- Email: [email protected]
Optimal Blood Pressure in Patients With Atrial Fibrillation (from the AFFIRM Trial)
Optimal Blood Pressure in Patients With Atrial Fibrillation (from the AFFIRM Trial) Apurva O. Badheka, MDa, Nileshkumar J. Patel, MDb, Peeyush M. Grover, MDc, Neeraj Shah, MDb, Nilay Patel, MDa, Vikas Singh, MDc, Abhishek J. Deshmukh, MDd, Kathan Mehta, MDe, Ankit Chothani, MDf, Ghanshyambhai T. Savani, MDc, Shilpkumar Arora, MDa, Ankit Rathod, MDg, George R. Marzouka, MDc, James Lafferty, MDb, Jawahar L. Mehta, MDd, and Raul D. Mitrani, MDc,* Many medications used to treat atrial fibrillation (AF) also reduce blood pressure (BP). The relation between BP and mortality is unclear in patients with AF. We performed a post hoc analysis of 3,947 participants from the Atrial Fibrillation Follow-Up Investigation of Rhythm Management trial. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) at baseline and follow-up were categorized by 10-mm Hg increments. The end points were all-cause mortality (ACM) and secondary outcome (combination of ACM, ventricular tachycardia and/or fibrillation, pulseless electrical activity, significant bradycardia, stroke, major bleeding, myocardial infarction, and pulmonary embolism). SBP and DBP followed a “U-shaped” curve with respect to primary and secondary outcomes after multivariate analysis. A nonlinear Cox proportional hazards model showed that the incidence of ACM was lowest at 140/78 mm Hg. Subgroup analyses revealed similar U-shaped curves. There was an increased ACM observed with BP <110/60 mm Hg (hazard ratio 2.4, p <0.01, respectively, for SBP and DBP). In conclusion, in patients with AF, U-shaped relation existed between BP and ACM. These data suggest that the optimal BP target in patients with AF may be greater than the general population and that pharmacologic therapy to treat AF may be associated with ACM or adverse events if BP is reduced to <110/60 mm Hg. Ó 2014 Elsevier Inc. All rights reserved. (Am J Cardiol 2014;114:727e736) The seventh report of the Joint National Committee considers a blood pressure (BP) of <120/80 mm Hg (systolic or diastolic) to be “normal” or “optimal.” The cardiovascular risk is known to double with each 20/10 mm Hg increment in BP >115/75 mm Hg in the elderly. This report also outlines a linear relation of systolic blood pressure (SBP) and diastolic blood pressure (DBP) with cardiovascular mortality.1,2 However, in certain populations such as the elderly and in patients with acute coronary syndrome, a “J-shaped” relation between BP and outcomes has been observed.3,4 Low BP (<110/70 mm Hg) has been shown to be associated with an increase in adverse events, with the lowest mortality demonstrable in the BP range 130 to 140/80 to 90 mm Hg.4 Similar findings have also been demonstrated with chronic
a Detroit Medical Center, Detroit, Michigan; bStaten Island University Hospital, Staten Island, New York; cJackson Memorial Hospital, University of Miami Miller School of Medicine, Miami, Florida; dUniversity of Arkansas, Little Rock, Arkansas; eDrexel University School of Public Health, Philadelphia, Pennsylvania; fInternal Medicine Department, MedStar Washington Hospital Center, Washington, DC; and gCedar Sinai Medical Center, Los Angeles, California. Manuscript received April 27, 2014; revised manuscript received and accepted June 7, 2014. Dr. Badheka, Dr. Patel, Dr. Grover, and Dr. Shah contributed equally to this work. No study-specific funding was used to support this work. The authors are solely responsible for the study design, conduct and analyses, and drafting and editing of the manuscript and its final contents. See page 735 for disclosure information. *Corresponding author: Tel: (305) 243-5070; fax: (305) 243-5565. E-mail address: [email protected] (R.D. Mitrani).
0002-9149/14/$ - see front matter Ó 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.amjcard.2014.06.002
coronary artery disease (CAD), hypertension, and stroke.4e12 However, the “optimal” or “goal” BP in atrial fibrillation (AF) has never been studied in the past and had not been addressed in the Joint National Committee-8 guidelines.13 Given the loss of atrial contractility, the optimal BP in patients with AF may differ from the general population. Additionally, most medications used to treat AF, for either rhythm or rate control, result in decreased BPs. Therefore, it would be critical to define not only optimal BP but thresholds in BP below which adverse events may increase. Using patients enrolled in the Atrial Fibrillation Follow-up Investigation of Rhythm Management (AFFIRM) trial,14,15 we hypothesized that patients with AF have a U-shaped relation between BP and outcomes. Furthermore, the goal of this study was to determine the optimal BP in patients with AF and also define lower boundaries of BP control at which mortality and/or adverse events increase. Methods We performed a post hoc analysis of patients enrolled in the AFFIRM trial.14,15 The details of AFFIRM trial have been described previously.9,14e17 In brief, AFFIRM was a prospective trial (n ¼ 4,060) comparing survival in patients with AF and at least 1 risk factor for stroke randomized to a strategy of rate control (n ¼ 2,027) versus a strategy of rhythm control (n ¼ 2,033). Our inclusion criteria included subjects who had initial (baseline) BP recordings and at least 1 other BP recording during the first year of follow-up. There were 3,947 patients (with available BP data) who were included into our study sample. Patients with limited www.ajconline.org
