Faculty Bibliography

BACKGROUND: Physicians have limited time for weight-loss counseling, and there is a lack of resources to which they can refer patients for assistance with weight loss. Weight-loss mobile applications (apps) have the potential to be a helpful tool, but the extent to which they include the behavioral strategies included in evidence-based interventions is unknown. PURPOSE: The primary aims of the study were to determine the degree to which commercial weight-loss mobile apps include the behavioral strategies included in evidence-based weight-loss interventions, and to identify features that enhance behavioral strategies via technology. METHODS: Thirty weight-loss mobile apps, available on iPhone and/or Android platforms, were coded for whether they included any of 20 behavioral strategies derived from an evidence-based weight-loss program (i.e., Diabetes Prevention Program). Data on available apps were collected in January 2012; data were analyzed in June 2012. RESULTS: The apps included on average 18.83% (SD=13.24; range=0%-65%) of the 20 strategies. Seven of the strategies were not found in any app. The most common technology-enhanced features were barcode scanners (56.7%) and a social network (46.7%). CONCLUSIONS: Weight-loss mobile apps typically included only a minority of the behavioral strategies found in evidence-based weight-loss interventions. Behavioral strategies that help improve motivation, reduce stress, and assist with problem solving were missing across apps. Inclusion of additional strategies could make apps more helpful to users who have motivational challenges.

IMPORTANCE: There is consensus that incorporating clinical decision support into electronic health records will improve quality of care, contain costs, and reduce overtreatment, but this potential has yet to be demonstrated in clinical trials. OBJECTIVE: To assess the influence of a customized evidence-based clinical decision support tool on the management of respiratory tract infections and on the effectiveness of integrating evidence at the point of care. DESIGN, SETTING, AND PARTICIPANTS: In a randomized clinical trial, we implemented 2 well-validated integrated clinical prediction rules, namely, the Walsh rule for streptococcal pharyngitis and the Heckerling rule for pneumonia. INTERVENTIONS AND MAIN OUTCOMES AND MEASURES: The intervention group had access to the integrated clinical prediction rule tool and chose whether to complete risk score calculators, order medications, and generate progress notes to assist with complex decision making at the point of care. RESULTS: The intervention group completed the integrated clinical prediction rule tool in 57.5% of visits. Providers in the intervention group were significantly less likely to order antibiotics than the control group (age-adjusted relative risk, 0.74; 95% CI, 0.60-0.92). The absolute risk of the intervention was 9.2%, and the number needed to treat was 10.8. The intervention group was significantly less likely to order rapid streptococcal tests compared with the control group (relative risk, 0.75; 95% CI, 0.58-0.97; P= .03). CONCLUSIONS AND RELEVANCE: The integrated clinical prediction rule process for integrating complex evidence-based clinical decision report tools is of relevant importance for national initiatives, such as Meaningful Use. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01386047.

BACKGROUND: Although higher visit-to-visit variability (VVV) of blood pressure (BP) is associated with increased cardiovascular disease risk, the physiological basis for VVV of BP is incompletely understood. METHODS: We examined the associations of aortic distensibility (assessed by magnetic resonance imaging) and artery elasticity indices (determined by radial artery pulse contour analysis) with VVV of BP in 2,640 and 4,560 participants, respectively, from the Multi-Ethnic Study of Atherosclerosis. Arterial measures were obtained at exam 1. BP readings were taken at exam 1 and at 3 follow-up visits at 18-month intervals (exams 2, 3, and 4). VVV was defined as the SD about each participant's mean systolic BP (SBP) across visits. RESULTS: The mean SDs of SBP were inversely associated with aortic distensibility: 7.7, 9.9, 10.9, and 13.2mm Hg for quartiles 4, 3, 2, and 1 of aortic distensibility, respectively (P trend < 0.001). This association remained significant after adjustment for demographics, cardiovascular risk factors, mean SBP, and antihypertensive medication use (P trend < 0.01). In a fully adjusted model, lower quartiles of large artery and small artery elasticity (LAE and SAE) indices were also associated with higher mean SD of SBP (P trend = 0.02 for LAE; P trend < 0.001 for SAE). CONCLUSIONS: In this multiethnic cohort, functional alterations of central and peripheral arteries were associated with greater long-term VVV of SBP.

