Validation of resonance Raman spectroscopy-measured skin carotenoid status as a biomarker for fruit and vegetable intake in Korean adults.

Blood carotenoid concentration measurement is considered the gold standard for fruit and vegetable (F&V) intake estimation; however, this method is invasive and expensive. Recently, skin carotenoid status (SCS) measured by optical sensors has been evaluated as a promising parameter for F&V intake estimation. In this cross-sectional study, we aimed to validate the utility of resonance Raman spectroscopy (RRS)-assessed SCS as a biomarker of F&V intake in Korean adults. We used data from 108 participants aged 20-69 years who completed SCS measurements, blood collection and 3-d dietary recordings. Serum carotenoid concentrations were quantified using HPLC, and dietary carotenoid and F&V intakes were estimated via 3-d dietary records using a carotenoid database for common Korean foods. The correlations of the SCS with serum carotenoid concentrations, dietary carotenoid intake and F&V intake were examined to assess SCS validity. SCS was positively correlated with total serum carotenoid concentration (r = 0·52, 95 % CI = 0·36, 0·64, P < 0·001), serum ß-carotene concentration (r = 0·60, 95 % CI = 0·47, 0·71, P < 0·001), total carotenoid intake (r = 0·20, 95 % CI = 0·01, 0·37, P = 0·04), ß-carotene intake (r = 0·30, 95 % CI = 0·11, 0·46, P = 0·002) and F&V intake (r = 0·40, 95 % CI = 0·23, 0·55, P < 0·001). These results suggest that SCS can be a valid biomarker of F&V intake in Korean adults.

Prediction Algorithms for Blood Pressure Based on Pulse Wave Velocity Using Health Checkup Data in Healthy Korean Men: Algorithm Development and Validation.

BACKGROUND: Pulse transit time and pulse wave velocity (PWV) are related to blood pressure (BP), and there were continuous attempts to use these to predict BP through wearable devices. However, previous studies were conducted on a small scale and could not confirm the relative importance of each variable in predicting BP. OBJECTIVE: This study aims to predict systolic blood pressure and diastolic blood pressure based on PWV and to evaluate the relative importance of each clinical variable used in BP prediction models. METHODS: This study was conducted on 1362 healthy men older than 18 years who visited the Samsung Medical Center. The systolic blood pressure and diastolic blood pressure were estimated using the multiple linear regression method. Models were divided into two groups based on age: younger than 60 years and 60 years or older; 200 seeds were repeated in consideration of partition bias. Mean of error, absolute error, and root mean square error were used as performance metrics. RESULTS: The model divided into two age groups (younger than 60 years and 60 years and older) performed better than the model without division. The performance difference between the model using only three variables (PWV, BMI, age) and the model using 17 variables was not significant. Our final model using PWV, BMI, and age met the criteria presented by the American Association for the Advancement of Medical Instrumentation. The prediction errors were within the range of about 9 to 12 mmHg that can occur with a gold standard mercury sphygmomanometer. CONCLUSIONS: Dividing age based on the age of 60 years showed better BP prediction performance, and it could show good performance even if only PWV, BMI, and age variables were included. Our final model with the minimal number of variables (PWB, BMI, age) would be efficient and feasible for predicting BP.

The Association between Serum Vitamin D Concentration and Colon Polyp: A Cross-Sectional Study Using Health Care Screening Database in a Tertiary Hospital in Korea.

BACKGROUND: As indoor activity increases with modern lifestyles changes, reduced exposure to sunlight may lead to reduced vitamin D synthesis. Previous studies demonstrated that increased vitamin D level is associated with decreased risk of colon cancer; therefore, this study attempted to determine the association between vitamin D and colon polyps, which may be precancerous lesions, in participants who underwent colonoscopy exams. METHODS: A total of 31,004 participants who underwent routine health checkups, including vitamin D level and colonoscopy, at Samsung Medical Center in South Korea from 2010 to 2018 were included in the study. Colorectal polyps were diagnosed through biopsy after performing colonoscopy exams. Participants were categorized into three groups according to level of vitamin D (deficient: <20 ng/mL), insufficient: 20≤ vitamin D <30 ng/mL, and sufficient: ≥30 ng/mL). We analyzed the presence of colorectal polyps according to vitamin D level, and performed multiple logistic regression analyses for the association between vitamin D level and colorectal polyps. RESULTS: About 50% of participants had colorectal polyps (hyperplastic polyp, n=4,864; adenomatous polyp, n=10,470; adenocarcinoma, n=24). There were no significant associations between vitamin D categories and colorectal polyp and colorectal cancer. However, when further analyzing by type of polyp, the risk of hyperplastic polyps significantly decreased with increasing vitamin D levels (P for trend=0.006). CONCLUSION: We did not find evidence for an association between vitamin D and overall colorectal polyps; however, we observed a trend for decreased odds of hyperplastic polyps with increased vitamin D levels in comparison to vitamin D deficient subjects.

