Abstract
Keywords
Introduction
- 1.An elevated level of cholesterol carried by circulating apolipoprotein (apo) B-containing lipoproteins (non-high-density lipoprotein cholesterol [non-HDL-C] and low-density lipoprotein cholesterol [LDL-C], termed atherogenic cholesterol) is a root cause of atherosclerosis, the key underlying process contributing to most clinical atherosclerotic cardiovascular disease (ASCVD) events;
- 2.Reducing elevated levels of atherogenic cholesterol will lower ASCVD risk in proportion to the extent that atherogenic cholesterol is reduced;
- 3.The intensity of risk-reduction therapy should generally be adjusted to the patient's absolute risk for an ASCVD event;
- 4.Atherosclerosis is a process that often begins early in life and progresses for decades before resulting in a clinical ASCVD event. Therefore, both intermediate-term and long-term/lifetime risk should be considered when assessing the potential benefits and hazards of risk-reduction therapies;
- 5.For patients in whom lipid-lowering drug therapy is indicated, statin treatment is the primary modality for reducing ASCVD risk;
- 6.Treatment goals and periodic monitoring of atherogenic cholesterol levels (non-HDL-C and LDL-C) are important tools in the implementation of a successful treatment strategy. These aid the clinician in assessing the adequacy of treatment and facilitate active participation by the patient through feedback and reinforcement of the beneficial effects of lifestyle and pharmaceutical therapies; and
- 7.Non-lipid ASCVD risk factors should also be managed appropriately, particularly high blood pressure, cigarette smoking, and diabetes mellitus.
Risk category | Criteria | Treatment goal | Consider drug therapy |
---|---|---|---|
Non–HDL-C, mg/dL LDL-C, mg/dL | Non–HDL-C, mg/dL LDL-C, mg/dL | ||
Low | • 0–1 major ASCVD risk factors | <130 | ≥190 |
• Consider other risk indicators, if known | <100 | ≥160 | |
Moderate | • 2 major ASCVD risk factors | <130 | ≥160 |
• Consider quantitative risk scoring | <100 | ≥130 | |
• Consider other risk indicators | |||
High | • ≥3 major ASCVD risk factors | <130 | ≥130 |
• Diabetes mellitus (type 1 or 2) | <100 | ≥100 | |
○ 0–1 other major ASCVD risk factors and | |||
○ No evidence of end-organ damage | |||
• Chronic kidney disease stage 3B or 4 ‡ For patients with chronic kidney disease (CKD) stage 3B (estimated glomerular filtration rate [eGFR], 30–44 mL/min/1.73 m2) or stage 4 (eGFR, 15–29 mL/min/1.73 m2) risk calculators should not be used because they may underestimate risk. Stage 5 CKD (or on hemodialysis) is a very high-risk condition, but results from randomized, controlled trials of lipid-altering therapies have not provided convincing evidence of reduced ASCVD events in such patients. Therefore, no treatment goals for lipid therapy have been defined for stage 5 CKD. | |||
• LDL-C of ≥190 mg/dL (severe hypercholesterolemia) § If LDL-C is ≥190 mg/dL, consider severe hypercholesterolemia phenotype, which includes familial hypercholesterolemia. Lifestyle intervention and pharmacotherapy are recommended for adults with the severe hypercholesterolemia phenotype. If it is not possible to attain desirable levels of atherogenic cholesterol, a reduction of at least 50% is recommended. For familial hypercholesterolemia patients with multiple or poorly controlled other major ASCVD risk factors, clinicians may consider attaining even lower levels of atherogenic cholesterol. Risk calculators should not be used in such patients. | |||
• Quantitative risk score reaching the high-risk threshold High-risk threshold is defined as ≥10% using Adult Treatment Panel III Framingham Risk Score for hard coronary heart disease (CHD; myocardial infarction or CHD death), ≥15% using the 2013 Pooled Cohort Equations for hard ASCVD (myocardial infarction, stroke, or death from CHD or stroke), or ≥45% using the Framingham long-term cardiovascular disease (myocardial infarction, CHD death or stroke) risk calculation. Clinicians may prefer to use other risk calculators, but should be aware that quantitative risk calculators vary in the clinical outcomes predicted (eg, CHD events, ASCVD events, cardiovascular mortality); the risk factors included in their calculation; and the timeframe for their prediction (eg, 5 years, 10 years, or long-term or lifetime). Such calculators may omit certain risk indicators that can be very important in individual patients, provide only an approximate risk estimate, and require clinical judgment for interpretation. | |||
Very high | • ASCVD | <100 | ≥100 |
• Diabetes mellitus (type 1 or 2) | <70 | ≥70 | |
○ ≥2 other major ASCVD risk factors or | |||
○ Evidence of end-organ damage | |||
For patients with ASCVD or diabetes mellitus, consideration should be given to use of moderate or high-intensity statin therapy, irrespective of baseline atherogenic cholesterol levels. |
NLA Part 2 recommendations
- 1.Lifestyle therapies–nutrition and exercise/physical activity;
- 2.Groups with special considerations that span the lifespan from children to seniors and from pregnancy to menopause;
- 3.Ethnic groups including Hispanics/Latinos, African Americans (AAs), South Asians (SAs), and American Indians (AIs)/Alaska Natives (ANs);
- 4.Groups with increased ASCVD risk, including patients with human immunodeficiency virus (HIV), rheumatologic disease, and those with high residual risk despite statin and lifestyle therapies; and
- 5.Strategies to improve patient outcomes centered on improving adherence and maximizing team-based collaborative care.
