[Show abstract][Hide abstract] ABSTRACT: Introduction: Self-monitoring of blood pressure is effective in reducing blood pressure in hypertension.
However previous meta-analyses have shown a considerable amount of heterogeneity between studies,
only part of which can be accounted for by meta-regression. This may be due to differences in design, recruited populations, intervention components or results among patient subgroups. To further investigate these differences, an individual patient data (IPD) meta-analysis of self-monitoring of blood pressure will be performed. Methods and analysis: We will identify randomised trials that have compared patients with hypertension who are self-monitoring blood pressure with those who are not and invite trialists to provide IPD including clinic and/ or ambulatory systolic and diastolic blood pressure at baseline and all follow-up points where both intervention and control groups were measured. Other data requested will include measurement methodology, length of followup, cointerventions, baseline demographic (age, gender) and psychosocial factors (deprivation, quality of life), setting, intensity of self-monitoring, self-monitored blood pressure, comorbidities, lifestyle factors (weight, smoking) and presence or not of antihypertensive treatment. Data on all available patients will be included in order to take an intention-to-treat approach. A twostage procedure for IPD meta-analysis, stratified by trial and taking into account age, sex, diabetes and baseline systolic BP will be used. Exploratory subgroup analyses will further investigate non-linear relationships between the prespecified variables. Sensitivity analyses will assess the impact of trials which have and have not provided IPD. Ethics and dissemination: This study does not include identifiable data. Results will be disseminated in
a peer-reviewed publication and by international conference presentations. Conclusions: IPD analysis should help the understanding of which self-monitoring interventions for which patient groups are most effective in the control of blood pressure.
BMJ Open 09/2015; 5(9):e008532. DOI:10.1136/bmjopen-2015-008532 · 2.27 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Introduction:
Elevated blood pressure in childhood may predict increased cardiovascular risk in young adulthood. The Task Force on the Diagnosis, Evaluation and Treatment of High Blood pressure in Children and Adolescents recommends that blood pressure be measured in children aged 3 years or older at all health care visits. Guidelines from both Bright Futures and the Expert Panel of Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents recommend annual blood pressure screening. Adherence to these guidelines is unknown.
We conducted a cross-sectional study to assess compliance with blood pressure screening recommendations in 2 integrated health care delivery systems. We analyzed electronic health records of 103,693 subjects aged 3 to 17 years. Probability of blood pressure measurement documented in the electronic health record was modeled as a function of visit type (well-child vs nonwell-child); patient age, sex, race/ethnicity, and body mass index; health care use; insurance type; and type of office practice or clinic department (family practice or pediatrics).
Blood pressure was measured at 95% of well-child visits and 69% of nonwell-child outpatient visits. After adjusting for potential confounders, the percentage of nonwell-child visits with measurements increased linearly with patient age (P < .001). Overall, the proportion of children with annual blood pressure measurements was high and increased with age. Family practice clinics were more likely to adhere to blood pressure measurement guidelines compared with pediatric clinics (P < .001).
These results show good compliance with recommendations for routine blood pressure measurement in children and adolescents. Findings can inform the development of EHR-based clinical decision support tools to augment blood pressure screening and recognition of prehypertension and hypertension in pediatric patients.
[Show abstract][Hide abstract] ABSTRACT: Most patients with asthma take fewer than half of prescribed doses of controller medication. Interventions to improve adherence have typically been costly, impractical, and at best only minimally successful.
To test a speech recognition (SR) intervention to improve adherence to pediatric asthma controller medication.
The Breathe Well study was a 24-month pragmatic randomized clinical trial. The study was conducted within Kaiser Permanente Colorado, a large, group-model health maintenance organization. A total of 1187 children aged 3 to 12 years with a persistent asthma diagnosis and prescription for an inhaled corticosteroid were randomized to the computerized SR intervention or usual care condition and followed up for 24 months between October 2009 and February 2013.
Speech recognition telephone calls to parents in the intervention condition were triggered when an inhaled corticosteroid refill was due or overdue. Calls were automatically tailored with medical and demographic information from the electronic health record and from parent answers to questions in the call regarding recent refills or a desire to receive help refilling, learn more about asthma control, or speak with an asthma nurse or pharmacy staff member.
