Search

The pooled cohort equations (PCE) predict atherosclerotic cardiovascular disease (ASCVD) risk in patients with characteristics within prespecified ranges and has uncertain performance among Asians or Hispanics. It is unknown if machine learning (ML) models can improve ASCVD risk prediction across broader diverse, real-world populations. We developed ML models for ASCVD risk prediction for multi-ethnic patients using an electronic health record (EHR) database from Northern California. Our cohort included patients aged 18 years or older with no prior CVD and not on statins at baseline (n = 262,923), stratified by PCE-eligible (n = 131,721) or PCE-ineligible patients based on missing or out-of-range variables. We trained ML models [logistic regression with L2 penalty and L1 lasso penalty, random forest, gradient boosting machine (GBM), extreme gradient boosting] and determined 5-year ASCVD risk prediction, including with and without incorporation of additional EHR variables, and in Asian and Hispanic subgroups. A total of 4309 patients had ASCVD events, with 2077 in PCE-ineligible patients. GBM performance in the full cohort, including PCE-ineligible patients (area under receiver-operating characteristic curve (AUC) 0.835, 95% confidence interval (CI): 0.825–0.846), was significantly better than that of the PCE in the PCE-eligible cohort (AUC 0.775, 95% CI: 0.755–0.794). Among patients aged 40–79, GBM performed similarly before (AUC 0.784, 95% CI: 0.759–0.808) and after (AUC 0.790, 95% CI: 0.765–0.814) incorporating additional EHR data. Overall, ML models achieved comparable or improved performance compared to the PCE while allowing risk discrimination in a larger group of patients including PCE-ineligible patients. EHR-trained ML models may help bridge important gaps in ASCVD risk prediction.

Results from cardiovascular (CV) outcome trials have revealed important insights into the CV safety and efficacy of glucose-lowering agents, including dipeptidyl peptidase-4 inhibitors (DPP-4i) and glucagon-like peptide-1 receptor agonists (GLP-1RA). Among patients with T2DM, DPP-4i have no significant effect on risk of major adverse CV events (MACE: CV death, myocardial infarction, or stroke) with mixed results regarding risk for heart failure (HF). While sitagliptin and linagliptin have neutral effects on HF risk, saxagliptin significantly increases the risk of HF. The CV safety of the GLP-1RA class of medications has been clearly demonstrated, and select agents, such as liraglutide, semaglutide, albiglutide, and dulaglutide, reduce the risk of MACE in patients with T2DM and established CV disease. CV outcome trials have demonstrated CV safety but not incremental efficacy for DPP-4i in most cases. Select GLP-1RA have proven efficacy for MACE and should be considered by cardiologists for CV risk mitigation in the care of patients with T2DM and established CV disease.

Dietary patterns are related to mortality in selected populations with comorbidities. We studied whether dietary patterns are associated with long-term survival in a middle-aged, healthy population.In this observational cohort study at the Cooper Clinic preventive medicine center (Dallas, Tex), a volunteer sample of 11,376 men and women with no history of myocardial infarction or stroke completed a baseline dietary assessment between 1987 and 1999 and were observed for an average of 18 years. Proportional hazard regressions, including a tree-augmented model, were used to assess the association of the Dietary Approaches to Stop Hypertension (DASH) dietary pattern, Mediterranean dietary pattern, and individual dietary components with mortality. The primary outcome was all-cause mortality. The secondary outcome was cardiovascular mortality.Mean baseline age was 47 years. Each quintile increase in the DASH diet score was associated with a 6% lower adjusted risk for all-cause mortality (P .02). The Mediterranean diet was not independently associated with all-cause or cardiovascular mortality. Solid fats and added sugars were the most predictive of mortality. Individuals who consumed34% of their daily calories as solid fats had the highest risk for all-cause mortality.The DASH dietary pattern was associated with significantly lower all-cause mortality over approximately 2 decades of follow-up in a middle-aged, generally healthy population. Added solid fat and added sugar intake were the most predictive of all-cause mortality. These results suggest that promotion of a healthy dietary pattern should begin in middle age, before the development of comorbid risk factors.

