Risk Of Heart Disease In Patients Research Articles

Application of machine learning algorithms to construct and validate a prediction model for coronary heart disease risk in patients with periodontitis: a population-based study

BackgroundThe association between periodontitis and cardiovascular disease is increasingly recognized. In this research, a prediction model utilizing machine learning (ML) was created and verified to evaluate the likelihood of coronary heart disease in individuals affected by periodontitis.MethodsWe conducted a comprehensive analysis of data obtained from the National Health and Nutrition Examination Survey (NHANES) database, encompassing the period between 2009 and 2014.This dataset comprised detailed information on a total of 3,245 individuals who had received a confirmed diagnosis of periodontitis. Subsequently, the dataset was randomly partitioned into a training set and a validation set at a ratio of 6:4. As part of this study, we conducted weighted logistic regression analyses, both univariate and multivariate, to identify risk factors that are independent predictors for coronary heart disease in individuals who have periodontitis. Five different machine learning algorithms, namely Logistic Regression (LR), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Classification and Regression Tree (CART), were utilized to develop the model on the training set. The evaluation of the prediction models’ performance was conducted on both the training set and validation set, utilizing metrics including AUC (Area under the receiver operating characteristic curve), Brier score, calibration plot, and decision curve analysis (DCA). Additionally, a graphical representation called a nomogram was created using logistic regression to visually depict the predictive model.ResultsThe factors that were found to independently contribute to the risk, as determined by both univariate and multivariate logistic regression analyses, encompassed age, race, presence of myocardial infarction, chest pain status, utilization of lipid-lowering medications, levels of serum uric acid and serum creatinine. Among the five evaluated machine learning models, the KNN model exhibited exceptional accuracy, achieving an AUC value of 0.977. The calibration plot and brier score illustrated the model's ability to accurately estimate probabilities. Furthermore, the model's clinical applicability was confirmed by DCA.ConclusionOur research showcases the effectiveness of machine learning algorithms in forecasting the likelihood of coronary heart disease in individuals with periodontitis, thereby aiding healthcare professionals in tailoring treatment plans and making well-informed clinical decisions.

Can We Mitigate Coronary Heart Disease Risk in Patients with Cancer?

The review focuses on the shared risk factors observed between coronary heart disease and cancer, cancer therapeutics causing coronary heart disease, and potential strategies to mitigate atherosclerosis in patients with cancer. The pathophysiology behind how traditional cardiovascular risk factors also contribute to cancer development and mortality is increasingly recognized. In addition, newer cancer therapies, such as immune checkpoint inhibitors, cause increased inflammation leading to increased cardiovascular events. Traditional coronary heart disease risk factors such as obesity, hypertension, diabetes, and hyperlipidemia also contribute to cancer development and worse cancer outcomes. Cancer therapeutics can also lead to atherosclerotic events in addition to the shared risk factors present at the time of cancer diagnosis. Understanding the pathophysiology, using multidisciplinary care teams, and developing machine learning algorithms for individualized patient care will help to mitigate the risk of coronary heart disease in patients with cancer.

Machine Learning Algorithms for Heart Disease Prediction

Cardiovascular disease, otherwise known as heart disease, encompasses many diseases that affect the heart. Heart disease prediction is among the most complicated tasks in medical field. In the modern age, about one person dies every minute as a result of heart disease. In addition to many factors that contribute to heart disease, it's necessary at this point in time to acquire accurate, reliable, and sensible approaches to make an early diagnosis so that the disease may be managed appropriately. Due to the complexity of finding out the heart condition, the prediction process must be automated to avoid risks related to it and to alert the patient at an early stage. In the healthcare domain, data mining is commonly used to analyze huge, complex medical data and predict heart disease. Researchers apply a variety of data mining and machine learning approaches to analyse huge complex medical data and predict heart disease. In this study, various heart disease attribute are presented, and model is developed on the basis of supervised learning algorithm as K-nearest neighbor, Decision Tree, Random Forest, Logistic Regression, SVM, Light GBM and Naïve bayes. This Paper makes use of heart condition dataset available in Kaggle repository. The purpose of this study is to anticipate heart disease risk in patients. The results show that K-nearest neighbor provides the most accurate result.

