To assess the potential benefit of digital health interventions (DHIs) on cardiovascular disease (CVD) outcomes (CVD events, all-cause mortality, hospitalizations) and risk factors compared with ...non-DHIs.
We conducted a systematic search of PubMed, MEDLINE, EMBASE, Web of Science, Ovid, CINHAL, ERIC, PsychINFO, Cochrane, and Cochrane Central Register of Controlled Trials for articles published from January 1, 1990, through January 21, 2014. Included studies examined any element of DHI (telemedicine, Web-based strategies, e-mail, mobile phones, mobile applications, text messaging, and monitoring sensors) and CVD outcomes or risk factors. Two reviewers independently evaluated study quality utilizing a modified version of the Cochrane Collaboration risk assessment tool. Authors extracted CVD outcomes and risk factors for CVD such as weight, body mass index, blood pressure, and lipid levels from 51 full-text articles that met validity and inclusion criteria.
Digital health interventions significantly reduced CVD outcomes (relative risk, 0.61; 95% CI, 0.46-0.80; P<.001; I(2)=22%). Concomitant reductions in weight (-2.77 lb 95% CI, -4.49 to -1.05 lb; P<.002; I(2)=97%) and body mass index (-0.17 kg/m(2) 95% CI, -0.32 kg/m(2) to -0.01 kg/m(2); P=.03; I(2)=97%) but not blood pressure (-1.18 mm Hg 95% CI, -2.93 mm Hg to 0.57 mm Hg; P=.19; I(2)=100%) were found in these DHI trials compared with usual care. In the 6 studies reporting Framingham risk score, 10-year risk percentages were also significantly improved (-1.24%; 95% CI, -1.73% to -0.76%; P<.001; I(2)=94%). Results were limited by heterogeneity not fully explained by study population (primary or secondary prevention) or DHI modality.
Overall, these aggregations of data provide evidence that DHIs can reduce CVD outcomes and have a positive impact on risk factors for CVD.
Abstract One of the best-studied diets for cardiovascular health is the Mediterranean diet. This consists of fish, monounsaturated fats from olive oil, fruits, vegetables, whole grains, legumes/nuts, ...and moderate alcohol consumption. The Mediterranean diet has been shown to reduce the burden, or even prevent the development, of cardiovascular disease, breast cancer, depression, colorectal cancer, diabetes, obesity, asthma, erectile dysfunction, and cognitive decline. This diet is also known to improve surrogates of cardiovascular disease, such as waist-to-hip ratio, lipids, and markers of inflammation, as well as primary cardiovascular disease outcomes such as death and events in both observational and randomized controlled trial data. These enhancements easily rival those seen with more established tools used to fight cardiovascular disease such as aspirin, beta-blockers, angiotensin-converting enzyme inhibitors, and exercise. However, it is unclear if the Mediterranean diet offers cardiovascular disease benefit from its individual constituents or in aggregate. Furthermore, the potential benefit of the Mediterranean diet or its components is not yet validated by concrete cardiovascular disease endpoints in randomized trials or observational studies. This review will focus on the effects of the whole and parts of the Mediterranean diet with regard to both population-based and experimental data highlighting cardiovascular disease morbidity or mortality and cardiovascular disease surrogates when hard outcomes are not available. Our synthesis will highlight the potential for the Mediterranean diet to act as a key player in cardiovascular disease prevention, and attempt to identify certain aspects of the diet that are particularly beneficial for cardioprotection.
Background Digital health interventions (DHI) have been shown to improve intermediates of cardiovascular health, but their impact on cardiovascular (CV) outcomes has not been fully explored. The aim ...of this study was to determine whether DHI administered during cardiac rehabilitation (CR) would reduce CV-related emergency department (ED) visits and rehospitalizations in patients after percutaneous coronary intervention (PCI) for acute coronary syndrome (ACS). Methods We randomized patients undergoing CR following ACS and PCI to standard CR (n = 40) or CR + DHI (n = 40) for 3 months with 3 patients withdrawing from CR prior to initiation in the treatment arm and 6 in the control group. The DHI incorporated an online and smartphone-based CR platform asking the patients to report of dietary and exercise habits throughout CR as well as educational information toward patients' healthy lifestyles. We obtained data regarding ED visits and rehospitalizations at 180 days, as well as other metrics of secondary CV prevention at baseline and 90 days. Results Baseline demographics were similar between the groups. The DHI + CR group had improved weight loss compared to the control group (−5.1 ± 6.5 kg vs. −0.8 ± 3.8 kg, respectively, P = .02). Those in the DHI + CR group also showed a non-significant reduction in CV-related rehospitalizations plus ED visits compared to the control group at 180 days (8.1% vs 26.6%; RR 0.30, 95% CI 0.08-1.10, P = .054). Conclusions The current study demonstrated that complementary DHI significantly improves weight loss, and might offer a method to reduce CV-related ED visits plus rehospitalizations in patients after ACS undergoing CR. The study suggests a role for DHI as an adjunct to CR to improve secondary prevention of CV disease. Trial registration This trial is registered at clinicaltrials.gov ( NCT01883050 ).