ObjectivesIdentifying high-risk patients is crucial for effective cardiovascular disease (CVD) prevention. It is not known whether electronic health record (EHR)-based machine-learning (ML) models can improve CVD risk stratification compared with a secondary prevention risk score developed from randomised clinical trials (Thrombolysis in Myocardial Infarction Risk Score for Secondary Prevention, TRS 2°P).MethodsWe identified patients with CVD in a large health system, including atherosclerotic CVD (ASCVD), split into 80% training and 20% test sets. A rich set of EHR patient features was extracted. ML models were trained to estimate 5-year CVD event risk (random forests (RF), gradient-boosted machines (GBM), extreme gradient-boosted models (XGBoost), logistic regression with an L2 penalty and L1 penalty (Lasso)). ML models and TRS 2°P were evaluated by the area under the receiver operating characteristic curve (AUC).ResultsThe cohort included 32 192 patients (median age 74 years, with 46% female, 63% non-Hispanic white and 12% Asian patients and 23 475 patients with ASCVD). There were 4010 events over 5 years of follow-up. ML models demonstrated good overall performance; XGBoost demonstrated AUC 0.70 (95% CI 0.68 to 0.71) in the full CVD cohort and AUC 0.71 (95% CI 0.69 to 0.73) in patients with ASCVD, with comparable performance by GBM, RF and Lasso. TRS 2°P performed poorly in all CVD (AUC 0.51, 95% CI 0.50 to 0.53) and ASCVD (AUC 0.50, 95% CI 0.48 to 0.52) patients. ML identified nontraditional predictive variables including education level and primary care visits.ConclusionsIn a multiethnic real-world population, EHR-based ML approaches significantly improved CVD risk stratification for secondary prevention.

The goal of this analysis was to evaluate the ability of insulin resistance, identified by the presence of prediabetes mellitus (PreDM) combined with either an elevated triglyceride (TG >1.7 mmol/l) or body mass index (BMI ≥27.0 kg/m(2)), to identify increased risk of statin-associated type 2 diabetes mellitus (T2DM). Consequently, a retrospective analysis of data from subjects without diabetes in the Treating to New Targets and the Stroke Prevention by Aggressive Reduction in Cholesterol Levels randomized controlled trials was performed, subdividing participants into 4 experimental groups: (1) normal fasting glucose (NFG) and TG ≤1.7 mmol/l (42%); (2) NFG and TG >1.7 mmol/l (22%); (3) PreDM and TG ≤1.7 mmol/l (20%); and (4) PreDM and TG >1.7 mmol/l (15%). Comparable groupings were created substituting BMI values (kg/m(2) 1.7 mmol/l) with intermediate values for only an elevated TG >1.7 mmol/l (5.2%/4.3%) or only PreDM (12.8%/7.6%). Comparable differences were observed when BMI values were substituted for TG concentrations. In conclusion, these data suggest that (1) the diabetogenic impact of statin treatment is relatively modest in general; (2) the diabetogenic impact is accentuated relatively dramatically as FPG and TG concentrations and BMI increase; and (3) PreDM, TG concentrations, and BMI identify people at highest risk of statin-associated T2DM.

In the CREDENCE trial, CANA reduced renal and CV events including hospitalization for HF (HHF) in patients with type 2 diabetes and chronic kidney disease (CKD). We assessed the efficacy of CANA in CREDENCE participants with and without HF at baseline. CREDENCE randomized 4401 participants with

Familial hypercholesterolemia (FH) is an underdiagnosed dominant genetic condition affecting approximately 0.4% of the population and has up to a 20-fold increased risk of coronary artery disease if untreated. Simple screening strategies have false positive rates greater than 95%. As part of the FH Foundation′s FIND FH initiative, we developed a classifier to identify potential FH patients using electronic health record (EHR) data at Stanford Health Care. We trained a random forest classifier using data from known patients (n = 197) and matched non-cases (n = 6590). Our classifier obtained a positive predictive value (PPV) of 0.88 and sensitivity of 0.75 on a held-out test-set. We evaluated the accuracy of the classifier′s predictions by chart review of 100 patients at risk of FH not included in the original dataset. The classifier correctly flagged 84% of patients at the highest probability threshold, with decreasing performance as the threshold lowers. In external validation on 466 FH patients (236 with genetically proven FH) and 5000 matched non-cases from the Geisinger Healthcare System our FH classifier achieved a PPV of 0.85. Our EHR-derived FH classifier is effective in finding candidate patients for further FH screening. Such machine learning guided strategies can lead to effective identification of the highest risk patients for enhanced management strategies.

