Accurate Cardiovascular Risk Stratification Research Articles

Predictors and markers of the cardiovascular impact of obstructive sleep apnoea.

Obstructive sleep apnoea (OSA) is the most common form of sleep-disordered breathing and has been linked to cardiovascular health. However, some of the findings supporting this are controversial. These discrepancies might be a result of heterogeneity among OSA patients, and thus, additional information would be required to better stratify OSA patients according to cardiovascular risk. In this review, we aim to discuss the potential of biomarkers to fulfil this role. Randomized controlled trials have been unable to confirm whether OSA treatment with continuous positive airway pressure (CPAP) has a positive effect on cardiovascular outcomes. Emerging physiology-based metrics of OSA seem to be more suitable for identifying patients at higher risk of cardiovascular disease and predicting the effects of CPAP outcomes on cardiovascular health. Similarly, blood-based molecular markers have gained attention in this context over the last few years. Accurate cardiovascular risk stratification and appropriate treatment allocation for OSA patients remain challenging. However, significant efforts are being made to develop novel tools to address these important issues.

Abstract 17498: Association Between 5-Year Change in Cardiovascular Risk and Atherosclerotic Cardiovascular Disease Incidence: A Multicohort Study

Introduction: Early measurement of atherosclerotic cardiovascular disease (ASCVD) risk factors contains valuable information about an individual's risk history. Hypothesis: Individuals with different historical cardiovascular risk statuses have varied risks of future ASCVD incidence. Methods: We analyzed pooled data from 7 community-based prospective cohort studies with up to 20-year follow-ups ( panel A ). White or Black participants aged 40-75 years without prevalent ASCVD were included. Cardiovascular risk was assessed using the pooled cohort equation and was categorized into non-high (<20%) or high risk (≥20%). Changes in CVD risk over a 5-year interval were considered. The main outcome is incident ASCVD. Results: Among 11026 participants (mean [SD] age,60.0 [8.1] years). 4272 (38.7%) were female and 3127 (28.4%) were Black. During a median follow-up of 9.9 years, 2560 (23.2%) ASCVD events occurred. Compared to individuals with consistently high risk, participants with non-high to high risk (HR 0.67; 95%CI 0.59-0.77), high to non-high risk (HR 0.57; 95%CI 0.41-0.80), and consistently non-high risk (HR 0.33; 95%CI 0.29-0.37) had a lower risk of incident ASCVD. Compared to individuals with consistently non-high risk, participants with high to non-high risk (HR 1.74; 95%CI 1.26-2.41), non-high to high risk (HR 2.04; 95%CI 1.84-2.27), and consistently high risk (HR 3.03; 95%CI 2.69-3.42) had an increased risk of incident ASCVD ( panel B ). Conclusions: Changes in the CVD risk status over time inform dissimilar ASCVD risk than a single risk assessment. Dynamic risk evaluation might enable more accurate cardiovascular risk stratification and decision on preventive interventions should take historical risk status into account.

Association between 5-year change in cardiovascular risk and the incidence of atherosclerotic cardiovascular diseases: a multi-cohort study

