Objectives: Emergency department (ED) overcrowding significantly impacts healthcare efficiency, safety, and resource management. Predictive models that utilize triage information can streamline the admission process. This review evaluates existing hospital admission prediction models that have been developed or validated using triage data for adult ED patients. Methods: A systematic search of PubMed, Embase, CINAHL, Web of Science, and the Cochrane Library was conducted. Studies were selected if they developed or validated predictive models for hospital admission using triage data from adult ED patients. Data extraction adhered to the CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies), and the risk of bias was evaluated using PROBAST (Prediction model Risk of Bias Assessment Tool). Results: Twenty studies met the inclusion criteria, employing logistic regression and machine learning techniques. Logistic regression was noted for its traditional use and clinical interpretability, whereas machine learning provided enhanced flexibility and potential for better predictive accuracy. Common predictors included patient demographics, triage category, vital signs, and mode of arrival. The area under the curve values for model performance ranged from 0.80 to 0.89, demonstrating strong discriminatory ability. However, external validation was limited, and there was variability in outcome definitions and model generalizability. Conclusions Predictive models based on triage data show promise in supporting ED operations by facilitating early predictions of hospital admissions, which could help decrease boarding times and enhance patient flow. Further research is necessary to validate these models in various settings to confirm their applicability and reliability.

Objectives: Emergency department (ED) overcrowding significantly impacts healthcare efficiency, safety, and resource management. Predictive models that utilize triage information can streamline the admission process. This review evaluates existing hospital admission prediction models that have been developed or validated using triage data for adult ED patients. Methods: A systematic search of PubMed, Embase, CINAHL, Web of Science, and the Cochrane Library was conducted. Studies were selected if they developed or validated predictive models for hospital admission using triage data from adult ED patients. Data extraction adhered to the CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies), and the risk of bias was evaluated using PROBAST (Prediction model Risk of Bias Assessment Tool). Results: Twenty studies met the inclusion criteria, employing logistic regression and machine learning techniques. Logistic regression was noted for its traditional use and clinical interpretability, whereas machine learning provided enhanced flexibility and potential for better predictive accuracy. Common predictors included patient demographics, triage category, vital signs, and mode of arrival. The area under the curve values for model performance ranged from 0.80 to 0.89, demonstrating strong discriminatory ability. However, external validation was limited, and there was variability in outcome definitions and model generalizability. Conclusions Predictive models based on triage data show promise in supporting ED operations by facilitating early predictions of hospital admissions, which could help decrease boarding times and enhance patient flow. Further research is necessary to validate these models in various settings to confirm their applicability and reliability.

Objectives: Emergency department (ED) overcrowding significantly impacts healthcare efficiency, safety, and resource management. Predictive models that utilize triage information can streamline the admission process. This review evaluates existing hospital admission prediction models that have been developed or validated using triage data for adult ED patients. Methods: A systematic search of PubMed, Embase, CINAHL, Web of Science, and the Cochrane Library was conducted. Studies were selected if they developed or validated predictive models for hospital admission using triage data from adult ED patients. Data extraction adhered to the CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies), and the risk of bias was evaluated using PROBAST (Prediction model Risk of Bias Assessment Tool). Results: Twenty studies met the inclusion criteria, employing logistic regression and machine learning techniques. Logistic regression was noted for its traditional use and clinical interpretability, whereas machine learning provided enhanced flexibility and potential for better predictive accuracy. Common predictors included patient demographics, triage category, vital signs, and mode of arrival. The area under the curve values for model performance ranged from 0.80 to 0.89, demonstrating strong discriminatory ability. However, external validation was limited, and there was variability in outcome definitions and model generalizability. Conclusions Predictive models based on triage data show promise in supporting ED operations by facilitating early predictions of hospital admissions, which could help decrease boarding times and enhance patient flow. Further research is necessary to validate these models in various settings to confirm their applicability and reliability.