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Table 1 Demographic and baseline characteristics (complete cohort) by average systolic blood pressure categories Variable
Age (years) Men Body mass index (kg/m2) Hypertension Coronary artery diseases Myocardial infarction Revascularization Heart failure NYHA HF class 0 1 2 3 Peripheral vascular disease Prior stroke Smoker Diabetes mellitus Pacemaker Aspirin Warfarin Lipid lowering drug Beta blocker ACE inhibitors Diuretics Other antihypertensive CCBs Digoxin (%) Amiodarone (%) Sotalol (%) Class 1 antiarrhythmic Ejection fraction* >50% 40%e49% 30%e39% <30% Ventricular septal thickness (mm)* LV posterior wall thickness (mm)* Left atrial diameters (mm)*
Systolic Blood Pressure (mm Hg)
p Value
110 (n ¼ 143)
>110 to 120 (n ¼ 426)
>120 to 130 (n ¼ 849)
>130 to 140 (n ¼ 1107)
>140 to 150 (n ¼ 854)
>150 to 160 (n ¼ 383)
>160 (n ¼ 185)
68.6 9.5 108 (75.5%) 26.3 5.4
69.0 8.4 289 (67.8%) 28.3 5.7
69.3 8.2 555 (65.3%) 28.7 5.6
69.1 8.1 673 (60.7%) 29.1 6.2
69.9 7.8 478 (55.9%) 29.5 6.1
70.4 7.9 206 (53.7%) 29.3 6.5
70.7 7.5 93 (50.2%) 29.0 5.9
0.02 <0.01 0.001
63 (44.0%) 78 (54.5%)
221 (51.8%) 190 (44.6%)
510 (60.0%) 336 (39.5%)
806 (72.8%) 396 (35.7%)
695 (81.3%) 295 (34.5%)
343 (89.5%) 138 (36.0%)
170 (91.8%) 72 (38.9%)
<0.01 <0.01
51 (35.6%) 39 (27.2%) 68 (47.5%)
104 (24.4%) 100 (23.4%) 121 (28.4%)
161 (18.9%) 175 (20.6%) 201 (23.6%)
169 (15.2%) 186 (16.8%) 220 (19.8%)
117 (13.7%) 138 (16.1%) 172 (20.1%)
62 (16.1%) 68 (17.7%) 77 (20.1%)
25 (13.5%) 32 (17.3%) 42 (22.7%)
<0.01 0.001 <0.01 <0.01
83 24 22 14 10
(58.0%) (16.7%) (15.3%) (9.7%) (7%)
323 48 46 9 33
(75.8%) (11.2%) (10.8%) (2.1%) (7.8%)
679 88 63 19 50
(79.9%) (10.3%) (7.4%) (2.2%) (5.9%)
922 108 64 13 72
(83.2%) (9.7%) (5.7%) (1.1%) (6.5%)
699 98 46 11 52
(81.8%) (11.4%) (5.3%) (1.2%) (6.1%)
316 38 25 4 39
(82.5%) (9.9%) (6.5%) (1.0%) (10.2%)
148 23 13 0 11
(80.4%) (12.5%) (7.0%) (0%) (6%)
22 26 26 17 39 124 33 42 67 74 48 30 87 29 18 12
(15.4%) (18.2%) (18.2%) (11.9%) (27.3%) (86.7%) (23.1%) (35%) (46.9%) (51.8%) (33.6%) (25%) (60.8%) (20.3%) (12.6%) (8.4%)
60 66 69 31 123 372 102 146 153 181 132 84 227 83 56 43
(14.1%) (15.5%) (16.2%) (7.3%) (28.9%) (87.3%) (23.9%) (41.6%) (35.9%) (42.5%) (31%) (23.9%) (53.3%) (19.5%) (13.2%) (10.1%)
108 101 149 56 216 712 200 242 287 335 236 219 446 136 121 104
(12.7%) (11.9%) (17.6%) (6.6%) (25.4%) (83.9%) (23.6%) (36.5%) (33.8%) (39.5%) (27.8%) (33.1%) (52.6%) (16%) (14.3%) (12.3%)
134 134 199 67 284 962 269 325 405 435 355 295 593 208 156 150
(12.1%) (12.1%) (18%) (6.1%) (25.7%) (86.9%) (24.3%) (37.9%) (36.6%) (39.3%) (32.1%) (34.4%) (53.6%) (18.8%) (14.1%) (13.6%)
121 90 192 49 214 715 175 257 343 374 278 219 434 150 140 122
(14.2%) (10.5%) (22.5%) (5.7%) (25.1%) (83.7%) (20.5%) (38.1%) (40.2%) (43.8%) (32.6%) (32.4%) (50.8%) (17.6%) (16.4%) (14.3%)
49 43 105 17 109 317 76 105 181 180 139 97 216 78 76 50
(12.8%) (11.2%) (27.4%) (4.4%) (28.5%) (82.8%) (19.8%) (36.6%) (47.3%) (47%) (36.3%) (33.9%) (56.4%) (20.4%) (19.8%) (13.1%)
30 21 51 8 52 151 39 58 106 96 69 53 89 37 33 25
(16.2%) (11.4%) (27.6%) (4.3%) (28.1%) (81.6%) (21.1%) (40.6%) (57.3%) (51.9%) (37.3%) (37.3%) (48.1%) (20%) (17.8%) (13.5%)
0.14 0.62 0.07 <0.01 0.05 0.68 0.11 0.34 0.72 <0.01 0.001 0.04 0.006 0.18 0.46 0.06 0.25 <0.01
37 (37.8%) 15 (15.3%) 21 (21.4%) 25 (25.5%) 1.0 0.2
193 (66.1%) 33 (11.3%) 32 (11%) 34 (11.6%) 1.0 0.2
490 (76.8%) 73 (11.4%) 41 (6.4%) 34 (5.3%) 1.1 0.2
632 (75.6%) 120 (14.4%) 59 (7.1%) 25 (3%) 1.1 0.2
519 (78.8%) 71 (10.8%) 50 (7.6%) 19 (2.9%) 1.1 0.2
209 (74.9%) 45 (16.1%) 19 (6.8%) 6 (2.2%) 1.1 0.2
114 (78.1%) 22 (15.1%) 8 (5.5%) 2 (1.4%) 1.1 0.2
1.0 0.2
1.0 0.1
1.1 0.2
1.1 0.2
1.1 0.2
1.1 0.2
1.1 0.2
0.002
4.4 0.7
4.4 0.7
4.3 0.7
4.3 0.6
4.3 0.6
4.3 0.6
4.2 0.6
0.05
<0.01
ACE inhibitors ¼ angiotensin-converting enzyme inhibitors; CCBs ¼ calcium channel blockers; NYHA HF class ¼ New York Heart Association heart failure class. * Echocardiographic data available for 2,948 patients (74.7% of entire study population).
or no BP data were excluded (n ¼ 113). BP measurements were consistent with the American Heart Association’s scientific statement on human BP determination by sphygmomanometer.18,19 Per study protocol, the BP was recorded in the preferred arm after the patient has been sitting quietly for at least 5 minutes.14,15,18e20 The average BP was defined as the average of all available BP measurements taken during each postbaseline visit. SBP and DBP were categorized into 10-mm Hg increments to study the association between BP and primary and
secondary clinical outcomes. The primary end point of our analysis was all-cause mortality (ACM). The secondary outcome considered was a composite of ACM and events including sustained ventricular tachycardia, ventricular fibrillation, pulseless electrical activity, concurrent AF, bradycardia, stroke, major bleeding, myocardial infarction, and pulmonary embolism. Our definitions remained consistent with the original trial.14,15 Follow-up data were available at 2, 4, 8, and 12 months and then 3 visits per year until a period of 6 years or study termination.