Application of Efficient Data Cleaning Using Text Clustering for Semistructured Medical Reports to Large-Scale Stool Examination Reports: Methodology Study.

BACKGROUND: Since medical research based on big data has become more common, the community's interest and effort to analyze a large amount of semistructured or unstructured text data, such as examination reports, have rapidly increased. However, these large-scale text data are often not readily applicable to analysis owing to typographical errors, inconsistencies, or data entry problems. Therefore, an efficient data cleaning process is required to ensure the veracity of such data. OBJECTIVE: In this paper, we proposed an efficient data cleaning process for large-scale medical text data, which employs text clustering methods and value-converting technique, and evaluated its performance with medical examination text data. METHODS: The proposed data cleaning process consists of text clustering and value-merging. In the text clustering step, we suggested the use of key collision and nearest neighbor methods in a complementary manner. Words (called values) in the same cluster would be expected as a correct value and its wrong representations. In the value-converting step, wrong values for each identified cluster would be converted into their correct value. We applied these data cleaning process to 574,266 stool examination reports produced for parasite analysis at Samsung Medical Center from 1995 to 2015. The performance of the proposed process was examined and compared with data cleaning processes based on a single clustering method. We used OpenRefine 2.7, an open source application that provides various text clustering methods and an efficient user interface for value-converting with common-value suggestion. RESULTS: A total of 1,167,104 words in stool examination reports were surveyed. In the data cleaning process, we discovered 30 correct words and 45 patterns of typographical errors and duplicates. We observed high correction rates for words with typographical errors (98.61%) and typographical error patterns (97.78%). The resulting data accuracy was nearly 100% based on the number of total words. CONCLUSIONS: Our data cleaning process based on the combinatorial use of key collision and nearest neighbor methods provides an efficient cleaning of large-scale text data and hence improves data accuracy.

Results of a survey of residents who experience pregnancy and delivery.

PURPOSE: A growing number of residents bear children during residency training. This study was conducted to examine the pregnancy and maternity leave experiences of women who delivered infants during their residency training. METHODS: From March 2007 through June 2007, we surveyed 94 women who had given birth during their residency training during the past 5 years from the survey date. Participants were recruited using snowball sampling. RESULTS: Most of the respondents (70.2%) delivered in the 3rd and 4th year of residency. The average length of leave was 68.9 days, and more than half (54.3%) of the women expressed that a maternity leave policy was not formally established in the department. In general, participants believed that having a child during residency was difficult (mean=4.18 in 5-point Likert scale), and this perception was inversely related with systematic departmental support. CONCLUSION: Pregnancy is a special challenge for residents, with regard to not only physical overexertion but also psychosocial impacts on pregnant residents and their colleagues. However, most current residency programs do not have written policies on pregnancy. A formal policy and more flexible curriculum can help both the training program and the pregnant resident.

Trends in avoidable death over 20 years in Korea.

To evaluate the achievement of health care services in Korea independent of other socioeconomic factors, we observed the time trend of avoidable death between 1983 and 2004. A list of avoidable causes of death was constructed based on the European Community Atlas of "Avoidable Death". We calculated sex- and age-standardized mortality rates of Korean aged 1-64 yr using data of the Korea National Statistical Office. The avoidable mortality rate (per 100,000 persons) decreased from 225 to 84 in men and from 122 to 41 in women. Accordingly, the proportion of avoidable deaths among all classifiable deaths was reduced by 8.1% in men and 6.4% in women. However, mortality rates from some preventable causes such as ischemic heart disease and malignant neoplasms of lung, breast, cervix, and colorectum have been on the rise. Mortality preventable by appropriate medical care showed the greatest reduction (by 77.8%), while the mortality preventable by primary prevention showed the least reduction (by 50.0%). These findings suggest that health care service has significantly contributed to the improvement of health in Korea. However, more effective intervention programs would be needed given the less reduction in mortality avoidable by primary or secondary prevention than expected and unexpectedly increasing mortality from several preventable causes.