Background and Objectives: Outcomes of deferring percutaneous coronary intervention (PCI) without invasive physiologic assessment for intermediate coronary lesions is uncertain.We sought to compare long-term outcomes between medical treatment and PCI of intermediate lesions without invasive physiologic assessment. Methods: A total of 899 patients with intermediate coronary lesions between 50% and 70% diameter-stenosis were randomized to the conservative group (n=449) or the aggressive group (n=450). For intermediate lesions, PCI was performed in the aggressive group, but was deferred in the conservative group. The primary endpoint was major adverse cardiac events (MACE, a composite of all-cause death, myocardial infarction [MI], or ischemia-driven any revascularization) at 3 years. Results: The number of treated lesions per patient was 0.8±0.9 in the conservative group and 1.7±0.9 in the aggressive group (p=0.001). At 3 years, the conservative group had a significantly higher incidence of MACE than the aggressive group (13.8% vs. 9.3%; hazard ratio [HR], 1.49; 95% confidence interval [CI], 1.00–2.21; p=0.049), mainly driven by revascularization of target intermediate lesion (6.5% vs. 1.1%; HR, 5.69; 95% CI, 2.20–14.73;p<0.001). Between 1 and 3 years after the index procedure, compared to the aggressive group, the conservative group had significantly higher incidence of cardiac death or MI (3.2% vs.0.7%; HR, 4.34; 95% CI, 1.24–15.22; p=0.022) and ischemia-driven any revascularization. Conclusions For intermediate lesions, medical therapy alone, guided only by angiography, was associated with a higher risk of MACE at 3 years compared with performing PCI, mainly due to increased revascularization.

Background and Objectives: Outcomes of deferring percutaneous coronary intervention (PCI) without invasive physiologic assessment for intermediate coronary lesions is uncertain.We sought to compare long-term outcomes between medical treatment and PCI of intermediate lesions without invasive physiologic assessment. Methods: A total of 899 patients with intermediate coronary lesions between 50% and 70% diameter-stenosis were randomized to the conservative group (n=449) or the aggressive group (n=450). For intermediate lesions, PCI was performed in the aggressive group, but was deferred in the conservative group. The primary endpoint was major adverse cardiac events (MACE, a composite of all-cause death, myocardial infarction [MI], or ischemia-driven any revascularization) at 3 years. Results: The number of treated lesions per patient was 0.8±0.9 in the conservative group and 1.7±0.9 in the aggressive group (p=0.001). At 3 years, the conservative group had a significantly higher incidence of MACE than the aggressive group (13.8% vs. 9.3%; hazard ratio [HR], 1.49; 95% confidence interval [CI], 1.00–2.21; p=0.049), mainly driven by revascularization of target intermediate lesion (6.5% vs. 1.1%; HR, 5.69; 95% CI, 2.20–14.73;p<0.001). Between 1 and 3 years after the index procedure, compared to the aggressive group, the conservative group had significantly higher incidence of cardiac death or MI (3.2% vs.0.7%; HR, 4.34; 95% CI, 1.24–15.22; p=0.022) and ischemia-driven any revascularization. Conclusions For intermediate lesions, medical therapy alone, guided only by angiography, was associated with a higher risk of MACE at 3 years compared with performing PCI, mainly due to increased revascularization.

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.

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.

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 and Objectives: Outcomes of deferring percutaneous coronary intervention (PCI) without invasive physiologic assessment for intermediate coronary lesions is uncertain.We sought to compare long-term outcomes between medical treatment and PCI of intermediate lesions without invasive physiologic assessment. Methods: A total of 899 patients with intermediate coronary lesions between 50% and 70% diameter-stenosis were randomized to the conservative group (n=449) or the aggressive group (n=450). For intermediate lesions, PCI was performed in the aggressive group, but was deferred in the conservative group. The primary endpoint was major adverse cardiac events (MACE, a composite of all-cause death, myocardial infarction [MI], or ischemia-driven any revascularization) at 3 years. Results: The number of treated lesions per patient was 0.8±0.9 in the conservative group and 1.7±0.9 in the aggressive group (p=0.001). At 3 years, the conservative group had a significantly higher incidence of MACE than the aggressive group (13.8% vs. 9.3%; hazard ratio [HR], 1.49; 95% confidence interval [CI], 1.00–2.21; p=0.049), mainly driven by revascularization of target intermediate lesion (6.5% vs. 1.1%; HR, 5.69; 95% CI, 2.20–14.73;p<0.001). Between 1 and 3 years after the index procedure, compared to the aggressive group, the conservative group had significantly higher incidence of cardiac death or MI (3.2% vs.0.7%; HR, 4.34; 95% CI, 1.24–15.22; p=0.022) and ischemia-driven any revascularization. Conclusions For intermediate lesions, medical therapy alone, guided only by angiography, was associated with a higher risk of MACE at 3 years compared with performing PCI, mainly due to increased revascularization.

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.