Effect of Uric Acid on the Development of Chronic Kidney Disease: The Korean Multi-Rural Communities Cohort Study / 예방의학회지

OBJECTIVES: Several studies have investigated the effects of serum uric acid (SUA) levels on chronic kidney disease (CKD), with discrepant results. The effect of SUA levels on CKD development was studied in the Korean rural population. METHODS: A total of 9695 participants aged ≥40 years were recruited from 3 rural communities in Korea between 2005 and 2009. Of those participants, 5577 who participated in the follow-up and did not have cerebrovascular disease, myocardial infarction, cancer, or CKD at baseline were studied. The participants, of whom 2133 were men and 3444 were women, were grouped into 5 categories according to their quintile of SUA levels. An estimated glomerular filtration rate of < 60 mL/min/1.73 m2 at the time of follow-up was considered to indicate newly developed CKD. The effects of SUA levels on CKD development after adjusting for potential confounders were assessed using Cox proportional hazard models. RESULTS: Among the 5577 participants, 9.4 and 11.0% of men and women developed CKD. The hazard ratio (HR) of CKD was higher in the highest quintile of SUA levels than in the third quintile in men (adjusted HR, 1.60; 95% confidence interval [CI], 1.02 to 2.51) and women (adjusted HR, 1.56; 95% CI, 1.14 to 2.15). Furthermore, CKD development was also more common in the lowest quintile of SUA levels than in the third quintile in men (adjusted HR, 1.83; 95% CI, 1.15 to 2.90). The effect of SUA was consistent in younger, obese, and hypertensive men. CONCLUSIONS: Both high and low SUA levels were risk factors for CKD development in rural Korean men, while only high levels were a risk factor in their women counterparts.

Verification of learner’s differences by team-based learning in biochemistry classes / 한국의학교육

PURPOSE: We tested the effect of team-based learning (TBL) on medical education through the second-year premedical students’ TBL scores in biochemistry classes over 5 years. METHODS: We analyzed the results based on test scores before and after the students’ debate. The groups of students for statistical analysis were divided as follows: group 1 comprised the top-ranked students, group 3 comprised the low-ranked students, and group 2 comprised the medium-ranked students. Therefore, group T comprised 382 students (the total number of students in group 1, 2, and 3). To calibrate the difficulty of the test, original scores were converted into standardized scores. We determined the differences of the tests using Student t-test, and the relationship between scores before, and after the TBL using linear regression tests. RESULTS: Although there was a decrease in the lowest score, group T and 3 showed a significant increase in both original and standardized scores; there was also an increase in the standardized score of group 3. There was a positive correlation between the pre- and the post-debate scores in group T, and 2. And the beta values of the pre-debate scores and “the changes between the pre- and post-debate scores” were statistically significant in both original and standardized scores. CONCLUSION: TBL is one of the educational methods for helping students improve their grades, particularly those of low-ranked students.