BackgroundThe influence of the historical cardiovascular risk status on future risk of atherosclerotic cardiovascular disease (ASCVD) is poorly understood. We aimed to investigate the association between 5-year changes in cardiovascular risk and ASCVD incidence.MethodsWe analyzed pooled data from seven community-based prospective cohort studies with up to 20 years of follow-up data. The study populations included White or Black participants aged 40–75 years without prevalent ASCVD. Cardiovascular risk was assessed using the pooled cohort equation and was categorized into non-high (< 20%) or high risk (≥ 20%). Changes in cardiovascular disease (CVD) risk over a 5-year interval were recorded. The main outcome was incident ASCVD.ResultsAmong 11,026 participants (mean [SD] age, 60.0 [8.1] years), 4272 (38.7%) were female and 3127 (28.4%) were Black. During a median follow-up period of 9.9 years, 2560 (23.2%) ASCVD events occurred. In comparison with individuals showing a consistently high CVD risk, participants whose CVD risk changed from non-high to high (hazard ratio [HR], 0.67; 95% confidence interval [CI] 0.59–0.77) or high to non-high (HR, 0.57; 95% CI 0.41–0.80) and those with a consistently non-high risk (HR, 0.33; 95% CI 0.29–0.37) had a lower risk of incident ASCVD. In comparison with individuals showing a consistently non-high CVD risk, participants whose CVD risk changed from high to non-high (HR, 1.74; 95% CI 1.26–2.41) or from non-high to high risk (HR, 2.04; 95% CI 1.84–2.27) and those with a consistently high risk (HR 3.03; 95% CI 2.69–3.42) also showed an increased risk of incident ASCVD.ConclusionsIndividuals with the same current CVD risk status but different historical CVD risks exhibited varying risks of future ASCVD incidents. Dynamic risk evaluation may enable more accurate cardiovascular risk stratification, and decision-making regarding preventive interventions should take the historical risk status into account.Graphical

Predicting the subclinical carotid atherosclerosis in overweight and obese patients using a machine learning model

Aim. To develop a model for predicting the subclinical carotid atherosclerosis (SCA) in order to refine cardiovascular risk (CVR) using machine learning methods in overweight and obese patients without hypertension, diabetes and/or cardiovascular disease (CVD).Material and methods. Anonymized database (DB) Webiomed (2.9 million patients) was used. There were following inclusion criteria: age ≥18 years, body mass index ≥25 kg/m2, availability of data on ultrasound of extracranial arteries. Patients with hypertension, diabetes and/or CVD were excluded from the analysis. Data on 5750 patients were selected, of which atherosclerotic plaques were detected in 385 people. The final data set contained information on 447 patients, 197 (44,1%) of which had SCA. Quantitative and categorical traits for model training were taken with 40% occupancy in the database. The number of final traits for machine learning was 28. When creating the model, 3 Random Forest algorithms, AdaBoostClassifier, KNeighborsClassifier and the Scikit-learn library were used. To improve the model performance, the fill missing function was used. The target parameters of the model were given a predictive ability (accuracy) of at least 75%, while the area under the ROC curve was at least 0,75.Results. The resulting dataset was divided into training and test parts in a ratio of 80:20. Depending on the applied algorithms, the learned model was characterized by a predictive ability of 75-97%, sensitivity of 77-92%, specificity of 80-98%, and area under the ROC-curve of 0,88-0,97. Taking into account the accuracy metrics, the best results were obtained for the model learned by the Random Forest algorithm (95%, 92%, 98% and 0,95, respectively).Conclusion. The developed model can help a physician make a decision to refer an overweight and obese patient without cardiovascular diseases for ultrasound of extracranial arteries, which contributes to a more accurate CVR stratification. The introduction of such risk stratification algorithms into practice will increase the accuracy and quality of CVR prediction and optimize the system of preventive measures.

Predicting the subclinical carotid atherosclerosis in overweight and obese patients using a machine learning model

