Circulation 2010 Pladevall 1183 91

Hypertension

Multicenter Cluster-Randomized Trial of a MultifactorialIntervention to Improve Antihypertensive Medication

Adherence and Blood Pressure Control Among Patients atHigh Cardiovascular Risk (The COM99 Study)

Manel Pladevall, MD, MS; Carlos Brotons, MD, PhD; Rafael Gabriel, MD, MPH; Anna Arnau, PhD;Carmen Suarez, MD, PhD; Mariano de la Figuera, MD; Emilio Marquez, MD;

Antonio Coca, MD, PhD; Javier Sobrino, MD, PhD; George Divine, PhD; Michele Heisler, MD, MPA;L. Keoki Williams, MD, MPH; Writing Committee on behalf of the COM99 Study Group*

Background—Medication nonadherence is common and results in preventable disease complications. This study assessedthe effectiveness of a multifactorial intervention to improve both medication adherence and blood pressure control andto reduce cardiovascular events.

Methods and Results—In this multicenter, cluster-randomized trial, physicians from hospital-based hypertension clinicsand primary care centers across Spain were randomized to receive and provide the intervention to their high-riskpatients. Eligible patients were �50 years of age, had uncontrolled hypertension, and had an estimated 10-yearcardiovascular risk greater than 30%. Physicians randomized to the intervention group counted patients’ pills,designated a family member to support adherence behavior, and provided educational information to patients. Theprimary outcome was blood pressure control at 6 months. Secondary outcomes included both medication adherence anda composite end point of all-cause mortality and cardiovascular-related hospitalizations. Seventy-nine physicians and877 patients participated in the trial. The mean duration of follow-up was 39 months. Intervention patients were lesslikely to have an uncontrolled systolic blood pressure (odds ratio 0.62, 95% confidence interval 0.50 to 0.78) and weremore likely to be adherent (odds ratio 1.91, 95% confidence interval 1.19 to 3.05) than control group patients at 6months. After 5 years, 16% of the patients in the intervention group and 19% in the control group met the compositeend point (hazard ratio 0.97, 95% confidence interval 0.67 to 1.39).

Conclusions—A multifactorial intervention to improve adherence to antihypertensive medication was effective inimproving both adherence and blood pressure control, but it did not appear to improve long-term cardiovascular events.

Clinical Trial Registration—URL: http://www.controlled-trials.com. Unique identifier: ISRCTN35208258.(Circulation. 2010;122:1183-1191.)

Key Words: hypertension � medication adherence � blood pressure � intervention studies

Hypertension is a major but modifiable contributoryfactor to cardiovascular diseases such as stroke and

coronary heart disease.1,2 According to the Seventh Reportof the Joint National Committee on Prevention, Detection,

and Treatment of High Blood Pressure in the UnitedStates, the percentage of patients whose blood pressure(BP) is under control (ie, �140/90 mm Hg) increased from10% in 1976 –1980 to 34% in the period 1999 –2000.

Continuing medical education (CME) credit is available for this article. Go to http://cme.ahajournals.org to take the quiz.Received October 30, 2009; accepted July 14, 2010.From the Center for Health Services Research (M.P., L.K.W.), Department of Internal Medicine (L.K.W.), and Department of Biostatistics and

Research Epidemiology (G.D.), Henry Ford Hospital, Detroit, Mich; Equip d’Atencio Primaria de Vic (M.P.), Vic (Barcelona), Spain; Research Unit(C.B., M.d.l.F.), EAP Sardenya, Institute of Biomedical Research (IIB Sant Pau) (C.B.), Barcelona, Spain; Unidad de Investigacion-Epidemiologıa Clınica(R.G.), Red Cooperativa de Investigacion de Enfermedades Cardiovasculares, RECAVA del Instituto de Salud Carlos III (RD06 0014/0015), InstitutoIdiPAZ, Hospital Universitario La Paz, Madrid, Spain; Fundacio Althaia Xarxa Assitencial de Manresa (A.A.), Manresa, Barcelona, Spain; Servicio deMedicina Interna (C.S.), Hospital Universitario de la Princesa, Madrid, Spain; La Orden Health Care (E.M.), Huelva, Spain (Compliance GroupCoordinator, Spanish Society of Hypertension); Unidad de Hipertension (A.C.), Servicio de Medicina Interna General, Instituto de Medicina yDermatologıa, Hospital Clınic (IDIBAPS), Barcelona, Spain; Universidad de Barcelona (A.C., J.S.), Barcelona, Spain; Fundacio Hospital de l’Esperit Sant(J.S.), Santa Coloma de Gramanet, Spain; and the Veterans Affairs Center for Practice Management and Outcomes Research (M.H.), VA Ann ArborHealth System (M.H.), Department of Internal Medicine, University of Michigan (M.H.), and Michigan Diabetes Research and Training Center (M.H.),Ann Arbor, Mich.

*See the appendix in the online-only Data Supplement for a complete list of investigators.The online-only Data Supplement is available with this article at http://circ.ahajournals.org/cgi/content/full/CIRCULATIONAHA.109.892778/DC1.Correspondence to Manel Pladevall, Center for Health Services Research, Henry Ford Hospital, One Ford Place, 3A, Detroit, MI. E-mail

[email protected]© 2010 American Heart Association, Inc.

Circulation is available at http://circ.ahajournals.org DOI: 10.1161/CIRCULATIONAHA.109.892778

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Nevertheless, BP control rates are far below the HealthyPeople 2000 goal of 50%.3–5 The situation in Spain issimilar, with at best 40% of patients with hypertensionunder control.3,6

Editorial see p 1141Clinical Perspective on p 1191

A major modifiable reason for the lack of BP control ismedication nonadherence, where adherence is defined as theextent to which a person’s behavior corresponds with therecommendations of their healthcare provider.7 In general,poor adherence to medications is associated with the develop-ment of complications, disease progression, avoidable hospital-izations, premature disability, and death.7–10 The same is true foradherence to antihypertensive medications.11,12

Most previous adherence intervention studies share the fol-lowing methodological limitations: A lack of patient-centeredoutcomes; limited statistical power; short duration of follow-up;unreliable measures of adherence; and limited generalizabilitydue to their intensity and complexity.13,14 The objective of thepresent study was to assess the effectiveness of a simple,multifactorial intervention aimed at increasing antihypertensivemedication adherence, improving BP control, and reducingcardiovascular events in high-risk patients with uncontrolledhypertension. The intervention was designed to be implementedin resource-poor settings, and it combined behavioral, cognitive,and social support components. The behavioral componentincluded counting pills in front of the patients. Counting pills bydoctors is a routine activity in most clinical trials, and patientstend to adhere better in clinical trials than in routine clinicalpractice.15,16 On the basis of prior research, we hypothesized thatthis Hawthorne effect could be used to improve medicationadherence in routine practice.15,17 In the present study, adherencewas monitored electronically, and study participants were fol-lowed up for up to 5 years. A cluster-randomized design thatrandomized physicians was chosen to avoid within-physiciancontamination.

