Dyslipidaemia and cardiovascular risk

After 30+ years of studying scientific journals, attending professional conferences, conducting research and communicating (often in person) with opinion makers at NIH and elsewhere about diagnosis, treatment and research for dyslipidemia, I disagree with the guidelines in this article.
According to my research, the best treatment for most patients is substantial weight loss and eating more essential fats (PUFAs of w3, w6 families). The reasons are explained in my publications and forthcoming books.
For these purposes, and most patients, blood tests are not needed. Instead, use “eyes” (observation), measuring tape around the waist, a scale, height measure. Most cost/effective diagnosis can be accomplished in 2 minutes (most people are overweight and do not eat enough essential fats).
Instead of expensive treatments, send patients to work on farms growing organic foods, 12 to 14 hrs/day, 7 days per week, few calories, enough water and music (remember to get signed informed consent; people accustomed to eating too much may resent healthy lifestyles and prefer taxpayer’s subsidies; those who profit from expensive health care may complain to journals and others). My approach is cost/effective; lowers costs, improves desirable outcomes. If you disagree, I challenge to prove otherwise in a well-designed clinical trial; for better compliance use a dungeon with internet access (“Where There's a Whip, There's a Way”, http://tolkiengateway.net/wiki/Where_There%27s_a_Whip,_There%27s_a_Way).
I disagree with the presentation on evaluation questions and proposed treatments.
Diagnostic tests. “Full lipid profile (total cholesterol, low density lipoprotein, high density lipoprotein, and triglyceride) is necessary for the diagnosis of hypercholesterolaemia.” TC/HDL > 6 is VERY high. According to my research, the ratio of PUFA/NoPUFA is one of the most important determinants in TC/HDL. Increasing the ratio by eating more PUFA lowers TC/HDL (one of the most important risk factors for CVD). Measuring a fatty acid profile is needed to calculate PUFA/NoPUFA; because most people have low body levels of PUFA, eating meals high in PUFAs and low in calories works well.
Diet. “The person’s diet (is it high in fat and/or sugar?)”
To me, inadequate questions. According to my research diets high or low in fat or sugar may be healthy or harmful, depending on the chemical composition of the diet. The concept of asking about total fat is long gone. I explained the biochemical reasons for good and bad fats. The better questions are: what is total calorie intake? What is total calorie use (e.g., exercise, etc.). Is the intake of calories + or - ? How many calories come of PUFAs of the w3 and w6 family v. calories from all other sources (notice that I do not distinguish calories from protein, sugar, carbs, vegetables, fat because, biochemically, all excessive or leftover calories are stored as saturated fatty acids; this is a very rough approximation, read my books, publications and websites for details which are complex). In my experience, patients report eating salads, apples, carrots, celery, lettuce. I think they convert air to carbon molecules (have genes with the missing link to plants).
In my analysis, CVD risk calculators are inaccurate, misleading and rarely useful. Several years ago, I reviewed some of the Framingham Heart Disease data and its risk calculators. I found that the predictive value based on R squares was small. I analyzed hundreds of samples from Framingham subjects, and wrote that the fatty acid profile is likely a better predictor of CVD risk. I ask authors to publish the raw data used to calculate CVD risk, the specific mathematical equations used (often difficult to figure out among complex statistical analysis) and the R square of the mathematical predictor models (instead of other measures difficult to compare). If the patient is overweight and eats poorly, he is at high risk. I can look at a patient and decide in a few minutes.
Using statins. “Statins are first line management based on global cardiovascular disease risk assessment.”
I disagree; statins are not appropriate for most people. There is probably a small group, perhaps 5% of the population (a higher percent of those with CVD) who may benefit from statins. Specialized genetic and biochemical tests are required to identify them (these are issues that I am researching now, and did not find adequate answers in published research). Other researchers also disagree with the use of statins for most people.
I challenge researchers and readers to list 3 to 5 of the best articles that support the hypothesis that lowering high cholesterol or triglycerides with enzyme inhibitors such as statins prevent or treat cardiovascular (CVD) or heart disease. Exclude about 5% of individuals with genetic disorders that cause severe high levels of lipids. Provide articles in these categories: theories of CVD with clear description of the theory, hypothesis, predictions); experimental data (e.g., clinical trials); empirical data (e.g., epidemiology); all in humans. A theory should describe its hypothesis and math relationships; provide specific quantitative predictions. For data, provide access to the data used as evidence, the detailed procedures used to select subjects and measure data, the payments received by participants (entities involved in research, physicians, etc.); the auditing procedures to prevent errors in data (e.g., random selection for review of 10% of subjects and data points), how many subjects stayed or dropped out, procedures to evaluate biases in allocation of subjects to treatment or control, and evidence to overcome criticisms of studies reported in many publications. I will review and explain why I think the experiments with statins provide misleading data that cannot be applied to most patients. I did not find persuasive the articles I read.