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Table 2 Demographic and baseline characteristics (complete cohort) by average diastolic blood pressure categories Variable
Diastolic Blood Pressure (mm Hg)
p Value
60 (n ¼ 90) >60 to 70 (n ¼ 804) >70 to 80 (n ¼ 1986) >80 to 90 (n ¼ 964) >90 (n ¼ 103) Age (years) Male gender Body mass index (kg/m2) Hypertension Coronary artery diseases Myocardial infarction Revascularization Heart failure NYHA HF class 0 1 2 3 Peripheral vascular diseases Prior stroke Smoker Diabetes mellitus Pacemaker Aspirin Warfarin Lipid lowering drug Beta blocker ACE inhibitors Diuretics Other antihypertensive CCBs Digoxin Amiodarone Sotalol Class 1 antiarrhythmic Ejection fraction* >50% 40%e49% 30%e39% <30% Ventricular septal thickness (mm)* LV posterior wall thickness (mm)* Left atrial diameters (mm)*
72.5 8.2 52 (57.8%) 26.2 6.0 57 (63.3%) 57 (63.3%) 34 (37.8%) 37 (41.1%) 52 (57.8%)
71.8 7.1 491 (61.1%) 28.0 5.6 469 (58.3%) 397 (49.4%) 206 (25.6%) 221 (27.5%) 243 (30.2%)
70.1 7.6 1,178 (59.3%) 28.8 6.0 1,390 (70%) 722 (36.4%) 316 (15.9%) 335 (16.9%) 417 (21%)
66.8 8.6 605 (62.8%) 30.1 6.0 795 (82.5%) 300 (31.1%) 121 (126%) 137 (14.2%) 167 (17.3%)
62.8 9.0 76 (73.8%) 30.6 6.5 97 (94.2%) 29 (28.2%) 12 (11.6%) 8 (7.8%) 22 (21.4%)
48 19 17 6 10 15 12 27 11 31 75 21 20 42 64 35 21 69 22 10 12
585 113 79 27 77 112 101 196 55 228 675 214 223 308 373 312 204 432 183 117 78
1,624 210 122 30 128 266 225 390 121 524 1,680 443 603 723 804 615 508 1,059 338 290 266
826 79 53 5 47 123 120 164 53 235 836 202 297 408 378 268 240 476 162 165 135
87 6 8 2 5 8 23 14 5 19 87 14 32 61 56 27 24 56 16 18 15
(53.3%) (21.1%) (18.9%) (6.7%) (11.1%) (16.7%) (13.3%) (30%) (12.2%) (34.4%) (83.3%) (23.3%) (26.7%) (46.7%) (71.1%) (38.9%) (28%) (76.7%) (24.4%) (11.1%) (13.3%)
31 (45.6%) 13 (19.1%) 10 (14.7%) 14 (20.6%) 1.1 0.2 1.0 0.2 4.5 0.6
(72.8%) (14.1%) (9.8%) (3.4%) (9.6%) (13.9%) (12.6%) (24.4%) (6.8%) (28.4%) (84%) (26.6%) (34.4%) (38.3%) (46.4%) (38.8%) (31.5%) (53.8%) (22.8%) (14.6%) (9.7%)
414 (70.2%) 77 (13.1%) 49 (8.3%) 50 (8.5%) 1.1 0.2 1.0 0.2 4.3 0.7
(81.8%) (10.6%) (6.1%) (1.5%) (6.5%) (13.4%) (11.3%) (19.6%) (6.1%) (26.4%) (84.6%) (22.3%) (38.6%) (36.4%) (40.5%) (31%) (32.5%) (53.4%) (17%) (14.6%) (13.4%)
1,122 (75.9%) 187 (12.7%) 114 (7.7%) 55 (3.7%) 1.1 0.2 1.0 0.2 4.3 0.6
(85.8%) (8.2%) (5.5%) (0.5%) (4.9%) (12.8%) (12.5%) (17%) (5.5%) (24.4%) (86.7%) (21%) (40.5%) (42.3%) (39.2%) (27.8%) (32.8%) (49.4%) (16.8%) (17.1%) (14%)
567 (77.6%) 89 (12.2%) 52 (7.1%) 23 (3.2%) 1.2 0.2 1.1 0.2 4.3 0.6
(84.5%) (5.8%) (7.8%) (1.9%) (4.9%) (7.8%) (22.3%) (13.6%) (4.9%) (18.5%) (84.5%) (13.6%) (41.6%) (59.2%) (54.4%) (26.2%) (31.6%) (54.4%) (15.5%) (17.5%) (14.6%)
60 (74.1%) 13 (16.1%) 5 (6.2%) 3 (3.7%) 1.2 0.2 1.1 0.2 4.2 0.7
0.0001 0.03 0.0001 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01
0.001 0.39 0.02 <0.01 0.12 0.04 0.5 0.008 0.04 <0.01 <0.01 <0.01 0.91 <0.01 0.002 0.27 0.06 <0.01
0.0001 0.0005 0.08
ACE inhibitors ¼ angiotensin-converting enzyme inhibitors; CCBs ¼ calcium channel blockers; NYHA HF class ¼ New York Heart Association heart failure class. * Echocardiographic data available for 2,948 patients (74.7% of entire study population).
Baseline characteristics of the study population were compared across the SBP and DBP groups by the chi-square test for categorical variables and the 1-way analysis of variance or the Kruskal-Wallis test for continuous variables, depending on the distribution of the variable. We hypothesized that if a J- or U-shaped relation is discovered between BP and outcome, it is more likely to be seen with average on-treatment follow-up BP (which is closer to the patient’s “actual” long-term BP) rather than a single baseline BP value.4 We also conducted formal tests of linearity for the relation between BP and outcomes. The R2 of the quadratic model of SBP was significantly better than that of the linear model of SBP (p <0.001). Thus, the model with SBP as a quadratic function gives a better fit. Similar results were obtained using DBP and for secondary outcome as well. Hence, we decided to define the relation between average on-treatment BP and outcomes as a quadratic
nonlinear relation. A nadir BP was calculated with the delta method, which is equal to coefficient of the linear term divided by 2 times the coefficient of the quadratic (square) term.21 The value of nadir BP was then used to determine the range of SBP and DBP at which the event rate would be the lowest, and this range of SBP (130e140 mmHg) and DBP (70e80 mmHg) was subsequently used as the referent group in the Cox proportional hazards models. We created 2 separate adjusted models using baseline BP and average on-treatment follow-up BP. The predictive value for each model was calculated using Harrell’s concordance index (C index), and a comparison was drawn between them using bootstrapping. Because the predictive value of models with average on-treatment BP was significantly better than that of baseline BP models, all subsequent mention of BP relates to average follow-up BP and not to baseline BP.
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Figure 1. Relation between blood pressure and primary outcome in the overall population. (A) Adjusted HR of the primary outcome as a function of average followup SBP categories. (B) Adjusted HR of the primary outcome as a function of average follow-up DBP categories. (C) Adjusted restricted cubic spline of the primary outcome as a function of average follow-up SBP. (D) Adjusted restricted cubic spline of the primary outcome as a function of average follow-up DBP.
Univariate Cox proportional hazards analysis was performed to investigate individual variables significantly associated with primary and secondary outcomes. Variables with p <0.2 in the initial univariate screen and those believed to be clinically relevant were included in the multivariate model.22 Initially, we constructed multivariate Cox proportional hazards models incorporating all potential confounding variables. Subsequently, we created reduced models including only variables with p <0.05 using backward regression techniques. These reduced models showed similar results and adjusted hazard ratio (HR) values compared with the full model. We decided to use the reduced model for our analysis to avoid “overfitting.” The variables included in the final multivariate models were BP group, age, history of hypertension, history of congestive heart failure (CHF), history of myocardial infarction, history of revascularization, history of stroke, history of diabetes, smoking status, use of warfarin, lipid-lowering therapy, diuretics, and randomized (rate vs rhythm) treatment group. This analysis was performed for the complete cohort and was also performed separately for the rate and the rhythm control arms. The adjusted HR for each category of BP was calculated in reference to the SBP and DBP range in which the event rate was the lowest, that is, for that group, the HR was considered as 1. We thoroughly checked for interactions and tested for collinearity using variance inflation factor, with variance inflation factor >10 signifying collinearity. No significant interactions or multicollinearity was observed. The variance inflation factor for all variables in the model was <10. To evaluate the relation between SBP (in a continuous manner) and HR of primary and secondary outcomes, we performed restricted cubic spline analysis for the Cox