Both HeFH and HoFH require dietary and lifestyle modification. Pharmacotherapy of adult HeFH patients is largely driven by the American Heart Association (AHA) algorithm. A high-potency statin is started initially with a goal low-density lipoprotein cholesterol (LDL-C) reduction of50 %. The LDL-C target is adjusted to100 or70 mg/dL in subjects with coronary artery disease (CAD) with ezetimibe being second line. If necessary, a third adjunctive therapy, such as a PSCK9 inhibitor (not yet approved in children) or bile acid-binding resin, can be added. Finally, LDL-C apheresis can be considered in patients with LDL-C300 mg/dL (or200 mg/dL with significant CAD, although now approved for LDL-C as low as 160 mg/dL with CAD). Due to the early, severe LDL-C elevation in HoFH patients, concerning natural history, rarity of the condition, and nuances of treatment, all HoFH patients should be treated at a pediatric or adult center with HoFH experience. LDL-C apheresis should be considered as early as 5 years of age. However, apheresis availability and tolerability is limited and pharmacotherapy is required. Generally, the AHA algorithm with reference to the European Atherosclerosis Society Consensus Panel recommendations is reasonable with all patients initiated on high-dose, high-potency statin, ezetimibe, and bile acid-binding resins. In most, additional LDL-C lowering is required with PCSK9 inhibitors and/or lomitapide or mipomersen. Liver transplantation can also be considered at experienced centers as a last resort.

Cardiovascular disease is the leading cause of death among adults in the USA. Both type 1 (T1DM) and type 2 diabetes mellitus (T2DM) are known risk factors for cardiovascular disease. Despite the development of numerous effective anti-glycemic therapies, we have been unable to completely mitigate cardiovascular risk with glucose lowering alone, and prevention of cardiovascular disease in patients with diabetes is primarily achieved with the use of medications that address other risk factors such as anti-hypertensives or statins. Glucagon-like peptide-1 (GLP-1) is a key hormone in the pathophysiology of diabetes. GLP-1 agonists have been recently approved for the treatment of T2DM as well as for chronic weight management. In this review, we aim to explore the effects of GLP-1 agonists on cardiovascular health with a focus on cardiometabolic variables and cardiac function.

Lanthanide-binding tags (LBTs), peptide-based coexpression tags with high affinity for lanthanide ions, have previously been applied as luminescent probes to provide phasing for structure determination in X-ray crystallography and to provide restraints for structural refinement and distance information in NMR. The native affinity of LBTs for Gd(3+) indicates their potential as the basis for engineering of peptide-based MRI agents. However, the lanthanide coordination state that enhances luminescence and affords tightest binding would not be ideal for applications of LBTs as contrast agents, due to the exclusion of water from the inner coordination sphere. Herein, we use structurally defined LBTs as the starting point for re-engineering the first coordination shell of the lanthanide ion to provide for high contrast through direct coordination of water to Gd(3+) (resulting in the single LBT peptide, m-sLBT). The effectiveness of LBTs as MRI contrast agents was examined in vitro through measurement of binding affinity and proton relaxivity. For imaging applications that require targeted observation, fusion to specific protein partners is desirable. However, a fusion protein comprising a concatenated double LBT (dLBT) as an N-terminal tag for the model protein ubiquitin had reduced relaxivity compared with the free dLBT peptide. This limitation was overcome by the use of a construct based on the m-sLBT sequence (q-dLBT-ubiquitin). The structural basis for the enhanced contrast was examined by comparison of the X-ray crystal structure of xq-dLBT-ubiquitin (wherein two tryptophan residues are replaced with serine), to that of dLBT-ubiquitin. The structure shows that the backbone conformational dynamics of the MRI variant may allow enhanced water exchange. This engineered LBT represents a first step in expanding the current base of specificity-targeted agents available.