MethodsStudy DesignThe study was approved by the ethics committees of the HospitalGeneral de Vic (Barcelona, Spain) and Hospital de la Princesa(Madrid, Spain). In this multicenter cluster-randomized trial, partic-ipating physicians from hospital-based hypertension clinics andprimary care centers across Spain were randomized in blocks of 2within their site of practice. Block randomization was used to ensurethat physicians were balanced across intervention and control groupswithin hospitals and primary care clinics. Randomization was cen-tralized through a single coordinating center, and the sequence wasconcealed until interventions were assigned. A computer-generatedrandom-number list was used to randomize physicians, and investi-gators were not aware of the randomization scheme. The trial wasactively monitored by both internal and external quality controlauditors.

ParticipantsPatients were �50 years of age; they had uncontrolled essentialhypertension, as defined by an average systolic BP (SBP)�140 mm Hg and/or an average diastolic BP (DBP) �90 mm Hg;and they had a calculated 10-year cardiovascular risk �30%, asdefined by the World Health Organization/International Society of

Hypertension 1999 guidelines.18 There were only 2 exclusion crite-ria: Participation in another clinical trial in the preceding 3 monthsand refusal/incapacity to provide informed consent. There were 2coordinating centers (in Catalonia and Madrid, Spain), which sepa-rately recruited physicians. Patients were recruited by their physi-cians after assessment for eligibility. The coordinating center inCatalonia was also in charge of randomization, the validation ofpatients’ eligibility criteria, the provision and analysis of the MedicalEvents Monitoring Systems (MEMS) containers (Aardex Ltd, Zug,Switzerland), the provision and calibration of semiautomatic sphyg-momanometers, data entry, and study quality control. Patients wererecruited between January 2000 and July 2002 and were followed upuntil December 2005.

We administered a survey to all study physicians to assess theircharacteristics across intervention and control groups. Sixty-nine(87%) of 79 physicians who actively recruited patients responded tothe survey. Characteristics of recruiting physicians are depicted inTable 1. There were no differences in the survey response ratebetween control and intervention groups.

Study InterventionPatients in the control group received standard care, but theyfollowed the same schedule of visits as the intervention group.Patients in both groups had 2 baseline visits 1 week apart and beforestudy initiation to ensure that they met study criteria. These baselinevisits were followed by a study initiation visit in the same month,during which patients in both groups received their MEMS devices;this visit constituted the beginning of the study. Follow-up visitsoccurred at 1, 3, and 6 months after study initiation and every 6months thereafter. Medication changes were not allowed in eithergroup until the 3-month follow-up visit unless there was interveningsevere hypertension. The intervention to improve adherence in thetreatment group lasted 6 months and consisted of 3 main compo-nents: (1) The counting of pills during physician visits, (2) designa-tion of a family member to support adherence behavior, and (3)provision of an information sheet to patients at the start of theintervention. Patients were supposed to bring back the informationsheet at each follow-up visit. If they did not, they were provided anew sheet at the start of the follow-up visit.

The information sheet included information on each BP medicationdose and frequency, potential medication side effects, what to do if adose was missed, what to do when the medication was running low, andhow different types of antihypertensive medication could be takentogether. It also included 2 questions for the patient to complete beforeeach visit: One question on any problems taking the medication sincethe last visit and the other question on whether the patient experiencedany side effects. Space was provided on the information sheet forpatients to record BP readings, including self-measurements, and theircurrent antihypertensive regimen. Patients were encouraged to measuretheir BP every other week,19 and they were given calendars to mark theday that they took their medication. All intervention physicians under-went an initial 2-hour session on motivational interviewing techniquesto promote patient adherence.20 Physicians were advised to avoidconfrontation and to respect patients’ autonomy. Case vignettes repre-senting confrontational and motivational interviewing scenarios wereused during the training.

Outcome MeasuresThe primary outcome was SBP and DBP control at the end of thefirst 6 months of follow-up. Medication adherence over 6 months offollow-up was the secondary outcome. As an additional exploratoryoutcome, we included a composite end point of all-cause mortalityand admission to a hospital for any cardiovascular event at 5 years offollow-up. The end points were defined identically to those in theValsartan Antihypertensive Long-term Use Evaluation (VALUE)trial.21 The end points were adjudicated by a clinical events com-mittee that was blinded to the patients’ treatment group.

Three BP readings were obtained at each visit with a semiauto-matic oscillometric BP monitor (Omron 705-CP, Omron Healthcare

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Group, Kyoto, Japan) that could print the readings. Each reading wasprinted and attached to the data collection instruments. The averageof the 3 readings was used in the analysis.

Adherence was measured electronically with MEMS bottles (Aar-dex Ltd, Zug, Switzerland) during the first 6 months of follow-up.Patients were informed of the MEMS functionality. Because of costlimitations, only 1 MEMS bottle was provided per patient, andfixed-dose combination antihypertensive medications were encour-aged when a patient required more than 1 BP medication. Therefore,when a patient was taking a fixed-dose combination antihypertensivemedication, that was the one introduced in the MEMS bottle. If thepatient was not using combination medications, the drug the patienthad been taking for the longest period of time was the one monitoredelectronically. The average number of antihypertensive drugs used was2.2 (SD 1.0), and the average number of drugs monitored electron-ically was 1.3 (SD 0.4). Accordingly, the average percentage ofantihypertensive drugs monitored electronically per patient was 67%of those taken. For the medications monitored, we defined adherenceas the percentage of days on which the correct number of doses wastaken. Two additional adherence measures were assessed: Medication-taking adherence and medication-timing adherence. Medication-takingadherence was defined as the percentage of prescribed doses taken,whereas medication-timing adherence was the percentage of prescribeddoses taken on time. We allowed a 12-hour window for medicationtaken once daily and a 6-hour window for medications taken twice daily.