Triglycerides and low HDL cholesterol predict coronary heart disease risk in patients with stable angina

We assessed whether high triglycerides (TG) and low high-density lipoprotein cholesterol (HDL-C) levels, expressed by an increased TG/HDL-C ratio, predict coronary atherosclerotic disease (CAD) outcomes in patients with stable angina. We studied 355 patients (60 ± 9 years, 211 males) with stable angina who underwent coronary computed tomography angiography (CTA), were managed clinically and followed for 4.5 ± 0.9 years. The primary composite outcome was all-cause mortality and non-fatal myocardial infarction. At baseline, the proportion of males, patients with metabolic syndrome, diabetes and obstructive CAD increased across TG/HDL-C ratio quartiles, together with markers of insulin resistance, hepatic and adipose tissue dysfunction and myocardial damage, with no difference in total cholesterol or LDL-C. At follow-up, the global CTA risk score (HR 1.06, 95% confidence interval (CI) 1.03–1.09, P = 0.001) and the IV quartile of the TG/HDL-C ratio (HR 2.85, 95% CI 1.30–6.26, P < 0.01) were the only independent predictors of the primary outcome. The TG/HDL-C ratio and the CTA risk score progressed over time despite increased use of lipid-lowering drugs and reduction in LDL-C. In patients with stable angina, high TG and low HDL-C levels are associated with CAD related outcomes independently of LDL-C and treatments.Trial registration. EVINCI study: ClinicalTrials.gov NCT00979199, registered September 17, 2009; SMARTool study: ClinicalTrials.gov NCT04448691, registered June 26, 2020.

Increased lipoprotein(a) multiplies coronary heart disease risk in patients with familial hypercholesterolemia

Abstract Background Familial hypercholesterolemia (FH) and elevated lipoprotein(a) (Lp[a]) are individually associated with increased coronary heart disease (CHD) risk. Purpose To determine the independent and joint associations of FH and Lp(a) with CHD. Methods This was a cross-sectional study including adult patients with dyslipidemia followed at our University General Hospital, Greece. FH diagnosis was based on the Dutch Clinic Lipid Network Criteria (score ≥5), while elevated Lp(a) levels were defined as &amp;gt;30 mg/dL. Independent and joint associations of FH and Lp(a) with CHD prevalence were determined using binary logistic regression models adjusted for traditional cardiovascular risk factors. Results Among 941 participants (49 years, 47% males, 54% with FH, 36% with increased Lp[a]), the prevalence of CHD was 7.7% (n=72). Compared with subjects without FH and non-elevated Lp(a) (n=296), those with either FH (adjusted OR: 3.21, 95% CI: 1.35–7.62, n=271) or elevated Lp(a) (adjusted OR: 1.89, 95% CI: 0.76–4.69, n=180) were at higher CHD risk. The patients with both FH and elevated Lp(a) had the highest CHD risk (adjusted OR: 7.31; 95% CI: 3.09–17.32, n=195). Among FH patients, increased Lp(a) doubled CHD risk (adjusted OR: 2.22, 95% CI: 1.02–4.83), whereas among patients with elevated Lp(a), FH was associated with a 5-fold increase in CHD risk (adjusted OR: 4.96, 95% CI: 1.83–13.43). Conclusions FH and elevated Lp(a) have independent and additive associations with CHD prevalence. This may have therapeutic implications regarding treatment intensity. Funding Acknowledgement Type of funding sources: None.