Adherence to pediatric asthma controller medication, measured as the medication possession ratio over 24 months.
In the intention-to-treat analysis, inhaled corticosteroid adherence was 25.4% higher in the intervention group than in the usual care group (24-month mean [SE] adherence, 44.5% [1.2%] vs 35.5% [1.1%], respectively; P < .001). Asthma-related urgent care events did not differ between the 2 groups. The intervention effect was consistent in subgroups stratified by age, sex, race/ethnicity, body mass index, and disease-related characteristics.
The intervention's significant impact on adherence demonstrates strong potential for low-cost SR adherence programs integrated with an electronic health record. The absence of change in urgent care visits may be attributable to the already low number of asthma urgent care visits within Kaiser Permanente Colorado. Application of electronic health record-leveraged SR interventions may reduce health care utilization when applied in a population with less-controlled asthma.
clinicaltrials.gov Identifier: NCT00958932.
[Show abstract][Hide abstract] ABSTRACT: Importance
Little is known about cardiac adverse events among patients with nonobstructive coronary artery disease (CAD).Objective
To compare myocardial infarction (MI) and mortality rates between patients with nonobstructive CAD, obstructive CAD, and no apparent CAD in a national cohort.Design, Setting, and Participants
Retrospective cohort study of all US veterans undergoing elective coronary angiography for CAD between October 2007 and September 2012 in the Veterans Affairs health care system. Patients with prior CAD events were excluded.Exposures
Angiographic CAD extent, defined by degree (no apparent CAD: no stenosis >20%; nonobstructive CAD: ≥1 stenosis ≥20% but no stenosis ≥70%; obstructive CAD: any stenosis ≥70% or left main [LM] stenosis ≥50%) and distribution (1, 2, or 3 vessel).Main Outcomes and Measures
The primary outcome was 1-year hospitalization for nonfatal MI after the index angiography. Secondary outcomes included 1-year all-cause mortality and combined 1-year MI and mortality.Results
Among 37 674 patients, 8384 patients (22.3%) had nonobstructive CAD and 20 899 patients (55.4%) had obstructive CAD. Within 1 year, 845 patients died and 385 were rehospitalized for MI. Among patients with no apparent CAD, the 1-year MI rate was 0.11% (n = 8, 95% CI, 0.10%-0.20%) and increased progressively by 1-vessel nonobstructive CAD, 0.24% (n = 10, 95% CI, 0.10%-0.40%); 2-vessel nonobstructive CAD, 0.56% (n = 13, 95% CI, 0.30%-1.00%); 3-vessel nonobstructive CAD, 0.59% (n = 6, 95% CI, 0.30%-1.30%); 1-vessel obstructive CAD, 1.18% (n = 101, 95% CI, 1.00%-1.40%); 2-vessel obstructive CAD, 2.18% (n = 110, 95% CI, 1.80%-2.60%); and 3-vessel or LM obstructive CAD, 2.47% (n = 137, 95% CI, 2.10%-2.90%). After adjustment, 1-year MI rates increased with increasing CAD extent. Relative to patients with no apparent CAD, patients with 1-vessel nonobstructive CAD had a hazard ratio (HR) for 1-year MI of 2.0 (95% CI, 0.8-5.1); 2-vessel nonobstructive HR, 4.6 (95% CI, 2.0-10.5); 3-vessel nonobstructive HR, 4.5 (95% CI, 1.6-12.5); 1-vessel obstructive HR, 9.0 (95% CI, 4.2-19.0); 2-vessel obstructive HR, 16.5 (95% CI, 8.1-33.7); and 3-vessel or LM obstructive HR, 19.5 (95% CI, 9.9-38.2). One-year mortality rates were associated with increasing CAD extent, ranging from 1.38% among patients without apparent CAD to 4.30% with 3-vessel or LM obstructive CAD. After risk adjustment, there was no significant association between 1- or 2-vessel nonobstructive CAD and mortality, but there were significant associations with mortality for 3-vessel nonobstructive CAD (HR, 1.6; 95% CI, 1.1-2.5), 1-vessel obstructive CAD (HR, 1.9; 95% CI, 1.4-2.6), 2-vessel obstructive CAD (HR, 2.8; 95% CI, 2.1-3.7), and 3-vessel or LM obstructive CAD (HR, 3.4; 95% CI, 2.6-4.4). Similar associations were noted with the combined outcome.Conclusions and Relevance
In this cohort of patients undergoing elective coronary angiography, nonobstructive CAD, compared with no apparent CAD, was associated with a significantly greater 1-year risk of MI and all-cause mortality. These findings suggest clinical importance of nonobstructive CAD and warrant further investigation of interventions to improve outcomes among these patients.