Statistical AnalysisSample size estimates accounted for the cluster-randomized design.Because of low initial enrollment, sample size estimates had to bedownwardly adjusted from a cluster size of 25 patients per physician

to 11 patients per physician. With the assumption of an intraclasscorrelation coefficient of 0.05 and 12% of patients lost to follow-up,an enrolled sample size of 900 patients (ie, 450 per arm) equated to aneffective sample size of 264 patients per arm. Therefore, with 264patients per arm and a type I error of 0.05, we estimated 80% power todetect a 3.9-mm Hg change in SBP and a 2.7-mm Hg change in DBP.

Continuous baseline variables were compared with either a2-sample t test or the Wilcoxon test. Categorical variables werecompared with a �2 test.

Outcomes were analyzed on an intention-to-treat basis. Mean BP wasanalyzed with generalized estimating equation repeated-measuresANOVA. The generalized estimating equation clusters were defined bymultiple patients sharing the same physician and the repeated measures(up to 3, ie, for the 1, 3, and 6-month visits) for each patient. Becausethe distribution of adherence measures appeared to be exponential,generalized estimating equation gamma and logistic regression modelswere used to analyze the continuous and binary measures of medicationadherence, respectively. Nonadherence was defined as measured adher-ence �80%. This cutoff is widely used and has been shown to beassociated with hypertensive clinical outcomes.22 The composite car-diovascular outcome was analyzed as time to event with Kaplan–Meierestimation and Cox proportional hazards regression models. Physicianclusters were accounted for with the COVSANDWICH (AGGRE-GATE) option in Proc PHREG in SAS version 9.1 (SAS Institute Inc,Cary, NC).23 Statistical analyses were performed by an independentgroup blinded to group assignment. A 2-sided �-level of 0.05 wasconsidered statistically significant.

ResultsBetween January 2000 and July 2002, 147 physicians wererecruited and randomized to the control and intervention

Table 1. Distribution of Physician-Related Characteristics in Control and Intervention Groups

Variable

Control Group(n�39; 36 Physicians

With Survey Data)

Intervention Group(n�40; 33 Physicians

With Survey Data) P

Variables with data available for all 79 analyzed physicians

Physicians under the coordination of the Catalancoordinating center

21/39 (53.8) 22/40 (55.0) 0.918

Female sex 18/39 (46.2) 15/40 (37.5) 0.498

Working place

Hospital 12/39 (30.8) 13/40 (32.5)

Primary care center 27/39 (69.2) 27/40 (67.5) 0.869

Average No. of patients per physician 11.8�8.3 [39] 10.6�7.9 [40] 0.529

Variables with data available only for the 69 physicianswho completed the survey*

MD degree year 1982.9�5.3 [35] 1982.8�6.4 [33] 0.834

Age, y 43.1�5.2 [35] 43.6�6.5 [33] 0.749

Employment in a teaching center 21/36 (58.3) 20/33 (60.6) 0.848

Previous participation in clinical trials 28/35 (80) 25/33 (75.8) 0.773

Specialty

Internal medicine 6/34 (17.6) 7/33 (21.2)

Family medicine 22/34 (64.7) 19/33 (57.6)

Nephrology 6/34 (17.6) 7/33 (21.2) 0.836

Practice size (No. of patients) in primary care centers 1629.8�490.3 [24] 1745.5�493.3 [22] 0.930

Hours per week with direct contact with patients 28.6�8.5 [35] 27.4�9.0 [31] 0.649

Average visit time in primary care centers, min 7.5�3.2 7.0�2.2 0.755

Average time for follow-up visits in hospital, min 15.0�4.4 16.25�5.3 0.722

Full-time employment in the health center 27/36 (75.0) 23/33 (69.7) 0.788

Numbers are mean�SD [N] or n (%).*Of 79 physicians who actively recruited patients, 69 (87%) completed the survey.

Pladevall et al Clinical Trial to Improve Adherence and BP 1185



groups (Figure 1). Fifty-four physicians (24 in the controlarm and 30 in the intervention arm) withdrew beforerecruiting any patients. Fourteen physicians (11 in thecontrol arm and 3 in the intervention arm) withdrew studyconsent before their 40 patients began follow-up. Twelvepatients (5 in the control arm and 7 in the intervention arm)were excluded because of protocol violations. Eight pa-tients (3 in the control arm and 5 in the intervention arm)did not have follow-up data. Therefore, 79 physicians (39in the control arm and 40 in the intervention arm) and 875of their patients (457 in the control arm and 418 in theintervention arm) were available for complete analysis.Among those, MEMS data were not available for 78patients (8.9%) for different reasons (14 devices were lost,2 patients never used the MEMS, 4 MEMS were defective,and 58 MEMS were not returned by the patient or theinvestigator). There were no statistically significant differ-ences in the distribution of those patients between theintervention and the control group.

Tables 1 and 2 show the characteristics of physiciansand patients, respectively, in the control and interventiongroups. All characteristics were similar with the exception

that baseline DBP, heart rate, and self-reported medicationnonadherence were significantly higher among patients inthe intervention group than among control group patients.

The mean duration of patient follow-up was 39 months,and 67% of the patients had at least 36 months of follow-up.The intraclass correlation coefficients for the outcomes ofinterest were as follows: 0.197 for SBP, 0.194 for DBP, 0.107for adherence, and 0.063 for combined cardiovascular events.Table 3 shows the study results for BP and adherenceoutcomes in the first 6 months of follow-up. At 6 months,intervention patients had significantly lower mean SBP(148.9 versus 151.1 mm Hg, P�0.008) and lower mean DBP(81.9 mm Hg versus 83.0 mm Hg, P�0.013) than controlpatients. Moreover, intervention patients were less likely tohave an uncontrolled SBP (ie, �140 mm Hg) than controlpatients (odds ratio 0.62, 95% confidence interval [CI] 0.50 to0.78). On the other hand, intervention patients were not lesslikely to have an uncontrolled DBP (ie, �90 mm Hg) thancontrol patients (odds ratio 0.94, 95% CI 0.73 to 1.20).Differences of �2 mm Hg in SBP between groups persistedover the 5 years of follow-up, whereas differences in DBPbetween groups were �1 mm Hg after 18 months of

Figure 1. Flow of patients and physi-cians during recruitment and the first 6months of follow-up. *Patients alsoincluded in Table 1 (baselinecharacteristics).




follow-up (Figure 2). Only a few of the SBP differences afterthe 6-month visit were statistically significant.

