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"Biological Markers"

Original Articles
Relationships between the Level of Alcohol Consumption and Abnormality in Biomarkers According to Facial Flushing in Korean Male Drinkers
Seong Gu Kim, Jong Sung Kim, Sung Soo Kim, Jin Gyu Jung, Seok Jun Yun, Eo Chin Kim
Korean J Fam Med 2013;34(2):123-130.   Published online March 20, 2013
DOI: https://doi.org/10.4082/kjfm.2013.34.2.123
Background

This research investigated the association between facial flushing after drinking and alcohol-induced biomarker abnormalities.

Methods

This retrospective study included 374 male drinkers who visited the department of Family Medicine of Chungnam National University Hospital between January and December of 2010. The participants were classified into two groups: the flushing group (n = 107) and the non-flushing group (n = 267). The biomarkers assessed were % carbohydrate-deficient transferrin (CDT) and gamma glutamyl transferase (rGTP). The upper limits of %CDT and rGTP were set as 2.47 and 50, respectively. The receiver operating characteristic (ROC) curve was used to obtain the cut-off value for the amount of drinking that caused abnormal %CDT and rGTP levels in the two groups. The sensitivity and specificity of the cut-off drinking amount for %CDT and rGTP abnormalities were analyzed in each group.

Results

In the flushing group, the cut-off value for alcohol-induced %CDT abnormality was 3.38 drinks (1 drink: 14 g of alcohol) per week, with sensitivity of 77.8% and specificity of 70.4%. In the non-flushing group, the cut-off value was 11.25 drinks per week, with sensitivity of 62.2% and specificity of 69.6%. The cut-off value for the amount of alcohol that induced rGTP abnormality was 3.38 drinks per week in the flushing group, with sensitivity of 68.0% and specificity of 76.8%, whereas it was 8.75 drinks in the non-flushing group, with sensitivity of 71.1% and specificity of 66.7%. The area under the ROC of the drinking level was 0.726 in the flushing group and 0.684 in the non-flushing group for %CDT. For rGTP, the value was 0.738 in the flushing group and 0.718 in the non-flushing group.

Conclusion

The weekly drinking amount required to induce biomarker abnormalities was lower in the flushers than in the non-flushers.

Citations

Citations to this article as recorded by  
  • Guidelines for an alcohol clinic in primary healthcare clinics
    Jin-Gyu Jung, Jong-Sung Kim, Seok-Joon Yoon, Jang-Hee Hong, Jung Sunwoo
    Journal of the Korean Medical Association.2024; 67(4): 256.     CrossRef
  • Current Status of Korean Alcohol Drinking in Accordance with the Korean Alcohol Guidelines for Moderate Drinking Based on Facial Flushing
    Sami Lee, Jihan Kim, Jong Sung Kim
    Korean Journal of Family Medicine.2023; 44(3): 129.     CrossRef
  • Korean Alcohol Guidelines for Primary Care Physician
    Jin-Gyu Jung, Jong-Sung Kim, Seok-Joon Yoon, Sami Lee, Soon-Ki Ahn
    Korean Journal of Family Practice.2021; 11(1): 14.     CrossRef
  • Korean Alcohol Guidelines for Moderate Drinking Based on Facial Flushing
    Sami Lee, Jong-Sung Kim, Jin-Gyu Jung, Mi-Kyeong Oh, Tae-Heum Chung, Jihan Kim
    Korean Journal of Family Medicine.2019; 40(4): 204.     CrossRef
  • Diagnostic Usefulness of Korean Standard on Heavy Drinking for the DSM-5 Alcohol Use Disorder
    Seong Gu Kim, Jong Sung Kim, Han Ju Pack, Han Na Sung
    Korean Journal of Health Promotion.2017; 17(2): 91.     CrossRef
  • Drinking Amount Associated with Abnormal Gamma-Glutamyl Transpeptidase Expression in Women
    Jun-Seok Yang, Jong-Sung Kim, Won-Yoon Seo, Sir-Chae Paik
    Korean Journal of Family Medicine.2016; 37(1): 2.     CrossRef
  • Biomolecules and Biomarkers Used in Diagnosis of Alcohol Drinking and in Monitoring Therapeutic Interventions
    Radu Nanau, Manuela Neuman
    Biomolecules.2015; 5(3): 1339.     CrossRef
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The pattern of urinary deoxypyridinoline and serum osteocalcin across menopausal transition in women.
Sang Han Choi, Sang Yeoup Lee, Yun Jin Kim
J Korean Acad Fam Med 2000;21(12):1552-1559.   Published online December 1, 2000
Background
: Biochemical markers have been proposed as sensitive indicators of high bone turnover and for monitoring response to osteoporosis treatment. We conducted a retrospective study to investigate the pattern of biochemical markers of bone metabolism (urinary deoxypryridinoline (D-PYD), serum osteocalcin) across menopausal transition in women.

Methods : We measured the urinary excretion of D-PYD, serum osteocalcin and BMD in 44 premenopausal and age-matched 44 postmenopausal women who visited a tertiary hospital from May 1, 1997 to July 31, 1997. Each values between premenopausal and postmenopausal women were anaysed with paired t-tests. Pearson's correlation coefficients were performed to assess the relationships between the three values.

Results : Urinary excretion of D-PYD in postmenopausal women (12.103±2.27 nM/mM creatinine) was higher than in premenopausal women (9.322±.53 nM/mM creatinine) (P<0.05). Serum osteocalcin in postmenopausal women (12.8698±3.1 ng/ml) was higher than in premenopausal women (9.0949±2.7 ng/ml) (P<0.01). BMD in postmenopausal women (0.9979±0.1863 g/cm2) was lower than in postmenopausal women (1.1845±0.1591 g/cm2)(P<0.01). The serum osteocalcin level was positively correlated with D-PYD (r=0.547, p<0.01). Urine excretion of D-PYD was negatively correlated with BMD (r=-0.36, p<0.01). Serum osteocalcin was negatively correlated with BMD (r=-0.427, P<0.01).

Conclusion : Urinary D-PYD excretion and serum osteocalcin were increased, by BMD was decreased significantly in postmenopausal women. Urinary D-PYD, serum osteocalcin, and BMD were significantly correlated with each other in women.
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