2022
DOI: 10.3389/fnut.2022.916704
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Evaluated Glomerular Filtration Rate Is Associated With Non-alcoholic Fatty Liver Disease: A 5-Year Longitudinal Cohort Study in Chinese Non-obese People

Abstract: ObjectiveEvidence regarding the association between evaluated glomerular filtration rate (eGFR) and non-alcoholic fatty liver disease (NAFLD) is still limited. On that account, the purpose of our research is to survey the link of evaluated eGFR on NAFLD.MethodsThis study is a retrospective cohort study. Which consecutively and non-selectively collected a total of 16,138 non-obese participants in a Chinese hospital from January 2010 to December 2014. We then used the Cox proportional-hazards regression model to… Show more

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Cited by 7 publications
(5 citation statements)
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“…The subgroup analyses were conducted using a stratified Cox proportional-hazards regression model across various subgroups (gender, age, UA, ALB, BMI, SBP, and DBP). Continuous variables such as age (<60 and ≥60 years old), UA (<420μmol/L and ≥420μmol/L), ALB (<30g/L and ≥30g/L), BMI (<25 and ≥25kg/m 2 ), SBP (<140 and ≥140 mmHg), DBP (<90 and ≥90 mmHg) [15][16][17] were transformed to a categorical variable based on the clinical cut point. Then, we adjusted each stratification for all factors (Models were adjusted for age, gender, BMI, SBP, DBP, ALT, AST, BUN, TC, TG, LDL-C, HDL-c, Scr, UA, CysC, TP, ALB, K, CA, P, HbA1c, 24h UP, and 24h UAlb, but not adjusted for stratification variables in each model).…”
Section: Discussionmentioning
confidence: 99%
“…The subgroup analyses were conducted using a stratified Cox proportional-hazards regression model across various subgroups (gender, age, UA, ALB, BMI, SBP, and DBP). Continuous variables such as age (<60 and ≥60 years old), UA (<420μmol/L and ≥420μmol/L), ALB (<30g/L and ≥30g/L), BMI (<25 and ≥25kg/m 2 ), SBP (<140 and ≥140 mmHg), DBP (<90 and ≥90 mmHg) [15][16][17] were transformed to a categorical variable based on the clinical cut point. Then, we adjusted each stratification for all factors (Models were adjusted for age, gender, BMI, SBP, DBP, ALT, AST, BUN, TC, TG, LDL-C, HDL-c, Scr, UA, CysC, TP, ALB, K, CA, P, HbA1c, 24h UP, and 24h UAlb, but not adjusted for stratification variables in each model).…”
Section: Discussionmentioning
confidence: 99%
“…The subgroup analyses were conducted using a stratified Cox proportional-hazards regression model across various subgroups (sex, age, SBP, DBP, BMI). Continuous variables as age (< 30, ≥ 30 to < 40, ≥ 40 to < 50, ≥ 50 to < 60, ≥ 60 to < 70, ≥ 70 years), BMI (< 25, ≥ 25 kg/m 2 ), SBP (< 140, ≥ 140 mmHg), DBP (< 90, ≥ 90 mmHg) [22][23][24] were transformed to a categorical variable based on the clinical cut point. Then we adjusted each stratification for all factors (Models were adjusted for age, sex, BMI, AST, ALT, SBP, DBP, HDL-c, LDL-C, BUN, Scr, smoking status, drinking status, and family history of diabetes, but not adjusted for stratification variables in each model).…”
Section: Discussionmentioning
confidence: 99%
“…Participants were stratified by eGFR quartile into Q1 (<82.88 ml/min/1.73 m 2 ), Q2 (≥82.88, <99.70), Q3 (≥99.70, <116.56), and Q4 (≥116.56) groups (43)(44)(45). For continuous variables, the mean (standard deviation) or median (range) (non-normal distribution) was used, and for categorical variables, the number (%) was used.…”
Section: Discussionmentioning
confidence: 99%