NLA expert panel steering committee members Terry A. Jacobson, MD, FNLA, Chair; Kevin C. Maki, PhD, CLS, FNLA; Carl Orringer, MD, FNLA; Peter Jones, MD, FNLA I. Lifestyle therapies section Nutrition Penny Kris-Etherton, PhD, RDN, CLS, FNLA, Co-Chair; Geeta Sikand, MA, RDN, CLS, FNLA, Co-Chair; Kevin C. Maki, PhD, CLS, FNLA, Co-Chair; Julie Bolick, MS, RDN, CLS, FNLA; Mary R. Dicklin, PhD; Carol Kirkpatrick, PhD, RDN, CLS, FNLA; Katherine Rhodes, PhD, RDN; Nancy T. Smith, MS, RDN, CDE, CLS Exercise Ralph La Forge, MSc, FNLA, Chair; Kevin C. Maki, PhD, FNLA II. The lifespan—children to seniors section Children and adolescents Stephen Daniels, MD, PhD, FNLA, Co-Chair; Don Wilson, MD, FNLA, Co-Chair; Piers Blackett, MD, FNLA; Sarah DeFerranti, MD; Samuel Gidding MD, FNLA; Rae-Ellen W. Kavey, MD, MPH; Brian McCrindle, MD; Catherine McNeal, MD, PhD, FNLA; Elaine Urbina, MD Women's health Pamela Morris, MD, FNLA, Chair From pregnancy to menopause Robert Wild, MD, MPH, PhD, FNLA, NCMP, Chair; Thomas Dayspring, MD, FNLA, NCMP; James A. Underberg, MS, MD, FNLA Older patients Carl Orringer, MD, FNLA, Co-Chair; Scott Grundy, MD, PhD, FNLA, Co-Chair; Joyce Ross, MSN, CRNP, FNLA III. Ethnic and racial groups section Hispanics/Latinos Martha Daviglus, MD, PhD, Chair; J Antonio G. Lopez, MD, FNLA; Amber Pirzada, MD; Carlos Jose Rodriguez, MD, MPH, FACC African Americans Keith Ferdinand, MD, FNLA, Chair South Asians Kris Vijay, MD, FNLA, Co-Chair; Prakash Deedwania, MD, Co-Chair American Indians/Alaska Natives Kevin C. Maki, PhD, FNLA, Co-Chair; Ralph La Forge, MSc, FNLA, Co-Chair IV. High-risk conditions and residual risk section HIV-infected persons Judith Aberg, MD, Chair; Carl J. Fichtenbaum, MD; Joel E. Gallant, MD; Michael A. Horberg, MD; Christopher T. Longenecker, MD; Merle Myerson, MD, FNLA; E. Turner Overton, MD Patients with rheumatoid arthritis Katherine Liao, MD, MPH, Chair; Jonathon S. Coblyn, MD; Jeffrey Curtis, MD, MS, MPH; Jorge Plutzky, MD, FNLA; Daniel Solomon, MD, MPH Patients with residual risk despite statin and lifestyle therapy Peter Jones, MD, FNLA, Co-Chair; James McKenney, PharmD, FNLA, Co-Chair V. Improving patient outcomes section Patient adherence Joyce Ross, MSN, CRNP, FNLA, Co-Chair; Lynne Braun, PhD, CNP, FNLA, Co-Chair Team-based collaborative care Lynne Braun, PhD, CNP, FNLA, Co-Chair; Matthew Ito, PharmD, FNLA, Co-Chair; Joyce Ross, MSN, CRNP, FNLA, Co-Chair VI. Additional general panel members Harold Bays, MD, FNLA; W. Virgil Brown, MD, FNLA |
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Evidence grading: strength of recommendation ∗ The system was adapted as a hybrid of the National Heart Lung and Blood Institutes (NHLBI) rating System (NHLBI cardiovascular-based methodology) used in thè new American Heart Association/American College of Cardiology cholesterol guidelines3 and adapted from the original GRADE system of evidence rating.4 | |
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Grade | Strength of recommendation |
A | Strong recommendation |
There is high certainty based on the evidence that the net benefit is substantial | |
B | Moderate recommendation |
There is moderate certainty based on the evidence that the net benefit is moderate to substantial, or there is high certainty that the net benefit is moderate | |
C | Weak recommendation |
There is at least moderate certainty based on the evidence that there is a small net benefit | |
D | Recommend against |
There is at least moderate certainty based on the evidence that it has no net benefit or that the risks/harms outweigh benefits | |
E | Expert opinion |
There is insufficient evidence or evidence is unclear or conflicting, but this is what the expert panel recommends | |
N | No recommendation for or against |
There is insufficient evidence or evidence is unclear or conflicting | |
Evidence grading: quality of evidence | |
Type of evidence | Quality rating ‡ The evidence quality rating system used in this guideline was developed by the National Heart Lung, and Blood Institute’s (NHLBI’s) Evidence-Based Methodology Lead (with input from NHLBI staff, external methodology team, and guideline panels and work groups) for use by all the NHLBI cardiovascular disease guideline panels and work groups during this project. As a result, it includes the evidence quality rating for many types of studies, including studies that were not used in this guideline. |
