared after dividing participants based on parameter cutoff points. Results: All parameters were significantly associated with IR and ALT elevation, even after adjusting for age and sex, and predicted IR and ALT elevation in ROC curves (all P<0.001). The areas under the ROC curve of SPISE and METS-IR were higher than those of TyG and TG/HDL-C for predicting IR and were higher than those of HOMA-IR, TyG, and TG/HDL-C for predicting ALT elevation. The proportions of individuals with IR and ALT elevation were higher among those with METS-IR, TyG, and TG/ HDL-C values higher than the cutoff points, whereas they were lower among those with SPISE higher than the cutoff point. Conclusion SPISE and METS-IR are superior to TG/HDL-C and TyG in predicting IR and ALT elevation. Thus, this study identified valuable predictive markers for young individuals.