Patients in the intervention group also appeared to be moreadherent over the 6 months of the intervention, because theytook their correct dose on a greater proportion of days thanpatients in the control group (92.2% versus 89.0%, respec-tively; P�0.002) and were more likely to be at least 80%adherent (odds ratio 1.91, 95% CI 1.19 to 3.05; Table 3). For

the other adherence measures, intervention patients were alsomore likely to achieve an adherence value of �80% over the6-month period. Expanded Tables I, II, and III and additionaldescriptions of the methods used in the present study areavailable in the online-only Data Supplement.

During the study, it was discovered that the MEMS chips of45 containers malfunctioned at least once in the study, whichresulted in inflated measurements of between 4 to 8 uses per day.

Table 2. Distribution of Patient-Related Characteristics in Control and Intervention Groups

VariableControl Group

(n�460)Intervention Group

(n�423) P

Geographic area 0.943

Madrid coordinating center 154 (33) 140 (33)

Barcelona coordinating center 306 (67) 283 (67)

Baseline SBP, mm Hg 160.8�15.0 [460] 162.1�16.3 [423] 0.222

Baseline DBP, mm Hg 86.1�9.8 [460] 88.6�11.1 [423] �0.001

Baseline heart rate, bpm 74.3�12.0 [459] 76.2�11.6 [421] 0.016

Baseline SBP �140 mm Hg 441/460 (96) 398/423 (94) 0.228

Baseline DBP �90 mm Hg 146/460 (32) 193/423 (46) �0.001

Severe hypertension 90/460 (20) 103/423 (24) 0.086

Age, y 66.8�8.6 [459] 66.3�8.1 [422] 0.391

Male sex 237/460 (52) 199/422 (47) 0.195

Body mass index �30 kg/m2 221/456 (48) 220/422 (52) 0.277

Current smoker 62/458 (14) 62/422 (15) 0.623

History of smoking 122/375 (32) 104/339 (31) 0.553

Hypertension duration, y 10.5�8.7 [460] 11.0�9.3 [420] 0.454

No. of antihypertensive drugs at baseline 2.24�1.10 [460] 2.20�1.06 [423] 0.670

No. of antihypertensive drugs grouped

0 2 (0.4) 2 (0.5)

1 137 (29.8) 125 (29.6)

2 147 (32.0) 138 (32.6)

3–4 164 (35.7) 150 (35.5)

�4 10 (2.2) 8 (1.9) 0.998

No. of drugs for which adherence was monitored with MEMS 1.24�0.43 [458] 1.28�0.45 [420] 0.196

Patients with combinations of 2 drugs for which adherencewas monitored with MEMS

109/458 (23.8) 116/420 (27.6) 0.195

Percentage of total No. of drugs monitored with MEMS 66.2�29.4 [457] 67.9�28.7 [420] 0.295

No. of risk factors 1.9�1.2 [460] 1.8�1.1 [423] 0.769

Left ventricular hypertrophy 128/460 (28) 120/422 (28) 0.840

Consumption of alcohol, g 40.4�117.3 [460] 35.2�86.6 [422] 0.447

Diabetes mellitus 289/460 (63) 266/422 (63) 0.949

Severe hypertensive retinopathy (III–IV) 12/460 (3) 11/422 (3) 0.998

Peripheral arteriopathy 33/460 (7) 23/422 (5) 0.294

Stroke history 58/460 (13) 60/422 (14) 0.467

Coronary heart disease 43/460 (9) 43/422 (10) 0.674

Congestive heart failure 20/460 (4) 12/422 (3) 0.233

Proteinuria 57/460 (12) 46/422 (11) 0.491

Abnormal creatinine 44/460 (10) 35/422 (8) 0.509

Self-reported nonadherence (Haynes-Sackett test)24 142/456 (31) 162/414 (39) 0.014

History of not attending scheduled visits in the previous6 months* (self-reported)24

123/415 (30) 95/383 (25) 0.126

Numbers are mean�SD [N] or n (%).*Patients without visits in the previous 6 months were coded as missing.




The malfunctioning MEMS containers were replaced by themanufacturer, who also developed an algorithm to identify anddelete invalid readings. Through this algorithm, we estimatedthat �5% of all readings on the defective devices were invalid.As a sensitivity analysis, we repeated the analysis excluding the45 patients who had defective devices, and the results did notchange (data not shown).

After 5 years of follow-up, 153 patients had at least 1 of thecomposite cardiovascular events: 67 (16%) in the interven-tion group and 86 (19%) in the control group (Figure 3).Although intervention patients had fewer events than controlpatients, after adjustment for DBP, age, sex, self-reportedmeasures of adherence, and cardiovascular risk profile, thisdifference was not statistically significant (hazard ratio 0.97,95% CI 0.67 to 1.39).

DiscussionThis multicomponent, low-intensity intervention to improveadherence to antihypertensive medication was effective inimproving both BP control and adherence. Although themagnitude of the SBP effect appeared small (a difference of2 mm Hg between groups), 1 large meta-analysis has sug-gested that such differences could be associated with a 10%reduction in stroke and a 7% reduction in coronary heartdisease mortality.1

The strengths of the study include the cluster-randomizeddesign, which avoided study contamination that could haveresulted from individual physicians treating patients in bothstudy arms. We also assessed adherence objectively, usedvalid methods to measure BP, and had adequate power for

both the BP and adherence study outcomes. Moreover, ourfindings are consistent with the findings of other recentstudies. For example, a smaller study by Qureshi et al25 testeda physician-targeted educational intervention. The interven-tion consisted of 1 day of training, during which the seventhreport of the Joint National Committee on Prevention, Detec-tion, and Treatment of High Blood Pressure and the report ofthe Fourth Working Party of the British Hypertension Soci-ety, modified for the Indo-Asian population, were reviewed.The intervention was effective at improving patient adher-ence compared with the usual-care groups (48% versus 32%,respectively; P�0.05). Adherent patients experienced greaterdecreases in SBP than nonadherent patients (P�0.05), but thedifferences were not statistically significant for DBP. Anotherstudy by Ogedegbe et al26 tested an intervention that con-sisted of motivational interviewing sessions every 3 months(�4) that targeted medication adherence behavior amonglow-income black women with uncontrolled BP. In thatstudy, baseline adherence was measured with MEMS duringa 3-month run-in period, and patients were followed upafterward for an additional 9 months. The intervention wasassociated with a nearly 20% absolute increase in adherencelevels at 12 months but not with statistically significantchanges in BP. BP decreased in both groups, but the study didnot report results on the association between adherence levelsand BP control.