Aim. To develop a model for predicting the subclinical carotid atherosclerosis (SCA) in order to refine cardiovascular risk (CVR) using machine learning methods in overweight and obese patients without hypertension, diabetes and/or cardiovascular disease (CVD).Material and methods. Anonymized database (DB) Webiomed (2.9 million patients) was used. There were following inclusion criteria: age ≥18 years, body mass index ≥25 kg/m2, availability of data on ultrasound of extracranial arteries. Patients with hypertension, diabetes and/or CVD were excluded from the analysis. Data on 5750 patients were selected, of which atherosclerotic plaques were detected in 385 people. The final data set contained information on 447 patients, 197 (44,1%) of which had SCA. Quantitative and categorical traits for model training were taken with 40% occupancy in the database. The number of final traits for machine learning was 28. When creating the model, 3 Random Forest algorithms, AdaBoostClassifier, KNeighborsClassifier and the Scikit-learn library were used. To improve the model performance, the fill missing function was used. The target parameters of the model were given a predictive ability (accuracy) of at least 75%, while the area under the ROC curve was at least 0,75.Results. The resulting dataset was divided into training and test parts in a ratio of 80:20. Depending on the applied algorithms, the learned model was characterized by a predictive ability of 75-97%, sensitivity of 77-92%, specificity of 80-98%, and area under the ROC-curve of 0,88-0,97. Taking into account the accuracy metrics, the best results were obtained for the model learned by the Random Forest algorithm (95%, 92%, 98% and 0,95, respectively).Conclusion. The developed model can help a physician make a decision to refer an overweight and obese patient without cardiovascular diseases for ultrasound of extracranial arteries, which contributes to a more accurate CVR stratification. The introduction of such risk stratification algorithms into practice will increase the accuracy and quality of CVR prediction and optimize the system of preventive measures.

Association between change in cardiovascular risk scores and future cardiovascular disease: analyses of data from the Whitehall II longitudinal, prospective cohort study

SummaryBackgroundEvaluation of cardiovascular disease risk in primary care, which is recommended every 5 years in middle-aged and older adults (typical age range 40–75 years), is based on risk scores, such as the European Society of Cardiology Systematic Coronary Risk Evaluation (SCORE) and American College of Cardiology/American Heart Association Atherosclerotic Cardiovascular Disease (ASCVD) algorithms. This evaluation currently uses only the most recent risk factor assessment. We aimed to examine whether 5-year changes in SCORE and ASCVD risk scores are associated with future cardiovascular disease risk.MethodsWe analysed data from the Whitehall II longitudinal, prospective cohort study for individuals with no history of stroke, myocardial infarction, coronary artery bypass graft, percutaneous coronary intervention, definite angina, heart failure, or peripheral artery disease. Participants underwent clinical examinations in 5-year intervals between Aug 7, 1991, and Dec 6, 2016, and were followed up for incident cardiovascular disease until Oct 2, 2019. Levels of, and 5-year changes in, cardiovascular disease risk were assessed using the SCORE and ASCVD risk scores and were analysed as predictors of cardiovascular disease. Harrell’s C index, continuous net reclassification improvement, the Akaike information criterion, and calibration analysis were used to assess whether incorporating change in risk scores into a model including only a single risk score assessment improved the predictive performance. We assessed the levels of, and 5-year changes in, SCORE and ASCVD risk scores as predictors of cardiovascular disease and disease-free life-years using Cox proportional hazards and flexible parametric survival models.Findings7574 participants (5233 [69·1%] men, 2341 [30·9%] women) aged 40–75 years were included in analyses of risk score change between April 24, 1997, and Oct 2, 2019. During a mean follow-up of 18·7 years (SD 5·5), 1441 (19·0%; 1042 [72·3%] men and 399 [27·7%] women) participants developed cardiovascular disease. Adding 5-year change in risk score to a model that included only a single risk score assessment improved model performance according to Harrell’s C index (from 0·685 to 0·690, change 0·004 [95% CI 0·000 to 0·008] for SCORE; from 0·699 to 0·700, change 0·001 [0·000 to 0·003] for ASCVD), the Akaike information criterion (from 17 255 to 17 200, change −57 [95% CI −97 to −13] for SCORE; from 14 739 to 14 729, change −10 [−28 to 7] for ASCVD), and the continuous net reclassification index (0·353 [95% CI 0·234 to 0·447] for SCORE; 0·232 [0·030 to 0·344] for ASCVD). Both favourable and unfavourable changes in SCORE and ASCVD were associated with cardiovascular disease risk and disease-free life-years. The associations were seen in both sexes and all age groups up to the age of 75 years. At the age of 45 years, each 2-unit improvement in risk scores was associated with an additional 1·3 life-years (95% CI 0·4 to 2·2) free of cardiovascular disease for SCORE and an additional 0·9 life-years (95% CI 0·5 to 1·3) for ASCVD. At age 65 years, this same improvement was associated with an additional 0·4 life-years (95% CI 0·0 to 0·7) free of cardiovascular disease for SCORE and 0·3 life-years (95% CI 0·1 to 0·5) for ASCVD. These models were developed into an interactive calculator, which enables estimation of the number of cardiovascular disease-free life-years for an individual as a function of two risk score measurements.InterpretationChanges in the SCORE and ASCVD risk scores over time inform cardiovascular disease risk prediction beyond a single risk score assessment. Repeat data might allow more accurate cardiovascular risk stratification and strengthen the evidence base for decisions on preventive interventions.FundingUK Medical Research Council, British Heart Foundation, Wellcome Trust, and US National Institute on Aging.