proportional hazards model using the covariates listed previously. Separate subgroup analyses were also performed in important subgroups. A p value of <0.05 was considered statistically significant. All analyses were performed using the Stata software, version 11.0 (StataCorp LP, College Station, Texas). Results The baseline characteristics of the study population, stratified by average SBP and DBP ranges, are listed in Tables 1 and 2. Participants with a lower mean SBP were likely to be younger, men, and have a lower body mass index, history of CAD, and history of myocardial infarction and/or CHF. Participants with a lower mean DBP were more likely to be older, leaner, and have a history of CAD, myocardial infarction, peripheral vascular disease, and diabetes. Lower SBP and DBP were significantly associated with a decreased left ventricular ejection fraction (LVEF; <30%). Higher SBP and DBP were significantly associated with a normal LVEF (>50%). Use of angiotensinconverting enzyme inhibitors, diuretics, calcium channel blockers, and other antihypertensive drugs was associated with a higher SBP. Use of diuretics, other antihypertensive drugs, digoxin, and/or amiodarone was associated with lower DBP. The mean follow-up period was 42.4 14.7 months. C indexes of average and baseline SBP models were 0.73 (95% confidence interval [CI] 0.71 to 0.74) and 0.71 (95% CI 0.69 to 0.73), respectively. Similarly, C indexes of average and baseline DBP models were 0.72 (95% CI 0.70 to 0.74) and 0.71 (95% CI 0.69 to 0.73), respectively. The C indexes of the models with average on-treatment BP were
Table 3 Hazard ratio of primary and secondary outcomes in various subgroups compared with the reference range (130 to 140/80 to 90 mm Hg) Subgroups
Rhythm control (1,973) CAD absent (2,442) CAD present (1,505) Hypertension absent (1,139) Hypertension present (2,808) CHF absent (3,046) CHF present (901) EF 30% (2,803) EF < 30% (145)
Secondary Outcome (Hazards Ratio, (CI) p Value)
*SBP < 110
*SBP > 160
*DBP < 60
*DBP > 90
SBP < 110
SBP > 160
DBP < 60
DBP > 90
3.9 (2.9e5.4), p <0.001 4.2 (2.7e6.7), p <0.001 3.6 (2.3e5.7), p <0.001 3.0 (1.7e5.3), p <0.001 4.7 (3.1e7.0), p <0.001 3.3 (1.8e5.9), p <0.001 4.7 (3.2e6.9), p <0.001 3.3 (1.9e5.7), p <0.001 4.2 (2.7e6.4), p <0.001 4.0 (2.6e6.4), p <0.001 1.8 (0.7e4.5), p ¼ 0.22
1.9 (1.4e2.7), p <0.001 2.8 (1.7e4.6), p <0.001 1.4 (0.9e2.3), p ¼ 0.13 1.6 (0.9e2.6), p ¼ 0.09 2.3 (1.4e3.7), p <0.001 7.2 (3.2e16), p <0.001 1.6 (1.1e2.3), p ¼ 0.02 1.9 (1.2e2.9), p ¼ 0.01 2.0 (1.1e3.4), p ¼ 0.01 1.9 (1.2e2.8), p <0.001 0.7 (0.1e6.7), p ¼ 0.75
3.9 (2.8e5.3), p <0.001 4.2 (2.6e6.8), p <0.001 3.6 (2.4e5.6), p <0.001 4.8 (2.7e8.5), p <0.001 3.9 (2.6e5.6), p <0.001 2.9 (1.6e5.5), p <0.001 4.6 (3.1e6.6), p <0.001 4.7 (2.9e7.9), p <0.001 4.0 (2.6e6.1), p <0.001 3.7 (2.4e5.6), p <0.001 5.0 (2.0e13), p <0.001
1.8 (1.1e3.0), p ¼ 0.02 3.5 (1.8e6.7), p <0.001 0.9 (0.4e2.2), p ¼ 0.8 1.5 (0.7e3.3), p ¼ 0.28 2.1 (1.0e4.3), p ¼ 0.03 2.0 (0.3e15), p ¼ 0.5 1.9 (1.1e3.2), p ¼ 0.02 1.8 (0.9e3.4), p ¼ 0.07 1.8 (0.7e4.3), p ¼ 0.16 1.8 (1.0e3.4), p ¼ 0.07 6.5 (1.1e36), p ¼ 0.04
2.5 (1.9e3.3), p <0.001 2.5 (1.7e3.7), p <0.001 2.4 (1.6e3.7), p <0.001 1.9 (1.1e3.1), p ¼ 0.01 2.9 (2.0e4.2), p <0.001 2.5 (1.5e3.9), p <0.001 2.8 (1.9e4.0), p <0.001 2.1 (1.3e3.3), p <0.001 2.8 (1.9e4.1), p <0.001 2.9 (1.9e4.2), p <0.001 1.8 (0.8e4.2), p ¼ 0.16
1.4 (1.0e1.9), p ¼ 0.03 1.5 (1.0e2.3), p ¼ 0.08 1.4 (0.9e2.1), p ¼ 0.09 1.2 (0.8e1.9), p ¼ 0.33 1.6 (1.0e2.4), p ¼ 0.02 4.6 (2.1e9.8), p <0.001 1.2 (0.9e1.7), p ¼ 0.2 1.3 (0.9e1.9), p ¼ 0.12 1.5 (0.9e2.5), p ¼ 0.08 1.5 (1.0e2.1), p ¼ 0.04 0.8 (0.1e6.9), p ¼ 0.84
2.5 (1.9e3.3), p <0.001 2.2 (1.4e3.5), p <0.001 2.7 (1.8e4.0), p <0.001 2.7 (1.6e4.6), p <0.001 2.6 (1.8e3.7), p <0.001 1.9 (1.1e3.4), p ¼ 0.02 3.0 (2.1e4.2), p <0.001 2.4 (1.5e3.9), p <0.001 2.9 (2.0e4.2), p <0.001 2.4 (1.6e3.6), p <0.001 5.2 (2.2e12), p <0.001
1.5 (1.0e2.3), p ¼ 0.04 2.1 (1.2e3.6), p ¼ 0.01 1.2 (0.6e2.2), p ¼ 0.61 1.2 (0.6e2.1), p ¼ 0.62 2.0 (1.1e3.6), p ¼ 0.01 5.3 (1.6e17), p ¼ 0.01 1.4 (0.9e2.2), p ¼ 0.01 1.3 (0.8e2.2), p ¼ 0.28 2.1 (1.0e4.3), p ¼ 0.03 1.7 (1.0e2.7), p ¼ 0.04 3.6 (0.7e19), p ¼ 0.12
Systemic Hypertension/Blood Pressure Control and Atrial Fibrillation
Complete cohort (3,947) Rate control (1,974)
All-Cause Mortality (Hazards Ratio, (CI) p Value)
Model was adjusted for age, history of hypertension, history of congestive heart failure, history of myocardial infarction, history of revascularization, history of stroke, history of diabetes, smoking status, use of warfarin, lipid-lowering therapy, diuretics, and randomized (rate vs rhythm) treatment group. We did not include the subgroup variable in the model while carrying out the multivariate model for particular subgroup of interest, for example, history of CAD was not included in the model for subgroup analysis in CAD present and CAD absent subgroups. CAD ¼ coronary artery disease; CHF ¼ congestive heart failure; DBP ¼ diastolic blood pressure; EF ¼ ejection fraction; SBP ¼ systolic blood pressure. * Referent groups for systolic and diastolic blood pressures were 130 to 140 mm Hg and 70 to 80 mm Hg, respectively.
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Figure 2. Relation between blood pressure and secondary outcome in the overall population. (A) Adjusted HR of the secondary outcome as a function of average followup SBP categories. (B) Adjusted HR of the secondary outcome as a function of average follow-up DBP categories. (C) Adjusted restricted cubic spline of the secondary outcome as a function of average follow-up SBP. (D) Adjusted restricted cubic spline of the secondary outcome as a function of average follow-up DBP.
Figure 3. Figure showing the relation between BP and primary outcome in the rate control group. (A) Adjusted HR of the primary outcome as a function of average follow-up SBP categories in the rate control group. (B) Adjusted HR of the primary outcome as a function of average follow-up DBP categories in the rate control group. (C) Adjusted restricted cubic spline of the primary outcome as a function of average follow-up SBP in the rate control group. (D) Adjusted restricted cubic spline of the primary outcome as a function of average follow-up DBP in the rate control group.
significantly better than those of models with baseline BP (p values of 0.02 and 0.007 for SBP and DBP, respectively). The nadir BP (SBP and/or DBP) for the complete cohort resulting in the lowest ACM was calculated to be 140/ 78 mm Hg.