The fact that mean adherence was close to 90% in bothgroups in the present study could suggest a Hawthorne effecton both groups, whereby patients’ knowledge that theiradherence was being monitored caused them to change theirbehavior accordingly. Periods longer than 6 months might be

Table 3. Comparison of BP and Adherence Outcomes Between the Control and Intervention Group During the First 6 Monthsof Follow-Up

Unadjusted Analysis Adjusted Analysis

Intervention Control Intervention Control

Repeated BP measures (1-, 3-, and 6-month visits)*

No. of subjects 418 457 417 453

SBP, mm Hg, mean (SE) 149.7 (0.82) 151.1 (0.70) 148.9 (0.69)‡ 151.1 (0.57)

Uncontrolled SBP �140 mm Hg, % 65.6‡ 73.3 66.6§ 76.3

Uncontrolled SBP �140 mm Hg, OR (95% CI) 0.70 (0.56–0.87) 1.00 (Reference group) 0.62 (0.50–0.78) 1.00 (Reference group)

DBP, mm Hg, mean (SE) 82.8 (0.49) 82.3 (0.42) 81.9 (0.35)� 83.0 (0.30)

Uncontrolled DBP �90 mm Hg, % 26.1 22.4 18.1 19.0

Uncontrolled DBP �90 mm Hg, OR (95% CI) 1.22 (0.97–1.55) 1.00 (Reference group) 0.94 (0.73–1.20) 1.00 (Reference group)

6-Month cumulative main adherence outcomes†

No. of subjects 374 423 332 377

Adherence, % days correct dose taken, mean (SE) 91.2 (0.11)� 88.2 (0.09) 92.2 (0.09)‡ 89.0 (0.07)

Adherence, % of patients with at least 80% adherence 88.2 83.5 91.9‡ 85.6

Adherence �80%, OR (95% CI) 1.49 (0.87–2.54) 1.00 (Reference group) 1.91 (1.19–3.05) 1.00 (Reference group)

OR indicates odds ratio; CI, confidence interval.*Analyses for BP outcomes were adjusted for geographic area (Catalonia vs Madrid), number of risk factors, body mass index, age, and the baseline level of the

outcome variable.†Analyses for adherence outcomes were adjusted for baseline DBP, geographic area, self-reported measure of adherence at baseline, and self-reported measure

of not showing up at the scheduled doctor visits.‡P�0.01.§P�0.0001.�P�0.05.




required to observe a significant attenuation of the Hawthorneeffect.27–29 Although we hypothesized that counting pillscould promote a Hawthorne effect in the intervention group,the MEMS bottles also may have resulted in a Hawthorneeffect in both study arms, resulting in smaller than expecteddifferences in adherence between groups. On the other hand,high antihypertensive medication adherence rates have alsobeen found in studies measuring adherence with pharmacyrefill methods, thus indicating that high levels of adherencemight not always be attributable to the Hawthorne effect.30

Regardless of whether there was a Hawthorne effect, wefound clinically and statistically significant differences be-

tween the intervention and control groups in the present studyoutcomes.

We did not, however, observe a direct association betweenadherence and BP control (data not shown). Therefore, it ispossible that the study intervention improved BP controlthrough mechanisms other than improved adherence. Forexample, the intervention may have helped overcome clinicalinertia (ie, clinicians’ reluctance to intensify therapy), result-ing in better overall BP control.31 However, changes in BPmedication were not allowed by protocol until the thirdmonth of follow-up, which suggests that BP improvementswere not the result of overcoming clinical inertia. Althoughother factors may account for the BP improvement, we werelikely underpowered to detect the association between adher-ence and BP control owing to the overall high levels ofadherence in both groups, with limited variability.15,32,33 Inaddition, �37% of the patients were using at least 1 antihy-pertensive medication for which adherence was not moni-tored electronically. Perhaps with the additional assessmentof adherence for these medications, we would have seen astronger association between adherence and BP control.

The present study has additional limitations. As mentionedpreviously, we had a problem with some of the MEMScontainers that resulted in invalid readings; however, theinclusion or exclusion of data from the affected participantsdid not substantively influence our findings. Next, althoughwe instructed physicians to keep a log of how many patientswere offered enrollment in the study, many physicians did notcomplete these logs. Therefore, we are unable to comment onhow the present study population differed from the larger,eligible patient population. A similar situation occurred withthe physicians; an important proportion withdrew withoutrecruiting patients and no information is available on them.Thus, we have a limitation with regard to evaluating thegeneralizability of the present study results to the larger

Figure 2. SBP and DBP differences between the interventionand control groups during the 60-month follow-up. Asterisksmark the visits at which differences in BP favoring the interven-tion group were 1.5 mm Hg or more.

Figure 3. Kaplan–Meier survival curve for cardiovascular (CV)end points comparing the intervention and control groups (log-rank test, P�0.351). The plot shows unadjusted results. Survivalresults after adjustment, with a multivariable survival Cox modelaccounting for physician cluster effects, for DBP, age, sex, self-reported measures of adherence, and cardiovascular risk profilewere not statistically significant (hazard ratio 0.97, 95% CI 0.67to 1.39).




population of both patients and physicians. On the other hand,patients included in the study met the eligibility criteria ofhigh cardiovascular risk, and complete clinical informationwas available at baseline. Information on participating phy-sicians was also available from the physician survey. Finally,adherence is not the only thing that explains poor rates of BPcontrol. As mentioned above, clinician factors, such asclinical inertia, may also play an important role in unsatis-factory rates of BP control.31 Therefore, future studies shouldassess and address both patient adherence and the need forclinician intensification of antihypertensive medication si-multaneously. Future studies will also be needed to elucidatethe impact of this type of intervention on cardiovascularmorbidity and mortality, because this study was underpow-ered for those outcomes.

In summary, we conclude that a multifactorial interventionto improve adherence to antihypertensive medication waseffective in improving both adherence and BP control.Although the effect size was small, we did observe highlevels of adherence in both arms. This suggests that inaddition to the intervention described, other factors such asthe Hawthorne effect may have contributed to these results.The relative importance of various components of this inter-vention, including a potential Hawthorne effect, in improvingadherence and BP control has yet to be determined.

