Louise Falzon

Predictors of Nonadherence to Statins: A Systematic Review and Meta-Analysis

Background: Nonadherence to statins limits the benefits of this common drug class. Individual studies assessing predictors of nonadherence haue produced inconsistent results. Objective: To identify reliable predictors of nonadherence to statins through systematic review and meta-analysis. Methods: Multiple databases, including MEDLINE, EMBASE, and PsycINFO, were searched (from inception through February 2009) to identify studies that evaluated predictors of nonadherence to statins. Studies were selected using a priori defined criteria, and each study was reviewed by 2 authors who abstracted data on study characteristics and outcomes. Relative risks were then pooled, using an inverse-variance weighted random-effects model. Results: Twenty-two cohort studies met inclusion criteria. Age had a U-shaped association with adherence; the oldest (≥70 years) and youngest (<50 years) subjects had lower adherence than the middle-aged (50-69 years) subjects. Women and patients with lower incomes were more likely to be nonadherent than were men (odds of nonadherence 1.07; 95% CI 1.04 to 1.11) and those with higher incomes (odds of nonadherence 1.18:95% CI 1.10 to 1.28), respectively. A history of cardiovascular disease predicted better adherence to statins (odds of nonadherence 0.68; 95% CI 0.66 to 0.78). Similarly, a diagnosis of hypertension or diabetes was associated with better adherence. Although there were too few studies for quantitative pooling, increased testing of lipid levels and lower out-of-pocket costs appeared to be associated with better adherence. There was substantial (l2 range 68.7-96.3%) heterogeneity between studies across factors. Conclusions: Several sociodemographic, medical, and health-care utilization characteristics are associated with statin nonadherence. These factors may be useful guides for targeting statin adherence interventions.

Multinational evidence-based recommendations for the diagnosis and management of gout: integrating systematic literature review and expert opinion of a broad panel of rheumatologists in the 3e initiative

We aimed to develop evidence-based multinational recommendations for the diagnosis and management of gout. Using a formal voting process, a panel of 78 international rheumatologists developed 10 key clinical questions pertinent to the diagnosis and management of gout. Each question was investigated with a systematic literature review. Medline, Embase, Cochrane CENTRAL and abstracts from 2010–2011 European League Against Rheumatism and American College of Rheumatology meetings were searched in each review. Relevant studies were independently reviewed by two individuals for data extraction and synthesis and risk of bias assessment. Using this evidence, rheumatologists from 14 countries (Europe, South America and Australasia) developed national recommendations. After rounds of discussion and voting, multinational recommendations were formulated. Each recommendation was graded according to the level of evidence. Agreement and potential impact on clinical practice were assessed. Combining evidence and clinical expertise, 10 recommendations were produced. One recommendation referred to the diagnosis of gout, two referred to cardiovascular and renal comorbidities, six focused on different aspects of the management of gout (including drug treatment and monitoring), and the last recommendation referred to the management of asymptomatic hyperuricaemia. The level of agreement with the recommendations ranged from 8.1 to 9.2 (mean 8.7) on a 1–10 scale, with 10 representing full agreement. Ten recommendations on the diagnosis and management of gout were established. They are evidence-based and supported by a large panel of rheumatologists from 14 countries, enhancing their utility in clinical practice.

Posttraumatic Stress Disorder Prevalence and Risk of Recurrence in Acute Coronary Syndrome Patients: A Meta-analytic Review