Of the 3,947 participants, ACM was observed in 614 participants (15.6%). The relation between average SBP and ACM followed a U-shaped relation with increased event rates at the low and high SBP ranges (Figure 1 and Table 3). After adjusting for baseline covariates compared with the
Systemic Hypertension/Blood Pressure Control and Atrial Fibrillation
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Figure 4. Figure showing the relation between BP and primary outcome in the rhythm control group. (A) Adjusted HR of the primary outcome as a function of average follow-up SBP categories in the rhythm control group. (B) Adjusted HR of the primary outcome as a function of average follow-up DBP categories in the rhythm control group. (C) Adjusted restricted cubic spline of primary outcome as a function of average follow-up SBP in the rhythm control group. (D) Adjusted restricted cubic spline of primary outcome as a function of average follow-up DBP in the rhythm control group.
reference group (average SBP ¼ 130 to 140 mm Hg), the risk of ACM (complete cohort) increased by 3.9 fold (p <0.001) in the group with SBP 110 mm Hg and by 1.9 fold (p <0.001) in the group with SBP >160 mm Hg. This U-shaped relation was not observed only when the baseline SBP was used (Supplementary Figure 1). This relation remained unchanged when the analysis was repeated for patients after accounting for LVEF (Supplementary Table 1). The group with average SBP <110 mm Hg actually had greater mortality than the group with average SBP >160 mm Hg (HR 3.9, p <0.001). The relation between average DBP and ACM also followed a U-shaped relation with increased event rates at both the low and high DBP ranges. After adjusting for baseline covariates compared with the reference group (average DBP >80 to 90 mm Hg), the risk of ACM (complete cohort) increased by 3.9 fold (p <0.001) in the group with DBP 60 mm Hg and by 1.8 fold (p ¼ 0.02) in the group with DBP >90 mm Hg. The U-shaped relation was not observed only when the baseline DBP was used (Supplementary Figure 1). The group with average DBP 60 mm Hg actually had greater ACM than the group with average DBP >90 mm Hg (HR 3.9, p <0.001). Of the 3,947 participants, at least one of the composite end points comprising the secondary outcome was observed in 971 subjects (24.6%). A similar U-shaped relation with secondary outcome was found for average SBP and DBP (Figure 2). After adjusting for baseline covariates, compared with the reference group (average SBP ¼ 130 to 140 mm Hg, DBP ¼ 80 to 90 mm Hg), the risk of secondary outcome (complete cohort) increased by 2.4 fold (p <0.001) in the group with SBP 110 mm Hg and by 1.5 fold (p ¼ 0.02) in the group with SBP >160 mm Hg. Similarly, the risk of secondary outcome
(complete cohort) increased by 2.5 fold (p <0.001) in the group with DBP 60 mm Hg and by 1.5 fold (p ¼ 0.04) in the group with DBP >90 mm Hg (Figure 2). Subgroup analyses were performed on the rate and rhythm control arms (Table 3 and Figures 3 and 4). Additionally, subgroup analyses were performed on patients stratified by the presence or absence of CAD, hypertension, and CHF. A subgroup analysis was also performed on patients stratified by ejection fraction (EF) <30% versus those with EF 30% (Table 3). SBP: In patients with average SBP <110 mm Hg, all subgroups showed a statistically significant increase in ACM (HR range 3.0 to 4.7) except for those with EF <30% in which there was a nonstatistical trend toward increase in mortality (Table 3). In patients with average SBP >160 mm Hg, all subgroups, except for those assigned to rhythm control, those without CAD, and those with EF <30%, showed a statistically significant increase in ACM (HR 1.6 to 7.2; Table 3). DBP: In patients with average DBP <60 mm Hg, the ACM was significantly increased for all patient subgroups (Table 3). In patients with average DBP >90 mm Hg, there was a significant increase in ACM in the following subgroups: rate control, CAD, hypertension, and EF <30% (Table 3). Discussion The main finding of this study is the demonstration of a U-shaped relation between average BP (SBP and DBP) and ACM in patients with AF. This U-shaped relation was also observed with the composite secondary end points.
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Additionally, this study demonstrated significantly increased mortality and secondary events in patients with average SBP <110 mm Hg and DBP <60 mm Hg; this finding has implications for lower boundaries of BP, which may serve to limit pharmacologic rate and rhythm control drug therapies. Based on this post hoc analysis of the AFFIRM data set, the optimal BP associated with the lowest mortality (nadir) was 140/78 mm Hg. The “optimal” or “goal” BP in AF has never been studied in the past and had not been addressed in the Joint National Committee-8 guidelines.13 The current guidelines on hypertension therapy recommend tight control of BP.1,13,23,24 However, it has been recognized that tight control of BP (SBP <130 mm Hg) over a standard control of BP (SBP 130 to 140 mm Hg) has no benefit in patients with CAD or diabetes.25 Our study was based on a population of patients with AF who were elderly or are believed to have at least 1 risk factor for thromboembolic events.14,15 There was a significantly greater mortality for patients with average BP (SBP/DBP) <110/60 mm Hg compared with average BPs in the range of 130 to 140/70 to 80 mm Hg, which was the optimal range of BPs in this study. This finding has implications guiding the use and dosing of calcium channel blockers and b blockers, including sotalol, which may cause a significant BP decrease.14,15 Because there are no clinical practice guidelines recommending the lower boundary of BP that should limit rate and/or rhythm control use, the practitioner will rely on clinical judgment when using and dosing these drugs. These medications may be titrated to BPs <110/60 mm Hg to achieve the goal of rate or rhythm control. Across the cohort and almost all subgroups (Figures 1 to 4 and Table 3), there was a greater HR observed for the very low BPs (SBP/DBP <110/60 mm Hg) compared with optimal BP control. Because many of our therapies for AF include BP-lowering medications (rate or rhythm control), and many patients have concomitant hypertension requiring therapy, this raises the question as to whether we may be harming some patients with excessive pharmacologic therapy. Strict rate control has not been shown to be superior to lenient rate control.26 Perhaps, it can be speculated that lower BPs associated with the increased use of rate control drugs to achieve strict rate control may have negated any potential actual benefit of a stricter rate control strategy. Although future prospective studies may provide the actual optimal BP control in patients with AF, this study raises the question of whether rate and/or rhythm control drug therapies should be limited to avoid SBPs <100 to 110 mm Hg and DBPs <60 to 70 mm Hg. Given the findings that strict rate control is not superior to lenient rate control26 and that strict rate control is not recommended by the recent guidelines on AF treatment,27 the use of less rate control medication should facilitate avoidance of relative hypotension. The subgroup analysis of the rate and rhythm control arms demonstrated similar results. Those with the lowest BPs appeared to have the highest mortality and incidence of secondary outcomes regardless of the strategy used to control the AF. The possible explanation for the adverse events and low DBP may be related to the diminished coronary blood flow to the myocardial and subendocardial layers in the setting of AF (limited coronary reserve). This may increase the risk of ventricular ischemia and