AcknowledgmentWe thank Dr R. Brian Haynes from McMaster University for hisadvice and suggestions during the design phase of the trial.

Sources of FundingThis study was supported in part by Fondo de Investigacion Sanitaria(FIS00/0045-01 and FIS00/0045-02), Fondos Europeos de Desar-rollo Regional, and Fundacio d’Osona per a la Recerca i l’EducacioSanitaria (FORES), as well as the Catalan Agency for HealthTechnology Assessment and Research. The following drug compa-nies funded the study but were not involved in the design, analysis,or manuscript preparation: Novartis, Almirall Prodesfarma, andAventis. Drs Pladevall and Williams were funded in part through theFund for Henry Ford Hospital and grants from the National Instituteof Diabetes and Digestive and Kidney Diseases (R01DK64695) andthe National Heart, Lung, and Blood Institute (R01HL079055),National Institutes of Health.

DisclosuresNone.

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27. Wetzels GE, Nelemans PJ, Schouten JS, Dirksen CD, van der WT,Stoffers HE, Janknegt R, de Leeuw PW, Prins MH. Electronic monitoringof adherence as a tool to improve blood pressure control: a randomizedcontrolled trial. Am J Hypertens. 2007;20:119–125.

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CLINICAL PERSPECTIVENonadherence to antihypertensive medication is prevalent in clinical practice; however, the prevalence of nonadherence toantihypertensive medication might not be as high in Western societies as previously thought. In this study, we found highrates of adherence in both the control and the intervention group. Although electronic measurement of adherence may haveintroduced a Hawthorne effect in our study (and thereby promoted adherence in both groups), recent studies using othermethods of measuring adherence have also found high rates of adherence to antihypertensive medication. Thismultifactorial adherence intervention had 3 main components: (1) The counting of pills during physician visits, (2)designation of a family member to support adherence behavior, and (3) provision of an information sheet to patients thatincluded information on each antihypertensive medication dose and frequency, potential medication side effects, and howthe medication was to be taken. Patients in the intervention group had small but significant improvements in both adherenceand blood pressure control. No effects were found on cardiovascular morbidity and mortality, but the study was notsufficiently powered for these outcomes. Although the intervention was designed to be feasible in clinical practice (ie,simple and inexpensive to implement), it did increase the average length of an office visit by �7 minutes. Although thisamount of time might be prohibitive in some busy clinical settings, it did appear sufficient to improve patient adherence,which is often considered an intransigent problem. Perhaps future interventions can also involve other clinical professionalswho can provide additional time and focus on patient medication adherence.

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SUPPLEMENTAL MATERIAL

Supplemental methods description:

End point definition: First cardiovascular morbidity or mortality event.

The following were included as fatal cardiovascular event: sudden heart failure;

fatal myocardial infarction; death during or following a percutaneous transluminal

coronary angioplasty (PTCA) or an aortocoronary bypass; death due to

congestive heart failure; and fatal cerebrovacular accident (CVA).

The following were included as non-fatal cardiovascular events: new or

established congestive heart failure requiring hospitalization; non-fatal acute

myocardial infarction (i.e., verified by a ST-segment peak in the

electrocardiogram (ECG) with a typical enzyme pattern, emergency thrombolytic

treatment/fibrinolytic treatment, or emergency PTCA/aortocoronary bypass to

prevent extensive myocardial infarction); CVA verified by imaging or medical

records; angina diagnosed with positive exercise treadmill test results; routine

PTCA/aortocoronary bypass; unstable angina requiring hospitalization; silent

myocardial infarction detected during the study and not present in the ECG at the

start of the study; terminal renal insufficiency; and impaired renal function.

Quality control measures: The trial was actively monitored by both internal and

external quality control auditors. During the monitoring visits, the monitors

checked to make sure physicians were performing as instructed. These

assessments included reviewing the pill count results, examining whether or not

information sheets were given, and ascertaining whether or not relatives were

present at the visit to support adherence improvement efforts. As already

mentioned, we also collected data on the duration of the visit.

Cardiovascular risk factors variables used in the adjusted models (number of risk

factors present) : left ventricular hypertrophy, diabetes, severe hypertensive

retinopathy evidence, evidence of atheromatosis, history of congestive heart

failure, history of peripheral occlusive vascular disease, previous stroke, previous

coronary heart disease, previous renal failure or proteinuria, smoking, and high

cholesterol.

Supplemental Tables

Expanded Table 1. Distribution of physician related characteristics in control

and intervention groups. Numbers are mean ± SD[N], and N (%).

Variable Control group

(39, 36

physicians with

survey data)

Intervention

group (40, 33

physicians with

survey data)

P

value

Variables with data available for all

79 analyzed physicians

Physicians under the coordination

of the Catalan coordinating center

21/39 (53.8%) 22/40 (55.0%) 0.918

Female sex 18/39 (46.2%) 15/40 (37.5%) 0.498

Working place

Hospital 12/39 (30.8%) 13/40 (32.5%)

Primary care center 27/39 (69.2%) 27/40 (67.5%) 0.869

Average number of patients per

physician

11.8 ± 8.3 [39] 10.6 ± 7.9 [40] 0.529

Variables with data available only

for the 69 physicians who

completed the survey*

MD degree year 1982.9 ± 5.3

[35]

1982.8 ± 6.4

[33]

0.834

Age 43.1 ± 5.2 [35] 43.6 ± 6.5 [33] 0.749

Working in a Teaching Center 21/36 (58.3%) 20/33 (60.6%) 0.848

Previous participation in clinical

trials

28/35 (80%) 25/33 (75.8%) 0.773

Specialty

Internal medicine 6/34 (17.6%) 7/33 (21.2%)

Family medicine 22/34 (64.7%) 19/33 (57.6%)

Nephrology 6/34 (17.6%) 7/33 (21.2%) 0.836

Practice size in primary care

centers (number of patients)

1629.8 ± 490.3

[24]

1745.5 ± 493.3

[22] 0.930

Hours a week with direct contact

with patients 28.6 ± 8.5 [35] 27.4 ± 9.0 [31] 0.649

Average visit time in primary care

centers (in minutes)

