Hypertension is the most common condition seen in primary care and leads to myocardial infarction, stroke, renal failure, and death if not detected early and treated appropriately. Patients want to ...be assured that blood pressure (BP) treatment will reduce their disease burden, while clinicians want guidance on hypertension management using the best scientific evidence. This report takes a rigorous, evidence-based approach to recommend treatment thresholds, goals, and medications in the management of hypertension in adults. Evidence was drawn from randomized controlled trials, which represent the gold standard for determining efficacy and effectiveness. Evidence quality and recommendations were graded based on their effect on important outcomes. There is strong evidence to support treating hypertensive persons aged 60 years or older to a BP goal of less than 150/90 mm Hg and hypertensive persons 30 through 59 years of age to a diastolic goal of less than 90 mm Hg; however, there is insufficient evidence in hypertensive persons younger than 60 years for a systolic goal, or in those younger than 30 years for a diastolic goal, so the panel recommends a BP of less than 140/90 mm Hg for those groups based on expert opinion. The same thresholds and goals are recommended for hypertensive adults with diabetes or nondiabetic chronic kidney disease (CKD) as for the general hypertensive population younger than 60 years. There is moderate evidence to support initiating drug treatment with an angiotensin-converting enzyme inhibitor, angiotensin receptor blocker, calcium channel blocker, or thiazide-type diuretic in the nonblack hypertensive population, including those with diabetes. In the black hypertensive population, including those with diabetes, a calcium channel blocker or thiazide-type diuretic is recommended as initial therapy. There is moderate evidence to support initial or add-on antihypertensive therapy with an angiotensin-converting enzyme inhibitor or angiotensin receptor blocker in persons with CKD to improve kidney outcomes. Although this guideline provides evidence-based recommendations for the management of high BP and should meet the clinical needs of most patients, these recommendations are not a substitute for clinical judgment, and decisions about care must carefully consider and incorporate the clinical characteristics and circumstances of each individual patient.
Obesity treatment is less successful for socioeconomically disadvantaged populations, particularly when delivered in primary care. Digital health strategies can extend the reach of clinical obesity ...treatments to care settings serving patients at highest risk.
Track was an effectiveness RCT of a 12-month digital weight-loss intervention, embedded within a community health center system. Participants were 351 adult patients (aged 21–65 years) with obesity and hypertension, diabetes, and hyperlipidemia. Patients were randomized to usual care (n=175) or an intervention (n=176) comprising app-based self-monitoring of behavior change goals with tailored feedback, a smart scale, dietitian-delivered counseling calls, and clinician counseling informed by app-generated recommendations, delivered via electronic health record. The primary outcome was 12-month weight change. Randomization began on June 18, 2013, final assessments were completed on September 10, 2015. Data analysis was conducted in 2016 and 2017. The trial retained 92% of usual care and 96% of intervention participants at 12 months.
The Track intervention produced larger weight losses relative to usual care at 6 months (net effect: –4.4 kg, 95% CI= –5.5, –3.3, p<0.001) and 12 months (net effect: –3.8 kg, 95% CI= –5.0, –2.5, p<0.001). Intervention participants were more likely to lose ≥5% of their baseline weight at 6 months (43% vs 6%, p<0.001) and 12 months (40% vs 17%, p<0.001). Intervention participants completing ≥80% of expected self-monitoring episodes (–3.5 kg); counseling calls (–3.0 kg); or self-weighing days (–4.4 kg) lost significantly more weight than less engaged intervention participants (all p<0.01).
A digital obesity treatment, integrated with health system resources, can produce clinically meaningful weight-loss outcomes among socioeconomically disadvantaged primary care patients with elevated cardiovascular disease risk.
This study is registered at www.clinicaltrials.gov NCT01827800.
Obesity is an epidemic internationally. While weight loss interventions are efficacious, they are compounded by heterogeneity with regards to clinically relevant metabolic responses. Thus, we sought ...to identify metabolic biomarkers that are associated with beneficial metabolic changes to weight loss and which distinguish individuals with obesity who would most benefit from a given type of intervention. Liquid chromatography mass spectrometry-based profiling was used to measure 765 metabolites in baseline plasma from three different weight loss studies: WLM (behavioral intervention, N = 443), STRRIDE-PD (exercise intervention, N = 163), and CBD (surgical cohort, N = 125). The primary outcome was percent change in insulin resistance (as measured by the Homeostatic Model Assessment of Insulin Resistance %DELTAHOMA-IR) over the intervention. Overall, 92 individual metabolites were associated with %DELTAHOMA-IR after adjustment for multiple comparisons. Concordantly, the most significant metabolites were triacylglycerols (TAGs; p = 2.3e-5) and diacylglycerols (DAGs; p = 1.6e-4), with higher baseline TAG and DAG levels associated with a greater improvement in insulin resistance with weight loss. In tests of heterogeneity, 50 metabolites changed differently between weight loss interventions; we found amino acids, peptides, and their analogues to be most significant (4.7e-3) in this category. Our results highlight novel metabolic pathways associated with heterogeneity in response to weight loss interventions, and related biomarkers which could be used in future studies of personalized approaches to weight loss interventions.
