Clinical study on non-fasting blood lipids in patients with type 2 diabetes / 中华内分泌外科杂志

Objective:To study the feasibility of non-fasting blood lipid detection in patients with type 2 diabetes mellitus (T2DM) .Methods:A total of 426 diabetic patients hospitalized in the Second Hospital of Tianjin Medical University from Oct. 2018 to Apr. 2019 were selected to collect blood samples from the fasting and non-fasting state of the patients respectively. The levels of plasma three acylglycerol (TG) , total cholesterol (TC) , high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C) were measured at the same time, and self-control method was used. The results of two tests were compared with the wilcoxon signed-rank test.Results:Compared with the fasting results, non-fasting TG increased by 0.25 mmol/L (11.2%) , with statistical significance ( P<0.05) ; TC increased by 0.17 mmol/L (4.5%) , HDL-C increased by 0.08 mmol/L (5.7%) , and LDL-C decreased by 0.05 mmol/L (5.9%) , without significant differenc ( P>0.05) . Conclusion:Except for TG, non-fasting TC, HDL-C, LDL-C has little change compared with those in fasting state, which can replace fasting blood lipid detection as a method for detecting blood lipid profile in patients with T2DM.

Comparison between Fasting and Non-Fasting Sample for the Determination of Serum Lipid Profile.

For determination of serum lipid profile, traditionally we use fasting blood sample. Though it has been the most reliable method for testing lipid profile, it has some drawbacks. Fasting is not easy for some people specially children, diabetics and also it is a barrier for population screening. So, intent of our study is to check the authenticity of results obtained using non-fasting samples by correlating it with the results obtained using fasting samples. We wanted to estimate & compare fasting and non-fasting lipid profile values in severe diabetic patients and in apparently healthy controls.METHODSThis analytical cross sectional study included 40 apparently healthy controls and 40 diabetic patients as participants confirmed by history and biochemical tests. Blood sample was collected from each patient two times; once after 10-12 hours fasting and other as a random sample. Lipid profile parameters were estimated using standard tests. Statistical analysis was done by using Pearson’s correlation coefficient. Data analysis was carried by Statistical Package SPSS and Microsoft Excel and p<0.05 was considered as level of significance.RESULTSIn apparently healthy controls differences between fasting and non-fasting concentrations were small and clinically insignificant for lipid profile parameters like total cholesterol (p=0.861), LDL-cholesterol (p=0.203) and HDL-cholesterol (p=0.916). The difference was statistically significant (p=0.001) for triglycerides.CONCLUSIONSFasting samples are preferable for serum lipid profile measurement in all individuals with serum triglyceride levels greater than 350 mg/dL. But, non-fasting samples for lipid profile can be used for cardiovascular risk determination in the general people as it reduces patient’s inconvenience and promotes patient acquiescence towards lipid profile checking.

Comparison of fasting and non-fasting serum lipid profile in healthy population

Background: Serum lipids are routinely used for the assessment of cardiovascular risk. The test is usually performed under fasting condition. However, recently non-fasting lipid profile is also measured in certain cases. The present study was intended to estimate the concentration of total cholesterol (TC), triglyceride (TG), HDL cholesterol (HDL-C), LDL cholesterol (LDL-C) and VLDL cholesterol (VLDL-C) in fasting as well as non-fasting blood samples of a group of normal male and female subjects.Methods: The study recruited 50 normal healthy male and female subjects within the age group of 12-48 years. The concentration of TC, TG, HDL-C, LDL-C and VLDL-C in serum of these subjects were quantitatively determined using the commercially available kits based on CHOD/POD method.Results: The mean concentration of non-fasting TC, TG, HDL-C, LDL-C and VLDL-C was found to be 141.20 mg/dl, 132.20 mg/dl, 50.39 mg/dl, 64.30 mg/dl, 26.44 mg/dl respectively. On the other hand, the mean concentration of fasting TC, TG, HDL-C, LDL-C and VLDL-C was found to be 112.37 mg/dl, 100.90 mg/dl, 38.59 mg/dl, 53.59 mg/dl and 20.18 mg/dl respectively. The concentration of fasting lipid profile parameters was significantly low from the respective parameters of non-fasting lipid profile.Conclusions: The present study reveals that there was an increase in the levels of TC, TG, HDL-C, LDL-C, and VLDL-C in non-fasting state compared to the fasting state. Measuring the lipid profile parameters under non-fasting state cannot be usually considered for assessment of cardiovascular risk and for other clinical purposes.