Background Acute coronary syndromes (ACS; myocardial infarction or unstable angina) can induce posttraumatic stress disorder (PTSD), and ACS-induced PTSD may increase patients’ risk for subsequent cardiac events and mortality. Objective: To determine the prevalence of PTSD induced by ACS and to quantify the association between ACS-induced PTSD and adverse clinical outcomes using systematic review and meta-analysis. Data Sources: Articles were identified by searching Ovid MEDLINE, PsycINFO, and Scopus, and through manual search of reference lists. Methodology/Principal Findings Observational cohort studies that assessed PTSD with specific reference to an ACS event at least 1 month prior. We extracted estimates of the prevalence of ACS-induced PTSD and associations with clinical outcomes, as well as study characteristics. We identified 56 potentially relevant articles, 24 of which met our criteria (N = 2383). Meta-analysis yielded an aggregated prevalence estimate of 12% (95% confidence interval [CI], 9%–16%) for clinically significant symptoms of ACS-induced PTSD in a random effects model. Individual study prevalence estimates varied widely (0%–32%), with significant heterogeneity in estimates explained by the use of a screening instrument (prevalence estimate was 16% [95% CI, 13%–20%] in 16 studies) vs a clinical diagnostic interview (prevalence estimate was 4% [95% CI, 3%–5%] in 8 studies). The aggregated point estimate for the magnitude of the relationship between ACS-induced PTSD and clinical outcomes (ie, mortality and/or ACS recurrence) across the 3 studies that met our criteria (N = 609) suggested a doubling of risk (risk ratio, 2.00; 95% CI, 1.69–2.37) in ACS patients with clinically significant PTSD symptoms relative to patients without PTSD symptoms. Conclusions/Significance This meta-analysis suggests that clinically significant PTSD symptoms induced by ACS are moderately prevalent and are associated with increased risk for recurrent cardiac events and mortality. Further tests of the association of ACS-induced PTSD and clinical outcomes are needed.

Meta-Analysis of Perceived Stress and Its Association With Incident Coronary Heart Disease

Most studies examining potential associations between psychological factors and cardiovascular outcomes have focused on depression or anxiety. The effect of perceived stress on incident coronary heart disease (CHD) has yet to be reviewed systematically. We conducted a systematic review and meta-analysis of the association between perceived stress and incident CHD. Ovid, MEDLINE, and PsycINFO were searched as data sources. Prospective observational cohort studies were selected that measured self-reported perceived stress and assessed incident CHD at ≥6 months. We extracted study characteristics and estimates of the risk of incident CHD associated with high perceived stress versus low perceived stress. We identified 23 potentially relevant articles, of which 6 met our criteria (n = 118,696). Included studies measured perceived stress with validated measurements and nonvalidated simple self-report surveys. Incident CHD was defined as new diagnosis of, hospitalization for, or mortality secondary to CHD. Meta-analysis yielded an aggregate risk ratio of 1.27 (95% confidence interval 1.12 to 1.45) for the magnitude of the relation between high perceived stress and incident CHD. In conclusion, this meta-analysis suggests that high perceived stress is associated with a moderately increased risk of incident CHD.

Posttraumatic stress disorder and risk for coronary heart disease: A meta-analytic review

OBJECTIVE The aim of this study was to estimate the association of posttraumatic stress disorder (PTSD) with risk for incident coronary heart disease (CHD). DESIGN A systematic review and meta-analysis were used as study designs. DATA SOURCES Articles were identified by searching Ovid MEDLINE, PsycINFO, Scopus, Cochrane Library, PILOTS database, and PubMed Related Articles and through a manual search of reference lists (1948-present). STUDY SELECTION All studies that assessed PTSD in participants initially free of CHD and subsequently assessed CHD/cardiac-specific mortality were included. DATA EXTRACTION Two investigators independently extracted estimates of the association of PTSD with CHD, as well as study characteristics. Odds ratios were converted to hazard ratios (HRs), and a random-effects model was used to pool results. A secondary analysis including only studies that reported estimates adjusted for depression was conducted. RESULTS Six studies met our inclusion criteria (N = 402,274); 5 of these included depression as a covariate. The pooled HR for the magnitude of the relationship between PTSD and CHD was 1.55 (95% CI 1.34-1.79) before adjustment for depression. The pooled HR estimate for the 5 depression-adjusted estimates (N = 362,950) was 1.27 (95% CI 1.08-1.49). CONCLUSION Posttraumatic stress disorder is independently associated with increased risk for incident CHD, even after adjusting for depression and other covariates. It is common in both military veterans and civilian trauma survivors, and these results suggest that it may be a modifiable risk factor for CHD. Future research should identify the mechanisms of this association and determine whether PTSD treatment offsets CHD risk.