Peripheral Artery Disease and Stroke.

Peripheral artery disease (PAD) and stroke can occur as vascular complication of anticancer treatment. Although the mechanisms, monitoring, and management of cardiotoxicities have received broad attention, vascular toxicities remain often underrecognized. In addition, the development of new chemotherapeutic drugs bears the risk of vasotoxicities that are yet to be identified and may not be realized with short-term follow-up periods. The propensity to develop PAD and/or stroke reflects the complex interplay between patient's baseline risk and preexisting vascular disease, particularly hypertension and diabetes, while evidence for genetic predisposition is increasing. Chemotherapeutic agents with a prominent vascular side effect profile have been identified. Interruption of vascular endothelial growth factor (VEGF) inhibitors (VEGFIs) signaling (i.e., bevacizumab) is associated with vascular toxicity and clinical sequelae such as hypertension, stroke, and thromboembolism beyond acute coronary syndromes. Cisplatin and 5-fluorouracil are the main drugs involved in the stroke risk. In addition, circulating concentrations of VEGF are reduced by cyclophosphamide administered at continuous low doses, which might underpin some of the observed vascular toxicity, such as stroke, as seen in patients treated with VEGF inhibitors. The risk of stroke is also increased after treatment with anthracyclines that can induce endothelial dysfunction and increase arterial stiffness. Proteasome inhibitors ( bortezomib and carfilzomib) and immunomodulatory agents (thalidomide, lenalidomide, and pomalidomide), approved for use in multiple myeloma, carry a black box warning for an increased risk of stroke. Finally, head-and-neck radiotherapy is associated with a doubled risk of cerebrovascular ischemic event, especially if exposure occurs in childhood. The mechanisms involved in radiation vasculopathy are represented by endothelial dysfunction, medial necrosis, fibrosis, and accelerated atherosclerosis. However, BCR-ABL tyrosine kinase inhibitor (TKI), used for the treatment of chronic myeloid leukemia (CML), is the main antineoplastic drugs involved in the development of PAD. In particular, second- and third-generation TKIs, such as nilotinib and ponatinib, while emerging as a potent arm in contrasting CML, are associated with a higher risk of PAD development rather than traditional imatinib. Factors favoring vascular complication are the presence of traditional cardiovascular risk factors (CVRF) and predisposing genetic factors, high doses of BCR-ABL TKIs, longer time of drug exposure, and sequential use of potent TKIs. Therefore, accurate cardiovascular risk stratification is strongly recommended in patient candidate to anticancer treatment associated with higher risk of vascular complication, in order to reduce the incidence of PAD and stroke through CVRF correction and selection of appropriate tailored patient strategy of treatment. Then, a clinical follow-up, eventually associated with instrumental evaluation through vascular ultrasound, should be performed.

Imaging unstable plaque.