Elevated triglycerides and low HDL cholesterol predict coronary heart disease risk in patients with stable angina

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): The EVINCI study was supported by a grant from the European Union FP7-CP-FP506 2007 project (GA 222915). The SMARTool study was supported by a grant from the European Union H2020-PHC-30-2015 (GA 689068). This study was also partially supported by a grant from AMGEN (Protocol N. 20167781, 2017). Background. High triglycerides (TG) and low high-density lipoprotein cholesterol (HDL-C) characterize an atherosclerotic cardiovascular disease (CAD) risk condition defined as atherogenic dyslipidemia. Aim. To assess whether atherogenic dyslipidemia defined by TG/HDL-C ratio predicts CAD related outcomes in patients with stable angina, independently of other risk factors and treatments. Methods. We studied 355 patients (60 ± 9 y, 211m) with stable angina from the EVINCI Outcome study. Patients were characterized for clinical, bio-humoral and imaging profiles, managed clinically, and followed for 4.5 ± 0.9 years. A computed tomography angiography (CTA) coronary risk score was obtained at baseline in all patients, and at follow-up in 154 of them. The primary composite outcome was all-cause mortality and non-fatal myocardial infarction. CTA scan was repeated at follow-up in 154 patients to assess CAD progression. Results. The median value of TG/HDL-C ratio was 2.095 (2.079IQR). At baseline, the proportion of males, smoking, diabetes and metabolic syndrome, as well as circulating bio-markers of abnormal glucose metabolism and myocardial damage progressively increased across quartiles of TG/HDL-C ratio. The CTA score was significantly higher in the IV quartile of the TG/HDL-C ratio and both were the only independent predictors of the primary (CTA Score: HR 1.06, 95%CI 1.03-1.09, p = 0.001; TG/HDL-C IV quartile: HR 2.85, 95%CI 1.30-6.26, p &amp;lt; 0.01). In the 154 patients re-evaluated at follow-up, TG/HDL-C ratio associated cardio-metabolic disorder, systemic inflammation and CTA risk score progressed over time despite increased use of lipid-lowering drugs, anti-diabetics and other cardioactive medications and reduction in LDL-C levels. Conclusions. In patients with stable angina, the TG/HDL-C ratio expresses a cardio-metabolic atherogenic disorder which is progressive over time and is associated with CAD related outcomes independently of LDL-C levels and treatments.

Inflammation and Coronary Heart Disease Risk in Patients with Depression in China Mainland: A Cross-Sectional Study.

ObjectiveThe risk of coronary heart disease (CHD) in patients with major depressive disorder (MDD) is higher than that in the general population. However, the mechanisms underlying the increased CHD risk in patients with MDD remain unclear. Inflammation plays an important role in the pathogenesis of MDD and CHD. Therefore, we explored the relationship between inflammatory biomarkers and CHD risk in patients with MDD.MethodsWe included 454 patients with acute MDD and 458 controls that matched the sample in age and gender. A readily available complete blood count was used to reflect inflammation, and the risk of CHD was assessed using the Framingham risk score.ResultsThe results showed that patients with MDD showed low-grade inflammation with an elevated platelet (p<0.001) and monocyte count (p<0.001), high platelet/lymphocyte (p=0.003) and monocyte/lymphocyte ratios (p<0.001), and a raised systemic immune-inflammation index (p=0.002). In addition, monocyte count was the only factor significantly associated with CHD risk in patients with MDD (B=7.521, 95% CI: 3.409–11.633, t=3.594, p<0.001).ConclusionCollectively, the results of this study support the hypothesis that MDD is systemic inflammation, and suggest that monocyte count predicts the risk of CHD in patients with MDD.

Effects of Metformin Therapy on Coronary Endothelial Dysfunction in Patients With Prediabetes With Stable Angina and Nonobstructive Coronary Artery Stenosis: The CODYCE Multicenter Prospective Study.