Well-designed, well-executed RCTs that adequately represent populations to which the results are applied and directly assess effects on health outcomes Well-conducted meta-analyses of such studies Highly certain about the estimate of effect; further research is unlikely to change our confidence in the estimate of effect | High |
RCTs with minor limitations affecting confidence in, or applicability of, the results Well-designed, well-executed nonrandomized controlled studies and well-designed, well-executed observational studies Well-conducted meta-analyses of such studies Moderately certain about the estimate of effect; further research may have an impact on our confidence in the estimate of effect and may change the estimate | Moderate |
RCTs with major limitations Nonrandomized controlled studies and observational studies with major limitations affecting confidence in, or applicability of, the results Uncontrolled clinical observations without an appropriate comparison group (eg, case series, case reports) Physiological studies in humans Meta-analyses of such studies Low certainty about the estimate of effect; further research is likely to have an impact on our confidence in the estimate of effect and is likely to change the estimate | Low |
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Lifestyle therapies
Targets of lifestyle therapies and rationale for their use
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Nutrition
Dietary patterns to reduce risk of ASCVD
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Advise adults who would benefit from LDL-C lowering to consume a dietary pattern that emphasizes intake of vegetables, fruits and whole grains; includes low-fat dairy products, poultry, fish, legumes, non-tropical vegetable oils and nuts; and limits intakes of sweets, sugar-sweetened beverages and red meats. The dietary patterns that are recommended and representative of these foods/food groups are the DASH dietary pattern, the USDA Food Pattern, or the AHA diet. These recommended dietary patterns provide 5–6% of calories from saturated fat and are low in trans fats.
Dietary Approaches to Stop Hypertension (DASH) dietary patterns
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AHA diet patterns
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Associations of dietary patterns with ASCVD risk
DASH dietary pattern and USDA food pattern
Mediterranean-style dietary pattern
Vegetarian diet
Limitations of observational evidence
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Replacements for saturated and trans fatty acids in the diet
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Dietary component | Predicted effects on lipoprotein lipids of replacing 5% of energy from saturated fatty acids with 5% of energy from the specified dietary component, mg/dL | ||
---|---|---|---|
LDL-C | TG | HDL-C | |
PUFA | –9.0 | –2.0 | –1.0 |
MUFA | –6.5 | +1.0 | –6.0 |
Carbohydrate | –6.0 | +9.5 | –2.0 |
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Selected results from randomized controlled feeding trials
Lipid | Diet (% energy from carbohydrate/protein/fat) | |||
---|---|---|---|---|
Habitual baseline diet (various) | Carbohydrate diet (58/15/27) | Protein diet (48/25/27) | Unsaturated fat diet (48/15/37) | |
Mean, mg/dL | Mean or median change from baseline, mg/dL | |||
LDL-C | 129 | −11.6a | −14.2b | −13.1a,b |
Non-HDL-C | 154 | −11.0a | −17.3b | −15.1b |
HDL-C | 50 | −1.4a | −2.6b | −0.3c |
TG | 102 | 0.1a | −16.4b | −9.3c |
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Dietary cholesterol
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Weight loss
Effects of weight loss on lipoprotein lipids
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…evidence shows that a relatively high protein intake sustains weight maintenance by (a) favoring regain of fat free mass at the cost of fat at a similar physical activity level, (b) reducing the energy efficiency with respect to the body mass regained, and (c) increasing satiety.
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