Recent advances in imaging technology have enabled us to utilise a range of diagnostic approaches to better characterise high-risk atherosclerotic plaque. The aim of this article is to review current and emerging techniques used to detect and quantify unstable plaque in the context of large and small arterial systems and will focus on both invasive and non-invasive imaging techniques. While the diagnosis of clinically relevant atherosclerosis still relies heavily on anatomical assessment of arterial luminal stenosis, evolving multimodal cross-sectional imaging techniques that encompass novel molecular probes can provide added information with regard to plaque composition and overall disease burden. Novel molecular probes currently being developed to track precursors of plaque rupture such as inflammation, micro-calcification, hypoxia and neoangiogenesis are likely to have translational applications beyond diagnostics and have the potential to play a part in quantifying early responses to therapeutic interventions and more accurate cardiovascular risk stratification.

How arterial stiffness may affect coronary blood flow: a challenging pathophysiological link.

A relationship between arterial stiffening and coronary flow abnormalities, although not fully elucidated, has been observed. The purpose of this study was to investigate the relationship among carotid stiffness, measured using echo-tracking, and Doppler parameters of coronary blood flow, sampled at the left anterior descending (LAD) artery. We studied 88 consecutive patients (49 men, mean age 51.2 ± 16.2 years) with cardiovascular risk factors but without history of cardiovascular diseases. Each patient underwent echocardiographic evaluation for measurement of the diastolic velocity time integral (DVTI) and calculation of the diastolic velocity time integral coronary index (DVTICI), the ratio between DVTI and total velocity time integral of LAD artery flow × 100, and carotid ultrasound for measurement of carotid intima media thickness (IMT) and stiffness parameters such as β index and elastic modulus (Ep). DVTICI was significantly greater in men than in women (median 82, interquartile range 78-86 vs. median 80, interquartile range 73-83, respectively; P < 0.016). After correlating DVTICI with other variables, a significant inverse relation was obtained with β index (Rho = -0.449, P < 0.001), Ep (Rho = -0.478, P < 0.001), age (Rho = -0.52, P < 0.001), left ventricular mass index (Rho = -0.543, P < 0.001), E/E' (Rho = -0.411, P < 0.001), pulse pressure (Rho = -0.417, P < 0.001) and IMT (Rho = -0.480, P < 0.001). With linear multiple regression analysis, only β index (P < 0.001), Ep (P < 0.001), male sex (P < 0.001) and left ventricular mass index (P = 0.008) were independently associated with reduction of DVTICI. Increased arterial stiffness, directly affecting coronary perfusion, is associated with reduced diastolic coronary flow. Echo-tracking for feasible measurement of carotid artery stiffness parameters may be valuable in more accurate cardiovascular risk stratification.

Aortic Stiffness and Central Wave Reflections Predict Outcome in Renal Transplant Recipients

Although renal transplantation improves survival, cardiovascular morbidity and mortality remain significantly elevated compared with nonrenal populations. The negative impact of traditional, uremia-related, and transplantation-related risk factors in this process remains, however, largely unexplored. Surrogate markers such as aortic stiffness and central wave reflections may lead to more accurate cardiovascular risk stratification, but outcome data in renal transplant recipients are scarce. We aimed to establish the prognostic significance of these markers for fatal and nonfatal cardiovascular events in renal transplant recipients. Carotid-femoral pulse wave velocity, central augmentation pressure, and central augmentation index were measured in a cohort of 512 renal transplant recipients using the SphygmoCor system. After a mean follow-up of 5 years, 20 fatal and 75 nonfatal cardiovascular events were recorded. Using receiver operating characteristic curves, the area under the curve for predicting cardiovascular events was 0.718 (95% CI 0.659-0.776) for pulse wave velocity, 0.670 (95% CI 0.604-0.736) for central augmentation pressure, and 0.595 (95% CI 0.529-0.660) for central augmentation index. When we accounted for age, gender, and C-reactive protein in Cox-regression analysis, pulse wave velocity (hazard ratio: 1.349 per 1 SD increase; 95% CI 1.104-1.649; P=0.003) and central augmentation pressure (hazard ratio: 1.487 per 1 SD increase; 95% CI 1.219-1.814; P<0.001) remained independent predictors of outcome. Aortic stiffness and increased wave reflections are independent predictors of cardiovascular events in renal transplant recipients. As single parameter of wave reflection, central augmentation pressure was better than central augmentation index. Combined measurement of pulse wave velocity and central augmentation pressure may contribute to an accurate cardiovascular risk estimation in this heterogeneous population.