Mannose-binding lectin (MBL) is a key soluble effector of the innate immune system that recognizes pathogen-specific surface glycans. Surprisingly, low-producing MBL genetic variants that may predispose children and immunocompromised individuals to infectious diseases are more common than would be expected in human populations. Since certain immune defense molecules, such as immunoglobulins, can be exploited by invasive pathogens, we hypothesized that MBL might also enhance infections in some circumstances. Consequently, the low and intermediate MBL levels commonly found in human populations might be the result of balancing selection. Using model infection systems with pseudotyped and authentic glycosylated viruses, we demonstrated that MBL indeed enhances infection of Ebola, Hendra, Nipah and West Nile viruses in low complement conditions. Mechanistic studies with Ebola virus (EBOV) glycoprotein pseudotyped lentiviruses confirmed that MBL binds to N-linked glycan epitopes on viral surfaces in a specific manner via the MBL carbohydrate recognition domain, which is necessary for enhanced infection. MBL mediates lipid-raft-dependent macropinocytosis of EBOV via a pathway that appears to require less actin or early endosomal processing compared with the filovirus canonical endocytic pathway. Using a validated RNA interference screen, we identified C1QBP (gC1qR) as a candidate surface receptor that mediates MBL-dependent enhancement of EBOV infection. We also identified dectin-2 (CLEC6A) as a potentially novel candidate attachment factor for EBOV. Our findings support the concept of an innate immune haplotype that represents critical interactions between MBL and complement component C4 genes and that may modify susceptibility or resistance to certain glycosylated pathogens. Therefore, higher levels of native or exogenous MBL could be deleterious in the setting of relative hypocomplementemia which can occur genetically or because of immunodepletion during active infections. Our findings confirm our hypothesis that the pressure of infectious diseases may have contributed in part to evolutionary selection of MBL mutant haplotypes.

1-(5-Isoquinolinesulfonyl)-2-methylpiperazine dihydrochloride (H-7), a potent and selective inhibitor of protein kinase C (PKC), inhibited PHA-stimulated bovine peripheral blood mononuclear cell (PBMC) proliferation, interleukin-2 (IL-2) production, and cytosolic PKC activity without affecting the cell viabilities. Presence of exogenous cytokines, such as purified human IL-2 or recombinant bovine IL-2 (rbovIL-2), reversed the H-7 inhibitory effects on PHA-stimulated PBMC proliferation. We conclude that the PKC enzyme plays an important role as a second messenger in bovine PBMC proliferation in the early stages of cell activation.

PURPOSE To study occurrence, morphology, immunofluorescence, and ultrastructural features of congenital anterior capsular plaque (ACP) obtained from pediatric eyes undergoing cataract surgery. METHODS Two hundred sixty consecutive pediatric eyes undergoing congenital cataract surgery were enrolled in the present study. Anterior lens epithelium from cataract without ACP and with ACP was collected. Wholemounts of lens epithelium were stained with hematoxylin-eosin. Five-micrometer-thick sections of large ACPs were subjected to immunofluorescence localization of collagen type I, collagen type IV, alpha-smooth muscle actin (alpha SMA), and alpha A-crystallin. Ultrathin sections were studied by transmission electron microscope. RESULTS The overall occurrence of ACP in pediatric eyes undergoing congenital cataract surgery was 11.5%. The occurrence of ACP was highest in mature cataract followed by nuclear, lamellar, and mixed cataract. The wholemount of anterior lens epithelium revealed nonplaque and plaque region or ACP. Depending on the area, ACPs can be classified as small, medium, and large. The extracellular matrix of ACP was fibrous and amorphous. It was rich in collagen type I. The cells of the ACP were surrounded by a network of collagen type IV and were positive for alpha SMA and alpha A-crystallin. The cells of the ACP were rich in rough endoplasmic reticulum and mitochondria. CONCLUSIONS The occurrence of ACP in pediatric eyes undergoing cataract surgery for congenital cataract was 11.5%. ACP was more associated with mature cataract. Epithelial mesenchymal transdifferentiation of lens epithelial cells may be involved in the development of congenital ACP.