7.5 ± 3.2 7.0 ± 2.2 0.755

Average time visit for follow-up

visits in hospital (in minutes)

15.0 ± 4.4 16.25 ± 5.3 0.722

Holding a full time job in the health

center

27/36 (75.0%) 23/33 (69.7%) 0.788

Participation in medical meetings

(times a year)

0 4/36 (11.1%) 3/33 (9.1)

1-2 23/36 (63.9%) 24/33 (72.7)

3 9/36 (25.0%) 6/33 (18.2) 0.728

Participation in postgraduate

education (times a year)

0 6/36 (16.7%) 3 (9.1%)

1-2 22/36 (61.1%) 23 (69.7%)

3 8/36 (22.2%) 7 (21.2%) 0.619

*Of 79 physicians who actively recruit patients, 69 (87%) completed the survey

Expanded Table 2. Distribution of patient related characteristics in control and intervention groups. Numbers are mean ± SD[N], and Ns (%). Variable Control group

(N= 460)

Intervention

group

(N= 423)

P

value

Patient related characteristics

Geographical area

Madrid coordinating center

Barcelona coordinating center

154 (33%)

306 (67%)

140 (33%)

283 (67%)

0.943

Baseline SBP 160.8 ± 15.0

[460]

162.1 ± 16.3

[423]

0.222

Baseline DBP 86.1 ± 9.8 [460] 88.6 ± 11.1

[423]

<0.001

Baseline heart rate 74.3 ± 12.0

[459]

76.2 ± 11.6

[421]

0.016

Baseline SBP ≥ 140 441/460 ( 96%) 398/423 ( 94%) 0.228

Baseline DBP ≥ 90 146/460 ( 32%) 193/423 ( 46%) <0.001

Severe hypertension 90/460 (20%) 103/423 (24%) 0.086

Age 66.8 ± 8.6 [459] 66.3 ± 8.1 [422] 0.391

Male gender 237/460 (52%) 199/422 (47%) 0.195

BMI>30 221/456 (48%) 220/422 (52%) 0.277

Current smoker 62/458 (14%) 62/422 (15%) 0.623

History of smoking 122/375 (32%) 104/339 (31%) 0.553

HT duration (years) 10.5 ± 8.7 [460] 11.0 ± 9.3 [420] 0.454

Number of hypotensive drugs at

baseline

2.24 ± 1.10

[460]

2.20 ± 1.06

[423]

0.670

Number of hypotensive drugs

grouped

0 2 (0.4) 2 (0.5)

1 137 (29.8) 125 (29.6)

2 147 (32.0) 138 (32.6)

3-4 164 (35.7) 150 (35.5)

>4 10 (2.2) 8 (1.9) 0.998

Number of drugs adherence was

monitored with MEMS system

1.24 ± 0.43

[458]

1.28 ± 0.45

[420]

0.196

Patients with combinations of two

drugs adherence being monitored

with MEMS system

109/458

(23.8%)

116/420

(27.6%)

0.195

Percentage of total number of

drugs monitored with MEMS

66.2 ± 29.4

[457]

67.9 ± 28.7

[420]

0.295

system

Number of risk factors 1.9 ± 1.2 [460] 1.8 ± 1.1 [423] 0.769

Left ventricular hypertrohpy 128/460 (28%) 120/422 (28%) 0.840

Consumption of alcohol (grs) 40.4 ± 117.3

[460]

35.2 ± 86.6

[422]

0.447

Diabetes 289/460 (63%) 266/422 (63%) 0.949

Severe hypertensive retinopathy

(III-IV)

12/460 (3%) 11/422 (3%) 0.998

Peripheral artheriopathy 33/460 (7%) 23/422 (5%) 0.294

Stroke history 58/460 (13%) 60/422 (14%) 0.467

Coronary heart disease 43/460 (9%) 43/422 (10%) 0.674

Congestive heart failure 20/460 (4%) 12/422 (3%) 0.233

Proteinuria 57/460 (12%) 46/422 (11%) 0.491

Abnormal creatinine 44/460 (10%) 35/422 (8%) 0.509

Self-reported nonadherence 142/456 (31%) 162/414 (39%) 0.014

History of not attending scheduled

visits in the previous 6 months*

(self-reported)

123/415 (30%) 95/383 (25%) 0.126

*Patients without visits in the previous 6 months were coded missing.

Expanded Table 3. Comparison of blood pressure and adherence outcomes between the control and the intervention

group during the first 6 months of follow-up.

Unadjusted Analysis Adjusted analysis

Repeated Measures (1, 3 & 6 Months visits)* Intervention

(n=418)

Control (n=457) Intervention

(n=417)

Control

(n=453)

SBP mmHg [mean (SE)] 149.7 (0.82) 151.1 (0.70) 148.9 (0.69)‡ 151.1 (0.57)

Uncontrolled SPB >= 140 mmHg (%) 65.6‡ 73.3 66.6§ 76.3

Uncontrolled SPB >= 140 mmHg [OR (95% CI)] 0.70 (0.56,

0.87)

1.00 (Ref.

group)

0.62 (0.50,

0.78)

1.00 (Ref.

group)

DBP mmHg [mean (SE)] 82.8 (0.49) 82.3 (0.42) 81.9 (0.35)|| 83.0 (0.30)

Uncontrolled DBP >= 90 mmHg (%) 26.1 22.4 18.1 19.0

Uncontrolled DBP >= 90 mmHg [OR (95% CI)] 1.22 (0.97,

1.55)

1.00 (Ref.

group)

0.94 (0.73,

1.20)

1.00 (Ref.

group)

6 Month Cumulative Adherence Outcomes† Intervention

(n=374)

Control (n=423) Intervention

(n=332)

Control

(n=377)

Main adherence outcomes

Adherence, % days correct dose taken [mean

(SE)]

91.2 (0.11)|| 88.2 (0.09) 92.2 (0.09)‡ 89.0 (0.07)

Adherence, % of patients with at least

80% adherence

88.2 83.5 91.9‡ 85.6

Adherence ≥ 80% [OR (95% CI)] 1.49 (0.87,

2.54)

1.00 (Ref.

group)

1.91 (1.19,

3.05)

1.00 (Ref.

group)

Other adherence measures

Medication- Taking % Adherence [mean (SE)] 93.8 (0.15)|| 90.3 (0.13) 94.8 (0.14)‡ 91.1 (0.12)