Glycemic control is improved more after gastric bypass surgery (GBP) than after equivalent diet-induced weight loss in patients with morbid obesity and type 2 diabetes mellitus. We applied ...metabolomic profiling to understand the mechanisms of this better metabolic response after GBP. Circulating amino acids (AAs) and acylcarnitines (ACs) were measured in plasma from fasted subjects by targeted tandem mass spectrometry before and after a matched 10-kilogram weight loss induced by GBP or diet. Total AAs and branched-chain AAs (BCAAs) decreased after GBP, but not after dietary intervention. Metabolites derived from BCAA oxidation also decreased only after GBP. Principal components (PC) analysis identified two major PCs, one composed almost exclusively of ACs (PC1) and another with BCAAs and their metabolites as major contributors (PC2). PC1 and PC2 were inversely correlated with pro-insulin concentrations, the C-peptide response to oral glucose, and the insulin sensitivity index after weight loss, whereas PC2 was uniquely correlated with levels of insulin resistance (HOMA-IR). These data suggest that the enhanced decrease in circulating AAs after GBP occurs by mechanisms other than weight loss and may contribute to the better improvement in glucose homeostasis observed with the surgical intervention.
Abstract Objective To identify novel biomarkers through metabolomic profiles that distinguish metabolically well (MW) from metabolically unwell (MUW) individuals, independent of body mass index ...(BMI). Materials/Methods This study was conducted as part of the Measurement to Understand the Reclassification of Disease of Cabarrus/Kannapolis (MURDOCK) project. Individuals from 3 cohorts were classified as lean (BMI < 25 kg/m2 ), overweight (BMI ≥ 25 kg/m2 , BMI < 30 kg/m2 ) or obese (BMI ≥ 30 kg/m2 ). Cardiometabolic abnormalities were defined as: (1) impaired fasting glucose (≥ 100 mg/dL and ≤ 126 mg/dL); (2) hypertension; (3) triglycerides ≥ 150 mg/dL; (4) HDL-C < 40 mg/dL in men, < 50 mg/dL in women; and (5) insulin resistance (calculated Homeostatic Model Assessment (HOMA-IR) index of > 5.13). MW individuals were defined as having < 2 cardiometabolic abnormalities and MUW individuals had ≥ two cardiometabolic abnormalities. Targeted profiling of 55 metabolites used mass-spectroscopy-based methods. Principal components analysis (PCA) was used to reduce the large number of correlated metabolites into clusters of fewer uncorrelated factors. Results Of 1872 individuals, 410 were lean, 610 were overweight, and 852 were obese. Of lean individuals, 67% were categorized as MUW, whereas 80% of overweight and 87% of obese individuals were MUW. PCA-derived factors with levels that differed the most between MW and MUW groups were factors 4 (branched chain amino acids BCAA) p < .0001, 8 (various metabolites) p < .0001, 9 (C4/Ci4, C3, C5 acylcarnitines) p < .0001 and 10 (amino acids) p < .0002. Further, Factor 4, distinguishes MW from MUW individuals independent of BMI. Conclusion BCAA and related metabolites are promising biomarkers that may aid in understanding cardiometabolic health independent of BMI category.
There is burgeoning evidence that branch chain amino acids (BCAAs) are biomarkers of metabolic, cardiovascular, renal and cerebrovascular disease. The purpose of this review is to summarize the ...current evidence in this area.
Recent evidence demonstrates that BCAAs are associated with insulin resistance, type 2 diabetes, risk of cardiovascular disease, stage I and II chronic kidney disease and ischemic stroke. Further, circulating levels of BCAAs have the potential to predict populations at risk for cardiometabolic disease, type 2 diabetes and mortality from ischemic heart disease. Importantly, the relationship of BCAAs to insulin resistance is affected by the intake of fat in the diet as well as age.
Current evidence supports the potential use of BCAAs as biomarkers of disease. However, questions regarding the mechanisms underlying the relationship of BCAAs to disease process and severity need to be answered prior to the use of BCAAs as a biomarker in clinical practice.
Objective
To determine the effect on weight of two mobile technology‐based (mHealth) behavioral weight loss interventions in young adults.
Methods
Randomized, controlled comparative effectiveness ...trial in 18‐ to 35‐year‐olds with BMI ≥ 25 kg/m2 (overweight/obese), with participants randomized to 24 months of mHealth intervention delivered by interactive smartphone application on a cell phone (CP); personal coaching enhanced by smartphone self‐monitoring (PC); or Control.
Results
The 365 randomized participants had mean baseline BMI of 35 kg/m2. Final weight was measured in 86% of participants. CP was not superior to Control at any measurement point. PC participants lost significantly more weight than Controls at 6 months (net effect −1.92 kg CI −3.17, −0.67, P = 0.003), but not at 12 and 24 months.
Conclusions
Despite high intervention engagement and study retention, the inclusion of behavioral principles and tools in both interventions, and weight loss in all treatment groups, CP did not lead to weight loss, and PC did not lead to sustained weight loss relative to Control. Although mHealth solutions offer broad dissemination and scalability, the CITY results sound a cautionary note concerning intervention delivery by mobile applications. Effective intervention may require the efficiency of mobile technology, the social support and human interaction of personal coaching, and an adaptive approach to intervention design.
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