OBJECTIVE: Many studies of diabetes have examined risk factors at the time of diabetes diagnosis instead of considering the lifetime burden of adverse risk factor levels. We examined the 30-year cardiovascular disease (CVD) risk factor burden that participants have up to the time of diabetes diagnosis. RESEARCH DESIGN AND METHODS: Among participants free of CVD, incident diabetes cases (fasting plasma glucose >/= 126 mg/dL or treatment) occurring at examinations 2 through 8 (1979-2008) of the Framingham Heart Study Offspring cohort were age- and sex-matched 1:2 to controls. CVD risk factors (hypertension, high LDL cholesterol, low HDL cholesterol, high triglycerides, obesity) were measured at the time of diabetes diagnosis and at time points 10, 20, and 30 years prior. Conditional logistic regression was used to compare risk factor levels at each time point between diabetes cases and controls. RESULTS: We identified 525 participants with new-onset diabetes who were matched to 1,049 controls (mean age, 60 years; 40% women). Compared with those without diabetes, individuals who eventually developed diabetes had higher levels of hypertension (odds ratio [OR], 2.2; P = 0.003), high LDL (OR, 1.5; P = 0.04), low HDL (OR, 2.1; P = 0.0001), high triglycerides (OR, 1.7; P = 0.04), and obesity (OR, 3.3; P < 0.0001) at time points 30 years before diabetes diagnosis. After further adjustment for BMI, the ORs for hypertension (OR, 1.9; P = 0.02) and low HDL (OR, 1.7; P = 0.01) remained statistically significant. CONCLUSIONS: CVD risk factors are increased up to 30 years before diagnosis of diabetes. These findings highlight the importance of a life course approach to CVD risk factor identification among individuals at risk for diabetes.

Nonadherence to cardiovascular medications such as statins is a common, important problem. Clinicians currently rely on intuition to identify medication nonadherence. The visit-to-visit variability (VVV) of low-density lipoprotein (LDL) cholesterol might represent an opportunity to identify statin nonadherence with greater accuracy. We examined the clinical and pharmacy data from 782 members of the Boston Medical Center Health Plan, seen at either the Boston Medical Center or its affiliated community health centers, who were taking statins and had >/=3 LDL cholesterol measurements from 2008 to 2011. The LDL cholesterol VVV (defined by the within-patient SD) was categorized into quintiles. Multivariate logistic regression models were generated with statin nonadherence (defined by the standard 80% pharmacy refill-based medication possession ratio threshold) as the dependent variable. The proportion of statin nonadherence increased across the quintiles of LDL cholesterol VVV (64.3%, 71.2%, 89.2%, 92.3%, 91.7%). Higher quintiles of LDL cholesterol VVV had a strong positive association with statin nonadherence, with an adjusted odds ratio of 3.4 (95% confidence interval 1.7 to 7.1) in the highest versus lowest quintile of LDL cholesterol VVV. The age- and gender-adjusted model had poor discrimination (C-statistic 0.62, 95% confidence interval 0.57 to 0.67), but the final adjusted model (age, gender, race, mean LDL cholesterol) demonstrated good discrimination (C-statistic 0.75, 95% confidence interval 0.71 to 0.79) between the adherent and nonadherent patients. In conclusion, the VVV of LDL cholesterol demonstrated a strong association with statin nonadherence in a clinic setting. Furthermore, a VVV of LDL cholesterol-based model had good discrimination characteristics for statin nonadherence. Research is needed to validate and generalize these findings to other populations and biomarkers.

BACKGROUND: Same-day discharge after percutaneous coronary intervention (PCI) may be safe for some patients. Few data are available on patient-reported outcomes and preferences for same-day discharge after PCI. METHODS AND RESULTS: Between March 2008 and March 2010, a total of 298 patients undergoing elective PCI via femoral access at 2 medical centers (Mount Sinai Hospital, New York, NY, and Baylor Medical Center, Dallas, TX) were randomized to same-day (n=150) or next-day (n=148) discharge. The primary outcome was high patient coping during the 7 days after discharge defined as scores <20 on the validated postdischarge coping difficulty scale. Safety outcomes, clopidogrel adherence, and patient preferences were secondary outcomes. Before discharge, patients randomized to same-day and next-day discharge were similar with respect to sociodemographic and clinical characteristics. High-coping ability, assessed 7 days after PCI, was present for 79% of patients randomized to same-day discharge and for 77% of patients randomized to next-day discharge. The difference in high coping ability, 2 (95% confidence interval, -7 to 11), did not cross the noninferiority threshold of -12% (P<0.001 that same-day discharge is not noninferior to next-day discharge). At 30 days after PCI, clopidogrel adherence, physician and emergency room visits, and hospitalization were similar in the 2 randomization groups. In addition, 80% and 68% of those randomized to same-day and next-day discharge, respectively, stated they would prefer same-day discharge if they were to have another PCI procedure. CONCLUSIONS: Same-day discharge after PCI was associated with patient-reported and clinical outcomes similar to those of next-day discharge and was preferred by most patients.