mortality.28,29 We found a low DBP associated with increased ACM in patients regardless of CAD (Table 3). In patients with low average DBP, all subgroups showed an increase in ACM or a trend in increase in ACM in the subgroups without hypertension or CHF. Secondary outcomes were increased for all patient subgroups with average DBP <60 mm Hg (Table 3), thereby supporting the notion that excessively low DBPs may be associated with adverse outcomes in patients with AF. The relation between low SBP and mortality seems more complex. Increased risk of ischemic stroke may occur with low SBP.7 Potential confounders such as CAD and hypertension may also contribute to this finding. However, the U-shaped relations in AF were independent of the history of CAD and hypertension (Table 3). Lower SBP in CHF has been shown to be associated with a greater mortality.30 We found an increase in ACM and secondary outcomes in those patients with a history of CHF and low SBP. There was a trend toward increased ACM or secondary outcomes for those patients with EF <30%. The threshold for low SBP of 110 mm Hg may not have been sufficiently low to identify a high-risk group in those with EF <30%. Also because of a lack of LVEF data in the entire cohort, only 145 patients had reported EF <30%, which limits the power of a statistical analysis. In contrast, the low average DBP threshold of 60 mm Hg did identify a group of patients with clinical CHF and patients with low EF with increased ACM and secondary outcomes. Although low BPs were associated with adverse outcomes in both the rate and rhythm control groups, the higher BPs were associated with disparate responses. In the rhythm control arm, there were nonsignificant trends of increase in ACM and composite secondary outcomes for SBP >160 mm Hg and no difference in ACM or secondary outcomes for DBP >90 mm Hg (Table 3). In contrast, in the rate control arm, there was an increase in ACM in patients with SBP >160 and DBP >90 mm Hg and an increase in secondary outcomes in patients with DBP >90 mm Hg. The results from this study cannot explain this discrepancy in association between rate and rhythm control and the higher BPs. It is possible that higher BPs lead to more adverse outcomes in patients who are more likely to be in AF (rate control) compared with patients more likely to be in sinus rhythm (rhythm control). Alternatively, the higher BPs may reflect increased sympathetic tone and/or inadequate rate control in a sicker subgroup more susceptible to adverse outcomes. Although there was discrepancy in associations between high BPs and ACM in the rate and rhythm control, clearly, the lower BPs were associated with deleterious outcomes in both groups. As the findings were generated from a post hoc analysis, any causal relation cannot be proved from these results. Therefore, there were a significant number of patients in sinus rhythm for long periods in either rate or rhythm control arms. This could have also caused an error in the calculation of the average BP measurement as the presence of sinus rhythm has been shown to lower BP reading in patients with AF. Because of the limited number of patients in the group EF <30% (n ¼ 145) and other subgroups, the power for statistical analysis was limited with wide CIs observed in most of these subgroups. Despite the
Systemic Hypertension/Blood Pressure Control and Atrial Fibrillation
comprehensive analysis adjusting for several possible confounders in the relation between BP and outcomes, it is still possible that the statistical adjustments may not have accounted for some unknown confounders, leading to a possibility of residual confounding. Acknowledgment: The authors acknowledge Dr. George Wyse, MD, PhD, University of Calgary, Alberta, Canada, and Dr. Albert L. Waldo, MD, Case Western Reserve University, Cleveland, Ohio, regarding the help on accessing the “AFFIRM Manual of Operations on recording of BP.” The authors also acknowledge Dr. Sean Coady, MD, and Dr Kevin Purkiser, PhD, from the National Heart Lung and Blood Institute (NHLBI). None of the authors are affiliated with the NHLBI or were part of the AFFIRM trial.
11. 12.
13.
14.
15.
Disclosures Dr. Mitrani has consultant relationship with Medtronic (modest) and St. Jude Medical (modest), neither of which is relevant to this article. None of the other listed authors have any disclosures or potential conflict of interest.
16.
Supplementary Data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/ j.amjcard.2014.06.002. 1. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ. Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Hypertension 2003;42:1206e1252. 2. Badheka A, Shenoy M, Rathod A, Tuliani T, Afonso L. Long-term mortality and role of troponin elevation in hypertensive emergencies. Am J Cardiol 2012;109:600. 3. Boutitie F, Gueyffier F, Pocock S, Fagard R, Boissel JP. J-shaped relationship between blood pressure and mortality in hypertensive patients: new insights from a meta-analysis of individual-patient data. Ann Intern Med 2002;136:438e448. 4. Bangalore S, Qin J, Sloan S, Murphy SA, Cannon CP. What is the optimal blood pressure in patients after acute coronary syndromes?: Relationship of blood pressure and cardiovascular events in the PRavastatin OR atorVastatin Evaluation and Infection TherapyThrombolysis In Myocardial Infarction (PROVE IT-TIMI) 22 trial. Circulation 2010;122:2142e2151. 5. Lee TT, Chen J, Cohen DJ, Tsao L. The association between blood pressure and mortality in patients with heart failure. Am Heart J 2006;151:76e83. 6. Vokó Z, Bots ML, Hofman A, Koudstaal PJ, Witteman JC, Breteler MM. J-shaped relation between blood pressure and stroke in treated hypertensives. Hypertension 1999;34:1181e1185. 7. Witteman JC, Grobbee DE, Valkenburg HA, van Hemert AM, Stijnen T, Burger H, Hofman A. J-shaped relation between change in diastolic blood pressure and progression of aortic atherosclerosis. Lancet 1994;343:504e507. 8. Vagaonescu TD, Wilson AC, Kostis JB. Atrial fibrillation and isolated systolic hypertension: the systolic hypertension in the elderly program and systolic hypertension in the elderly program-extension study. Hypertension 2008;51:1552e1556. 9. Badheka AO, Rathod A, Kizilbash MA, Garg N, Mohamad T, Afonso L, Jacob S. Influence of obesity on outcomes in atrial fibrillation: yet another obesity paradox. Am J Med 2010;123:646e651. 10. Badheka AO, Rathod A, Kizilbash MA, Bhardwaj A, Ali O, Afonso L, Jacob S. Comparison of mortality and morbidity in patients with atrial