JAMA The Journal of the American Medical Association 11/2014; 312(17):1754-63. DOI:10.1001/jama.2014.14681 · 35.29 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Background: Prior research has shown that high- risk census tracts for out-of-hospital cardiac arrest (OHCA) can be identified. High-risk neighborhoods are defined as having a high incidence of OHCA and a low prevalence of bystander cardiopulmonary resuscitation (CPR). However, there is no consensus regarding the process for identifying high-risk neighborhoods. Objective: We propose a novel summary approach to identify high-risk neighborhoods through three separate spatial analysis methods: Empirical Bayes (EB), Local Moran's I (LISA), and Getis Ord Gi* (Gi*) in Denver, Colorado. Methods: We conducted a secondary analysis of prospectively collected Emergency Medical Services data of OHCA from January 1, 2009 to December 31, 2011 from the City and County of Denver, Colorado. OHCA incidents were restricted to those of cardiac etiology in adults >= 18 years. The OHCA incident locations were geocoded using Centrus. EB smoothed incidence rates were calculated for OHCA using Geoda and LISA and Gi* calculated using ArcGIS 10. Results: A total of 1102 arrests in 142 census tracts occurred during the study period, with 887 arrests included in the final sample. Maps of clusters of high OHCA incidence were overlaid with maps identifying census tracts in the below the Denver County mean for bystander CPR prevalence. Five census tracts identified were designated as Tier 1 high-risk tracts, while an additional 7 census tracts where designated as Tier 2 high-risk tracts. Conclusion: This is the first study to use these three spatial cluster analysis methods for the detection of high-risk census tracts. These census tracts are possible sites for targeted community-based interventions to improve both cardiovascular health education and CPR training.
[Show abstract][Hide abstract] ABSTRACT: Purpose To assess the impact of personalised physician learning (PPL) interventions using simulated learning cases on control of hypertension and dyslipidaemia in primary care settings.
Methods A total of 132 primary care physicians, 4568 eligible patients with uncontrolled hypertension, and 15 392 eligible patients with uncontrolled dyslipidaemia were cluster-randomised to one of three conditions: (a) no intervention, (b) PPL-electronic medical record (EMR) intervention in which 12 PPL cases were assigned to each physician based on observed patterns of care in the EMR in the previous year, or (c) PPL-ASSESS intervention in which 12 PPL cases were assigned to each physician based on their performance on four standardised assessment cases. General and generalised linear mixed models were used to account for clustering and to model differences in patient outcomes in the study arms.
Results Among patients with uncontrolled hypertension at baseline, 49.1%, 46.6% and 47.3% (p=0.43) achieved blood pressure (BP) targets at follow-up. Among patients with uncontrolled dyslipidaemia at baseline, 37.5%, 37.3% and 38.1% (p=0.72) achieved low density lipoprotein cholesterol targets at follow-up in PPL-EMR, PPL-ASSESS and the control group, respectively. Although systolic (BP) (p<0.001) and lipid (p<0.001) values significantly improved during the study, the group-by-time interaction term showed no differential change in systolic BP values (p=0.51) or lipid values (p=0.61) among the three study arms. No difference in intervention effect was noted when comparing the PPL-EMR with the PPL-ASSESS intervention (p=0.47).
Conclusions The two PPL interventions tested in this study did not lead to improved control of hypertension or dyslipidaemia in primary care clinics during a mean 14-month follow-up period. This null result may have been due in part to substantial overall improvement in BP and lipid control at the study sites during the study.
Trial registration number NCT00903071.