Abstract Objectives This study assessed the prevalence of coronary microvascular abnormalities in patients presenting with chest pain and nonobstructive coronary artery disease (CAD). Background ...Coronary microvascular abnormalities mediate ischemia and can lead to an increased risk of cardiovascular events. Methods Using an intracoronary Doppler guidewire, endothelial-dependent microvascular function was examined by evaluating changes in coronary blood flow in response to acetylcholine, whereas endothelial-independent microvascular function was examined by evaluating changes in coronary flow velocity reserve in response to intracoronary adenosine. Patients were divided into 4 groups depending on whether they had a normal (+) or abnormal (−) coronary blood flow (CBF) in response to acetylcholine (Ach) and a normal (+) or abnormal (−) coronary flow velocity reserve (CFR) in response to adenosine (Adn): CBFAch+, CFRAdn+ (n = 520); CBFAch−, CFRAdn+ (n = 478); CBFAch+, CFRAdn− (n = 173); and CBFAch−, CFRAdn− (n = 268). Results Two-thirds of all patients had some sort of microvascular dysfunction. Women were more prevalent in each group (56% to 82%). Diabetes was uncommon in all groups (7% to 12%), whereas hypertension and hyperlipidemia were relatively more prevalent in each group, although rates for most conventional cardiovascular risk factors did not differ significantly between groups. There were no significant differences in the findings of noninvasive functional testing between groups. In a multivariable analysis, age was the only variable that independently predicted abnormal microvascular function. Conclusions Patients with chest pain and nonobstructive CAD have a high prevalence of coronary microvascular abnormalities. These abnormalities correlate poorly with conventional cardiovascular risk factors and are dissociated from the findings of noninvasive functional testing.
In the extended follow-up of the Everolimus-Eluting Stents Versus Bare-Metal Stents in ST-Segment Elevation Myocardial Infarction (EXAMINATION) trial, Arévalos et al1 describe the age-related ...outcomes in a cohort of patients with ST-elevation myocardial infarction (STEMI). There are still some non–target-vessel revascularizations, and this underscores the importance of risk-factor modification with aggressive medical therapy, such as high-intensity statins and some of the newer agents such as PCSK-9 inhibitors or some of the novel diabetic therapies such as SGLT-2 inhibitors or the weight-loss impacts of GLP-1 agonists. ...the optimal antiplatelet strategy in these patients is yet to be fully understood. ...these extended follow-up data highlight important differences in outcomes among younger and older patients with STEMI who survive their index hospitalization.
MOTS-c is one of the newly identified mitochondrial-derived peptides which play a role in regulating metabolic homeostasis. The current study aimed to investigate whether circulating MOTS-c levels ...are also associated with endothelial dysfunction(ED) in patients without significant structural coronary lesions.
Forty patients undergoing coronary angiography and endothelial function testing for clinical indications of recurrent angina with no structural coronary lesions were included in the study. They were divided into two groups based on coronary blood flow response to intracoronary acetylcholine (ACh) as normal endothelial function (≥ 50% increase from baseline) or ED, (n=20 each). Aortic plasma samples were collected at the time of catheterization for analysis of circulating MOTS-c levels by ELISA. The effect of MOTS-c on vascular reactivity was assessed in organ chambers using aortic rings collected from rats and renal artery stenosis (RAS) mice.
Baseline characteristics were similar between the two groups. MOTS-c plasma levels were lower in patients with ED compared with patients with normal endothelial function (p=0.007). Furthermore, plasma MOTS-c levels were positively correlated with microvascular (p=0.01) and epicardial (p=0.02) coronary endothelial function. Although MOTS-c did not have direct vasoactive effects, pretreating aortic rings from rats or RAS mice with MOTS-c (2μg/ml) improved vessel responsiveness to ACh compared with vessels without MOTS-c treatment.
Lower circulating endogenous MOTS-c levels in human subjects are associated with impaired coronary endothelial function. In rodents, MOTS-c improves endothelial function in vitro. Thus, MOTS-c represents a novel potential therapeutic target in patients with ED.
This study sought to determine whether machine learning can be used to better identify patients at risk for death or congestive heart failure (CHF) rehospitalization after percutaneous coronary ...intervention (PCI).
Contemporary risk models for event prediction after PCI have limited predictive ability. Machine learning has the potential to identify complex nonlinear patterns within datasets, improving the predictive power of models.
We evaluated 11,709 distinct patients who underwent 14,349 PCIs between January 2004 and December 2013 in the Mayo Clinic PCI registry. Fifty-two demographic and clinical parameters known at the time of admission were used to predict in-hospital mortality and 358 additional variables available at discharge were examined to identify patients at risk for CHF readmission. For each event, we trained a random forest regression model (i.e., machine learning) to estimate the time-to-event. Eight-fold cross-validation was used to estimate model performance. We used the predicted time-to-event as a score, generated a receiver-operating characteristic curve, and calculated the area under the curve (AUC). Model performance was then compared with a logistic regression model using pairwise comparisons of AUCs and calculation of net reclassification indices.
The predictive algorithm identified a high-risk cohort representing 2% of all patients who had an in-hospital mortality of 45.5% (95% confidence interval: 43.5% to 47.5%) compared with a risk of 2.1% for the general population (AUC: 0.925; 95% confidence interval: 0.92 to 0.93). Advancing age, CHF, and shock on presentation were the leading predictors for the outcome. A high-risk group representing 1% of all patients was identified with 30-day CHF rehospitalization of 8.1% (95% confidence interval: 6.3% to 10.2%). Random forest regression outperformed logistic regression for predicting 30-day CHF readmission (AUC: 0.90 vs. 0.85; p = 0.003; net reclassification improvement: 5.14%) and 180-day cardiovascular death (AUC: 0.88 vs. 0.81; p = 0.02; net reclassification improvement: 0.02%).
Random forest regression models (machine learning) were more predictive and discriminative than standard regression methods at identifying patients at risk for 180-day cardiovascular mortality and 30-day CHF rehospitalization, but not in-hospital mortality. Machine learning was effective at identifying subgroups at high risk for post-procedure mortality and readmission.
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