Visit-to-Visit Variability of Blood Pressure and Cardiovascular Disease and All-Cause Mortality A Systematic Review and Meta-Analysis

Visit-to-visit variability of blood pressure (BP) has been associated with cardiovascular disease (CVD) and mortality in some but not all studies. We conducted a systematic review and meta-analysis to examine the association between visit-to-visit variability of BP and CVD and all-cause mortality. Medical databases were searched through June 4, 2014, for studies meeting the following eligibility criteria: adult participants; BP measurements at ≥3 visits; follow-up for CVD, coronary heart disease, stroke, or mortality outcomes; events confirmed via database, death certificate, or event ascertainment committee; and adjustment for confounders. Data were extracted by 2 reviewers and pooled using a random-effects model. Overall, 8870 abstracts were identified of which 37 studies, representing 41 separate cohorts, met inclusion criteria. Across studies, visit-to-visit variability of systolic BP and diastolic BP showed significant associations with outcomes in 181 of 312 (58.0%) and 61 of 188 (32.4%) analyses, respectively. Few studies provided sufficient data for pooling risk estimates. For each 5 mm Hg higher SD of systolic BP, the pooled hazard ratio for stroke across 7 cohorts was 1.17 (95% confidence interval [CI], 1.07–1.28), for coronary heart disease across 4 cohorts was 1.27 (95% CI, 1.07–1.51), for CVD across 5 cohorts was 1.12 (95% CI, 0.98–1.28), for CVD mortality across 5 cohorts was 1.22 (95% CI, 1.09–1.35), and for all-cause mortality across 4 cohorts was 1.20 (95% CI, 1.05–1.36). In summary, modest associations between visit-to-visit variability of BP and CVD and all-cause mortality are present in published studies. However, these findings are limited by the small amount of data available for meta-analysis.

Meta-Analysis Impact of Drug Class on Adherence to Antihypertensives

Background— Observational studies suggest that there are differences in adherence to antihypertensive medications in different classes. Our objective was to quantify the association between antihypertensive drug class and adherence in clinical settings. Methods and Results— Studies were identified through a systematic search of English-language articles published from the inception of computerized databases until February 1, 2009. Studies were included if they measured adherence to antihypertensives using medication refill data and contained sufficient data to calculate a measure of relative risk of adherence and its variance. An inverse-variance–weighted random-effects model was used to pool results. Hazard ratios (HRs) and odds ratios were pooled separately, and HRs were selected as the primary outcome. Seventeen studies met inclusion criteria. The pooled mean adherence by drug class ranged from 28% for &bgr;-blockers to 65% for angiotensin II receptor blockers. There was better adherence to angiotensin II receptor blockers compared with angiotensin-converting enzyme inhibitors (HR, 1.33; 95% confidence interval, 1.13 to 1.57), calcium channel blockers (HR, 1.57; 95% confidence interval, 1.38 to 1.79), diuretics (HR, 1.95; 95% confidence interval, 1.73 to 2.20), and &bgr;-blockers (HR, 2.09; 95% confidence interval, 1.14 to 3.85). Conversely, there was lower adherence to diuretics compared with the other drug classes. The same pattern was present when studies that used odds ratios were pooled. After publication bias was accounted for, there were no longer significant differences in adherence between angiotensin II receptor blockers and angiotensin-converting enzyme inhibitors or between diuretics and &bgr;-blockers. Conclusion— In clinical settings, there are important differences in adherence to antihypertensives in separate classes, with lowest adherence to diuretics and &bgr;-blockers and highest adherence to angiotensin II receptor blockers and angiotensin-converting enzyme inhibitors. However, adherence was suboptimal regardless of drug class.Background— Observational studies suggest that there are differences in adherence to antihypertensive medications in different classes. Our objective was to quantify the association between antihypertensive drug class and adherence in clinical settings. Methods and Results— Studies were identified through a systematic search of English-language articles published from the inception of computerized databases until February 1, 2009. Studies were included if they measured adherence to antihypertensives using medication refill data and contained sufficient data to calculate a measure of relative risk of adherence and its variance. An inverse-variance–weighted random-effects model was used to pool results. Hazard ratios (HRs) and odds ratios were pooled separately, and HRs were selected as the primary outcome. Seventeen studies met inclusion criteria. The pooled mean adherence by drug class ranged from 28% for β-blockers to 65% for angiotensin II receptor blockers. There was better adherence to angiotensin II receptor blockers compared with angiotensin-converting enzyme inhibitors (HR, 1.33; 95% confidence interval, 1.13 to 1.57), calcium channel blockers (HR, 1.57; 95% confidence interval, 1.38 to 1.79), diuretics (HR, 1.95; 95% confidence interval, 1.73 to 2.20), and β-blockers (HR, 2.09; 95% confidence interval, 1.14 to 3.85). Conversely, there was lower adherence to diuretics compared with the other drug classes. The same pattern was present when studies that used odds ratios were pooled. After publication bias was accounted for, there were no longer significant differences in adherence between angiotensin II receptor blockers and angiotensin-converting enzyme inhibitors or between diuretics and β-blockers. Conclusion— In clinical settings, there are important differences in adherence to antihypertensives in separate classes, with lowest adherence to diuretics and β-blockers and highest adherence to angiotensin II receptor blockers and angiotensin-converting enzyme inhibitors. However, adherence was suboptimal regardless of drug class. # Clinical Perspective {#article-title-43}