Dynamic Cardiovascular Risk Assessment in Elderly People

Abstract. Objectives. This study sought to determine whether serial measurement of N-terminal pro-B-type natriuretic peptide (NT-proBNP) in com-munity-dwelling elderly people would provide additional prognostic information to that from traditional risk factors. Background. Accurate cardiovascular risk stratification is challenging in elderly people. Methods. NT-proBNP was measured at baseline and 2 to 3 years later in 2975 community-dwelling older adults free of heart failure in the longitudinal Cardiovascular Health Study (CHS). This investigation examined the risk of new-onset heart failure (HF) and death from cardiovascular causes associated with baseline NT-proBNP and changes in NT-proBNP levels, adjusting for potential confounders. Results. NT-proBNP levels in the highest quintile (>267.7 pg/mL) were independently associated with greater risks of HF (hazard ratio [HR], 3.05; 95% confidence interval [CI], 2.46–3.78) and cardiovascular death (HR, 3.02; 95% CI, 2.36–3.86) compared with the lowest quintile (<47.5 pg/mL). The inflection point for elevated risk occurred at NT-proBNP 190 pg/mL. Among participants with initially low NT-proBNP (<190 pg/mL), those with a >25% increase on follow-up to >190 pg/mL (21%) were at greater adjusted risk for HF (HR, 2.13; 95% CI, 1.68–2.71) and cardiovascular death (HR, 1.91; 95% CI, 1.43–2.53) compared with those with sustained low levels. Among participants with initially high NT-proBNP, those with a >25% increase (40%) were at higher risk for HF (HR, 2.06; 95% CI, 1.56–2.72) and cardiovascular death (HR, 1.88; 95% CI, 1.37–2.57), whereas those with a >25% decrease to ≤190 pg/mL (15%) were at lower risk for HF (HR, 0.58; 95% CI, 0.36–0.93) and cardiovascular death (HR, 0.57; 95% CI, 0.32–1.01) compared with those with unchanged high values. Conclusions. NT-proBNP levels independently predict HF and cardiovascular death in older adults. NT-proBNP levels frequently change over time, and these fluctuations reflect dynamic changes in cardiovascular risk. deFilippi CR, Christenson RH, Gottdiener JS, et al. Dynamic cardiovascular risk assessment in elderly people. The role of repeated N-terminal pro-B-type natriuretic testing. J Am Coll Cardiol. 2010; 55: 441-450.

Usefulness of Optic Fundus Examination With Retinography in Initial Evaluation of Hypertensive Patients

Although international guidelines for management of hypertension recommend optic fundus examination in the initial evaluation of hypertensive patients, there have been no studies to evaluate the usefulness of retinography in this application. Two hundred and fifty consecutive new patients with hypertension but without known cardiovascular disease were studied. The average age was 57.2 years (s.d. 12.9) and 56% were men. The study was conducted in 14 primary care centers. Measurements included target organ damage (TOD) evaluation (electrocardiography, retinography, microalbuminuria, and serum creatinine) and blood pressure (BP) measurements. Outcome measurements were made to risk stratification according to 2003 World Health Organization and International Society of Hypertension (WHO-ISH) and 2007 European Society of Hypertension and European Society of Cardiology (ESH-ESC) guidelines, analyzed first without incorporating the retinography results and then reclassified using the retinography data. Advanced retinopathy was detected in 10.8%. The risk stratification arrived at as per the WHO-ISH guidelines, and without the retinography data was: 11.4% low risk, 62.4% moderate risk, and 26.2% high risk. When retinography results were taken into account, 8% from the moderate-risk group were reclassified to the high-risk group (11.4, 54.4, and 34.2%, respectively; P < 0.001). Using ESH-ESC guidelines, the risk stratification without the retinography data was 0.9% reference, 11.3% low, 58.8% moderate, 21.7% high, and 7.3% very high risk. With retinography, 10% were reclassified from a lower to a higher risk group (0.9, 10.4, 51.1, 20.4, and 17.2%, respectively; P < 0.001). As an alternative to optic fundus examination, retinography enables a more accurate cardiovascular risk stratification in the first evaluation after diagnosis of hypertension. When retinography is included in the assessment of cardiovascular risk, approximately 10% of patients are reclassified to a higher risk group.