It has been hypothesized that high visit-to-visit variability (VVV) of systolic blood pressure (SBP) may be the result of poor antihypertensive medication adherence. The authors studied this association using data from 1391 individuals taking antihypertensive medication selected from a large managed care organization. The 8-item Morisky Medication Adherence Scale, administered during 3 annual surveys, captured self-report adherence, with scores<6, 6 to <8, and 8 representing low, medium. and high adherence, respectively. The mean (standard deviation [SD]) for SD of SBP across study visits was 12.9 (4.4), 13.5 (4.8), and 14.1 (4.5) mm Hg in participants with high, medium, and low self-reported adherence, respectively. After multivariable adjustment and compared with those with high self-report adherence, SD of SBP was 0.60 (95% confidence interval, 0.13-1.07) and 1.08 (95% confidence interval, 0.29-1.87) mm Hg higher among participants with medium and low self-report adherence, respectively. Results were consistent when pharmacy fill was used to define adherence. These data suggest that low antihypertensive medication adherence explains only a small proportion of VVV of SBP.

BACKGROUND: Given the results of the Justification for the Use of Statins in Primary Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER) trial, statin initiation may be considered for individuals with elevated high-sensitivity C-reactive protein (hsCRP). However, if followed prospectively, many individuals with elevated CRP may become statin eligible, limiting the impact of elevated CRP as a treatment indication. This analysis estimates the proportion of people with elevated CRP that become statin eligible over time. HYPOTHESIS: Most people with elevated CRP become statin eligible over a short period of time. METHODS: We followed 2153 Multi-Ethnic Study of Atherosclerosis (MESA) participants free of cardiovascular disease and diabetes with low-density lipoprotein cholesterol <130 mg/dL at baseline to determine the proportion who become eligible for statins over 4.5 years. The proportion eligible for statin therapy, defined by the National Cholesterol Education Program (NCEP) 2004 updated guidelines, was calculated at baseline and during follow-up stratified by baseline CRP level (>/=2 mg/L). RESULTS: At baseline, 47% of the 2153 participants had elevated CRP. Among participants with elevated CRP, 29% met NCEP criteria for statins, compared with 28% without elevated CRP at baseline. By 1.5 years later, 26% and 22% (P = 0.09) of those with and without elevated CRP at baseline reached NCEP low-density lipoprotein cholesterol criteria and/or had started statins, respectively. These increased to 42% and 39% (P = 0.24) at 3 years and 59% and 52% (P = 0.01) at 4.5 years following baseline. CONCLUSIONS: A substantial proportion of those with elevated CRP did not achieve NCEP-based statin eligibility over 4.5 years of follow-up. These findings suggest that many patients with elevated CRP may not receive the benefits of statins if CRP is not incorporated into the NCEP screening strategy.

Several landmark studies based on the DASH diet have established the effectiveness of a lifestyle approach to blood pressure control that emphasizes a diet rich in fruits and vegetables with moderate portions of low-fat dairy and lean protein along with increased physical activity and reduced sodium intake. However, this evidence base remains underused due feasibility limitations of implementing these intense in-person interventions and poor engagement with desktop computer based versions. Mobile technologies such as smartphones and wireless sensors have the ability to deliver behavioral interventions in-the-moment and with reduced user burden. DASH Mobile is a new mHealth system being developed to deliver this evidence-based lifestyle intervention to hypertensive patients. The system consists of an Android based "app" that facilitates easy tracking of DASH food portions, integrated Bluetooth blood pressure, weight and pedometer monitoring, goal setting, simple data visualizations and multimedia video clips to train patients in the basic concepts of the lifestyle change plan. At present, the system is undergoing usability testing with a pilot clinical trial planned for Spring 2013.