Vitamin D Supplementation for Depressive Symptoms: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Objective The aim of this study was to review the effects of vitamin D supplementation on depressive symptoms in randomized controlled trials. Although low vitamin D levels have been observationally associated with depressive symptoms, the effect of vitamin D supplementation as an antidepressant remains uncertain. Methods MEDLINE, CINAHL, AMED, PsycINFO, Scopus, The Cochrane Library, and references of included reports (through May 2013) were searched. Two independent reviewers identified and extracted data from randomized trials that compared the effect of vitamin D supplementation on depressive symptoms to a control condition. Two additional reviewers assessed study quality using The Cochrane Risk of Bias Tool. Seven trials (3191 participants) were included. Results Vitamin D supplementation had no overall effect on depressive symptoms (standardized mean difference [SMD], 0.14; 95% confidence interval [CI], −0.33 to 0.05, p = .16), although considerable heterogeneity was observed. Subgroup analysis showed that vitamin D supplementation for participants with clinically significant depressive symptoms or depressive disorder had a moderate, statistically significant effect (2 studies: SMD, −0.60; 95% CI, −1.19 to −0.01; p = .046), but a small, nonsignificant effect for those without clinically significant depression (5 studies: SMD, −0.04; 95% CI, −0.20 to 0.12; p = .61). Most trials had unclear or high risk of bias. Studies varied in the amount, frequency, duration, and mode of delivery of vitamin D supplementation. Conclusions Vitamin D supplementation may be effective for reducing depressive symptoms in patients with clinically significant depression; however, further high-quality research is needed.

Diagnostic Accuracy of Noncontrast Computed Tomography for Appendicitis in Adults: A Systematic Review

STUDY OBJECTIVE We seek to determine the diagnostic test characteristics of noncontrast computed tomography (CT) for appendicitis in the adult emergency department (ED) population. METHODS We conducted a search of MEDLINE, EMBASE, the Cochrane Library, and the bibliographies of previous systematic reviews. Included studies assessed the diagnostic accuracy of noncontrast CT for acute appendicitis in adults by using the final diagnosis at surgery or follow-up at a minimum of 2 weeks as the reference standard. Studies were included only if the CT was completed using a multislice helical scanner. Two authors independently conducted the relevance screen of titles and abstracts, selected studies for the final inclusion, extracted data, and assessed study quality. Consensus was reached by conference, and any disagreements were adjudicated by a third reviewer. Unenhanced CT test performance was assessed with summary receiver operating characteristic curve analysis, with independently pooled sensitivity and specificity values across studies. RESULTS The search yielded 1,258 publications; 7 studies met the inclusion criteria and provided a sample of 1,060 patients. The included studies were of high methodological quality with respect to appropriate patient spectrum and reference standard. Our pooled estimates for sensitivity and specificity were 92.7% (95% confidence interval 89.5% to 95.0%) and 96.1% (95% confidence interval 94.2% to 97.5%), respectively; the positive likelihood ratio=24 and the negative likelihood ratio=0.08. CONCLUSION We found the diagnostic accuracy of noncontrast CT for the diagnosis of acute appendicitis in the adult population to be adequate for clinical decisionmaking in the ED setting.