To evaluate the effect of metformin therapy on coronary endothelial function and major adverse cardiac events (MACE) in patients with prediabetes with stable angina and nonobstructive coronary stenosis (NOCS). Metformin therapy may be needed to reduce coronary heart disease risk in patients with prediabetes. A total of 258 propensity score-matched (PSM) patients with stable angina undergoing coronary angiography were enrolled in the study. Data from 86 PSM subjects with normoglycemia (NG), 86 PSM subjects with prediabetes (pre-DM), and 86 PSM subjects with prediabetes treated with metformin (pre-DM metformin) were analyzed. During coronary angiography, NOCS was categorized by luminal stenosis <40% and fractional flow reserve >0.80. In addition, we assessed the endothelial function, measuring coronary artery diameter of left anterior descending coronary (LAD) at baseline and after the infusion of acetylcholine, by means of an intracoronary Doppler guide wire. MACE, as cardiac death, myocardial infarction, and heart failure, was evaluated at 24 months of follow-up. At baseline, NG patients had a lower percentage of LAD endothelial dysfunction compared with pre-DM patients (P < 0.05). The pre-DM patients had a higher percentage of endothelial LAD dysfunction as compared with the pre-DM metformin patients (P < 0.05). At the 24th month of follow-up, MACE was higher in pre-DM versus NG (P < 0.05). In pre-DM metformin patients, MACE was lower compared with pre-DM patients (P < 0.05). Metformin therapy may reduce the high risk of cardiovascular events in pre-DM patients by reducing coronary endothelial dysfunction.

A Longitudinal Study of Clinical Benefits with Implementation of the Deep Inspiration Breath-Hold Technique in Post-Operative Radiotherapy for Left-Sided Breast Cancer

Purpose/Objectives: We aimed to report clinical effects on critical organ dose and cardiac toxicity from implementation of the deep inspiration breath-hold (DIBH) technique in post-operative extern-beam radiotherapy of patients with left-sided breast cancer, using longitudinal clinical data. Materials/Methods: We retrieved three groups of patients who received post-operative radiotherapy of left-sided breast cancer in our institution in recent years: Groups A and B consist of patients whose treatment did not include internal mammary nodes (IMN) and who were treated with the free breathing technique and with the DIBH technique, respectively, and Group C consists of patients whose radiotherapy included internal mammary nodes with the DIBH technique. Dose parameters for the heart and left lung were retrieved from the treatment plans. Radiation-induced cardiac risks were estimated using existing risk models. Results: The average heart dose was 2.65 ± 0.98 Gy, 1.10 ± 0.29 Gy, and 1.26 ± 0.25 Gy in Groups A, B, and C, respectively. The average heart volumes receiving at least 25 Gy were 7.10 ± 9.79 cc in Group A, 0.07 ± 0.22 cc in Group B, and 0.03 ± 0.08 cc in Group C. On average, the excessive risk of having ischemic heart disease was estimated to be 19.6%, 8.1%, and 9.3% in Groups A, B, and C, respectively. The mean left lung doses were 5.73 ± 1.86 Gy, 5.93 ± 1.55 Gy, and 9.13 ± 1.57 Gy in Groups A, B, and C, respectively. Conclusion: Implementation of the DIBH technique significantly lowered heart dose and decreased the ischemic heart disease risk in patients receiving post-operative radiotherapy for left-sided breast cancer, without significant increase in left lung dose.

Coronary heart disease risk in patients with schizophrenia: a Lebanese cross-sectional study.

Background:Coronary heart disease (CHD) is a leading cause of premature death in patients with schizophrenia. CHD risk in Lebanese patients with schizophrenia remains unknown.Objectives:To (i) evaluate CHD risk of patients with schizophrenia in Lebanon; and (ii) detect the modifiable and non-modifiable factors affecting this risk.Methods:Cross-sectional study of 329 patients with schizophrenia aged 20–75 years. Ten-year hard CHD risk was calculated using the Framingham risk score. A logistic regression was conducted taking the dichotomous hard CHD (<10% and ≥10%) as the dependent variable.Results:Ten-year hard CHD risk was low (<10%) in 60.8% of patients, intermediate (10–20%) in 31.6%, and high (>20%) in 7.6%. Multivariate analysis showed that the mean 10-year hard CHD risk was 8.76±6.92 (10.82±6.83 in men and 3.18±2.90 in women). Ten-year hard CHD risk was higher in patients with the metabolic syndrome (odds ratio [OR] 2.67, confidence interval [CI] 1.54–4.64), a longer duration of schizophrenia (OR 1.03, CI 1.01–1.05), a history of other medical illnesses (OR 2.02, CI 1.18–3.47), and in those participating in art therapy (OR 2.13, CI 1.25–3.64) or therapeutic education (OR 1.93, CI 0.93–4.01). Ten-year hard CHD risk was lower in patients receiving risperidone (OR 0.23, CI 0.08–0.68), any anti-epileptic (OR 0.41, CI 0.24–0.73), or any benzodiazepine (OR 0.33, CI 0.17–0.66) medication.Conclusion:CHD is prevalent in patients with schizophrenia in Lebanon. Physicians are recommended to monitor the components of the metabolic syndrome to identify patients with increased risk of cardiovascular diseases.

