PURPOSE: This study was done to investigate the prevalence and risk factors of problem drinking among adolescents in South Korea. METHODS: The data of Youth Health Risk Behavior web-based Survey (2015) collected by Korean Centers for Disease Control and Prevention was analyzed using logistic regression for this study. RESULTS: The problem drinking (defined as two or more points in the CRAFFT) among current drinkers was 36.1%. Risk factors of the problem drinking were sexual activity after drinking (odds 6.33 for men, 4.72 for women), experience of smoking (odds 4.70 for men, 5.12 for women), experience of artificial abortion (odds 4.57 for women), experience of pregnancy (odds 4.45 for women), sexual transmitted infection (odds 1.90 for men, 2.53 for women), depression (odds 2.11 for men, 2.15 for women) and suicidal idea (odds 2.53 for men, 1.88 for women). CONCLUSION: It is necessary to develop proper problem drinking prevention programs focusing on men and women. Adjusted health education programs will contribute to maintain their health and protect effectively from these risk taking behaviors.
Adolescent* ; Alcohol Drinking ; Centers for Disease Control and Prevention (U.S.) ; Depression ; Drinking* ; Female ; Health Education ; Humans ; Korea* ; Logistic Models ; Male ; Pregnancy ; Prevalence ; Problem Behavior ; Risk Factors ; Risk-Taking ; Sexual Behavior ; Smoke ; Smoking

OBJECTIVE: There is a traditional assumption that to maximize stroke volume, the point beneath which the left ventricle (LV) is at its maximum diameter (P_max.LV) should be compressed. Thus, we aimed to derive and validate rules to estimate P_max.LV using anteroposterior chest radiography (chest_AP), which is performed for critically ill patients urgently needing determination of their personalized P_max.LV.METHODS: A retrospective, cross-sectional study was performed with non-cardiac arrest adults who underwent chest_AP within 1 hour of computed tomography (derivation:validation=3:2). On chest_AP, we defined cardiac diameter (CD), distance from right cardiac border to midline (RB), and cardiac height (CH) from the carina to the uppermost point of left hemi-diaphragm. Setting point zero (0, 0) at the midpoint of the xiphisternal joint and designating leftward and upward directions as positive on x- and y-axes, we located P_max.LV (x_max.LV, y_max.LV). The coefficients of the following mathematically inferred rules were sought: x_max.LV=α₀*CD-RB; y_max.LV=β₀*CH+γ₀ (α₀: mean of [x_max.LV+RB]/CD; β₀, γ₀: representative coefficient and constant of linear regression model, respectively).RESULTS: Among 360 cases (52.0±18.3 years, 102 females), we derived: x_max.LV=0.643*CD-RB and y_max.LV=55-0.390*CH. This estimated P_max.LV (19±11 mm) was as close as the averaged P_max.LV (19±11 mm, P=0.13) and closer than the three equidistant points representing the current guidelines (67±13, 56±10, and 77±17 mm; all P<0.001) to the reference identified on computed tomography. Thus, our findings were validated.CONCLUSION: Personalized P_max.LV can be estimated using chest_AP. Further studies with actual cardiac arrest victims are needed to verify the safety and effectiveness of the rule.
Adult ; Cardiopulmonary Resuscitation ; Critical Illness ; Cross-Sectional Studies ; Heart Arrest ; Heart Ventricles ; Humans ; Intensive Care Units ; Joints ; Linear Models ; Radiography ; Radiography, Thoracic ; Retrospective Studies ; Stroke Volume ; Thorax ; Tomography, X-Ray Computed

Objective: Peritonitis is a life-threatening, emergent surgical disease with very high mortality and morbidity. Currently, there are insufficient Korean studies using the P-POSSUM (Portsmouth-Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity) and the Mannheim Peritonitis Index (MPI) as risk prediction models for nontraumatic peritonitis patients who visit the emergency room. Methods: This retrospective study was carried out on 196 cases of non-traumatic peritonitis in a single emergency center from January 2015 to December 2019. Receiver operating characteristic (ROC) curves were obtained and the area under the ROC curve (AUC) was compared using both P-POSSUM and MPI. The observed mortality and expected mortality for P-POSSUM were compared using the goodness of fit assessed using the Hosmer-Lemeshow equation. Results: Diastolic blood pressure, blood urea nitrogen, potassium, length of stay, and intensive care unit admissions were significantly different between survivors and non-survivors. The AUC was 0.812 for P-POSSUM and 0.646 for MPI. The observed-to-expected mortality ratio for P-POSSUM indicated fewer than expected deaths in all quintiles of risk and this was more pronounced, especially when the expected mortality was over 60%. Conclusion In non-traumatic peritonitis patients, P-POSSUM was more useful in predicting risk than the MPI score. However, P-POSSUM overestimated the risk in high-risk patients. Although the MPI score is only somewhat useful for predicting mortality in patients with non-traumatic peritonitis, it is useful as an adjuvant.