Adherence, % of patients with at least

80% adherence

94.6|| 90.2 96.2‡ 91.4

Adherence ≥ 80% [OR (95% CI)] 1.89 (1.05,

3.40)

1.00 (Ref.

group)

2.37 (1.31,

4.29)

1.00 (Ref.

group)

Medication-Timing % Adherence [mean (SE)] 88.2 (0.07)|| 84.3 (0.09) 89.3 (0.07)‡ 85.1 (0.07)

Adherence, % of patients with at least 83.1|| 75.2 86.7‡ 76.6

80% adherence

Adherence ≥ 80% [OR (95% CI)] 1.63 (1.09,

2.43)

1.00 (Ref.

group)

1.98 (1.28,

3.06)

1.00 (Ref.

group)

*Analysis for BP outcomes were adjusted for geographic area (Catalonia versus Madrid), number of risk factors, body mass index, age, and the baseline level of the outcome variable. †Analysis for adherence outcomes were adjusted for baseline diastolic blood pressure, geographic area, self-reported measure of adherence at baseline, self-reported measure of not showing up at the scheduled doctor visits. ‡P<0.01

§P<0.0001

||P<0.05

COM99 Investigators:

CATALUNYA

Catalan Coordinating Center: A Arnau, M Pladevall, C Brotons, AM Yáñez (Fundació Caubet-Cimera, Bunyola, Mallorca), A Leiva (Unidad de

Investigación, Gerencia de Atención Primaria de Mallorca, Palma de Mallorca, Mallorca).

M Terns, S Serrallach, M Serrarols, J Casanovas (CAP El Remei, Vic), J Modol, J Soler (Centre Hospitalari de Manresa, Manresa), J Llibre

(Hospital Mútua de Terrassa, Terrassa), J Plana (Hospital Sant Camil, Sant Pere de Ribes), MJ Adrián, M Domenech (Hospital de l’Esperit Sant,

Santa Coloma de Gramenet), J Vila (Hospital Municipal de Badalona, Badalona), A Felip (Hospital de Mataró, Mataró), A Pelegrí (Hospital del

Sagrat Cor, Barcelona), M de la Figuera, E Vinyoles (CAP La Mina, Barcelona), E Castellote, L Comas, M Pladevall, J Feixas (Hospital General

de Vic, Vic), V Canal, J Deniel, M Vilamú, (CAP Manlleu, Manlleu), S Martínez, A Moreta, M Tordera, I Puig (Cap Vic Nord, Vic), F Olivé (CAP

Olost, Olost), MA Gómez, E Márquez, JP Moreno (CAP La Orden, Huelva), MA Casals, N de la Iglesia (CAP Torelló, Torelló), C Brotons, JL Tovar

(Hospital de la Vall d’Hebró, Barcelona), E Deig, E Llargués (Hospital de Granollers, Granollers), N Del Val (CAP Sant Hipòlit de Voltregà, Sant

Hipòlit de Voltregà), M Cuxart, R Sans (Hospital de Figueres, Figueres), T Gros, J Mallafré (CAP Mataró-5, Mataró), FX Fulladosa, JM Galceran,

R García (Hospital de Palamós, Palamós).

MADRID

Madrid Coodinating Center: LM Sánchez (Instituto de Salud Carlos III, Madrid), R Gabriel, I García, C Del Arco (Hospital Univesitario de la

Princesa. Madrid), VF Gil (Universidad Miguel Hernández), A Gómez (Hospital 12 Octubre), S Vega (Centro de Salud Arévalo, Ávila).

E Navarro, D García (Centro de Salud General Espartero, Alicante), JM Martínez (Centro de Salud Cabo de Huertas, Alicante), D Mira, MA

Navarro (Centro de Salud Marina Española, Elda), JL Martínez (Centro de Salud Hospital Provincial, Alicante), C De la Sen (Centro de Salud

Albatix, Elche), MA Payá (Centro de Salud Foietes, Benidorm), M González, I Núñez (Centro de Salud Montesa, Madrid), J Torregrosa, M

Navarro (Centro de Salud Monovar, Alicante), A García (Centro de Salud Padre Manjon, Elda), P Horcajo, M Pérez (Hospital de Guadalajara,

Guadalajara), C Santos (Centro de Salud Cervantes, Guadalajara), F Durán, ML Ortega, L de la Rosa (Centro de Salud Arévalo, Ávila), I López

(Centro de Salud de Begonte, Lugo), P Rodríguez (Centro de Salud de Seoane de Caurel, Lugo), M Sánchez de Enciso, ME Gómez (Centro de

Salud de Friol, Lugo), IL Álvarez (Unidad de Atención Primaria de Abadín, Lugo), MC López (Centro de Salud Palas de Rey, Lugo), E Álvarez

(Hospital Monforte de Lemos, Lugo), C Suárez (Hospital Univesitario de la Princesa, Madrid), A González (Centro de Salud Goya II, Madrid), MB

Sierra (Centro de Salud Nuñez Morgado, Madrid), FJ Cirujano, ML Barutell (Centro de Salud Prosperidad, Madrid), B Novella (Centro de Salud

Potosi, Madrid), JL Antón, J Damián Garcés (Centro de Salud Tamames, Madrid), I Blasco (Centro de Salud El Espinillo, Madrid), JL Berenguer

(Centro de Salud Acacias, Elda), I Montiel (Centro de Salud de Agost, Alicante).

End-Point Committee

G Permanyer (Hospital de la Vall d’Hebró, Barcelona), N Soriano (EAP Sardenya, Barcelona), C Falces (Hospital Clínic i Provincial de Barcelona,

Barcelona) i P Roura (Hospital General de Vic, Vic).

Keoki Williams and Writing Committee on behalf of the COM99 Study GroupFiguera, Emilio Marquez, Antonio Coca, Javier Sobrino, George Divine, Michele Heisler, L. Manel Pladevall, Carlos Brotons, Rafael Gabriel, Anna Arnau, Carmen Suarez, Mariano de la

High Cardiovascular Risk (The COM99 Study)Antihypertensive Medication Adherence and Blood Pressure Control Among Patients at

Multicenter Cluster-Randomized Trial of a Multifactorial Intervention to Improve

Print ISSN: 0009-7322. Online ISSN: 1524-4539 Copyright © 2010 American Heart Association, Inc. All rights reserved.

is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231Circulation doi: 10.1161/CIRCULATIONAHA.109.892778

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