Coronary heart disease risk in patients with schizophrenia: a Lebanese cross-sectional study (supplementary file)

Coronary heart disease risk in patients with schizophrenia: a Lebanese cross-sectional study (supplementary file)

Depletion of T lymphocytes ameliorates cardiac fibrosis in streptozotocin-induced diabetic cardiomyopathy

T cell infiltration has been associated with increased coronary heart disease risk in patients with diabetes mellitus. Effect of modulation of T cell trafficking on diabetes-induced cardiac fibrosis has yet to be determined. Therefore, our aim was to investigate the circulatory T cell depletion-mediated cardioprotection in streptozotocin-induced diabetic cardiomyopathy. Fingolimod (FTY720), an immunomodulatory drug, was tested in wild-type (WT) C57BL/6 and recombination activating gene 1 (Rag1) knockout (KO) mice without mature lymphocytes in streptozotocin-induced type 1 diabetic model. FTY720 (0.3mg/kg/day) was administered intraperitoneally daily for the first 4weeks with interim 3weeks then resumed for another 4weeks in 11weeks study period. T lymphocyte counts, cardiac histology, function, and fibrosis were examined in diabetic both WT and KO mice. FTY720 reduced both CD4+ and CD8+ T cells in diabetic WT mice. FTY720-treated diabetic WT mouse myocardium showed reduction in CD3 T cell infiltration and decreased expression of S1P1 and TGF-β1 in cardiac tissue. Fibrosis was reduced after FTY720 treatment in diabetic WT mice. Rag1 KO mice exhibited no CD4+ and CD8+ T cells in the blood and CD3 T cells in the heart. Diabetic Rag1 KO mouse hearts appeared no fibrosis and exhibited preserved myocardial contractility. FTY720-induced antifibrosis was abolished in diabetic Rag1 KO mice. These findings demonstrate that chronic administration with FTY720 induces lymphopenia and protects diabetic hearts in WT mice whereas FTY720 increases cardiac fibrosis and myocardial dysfunction in diabetic Rag1 KO mice without mature lymphocytes.

Effects of Exercise and Sertraline on Measures of Coronary Heart Disease Risk in Patients With Major Depression: Results From the SMILE-II Randomized Clinical Trial.

To assess the effects of supervised and home-based aerobic exercise training, and antidepressant pharmacotherapy (sertraline) on coronary heart disease (CHD) risk factors in a sample of participants with major depressive disorder (MDD). The Standard Medical Intervention versus Long-term Exercise (SMILE)-II study randomized 202 adults (153 women, 49 men) diagnosed as having MDD to one of four interventions, each of 4-month duration: supervised exercise, home-based exercise, antidepressant medication (sertraline, 50-200 mg daily), or placebo pill. Patients underwent a structured clinical interview for depression and completed the Hamilton Depression Rating Scale. CHD risk factors included brachial artery flow-mediated dilation, carotid intima-media thickness, serum lipids, and 10-year atherosclerotic cardiovascular disease (ASCVD) risk. Compared with placebo, active treatment of depression (supervised exercise, home-based exercise, sertraline therapy) was associated with an improvement in CHD risk factors (improved flow-mediated dilation [p = .032], reduced progression of intima-media thickness [p = .037], and a reduction in 10-year ASCVD [p = .049]). The active treatments did not differ from each other in their effects on the CHD risk outcomes. Both exercise and antidepressant medication improved CHD risk factors and lowered ASCVD risk in patients with MDD. Because MDD is associated with increased risk for CHD events, treatment of depression with exercise or sertraline may reduce the risk of developing CHD in patients with MDD. Clinical Trials Government Identifier: NCT-00331305.