Comparison of fasting and non－fasting blood lipid levels in children in Tianjin / 中华实用儿科临床杂志

Objective To compare the difference between fasting blood lipids and non－fasting blood lipids in children in Tianjin,and to explore the feasibility of non－fasting blood lipids detection in children.Methods A total of 223 child patients were enrolled in Department of Pediatrics,the Second Hospital of Tianjin Medical University from January 2017 to February 2018,fasting and 1－6 h post－dining blood samples were collected from each patient.Total cholesterol (TC),triglyceride (TG),high－density lipoprotein cholesterol (HDL－C)and low－density lipoprotein cholesterol (LDL－C)were measured.Self－control methods were used.Wilcoxon signed rank test was used for statisti-cal analysis.Results Compared with fasting lipids,non－fasting TC increased with 0.02 mmol/L,TG increased with 0.01 mmol/L,HDL－C increased with 0.03 mmol/L,while LDL－C decreased with 0.01 mmol/L,but non－high－density lipoprotein cholesterol did not change.Among them,only the difference in HDL －C between the fasting and non－fasting was statistically significant (Z＝ －2.870,P＜0.05).The difference in the change rate of all indicators was ＜3%.According to the dyslipidemia group comparison,the differences in hypercholesterolemia (0.72 mmol/L, Z＝ －2.551,P＝0.011),hypertriglyceridemia (0.73 mmol/L,Z＝ －3. 846,P＜0.001),low high－density lipopro-tein cholesterolemia (－0.04 mmol/L,Z ＝ －8.625,P ＜0.001)and normal level HDL －C (0.1 mmol/L,Z ＝－5.040,P＜0.001)between non －fasting lipids and fasting blood lipids were statistically significant.Conclusions The change of children's blood lipid profile in fasting and non－fasting conditions is little.Lipid testing in children does not require fasting.Blood tests can be performed at any appropriate time point in the normal diet.

Postprandial Lipid Concentrations and Daytime Biological Variation of Lipids in a Healthy Chinese Population

BACKGROUND: Several latest guidelines and consensus statements from Europe and the United States specify that there is no need for fasting prior to routine lipid tests. However, the latest Chinese guidelines still recommend fasting tests owing to a lack of local evidence. This study aimed to investigate postprandial lipid concentrations and daytime biological variation of lipids in a healthy Chinese population. METHODS: Venous blood samples were collected from 41 ostensibly healthy Chinese volunteers at five time points during the day (06:30, 09:00, 12:00, 15:00, and 18:30). The same batch of reagents was used to determine lipid concentrations. A nested ANOVA was performed to calculate within-subject biological variation (CVI) and between-subject biological variation (CVG). RESULTS: Postprandial concentrations of triglyceride were higher than fasting concentrations, with the maximum change occurring at 12:00 (0.5 hours after lunch, 0.21±0.65 mmol/L difference). The daytime biological variation of triglycerides was relatively high (CVI=25%, CVG=35.9%). The postprandial concentrations of total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, apolipoprotein A1, and apolipoprotein B were mostly lower than the fasting concentrations, and their daytime biological variations were relatively low (CVI=2.4–4.4%, CVG=11.8–18.7%). CONCLUSIONS: As most daytime lipid concentrations changed only slightly, non-fasting samples could be used for routine lipid tests. However, in cases of abnormal postprandial triglyceride concentrations, dietary factors and fasting time should be considered when interpreting the results.

Postprandial Triglyceride Is Associated with Fasting Triglyceride and HOMA-IR in Korean Subjects with Type 2 Diabetes

BACKGROUND: Recent studies indicate postprandial triglyceride (TG) had a better association with cardiovascular events and metabolic syndrome than fasting TG. The authors of the present study investigated the metabolic and clinical relevance of postprandial TG. METHODS: In a cross-sectional retrospective study, the authors of the present study compared fasting and postprandial TG and analyzed the relationship between postprandial TG and various demographic and metabolic parameters in 639 Korean subjects with type 2 diabetes (T2D, group I, n=539) and impaired fasting glucose (IFG, group II, n=100) after ingestion of a standardized liquid meal (total 500 kcal, 17.5 g fat, 68.5 g carbohydrate, and 17.5 g protein). RESULTS: Fasting and postprandial TG were significantly correlated (r=0.973, r=0.937, P<0.001) in group I and II, respectively. Of the variables, total cholesterol, waist circumference and body mass index were significantly correlated with fasting and postprandial TG in both groups. Only postprandial TG showed a significant correlation with glucose metabolic parameters (e.g., postprandial glucose, homeostatic model assessment of insulin resistance [HOMA-IR], and fasting C-peptide) in subjects with T2D. Multiple regression analysis showed fasting TG and HOMA-IR could be predictable variables for postprandial TG in subjects with T2D. CONCLUSION: Postprandial TG was very strongly correlated with fasting TG. The authors of the present study suggest insulin resistance may be more associated with postprandial TG than fasting TG in Korean T2D patients on a low-fat diet.