Purpose: This study analyzed and evaluated qualitative studies of nurses' experiences with cardiopulmonary resuscitation (CPR) to understand their awareness and develop effective strategies. Methods: This study used an integrated literature review method developed by Whittemore and Knafl (2005). The scope of the literature search was broad and encompassed qualitative research exploring the experiences of nurses involved in CPR in hospitals.This search was conducted on March 27, 2023. For domestic literature, databases such as KOREAMed, KMBASE, and RISS were used, while foreign literature was sourced from PubMed, EMBASE, CINAHL, and COCHRANE databases. Results: After careful analysis, nine relevant literature pieces were selected, leading to the derivation of four key themes: “Perception of CPR,” “Positive Experiences during CPR,” “Barriers Impacting CPR Execution,” and “Strategies for Enhancing CPR Effectiveness.” Conclusion To positively reinforce the CPR experiences of nurses, it is necessary to establish educational programs and debriefings that reflect situations for effective coping with sufficient consideration of the medical environment of individual hospitals. Future research should consider comparative analyses of nurses' CPR experiences based on cultural factors and their respective working departments to identify areas for improvement.

Purpose: This study analyzed and evaluated qualitative studies of nurses' experiences with cardiopulmonary resuscitation (CPR) to understand their awareness and develop effective strategies. Methods: This study used an integrated literature review method developed by Whittemore and Knafl (2005). The scope of the literature search was broad and encompassed qualitative research exploring the experiences of nurses involved in CPR in hospitals.This search was conducted on March 27, 2023. For domestic literature, databases such as KOREAMed, KMBASE, and RISS were used, while foreign literature was sourced from PubMed, EMBASE, CINAHL, and COCHRANE databases. Results: After careful analysis, nine relevant literature pieces were selected, leading to the derivation of four key themes: “Perception of CPR,” “Positive Experiences during CPR,” “Barriers Impacting CPR Execution,” and “Strategies for Enhancing CPR Effectiveness.” Conclusion To positively reinforce the CPR experiences of nurses, it is necessary to establish educational programs and debriefings that reflect situations for effective coping with sufficient consideration of the medical environment of individual hospitals. Future research should consider comparative analyses of nurses' CPR experiences based on cultural factors and their respective working departments to identify areas for improvement.

Purpose: This study analyzed and evaluated qualitative studies of nurses' experiences with cardiopulmonary resuscitation (CPR) to understand their awareness and develop effective strategies. Methods: This study used an integrated literature review method developed by Whittemore and Knafl (2005). The scope of the literature search was broad and encompassed qualitative research exploring the experiences of nurses involved in CPR in hospitals.This search was conducted on March 27, 2023. For domestic literature, databases such as KOREAMed, KMBASE, and RISS were used, while foreign literature was sourced from PubMed, EMBASE, CINAHL, and COCHRANE databases. Results: After careful analysis, nine relevant literature pieces were selected, leading to the derivation of four key themes: “Perception of CPR,” “Positive Experiences during CPR,” “Barriers Impacting CPR Execution,” and “Strategies for Enhancing CPR Effectiveness.” Conclusion To positively reinforce the CPR experiences of nurses, it is necessary to establish educational programs and debriefings that reflect situations for effective coping with sufficient consideration of the medical environment of individual hospitals. Future research should consider comparative analyses of nurses' CPR experiences based on cultural factors and their respective working departments to identify areas for improvement.

Purpose: This study analyzed and evaluated qualitative studies of nurses' experiences with cardiopulmonary resuscitation (CPR) to understand their awareness and develop effective strategies. Methods: This study used an integrated literature review method developed by Whittemore and Knafl (2005). The scope of the literature search was broad and encompassed qualitative research exploring the experiences of nurses involved in CPR in hospitals.This search was conducted on March 27, 2023. For domestic literature, databases such as KOREAMed, KMBASE, and RISS were used, while foreign literature was sourced from PubMed, EMBASE, CINAHL, and COCHRANE databases. Results: After careful analysis, nine relevant literature pieces were selected, leading to the derivation of four key themes: “Perception of CPR,” “Positive Experiences during CPR,” “Barriers Impacting CPR Execution,” and “Strategies for Enhancing CPR Effectiveness.” Conclusion To positively reinforce the CPR experiences of nurses, it is necessary to establish educational programs and debriefings that reflect situations for effective coping with sufficient consideration of the medical environment of individual hospitals. Future research should consider comparative analyses of nurses' CPR experiences based on cultural factors and their respective working departments to identify areas for improvement.