Role of Ambulatory and Home Blood Pressure Monitoring in Clinical Practice: A Narrative Review

Key Summary Points Ambulatory blood pressure monitoring (ABPM) assesses blood pressure during routine daily activities (typically during one 24-hour period), whereas home blood pressure monitoring (HBPM) assesses blood pressure at specific times during the day and night over a longer period while the patient is seated and resting. Blood pressure measures on ABPM and HBPM have a stronger association with cardiovascular disease outcomes than clinic blood pressure. ABPM and HBPM can quantify mean out-of-clinic blood pressure and can be used to identify white coat hypertension, masked hypertension, blood pressure variability, and hypotension. ABPM can also assess nighttime blood pressure and diurnal blood pressure patterns. Most guidelines, scientific statements, and position papers recommend that blood pressure monitoring outside of the clinic primarily be done using ABPM to rule out white coat hypertension in persons with elevated clinic blood pressure. HBPM is recommended if ABPM is not available or is poorly tolerated by the patient. Barriers have limited the implementation of ABPM and HBPM in clinical practice. Core competency requirements may be essential for successful ABPM and HBPM. There is a need for randomized, controlled trials to test whether treating blood pressure determined by ABPM or HBPM is more advantageous than treating clinic blood pressure on cardiovascular disease outcomes. Guidelines and scientific statements recommend measuring blood pressure in the clinic setting (1, 2). However, blood pressure measured in the clinic may not accurately reflect levels in the out-of-clinic naturalistic setting (3). Ambulatory blood pressure monitoring (ABPM) and home blood pressure monitoring (HBPM) are 2 well-accepted approaches for measuring blood pressure outside of the clinic (4, 5). The utility of these methods in guiding patient care has been widely debated (6, 7), and there is controversy about which is better for determining blood pressure outside of the clinic. This review describes ABPM and HBPM procedures, the blood pressure measures that can be obtained by using these methods, and the current evidence base supporting the use of ABPM and HBPM in clinical practice; barriers and clinical competencies that are required for the successful implementation of ABPM and HBPM in practice; and areas of future research. Methods We searched MEDLINE through July 2015 using the following key words: ambulatory blood pressure, home blood pressure, out of office blood pressure, self-measured blood pressure, and self-measurement of blood pressure. We focused on studies that had prospective follow-up for cardiovascular disease (CVD) events or mortality; systematic reviews, meta-analyses, and narrative reviews; and hypertension guidelines, scientific statements, and position papers. A search of PubMed for related articles and a cited reference search through ISI Web of Science were done using identified articles. We also manually searched the reference lists from identified reviews. This study was funded by the National Heart, Lung, and Blood Institute. The funding source had no role in the study design, collection, analysis, interpretation, or drafting of the manuscript or in the decision to submit the manuscript for publication. Fundamentals of ABPM and HBPM Overview of ABPM In the 1960s, a manually inflated device was introduced that could take blood pressure readings on an ambulatory basis throughout the day (8). Ambulatory monitors are now fully automated, use the oscillometric technique to estimate blood pressure, and are typically used to obtain blood pressure readings for 24 hours (3). Ambulatory monitors are compact, are typically worn on a belt or in a pouch, and are connected to a sphygmomanometer cuff on the upper arm by a tube. The monitors are usually programmed to obtain readings every 15 to 30 minutes throughout the day and night and set so the readings are not displayed to the patient. Although persons go about their normal daily activities during ABPM, they are asked to keep their arm still while the cuff is inflating and to avoid excessive motion, which is associated with unobtainable or artifactual readings. At the end of the recording period, the readings are downloaded into a computer for processing. Persons can fill out a diary during the monitoring period to document any symptoms, awakening and sleeping times, naps, periods of stress, timing of meals, and medication ingestion (4). Various criteria can be used to determine whether a 24-hour ABPM session is valid, such as requiring that a minimum of 70% or 80% of the planned readings are obtained (4, 9), at least 14 readings are obtained during the daytime period (10), or at least 10 readings are obtained during the daytime period and at least 5 during the nighttime period (11). None of these criteria is considered to be a gold standard. The daytime and nighttime periods on ABPM can be determined