Cardiac Imaging for Risk Stratification in Diabetes

Worldwide, 200 million individuals currently have diabetes, and projections by the World Health Organization and others suggest that its prevalence will exceed 300 million by 2025 and 360 million by 2030 (1,2). More than 90% of these individuals will have type 2 diabetes. Management guidelines in Europe (3) and the U.S. (4) consider type 2 diabetes to be a cardiovascular disease equivalent. These patients have a two- to fourfold higher risk of a cardiovascular event than nondiabetic patients. Importantly, cardiovascular death is the most common cause of mortality in the type 2 diabetic population (5). It has been estimated that after a myocardial infarction, 79% of diabetic patients die of cardiac complications (6). Accordingly, accurate cardiovascular risk stratification of patients with type 2 diabetes is needed. This can be problematic in that the clinical presentation and progression of coronary artery disease (CAD) differs between diabetic and nondiabetic patients. In addition to a higher prevalence of CAD (7), patients with diabetes experience more diffuse, calcified, and extensive CAD, more often have left ventricular dysfunction, often have more advanced coronary disease at the time of diagnosis, and more often experience silent ischemia. In addition, diabetic patients generally have a less favorable response to revascularization (with frequent need for repeat percutaneous coronary intervention or coronary artery bypass grafting) and a reduced long-term survival. Accordingly, early accurate diagnosis of CAD in patients with diabetes is needed, and reliable prognostication is mandatory. The American Diabetes Association has recommended an algorithm whereby symptomatic diabetic patients would be referred for either stress perfusion imaging or stress echo or evaluation by a cardiologist. The exception would be individuals with atypical chest pain and a normal electrocardiogram who might undergo a simple exercise stress test unless they have multiple other cardiovascular risk factors, in which case imaging …

How to Manage Metabolic Syndrome

Metabolic syndrome (MS) is a complex clinical condition, initially described as ‘metabolic syndrome X’, characterised by the presence in the same individual of multiple metabolic and cardiovascular traits, typically high blood pressure, abdominal obesity, lipid profile abnormalities, insulin resistance and glucose intolerance. More recently, other features have been proposed; in particular, chronic pro-inflammatory and pro-thrombotic states seem to further characterise MS. Because of its multifactorial pathogenesis, a unitary clinical management of MS is still debated and physicians tend to make individual choices. In particular, the threshold for treatment initiation is rather heterogeneous. However, a large body of observational studies have demonstrated that patients with MS have an increased incidence of major cardiovascular events, such as acute myocardial infarction and ischemic stroke, particularly in those patients with a high-risk profile (hypertensive patients with target organ damage or diabetes mellitus). An aggressive therapeutic approach for reducing global cardiovascular risk is effective in these subgroups. On the other hand, the lack of specific international guidelines, consisting of a diagnostic and therapeutic algorithm with accurate cardiovascular risk stratification, makes the clinical management of patients with MS by primary physicians difficult and not uniform. In particular, while there is convincing evidence that the progressive addition of components of MS increases cardiovascular risk, there are no consistent indications regarding treatment priorities and strategies. In this article we propose a global risk-based stratification, aimed at identifying ‘low-risk’ and ‘high-risk’ patients within those presenting the MS. This approach may prove to be of particular efficacy in clinical practice to identify patients with MS with different degrees of cardiovascular disease risk profile. This approach may also be helpful to develop therapeutic strategies based on global cardiovascular risk profile.