BACKGROUND: The importance of bone health is emphasized throughout the life cycle. Young adults have problems with bone health due to irregular lifestyle and unbalanced diet, but studies related to them are insufficient. The purpose of this study was to measure the bone mineral density (BMD) of college students and to analyze the differences in BMD according to lifestyle. METHODS: BMD was measured by bone ultrasound in 161 male and female college students. The questionnaire was surveyed about lifestyle, eating habits, and nutrient intake status. RESULTS: Osteopenia was 8.8% in male and 10.8% in female. The body fat percentage of female was significantly higher than male. Male college students, smoking, fast food consumption, and overeating rate were significantly higher than female. Nutrient intake was not significantly different between male and female students. But energy and vitamin A and C levels were inadequate, and protein and sodium intake was excessive compared with the recommended nutrient intake for Koreans. BMD was significantly lowest in male who often intake fast food than male who did not intake at all or intake sometimes. Female who often intake fast food had significantly lower BMD than female who did not eat at all. CONCLUSIONS: College students have different BMDs according to lifestyle. There was a difference in BMD according to smoking and fast food consumption.
Adipose Tissue ; Bone Density* ; Bone Diseases, Metabolic ; Diet ; Eating* ; Fast Foods ; Female ; Humans ; Hyperphagia ; Life Cycle Stages ; Life Style ; Male ; Nutritional Status ; Smoke ; Smoking ; Sodium ; Ultrasonography ; Vitamin A ; Young Adult

Background: In Korea, the Korean Community-based Noncommunicable Disease Prevention and Control Program (KCNPC) was implemented in 2012 for the management of patients with chronic diseases. Nineteen primary care clinics, public health centers, and education and consulting centers (ECCs) participated in the implementation of this program. This study assessed the effectiveness of this chronic disease control model by comparing mortality rate and the incidence of complications between patients participating in the KCNPC program and a control group. Methods: Using data from the National Health Insurance Service and data from hypertension and diabetes patients registered with 19 ECCs between January 1, 2010 and December 31, 2012, hypertension and diabetes patients who had been treated at a clinic were selected. The final analysis included 252,900 patients, with the intervention group and control group having 126,450 patients each. Survival for the two groups was analyzed using the Kaplan-Meier method. Complications were analyzed using the Cox proportional hazards model. Results: The 5-year survival rate in the intervention group (0.88) was higher than that in the control group (0.86). Cox proportional hazards analysis showed that the intervention group had lower risk for mortality (0.84; 95% confidence interval [CI], 0.82–0.86) compared to the control group. Hospitalization due to complications and the proportional risk of hospitalization were also lower in the intervention group. Conclusion The KCNPC model for prevention and control of chronic disease in Korea was found to be effective for hypertension and diabetes patients. Therefore, the KCNPC will be necessary to strengthen the capabilities of local communities, primary medical institutions, and individuals for prevention and control of chronic disease. Expanding the efficient prevention and control policies of the KCNPC to a nationwide scale may be effective as has been demonstrated through limited implementation in some regions.

Purpose: Breast cancer is known to be influenced by genetic and environmental factors, and several susceptibility genes have been discovered. Still, the majority of genetic contributors remain unknown. We aimed to analyze the plasma proteome of breast cancer patients in comparison to healthy individuals to identify differences in protein expression profiles and discover novel biomarkers. Methods: This pilot study was conducted using bioresources from Seoul National University Bundang Hospital’s Human Bioresource Center. Serum samples from 10 breast cancer patients and 10 healthy controls were obtained. Liquid chromatography-mass spectrometry analysis was performed to identify differentially expressed proteins. Results: We identified 891 proteins; 805 were expressed in the breast cancer group and 882 in the control group. Gene set enrichment and differential expression analysis identified 30 upregulated and 100 downregulated proteins in breast cancer. Among these, 10 proteins were selected as potential biomarkers. Three proteins were upregulated in breast cancer patients, including cluster of differentiation 44, eukaryotic translation initiation factor 2-α kinase 3, and fibronectin 1. Seven proteins downregulated in breast cancer patients were also selected: glyceraldehyde-3-phosphate dehydrogenase, α-enolase, heat shock protein member 8, integrin‑linked kinase, tissue inhibitor of metalloproteinases-1, vasodilatorstimulated phosphoprotein, and 14-3-3 protein gamma. All proteins had been previously reported to be related to tumor development and progression. Conclusion The findings suggest that plasma proteome profiling can reveal potential diagnostic biomarkers for breast cancer and may contribute to early detection and personalized treatment strategies. A further validation study with a larger sample cohort of breast cancer patients is planned.