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fibrillation and heart failure with preserved versus decreased left ventricular ejection fraction. Am J Cardiol 2011;108:1283e1288. Leonardi-Bee J, Bath PM, Phillips SJ, Sandercock PA. Blood pressure and clinical outcomes in the International Stroke Trial. Stroke 2002;33: 1315e1320. Samuelsson OG, Wilhelmsen LW, Pennert KM, Wedel H, Berglund GL. The J-shaped relationship between coronary heart disease and achieved blood pressure level in treated hypertension: further analyses of 12 years of follow-up of treated hypertensives in the Primary Prevention Trial in Gothenburg, Sweden. J Hypertens 1990;8:547e555. James PA, Oparil S, Carter BL, Cushman WC, Dennison-Himmelfarb C, Handler J, Lackland DT, LeFevre ML, MacKenzie TD, Ogedegbe O, Smith SC Jr, Svetkey LP, Taler SJ, Townsend RR, Wright JT Jr, Narva AS, Ortiz E. 2014 Evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the Eighth Joint National Committee (JNC 8). JAMA 2014;311:507e520. Wyse DG, Waldo AL, DiMarco JP, Domanski MJ, Rosenberg Y, Schron EB, Kellen JC, Greene HL, Mickel MC, Dalquist JE, Corley SD. A comparison of rate control and rhythm control in patients with atrial fibrillation. N Engl J Med 2002;347:1825e1833. Corley SD, Epstein AE, DiMarco JP, Domanski MJ, Geller N, Greene HL, Josephson RA, Kellen JC, Klein RC, Krahn AD, Mickel M, Mitchell LB, Nelson JD, Rosenberg Y, Schron E, Shemanski L, Waldo AL, Wyse DG. Relationships between sinus rhythm, treatment, and survival in the Atrial Fibrillation Follow-Up Investigation of Rhythm Management (AFFIRM) Study. Circulation 2004;109: 1509e1513. Mehta K, Grover PM, Shah N, Patel NJ, Chothani A, Singh V, Savani GT, Deshmukh A, Rathod A, Patel N, Panaich SS, Arora S, Nalluri N, Khalpada D, Bhalaria V, Parmar NG, Badheka AO, Viles-Gonzalez JF, Mitrani RD. Non-influence of lipid lowering therapy in atrial fibrillation recurrence. Int J Cardiol 2013;168:5006e5007. Patel NJ, Hoosien M, Deshmukh A, Badheka AO, Grover PM, Shah N, Singh V, Mehta K, Chothani A, Savani GT, Arora S, Bhalara V, Patel N, Khalpada D, Rathod A, Vazzana TJ, Lafferty J, Viles-Gonzalez JF, Mitrani RD. Digoxin significantly improves all-cause mortality in atrial fibrillation patients with severely reduced left ventricular systolic function. Int J Cardiol 2013;169:e84ee86. Perloff D, Grim C, Flack J, Frohlich ED, Hill M, McDonald M, Morgenstern BZ. Human blood pressure determination by sphygmomanometry. Circulation 1993;88:2460e2470. Atrial Fibrillation Follow-Up Investigation of Rhythm ManagementProtocol. Version 2.2, August 10, 1998. Atrial fibrillation follow-up investigation of rhythm management—the AFFIRM study design. The Planning and Steering Committees of the AFFIRM study for the NHLBI AFFIRM investigators. Am J Cardiol 1997;79:1198e1202. Durazo-arvizu R, McGee D, Li Z, Cooper R. Establishing the nadir of the body mass index-mortality relationship: a case study. J Am Stat Assoc 1997;92:312e319. Robert B, Bendel AAA. Comparison of stopping rules in forward “stepwise” regression. J Am Stat Assoc 1977;72:46e53. Whitworth JA. 2003 World Health Organization (WHO)/International Society of Hypertension (ISH) statement on management of hypertension. J Hypertens 2003;21:1983e1992. Williams B, Poulter NR, Brown MJ, Davis M, McInnes GT, Potter JF, Sever PS, Thom SM. British Hypertension Society guidelines for hypertension management 2004 (BHS-IV): summary. BMJ 2004;328:634e640. Cooper-DeHoff RM, Gong Y, Handberg EM, Bavry AA, Denardo SJ, Bakris GL, Pepine CJ. Tight blood pressure control and cardiovascular outcomes among hypertensive patients with diabetes and coronary artery disease. JAMA 2010;304:61e68. Van Gelder IC, Groenveld HF, Crijns HJ, Tuininga YS, Tijssen JG, Alings AM, Hillege HL, Bergsma-Kadijk JA, Cornel JH, Kamp O, Tukkie R, Bosker HA, Van Veldhuisen DJ, Van den Berg MP. Lenient versus strict rate control in patients with atrial fibrillation. N Engl J Med 2010;362:1363e1373. Anderson JL, Halperin JL, Albert NM, Bozkurt B, Brindis RG, Curtis LH, DeMets D, Guyton RA, Hochman JS, Kovacs RJ, Ohman EM, Pressler SJ, Sellke FW, Shen WK, Wann LS, Curtis AB, Ellenbogen KA, Estes NA 3rd, Ezekowitz MD, Jackman WM, January CT, Lowe JE, Page RL, Slotwiner DJ, Stevenson WG, Tracy CM, Fuster V, Rydén LE, Cannom DS, Crijns HJ, Le Heuzey JY, Kay GN, Olsson
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SB, Prystowsky EN, Tamargo JL, Wann S. Management of patients with atrial fibrillation (compilation of 2006 ACCF/AHA/ESC and 2011 ACCF/AHA/HRS recommendations): a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 2013;61:1935e1944. 28. Cruickshank JM. Coronary flow reserve and the J curve relation between diastolic blood pressure and myocardial infarction. BMJ 1988;297:1227e1230.
29. Kannel WB, Wilson PW, Nam BH, D’Agostino RB, Li J. A likely explanation for the J-curve of blood pressure cardiovascular risk. Am J Cardiol 2004;94:380e384. 30. Gheorghiade M, Abraham WT, Albert NM, Greenberg BH, O’Connor CM, She L, Stough WG, Yancy CW, Young JB, Fonarow GC. Systolic blood pressure at admission, clinical characteristics, and outcomes in patients hospitalized with acute heart failure. JAMA 2006;296: 2217e2226.
a Detroit Medical Center, Detroit, Michigan; bStaten Island University Hospital, Staten Island, New York; cJackson Memorial Hospital, University of Miami Miller School of Medicine, Miami, Florida; dUniversity of Arkansas, Little Rock, Arkansas; eDrexel University School of Public Health, Philadelphia, Pennsylvania; fInternal Medicine Department, MedStar Washington Hospital Center, Washington, DC; and gCedar Sinai Medical Center, Los Angeles, California. Manuscript received April 27, 2014; revised manuscript received and accepted June 7, 2014. Dr. Badheka, Dr. Patel, Dr. Grover, and Dr. Shah contributed equally to this work. No study-specific funding was used to support this work. The authors are solely responsible for the study design, conduct and analyses, and drafting and editing of the manuscript and its final contents. See page 735 for disclosure information. *Corresponding author: Tel: (305) 243-5070; fax: (305) 243-5565. E-mail address: [email protected] (R.D. Mitrani).
0002-9149/14/$ - see front matter Ó 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.amjcard.2014.06.002
