Huang HT, Zhang XY, Zhang C, Ling Q, Zheng SS. Predicting dyslipidemia after liver transplantation: A significant role of recipient metabolic inflammation profile. World J Gastroenterol 2020; 26(19): 2374-2387
Corresponding Author of This Article
Qi Ling, MD, PhD, Doctor, Surgeon, Department of Surgery, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, No. 79, Qingchun Road, Hangzhou 310003, Zhejiang Province, China. email@example.com
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Table 3 Logistic regression analysis of variables related to post-transplant dyslipidemia
OR (95% CI)
Overweight was defined as body mass index > 25 kg/m2; hyper-triglyceride was defined as triglyceride ≥ 200 mg/dL; hypo-high density lipoprotein cholesterol was defined as high density lipoprotein cholesterol < 40 mg/dL. The warm ischemia time and total intravenous fluids were dichotomized at the median into high and low levels. OR: Odds ratio; CI: Confidence interval; TG: Triglyceride; HDLC: High density lipoprotein cholesterol; HCC: Hepatocellular carcinoma; WIT: Warm ischemia time.
Table 4 Multivariate logistic regression analysis of risk factors associated with post-transplant dyslipidemia
Low IL-12 (p70) level
Overweight was defined as body mass index > 25 kg/m2; hypo-high-density lipoprotein cholesterol was defined as high-density lipoprotein cholesterol < 40 mg/dL; interleukin-12 (p70) level was dichotomized at the median into high and low levels. OR: Odds ratio; CI: Confidence interval; HDLC: High-density lipoprotein cholesterol.
Citation: Huang HT, Zhang XY, Zhang C, Ling Q, Zheng SS. Predicting dyslipidemia after liver transplantation: A significant role of recipient metabolic inflammation profile. World J Gastroenterol 2020; 26(19): 2374-2387