by using the patients self-report of awakening and sleeping (4), fixed periods (4), and actigraphy (12). Herein, the terms daytime and nighttime (or nocturnal) are used interchangeably with awake and sleep, respectively. The Figure (top) shows blood pressure readings obtained from a person in the clinic followed by 24-hour ABPM. Figure. Blood pressure data from an untreated healthy person who had clinic blood pressure assessment followed by 24-h ABPM (top ) and then HBPM (bottom). ABPM = ambulatory blood pressure monitoring; DBP = diastolic blood pressure; HBPM = home blood pressure monitoring; SBP = systolic blood pressure. Top. Clinic blood pressure assessment immediately followed by 24-h ABPM. The points for clinic blood pressure represent the average of 3 readings. On ABPM, blood pressure decreases to its lowest level during the night, followed by a surge in the morning hours coinciding with waking up. Average clinic blood pressure was 118/66 mm Hg, and average awake, sleep, and 24-h blood pressure was 129/86 mm Hg, 103/62 mm Hg, and 118/78 mm Hg, respectively. Bottom. After the 24-h ABPM assessment, HBPM was then done for 18 d. The points represent the average of 2 morning or 2 evening readings. Because blood pressure readings on HBPM are obtained at fixed times during the day and are measured at rest, the variability of blood pressure over time is less than what is seen on ABPM. Unlike ABPM, HBPM cannot measure blood pressure readings during sleep. Average home blood pressure was 116/79 mm Hg. Overview of HBPM Home blood pressure was initially measured with the auscultatory technique by an observer (13). Most current HBPM devices are automatic, use the oscillometric technique, and are initiated by the patient. Some devices have the ability to store readings for several weeks, which minimizes the need for patients to record the measurements. Devices for HBPM, which measure blood pressure in the brachial artery, are more reliable than other types of devices, such as wrist monitors (13). Home blood pressure monitoring should be done in a quiet room after 5 minutes of rest in the seated position, with the back and arm supported. A common recommendation for HBPM (2, 5, 14) is that blood pressure be measured by the patient 2 times in the morning and 2 times in the evening. A minimum of 3 consecutive days and a preferred period of 7 consecutive days of HBPM is a reasonable approach for clinical practice (2, 5, 14). For assessment of mean blood pressure, readings obtained on the first day of HBPM are excluded and all subsequent readings are averaged (2, 5, 14). The Figure shows blood pressure readings in the same person from ABPM (top) followed by HBPM (bottom). Validated Devices Only validated devices are recommended for ABPM and HBPM. Validation protocols from the following 3 organizations are widely accepted: the Association for the Advancement of Medical Instrumentation (15), British Hypertension Society (16), and European Society of Hypertension (17). The 2010 European Society of Hypertension International Protocol (17) is the most commonly used. An up-to-date list of validated ambulatory and home blood pressure monitors is available on the dabl Educational Trust Web site (www.dableducational.org) (18) and the British Hypertension Society Web site (www.bhsoc.org/bp-monitors/bp-monitors) (19). Similarities and Differences in ABPM and HBPM More measurements are typically obtained with ABPM and HBPM than in the clinic setting. Ambulatory blood pressure monitoring and HBPM can assess average blood pressure outside of the clinic setting, which allows for the identification of white coat hypertension (20, 21) and masked hypertension (2224); blood pressure variability on ABPM (25) and HBPM (26); and hypotension (2, 4). Because ABPM and HBPM devices use the oscillometric technique, which assesses the amplitude of pressure oscillations during cuff deflation to estimate blood pressure, accurate measurements can be affected by movement (27). The ability to obtain accurate readings is also limited by larger upper arm circumference, arterial stiffness, and variability in heart rate (such as atrial fibrillation) (27). Because ABPM and HBPM devices inflate the blood pressure cuff above estimated systolic blood pressure followed by deflation, persons with severe hypertension may have discomfort or pain with repeated measurements. The main difference between ABPM and HBPM is that ABPM assesses daytime and nighttime blood pressure during routine daily activities (typically during one 24-hour period), whereas HBPM assesses blood pressure at specific times during the day and night over a longer period while the patient is seated and resting. For almost all HBPM devices, blood pressure readings cannot be obtained during sleep. Clinical Significance Elevated Blood Pressure on ABPM and HBPM Many studies have reported associations of average out-of-clinic blood pressure measured by ABPM, including average 24-hour blood pressure; daytime and nighttime blood pressure; and,