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Nonfasting versus fasting lipid profile for cardiovascular risk prediction.

Pathology 2019 Februrary
Before 2009 essentially all societies, guidelines, and statements required fasting before measuring a lipid profile for cardiovascular risk prediction. This was mainly due to the increase seen in triglycerides during a fat tolerance test. However, individuals eat much less fat during a normal day and nonfasting triglycerides have been shown to be superior to fasting in predicting cardiovascular risk. Lipids and lipoproteins only change minimally in response to normal food intake: in four large prospective studies, maximal mean changes were +0.3 mmol/L (26 mg/dL) for triglycerides, -0.2 mmol/L (8 mg/dL) for total cholesterol, -0.2 mmol/L (8 mg/dL) for LDL cholesterol, and -0.1 mmol/L (4 mg/dL) for HDL cholesterol. Further, in 108,602 individuals from the Copenhagen General Population Study in random nonfasting samples, the highest versus the lowest quartile of triglycerides, total cholesterol, LDL cholesterol, remnant cholesterol, non-HDL cholesterol, lipoprotein(a), and apolipoprotein B were all associated with higher risk of both ischaemic heart disease and myocardial infarction. Finally, lipid-lowering trials using nonfasting blood samples for assessment of lipid levels found that reducing levels of nonfasting lipids reduced the risk of cardiovascular disease. To date there is no sound scientific evidence as to why fasting should be superior to nonfasting when evaluating a lipid profile for cardiovascular risk prediction. Indeed, nonfasting samples rather than fasting samples have many obvious advantages. First, it would simplify blood sampling in the laboratory. Second, it would benefit the patient, avoiding the inconvenience of fasting and therefore needing to have blood drawn early in the day. Third, for individuals with diabetes, the risk of hypoglycaemia due to fasting would be minimised. Many countries are currently changing their guidelines towards a consensus on measuring a lipid profile for cardiovascular risk prediction in the nonfasting state, simplifying blood sampling for patients, laboratories, and clinicians worldwide.

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