Effects of Exercise and Sertraline on Measures of Coronary Heart Disease Risk in Patients With Major Depression: Results From the SMILE-II Randomized Clinical Trial

Effects of Exercise and Sertraline on Measures of Coronary Heart Disease Risk in Patients With Major Depression: Results From the SMILE-II Randomized Clinical Trial

Optimal Monitoring For Coronary Heart Disease Risk in Patients with Systemic Lupus Erythematosus: A Systematic Review.

Premature coronary heart disease (CHD) significantly affects morbidity and mortality in systemic lupus erythematosus (SLE). Several studies have detected factors influencing the atherosclerotic process, as well as methods to quantify the atherosclerotic burden in subclinical stages. The aim of this systematic review was to identify the minimum investigations to optimally monitor CHD risk in SLE. English-restricted literature review was performed using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines through Ovid Medline, Embase, and Cochrane Central databases, from inception until May 2014 (Medline until October 2014). Specific search terms included, among others, "SLE," "atherosclerosis," "CHD," "myocardial ischemia," "acute coronary syndrome," "myocardial infarction," and "angina pectoris." We identified 101 eligible articles, 23 with cardiovascular events (CVE) as endpoints and 78 with measures of subclinical atherosclerosis. The Newcastle-Ottawa scale was used for quality assessment. Certain traditional and disease-specific factors were identified as independent predictors for CHD. Among the former were age (particularly postmenopausal state), male sex, arterial hypertension, dyslipidemia, and smoking. Disease activity and duration, cumulative damage, antiphospholipid antibodies, high sensitivity C-reactive protein, and renal disease were the most consistent disease-related factors. Corticosteroids were linked to increased CHD risk whereas antimalarials were protective. Concerning imaging techniques, carotid ultrasonography (intima-media thickness and plaque) was shown to independently predict CVE. Premature CHD in SLE is multifactorial; modifiable variables should be monitored at frequent intervals to ensure prompt management. Disease-specific factors also affect the atherogenic process and should be evaluated regularly. Carotid ultrasonography may hold promise in predicting CVE in selected high-risk patients.

Association between liver fibrosis and coronary heart disease risk in patients with nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease (NAFLD) is being increasingly recognized as the most common cause of chronic liver disease worldwide. It has been shown that NAFLD in adults is associated with increased risk of coronary heart disease (CHD). Because of the limitations of liver biopsy, noninvasive scoring indexes such as the NAFLD fibrosis score (NFS) were developed. The Framingham risk score (FRS) provides an estimate of CHD risk. In our study we aimed to investigate whether the severity of liver fibrosis estimated with the NFS is associated with a higher risk of CHD among individuals with ultrasonography-diagnosed NAFLD. A total of 155 patients and controls (81 patients with NAFLD and 74 controls) with ages ranging from 18 to 70 years were enrolled in this cross-sectional prospective study. Demographic, anthropometric, clinical, and laboratory data were obtained from each individual. The NAFLD patients were divided into subgroups on the basis of the severity of fatty liver. The FRS and NFS were adopted to predict the risk of CHD and the severity of hepatic fibrosis. In our study, we found that the FRS was higher in NAFLD patients than in controls (P<0.05). According to the FRS category, NFSs were higher in the intermediate/high probability CHD risk group in NAFLD (P<0.05). In multiple models, only age, sex, cholesterol, and HDL were independently associated with intermediate/high CHD risk (P<0.05). We also found a positive correlation between the NFS and the FRS (r=0.373, P<0.001). The optimum NFS cutoff point for identifying intermediate/high CHD risk in NAFLD patients was -2.1284, with a sensitivity and specificity of 95.20 and 48.30%, respectively. The predictive performance of the NFS in the determination of intermediate/high CHD risk in NAFLD patients was found to be 72% based on the area under the curve value. The FRS is associated with the NFS in NAFLD. The assessment of liver fibrosis may be useful for the risk stratification of CHD in the absence of liver biopsy in clinical practice.