I wrote that the best treatment for most patients is substantial weight loss and eating more essential fats (PUFAs of w3, w6 families). Ex: a 5’7” man should weigh about 135-145 lbs, probably less with CVD. My ideal weight is usually below the numbers considered adequate by most patients (based on my US experience). The reasons are explained in my publications and forthcoming books. Many very healthy physicians I meet at conferences are very slim. Some eat meals once or twice per day, do periodic fasting (reported in journals, but not in the government guidelines for CVD risk prevention).
If a person is walking towards an incoming locomotive, the best treatment is to grab the person and move it out of the way (except for Superman and others like him). Drugs for depression or federal subsidies are unlikely to help. Overweight and deficiencies of essential fats are by far the most substantial problem for most patients (according to my research). Focus should be first on them. I disagree that taxpayers should pay for expensive treatment for the consequences of overweight (such as type 2 diabetes or high lipids) when inexpensive substantial weight loss gets better outcomes.
According to my research, medical decisions that hypothesize that high cholesterol is associated with CVD and statins are a good treatment, are based on clinical trials and empirical evidence, not biophysical models. I have not seen a theoretical model that explains why cholesterol goes up, how far up it can go and why. What determines when the body has reached a desirable TC or Trig level? Why some people have TC of 200 and others 350, or Trig of 150 or 450. If you say it is genes, of course it is. But why? Could the same genes produce different levels and why? There is a physical chemistry theory behind these numbers. What is it? Readers who disagree with me, I challenge you to publish one biophysical model that identifies the factors that cause TC to increase and contribute to CVD, with specific mathematical relationships explaining the relative contribution of each factor (not just words or qualitative analysis). Not based on empirical data but based on physical-chemistry principles.
“A core principle of good public health practice is to base all policy decisions on the highest-quality scientific data, openly and objectively derived.” “improve the use of multiple data sources for health decision making.” Frieden TR. Evidence for health decision making—beyond randomized, controlled trials[Review]. N Engl J Med 2017;377:465-75. doi:10.1056/NEJMra1614394 pmid:28767357
Seems to make sense? I disagree. Data are meaningless without a good theory or math model to interpret it. The fallacy that data are King, supreme decider, is embodied in the fallacy that randomized, controlled trials (RCTs) are the golden rule or best evidence to identify the best treatments (e.g., compare treatments). Without a good model, researchers are like blind men touching different parts of an elephant (and not knowing it). Every experiment is a tiny surface in the multidimensional space of variables and chemicals in the body. Without knowing where we are, we don’t know if the study is in the part of the space where statins or other drugs help or hurt. Thus, I submit RCT should not be used for medical decisions unless they are used to test or support a biophysical model of the disease.
“Thought” experiments and theories that identify relevant variables and make good predictions are essential (sine qua non) to interpret data and best methods to identify optimal treatments.
References
Siguel, E. A New Relationship between Total/HDL Cholesterol and Polyunsaturated Fatty Acids. Lipids, 1996; 31, S51-S56.
Siguel E, Lerman RH. The Effects of Low-Fat Diet on Lipid Levels. JAMA, 1996; 275:759.
Siguel E, Lerman RH, MacBeath, B. Very Low-Fat Diets for Coronary Heart Disease: Perhaps, But Which One? JAMA, 1996:275: 1402-1403
Siguel, E. Dietary Fat: How Low Can or Should You Go? Abstracts, Am. Oil. Chemistry Society Annual Meeting 1997; INFORM, 1997:8, No7:714-717.
Siguel, E. Deficiencies and Abnormalities of Essential Fats in Gastrointestinal and Coronary Artery Disease. Journal of Clinical Ligand Assay 2000; 23:104–11.
Siguel EN, Lerman, RH. Altered Fatty Acid Metabolism in Patients With Angiographically Documented Coronary Artery Disease. Metabolism 1994; 43:982-993.
Siguel EN. Essential and Trans Fatty Acid Metabolism in Health and Disease. Nutrition Issue. Comprehensive Therapy, 1994; 20(9):500-510. Review
Siguel EN. Essential Fatty Acids in Health and Disease. 1994. (book, Amazon.com).