Organization of Diabetes Care

Organization of Diabetes Care

Time trends in absolute and modifiable coronary heart disease risk in patients with Type 2 diabetes in the Swedish National Diabetes Register (NDR) 2003–2008

The aim was to evaluate treatment goal achievements early in the course of Type 2 diabetes, and their effect on 10-year risk of coronary heart disease in patients receiving usual care. Assessment of risk factor control 3 years after diagnosis in patients with Type 2 diabetes with no previous coronary heart disease included from the Swedish National Diabetes Register; a total of 19,382 patients (mean age 58 years) in cross-sectional surveys from 2003 to 2008, and a subgroup of 4293 patients followed individually from year of diagnosis to follow-up after a mean 2.6 years. Estimation of absolute 10-year risk of coronary heart disease using the U.K. Prospective Diabetes Study risk engine, and modifiable 10-year risk defined as percentage excess risk above patients with 'normal' risk factor values. Treatment goals for HbA1c , blood pressure, total and LDL cholesterol were achieved in 78.4, 65.5, 55.6% and 61.0%, respectively, in the cross-sectional survey in 2008, following a trend of generally improved control. In the individually followed patients in the subgroup, mean absolute 10-year coronary heart disease risk increased from 13.7% (men/women 16.9/9.5%) to 14.2 (men/women 17.6/9.6%) (P < 0.001) from year of diagnosis to follow-up after 2.6 years, while mean modifiable risk decreased from 37.7% (men/women 28.6/49.9%) to 19.1% (13.2/26.9%) (P < 0.001 in all). A high achievement of treatment goals and a low mean modifiable 10-year coronary heart disease risk was found at the 3-year follow-up, both in the cross-sectional survey in 2008 and in patients individually followed since diagnosis. This indicates the feasibility and significance of early multifactorial risk factor treatment.

Spectral analysis of carotid distension rate and R–R interval (spontaneous baroreflex activity) predicts coronary heart disease risk in patients with moderate chronic kidney disease and in those with normal renal function: the EPP3 study

Spectral analysis of carotid distension rate and R–R interval (spontaneous baroreflex activity) predicts coronary heart disease risk in patients with moderate chronic kidney disease and in those with normal renal function: the EPP3 study

Apolipoprotein Isoform E4 Does Not Increase Coronary Heart Disease Risk in Carriers of Low-Density Lipoprotein Receptor Mutations

In humans, the E4 allele of the apolipoprotein E gene is associated with increased coronary heart disease risk. Surprisingly, in rodents, apolipoprotein E4 only accelerates the atherosclerotic process when transgenic for the human low-density lipoprotein receptor (LDLR) protein. We therefore investigated whether the LDLR locus interacted with the apolipoprotein E gene genotype on coronary heart disease risk in patients clinically diagnosed with familial hypercholesterolemia with and without LDLR mutation. We investigated whether the presence of an LDLR mutation diminishing LDLR function was protective in E4/E4 carriers. In a cohort of 2400 patients clinically diagnosed with familial hypercholesterolemia, we found an LDLR gene mutation in 1383 patients, whereas in 1013 patients, such mutation was not present. In 92 patients homozygous for the apolipoprotein E4, the presence of an LDLR mutation conferred lower coronary heart disease risk (hazard ratio, 0.16; 95% CI, 0.05-0.58; P=0.005). Mirroring these results, the apolipoprotein E4/E4 genotype was also associated with lower coronary heart disease risk in patients with familial hypercholesterolemia with an LDLR mutation (hazard ratio, 0.26; hazard ratio, 0.08-0.80; P=0.02). LDLR function is key to the detrimental effects of apolipoprotein E4 in humans. Kinetic studies in humans are now required to study the consequences of our observation for prevention of both coronary heart disease and Alzheimer disease.