coronary artery disease (CAD), hypertension, and stroke.4e12 However, the “optimal” or “goal” BP in atrial fibrillation (AF) has never been studied in the past and had not been addressed in the Joint National Committee-8 guidelines.13 Given the loss of atrial contractility, the optimal BP in patients with AF may differ from the general population. Additionally, most medications used to treat AF, for either rhythm or rate control, result in decreased BPs. Therefore, it would be critical to define not only optimal BP but thresholds in BP below which adverse events may increase. Using patients enrolled in the Atrial Fibrillation Follow-up Investigation of Rhythm Management (AFFIRM) trial,14,15 we hypothesized that patients with AF have a U-shaped relation between BP and outcomes. Furthermore, the goal of this study was to determine the optimal BP in patients with AF and also define lower boundaries of BP control at which mortality and/or adverse events increase. Methods We performed a post hoc analysis of patients enrolled in the AFFIRM trial.14,15 The details of AFFIRM trial have been described previously.9,14e17 In brief, AFFIRM was a prospective trial (n ¼ 4,060) comparing survival in patients with AF and at least 1 risk factor for stroke randomized to a strategy of rate control (n ¼ 2,027) versus a strategy of rhythm control (n ¼ 2,033). Our inclusion criteria included subjects who had initial (baseline) BP recordings and at least 1 other BP recording during the first year of follow-up. There were 3,947 patients (with available BP data) who were included into our study sample. Patients with limited www.ajconline.org
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Table 1 Demographic and baseline characteristics (complete cohort) by average systolic blood pressure categories Variable
Age (years) Men Body mass index (kg/m2) Hypertension Coronary artery diseases Myocardial infarction Revascularization Heart failure NYHA HF class 0 1 2 3 Peripheral vascular disease Prior stroke Smoker Diabetes mellitus Pacemaker Aspirin Warfarin Lipid lowering drug Beta blocker ACE inhibitors Diuretics Other antihypertensive CCBs Digoxin (%) Amiodarone (%) Sotalol (%) Class 1 antiarrhythmic Ejection fraction* >50% 40%e49% 30%e39% <30% Ventricular septal thickness (mm)* LV posterior wall thickness (mm)* Left atrial diameters (mm)*
Systolic Blood Pressure (mm Hg)
p Value
110 (n ¼ 143)
>110 to 120 (n ¼ 426)
>120 to 130 (n ¼ 849)
>130 to 140 (n ¼ 1107)
>140 to 150 (n ¼ 854)
>150 to 160 (n ¼ 383)
>160 (n ¼ 185)
68.6 9.5 108 (75.5%) 26.3 5.4
69.0 8.4 289 (67.8%) 28.3 5.7
69.3 8.2 555 (65.3%) 28.7 5.6
69.1 8.1 673 (60.7%) 29.1 6.2
69.9 7.8 478 (55.9%) 29.5 6.1
70.4 7.9 206 (53.7%) 29.3 6.5
70.7 7.5 93 (50.2%) 29.0 5.9
0.02 <0.01 0.001
63 (44.0%) 78 (54.5%)
221 (51.8%) 190 (44.6%)
510 (60.0%) 336 (39.5%)
806 (72.8%) 396 (35.7%)
695 (81.3%) 295 (34.5%)
343 (89.5%) 138 (36.0%)
170 (91.8%) 72 (38.9%)
<0.01 <0.01
51 (35.6%) 39 (27.2%) 68 (47.5%)
104 (24.4%) 100 (23.4%) 121 (28.4%)
161 (18.9%) 175 (20.6%) 201 (23.6%)
169 (15.2%) 186 (16.8%) 220 (19.8%)
117 (13.7%) 138 (16.1%) 172 (20.1%)
62 (16.1%) 68 (17.7%) 77 (20.1%)
25 (13.5%) 32 (17.3%) 42 (22.7%)
<0.01 0.001 <0.01 <0.01
83 24 22 14 10
(58.0%) (16.7%) (15.3%) (9.7%) (7%)
323 48 46 9 33
(75.8%) (11.2%) (10.8%) (2.1%) (7.8%)
679 88 63 19 50
(79.9%) (10.3%) (7.4%) (2.2%) (5.9%)
922 108 64 13 72
(83.2%) (9.7%) (5.7%) (1.1%) (6.5%)
699 98 46 11 52
(81.8%) (11.4%) (5.3%) (1.2%) (6.1%)
316 38 25 4 39
(82.5%) (9.9%) (6.5%) (1.0%) (10.2%)
148 23 13 0 11
(80.4%) (12.5%) (7.0%) (0%) (6%)
22 26 26 17 39 124 33 42 67 74 48 30 87 29 18 12
(15.4%) (18.2%) (18.2%) (11.9%) (27.3%) (86.7%) (23.1%) (35%) (46.9%) (51.8%) (33.6%) (25%) (60.8%) (20.3%) (12.6%) (8.4%)
60 66 69 31 123 372 102 146 153 181 132 84 227 83 56 43
(14.1%) (15.5%) (16.2%) (7.3%) (28.9%) (87.3%) (23.9%) (41.6%) (35.9%) (42.5%) (31%) (23.9%) (53.3%) (19.5%) (13.2%) (10.1%)
108 101 149 56 216 712 200 242 287 335 236 219 446 136 121 104
(12.7%) (11.9%) (17.6%) (6.6%) (25.4%) (83.9%) (23.6%) (36.5%) (33.8%) (39.5%) (27.8%) (33.1%) (52.6%) (16%) (14.3%) (12.3%)
134 134 199 67 284 962 269 325 405 435 355 295 593 208 156 150
(12.1%) (12.1%) (18%) (6.1%) (25.7%) (86.9%) (24.3%) (37.9%) (36.6%) (39.3%) (32.1%) (34.4%) (53.6%) (18.8%) (14.1%) (13.6%)
121 90 192 49 214 715 175 257 343 374 278 219 434 150 140 122
(14.2%) (10.5%) (22.5%) (5.7%) (25.1%) (83.7%) (20.5%) (38.1%) (40.2%) (43.8%) (32.6%) (32.4%) (50.8%) (17.6%) (16.4%) (14.3%)
49 43 105 17 109 317 76 105 181 180 139 97 216 78 76 50
(12.8%) (11.2%) (27.4%) (4.4%) (28.5%) (82.8%) (19.8%) (36.6%) (47.3%) (47%) (36.3%) (33.9%) (56.4%) (20.4%) (19.8%) (13.1%)
30 21 51 8 52 151 39 58 106 96 69 53 89 37 33 25
(16.2%) (11.4%) (27.6%) (4.3%) (28.1%) (81.6%) (21.1%) (40.6%) (57.3%) (51.9%) (37.3%) (37.3%) (48.1%) (20%) (17.8%) (13.5%)
0.14 0.62 0.07 <0.01 0.05 0.68 0.11 0.34 0.72 <0.01 0.001 0.04 0.006 0.18 0.46 0.06 0.25 <0.01
37 (37.8%) 15 (15.3%) 21 (21.4%) 25 (25.5%) 1.0 0.2
193 (66.1%) 33 (11.3%) 32 (11%) 34 (11.6%) 1.0 0.2
490 (76.8%) 73 (11.4%) 41 (6.4%) 34 (5.3%) 1.1 0.2
632 (75.6%) 120 (14.4%) 59 (7.1%) 25 (3%) 1.1 0.2
519 (78.8%) 71 (10.8%) 50 (7.6%) 19 (2.9%) 1.1 0.2
209 (74.9%) 45 (16.1%) 19 (6.8%) 6 (2.2%) 1.1 0.2
114 (78.1%) 22 (15.1%) 8 (5.5%) 2 (1.4%) 1.1 0.2
1.0 0.2
1.0 0.1
1.1 0.2
1.1 0.2
1.1 0.2
1.1 0.2
1.1 0.2
0.002
4.4 0.7
4.4 0.7
4.3 0.7
4.3 0.6
4.3 0.6
4.3 0.6
4.2 0.6
0.05
<0.01
ACE inhibitors ¼ angiotensin-converting enzyme inhibitors; CCBs ¼ calcium channel blockers; NYHA HF class ¼ New York Heart Association heart failure class. * Echocardiographic data available for 2,948 patients (74.7% of entire study population).
or no BP data were excluded (n ¼ 113). BP measurements were consistent with the American Heart Association’s scientific statement on human BP determination by sphygmomanometer.18,19 Per study protocol, the BP was recorded in the preferred arm after the patient has been sitting quietly for at least 5 minutes.14,15,18e20 The average BP was defined as the average of all available BP measurements taken during each postbaseline visit. SBP and DBP were categorized into 10-mm Hg increments to study the association between BP and primary and
secondary clinical outcomes. The primary end point of our analysis was all-cause mortality (ACM). The secondary outcome considered was a composite of ACM and events including sustained ventricular tachycardia, ventricular fibrillation, pulseless electrical activity, concurrent AF, bradycardia, stroke, major bleeding, myocardial infarction, and pulmonary embolism. Our definitions remained consistent with the original trial.14,15 Follow-up data were available at 2, 4, 8, and 12 months and then 3 visits per year until a period of 6 years or study termination.
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Table 2 Demographic and baseline characteristics (complete cohort) by average diastolic blood pressure categories Variable
Diastolic Blood Pressure (mm Hg)
p Value
60 (n ¼ 90) >60 to 70 (n ¼ 804) >70 to 80 (n ¼ 1986) >80 to 90 (n ¼ 964) >90 (n ¼ 103) Age (years) Male gender Body mass index (kg/m2) Hypertension Coronary artery diseases Myocardial infarction Revascularization Heart failure NYHA HF class 0 1 2 3 Peripheral vascular diseases Prior stroke Smoker Diabetes mellitus Pacemaker Aspirin Warfarin Lipid lowering drug Beta blocker ACE inhibitors Diuretics Other antihypertensive CCBs Digoxin Amiodarone Sotalol Class 1 antiarrhythmic Ejection fraction* >50% 40%e49% 30%e39% <30% Ventricular septal thickness (mm)* LV posterior wall thickness (mm)* Left atrial diameters (mm)*
72.5 8.2 52 (57.8%) 26.2 6.0 57 (63.3%) 57 (63.3%) 34 (37.8%) 37 (41.1%) 52 (57.8%)
71.8 7.1 491 (61.1%) 28.0 5.6 469 (58.3%) 397 (49.4%) 206 (25.6%) 221 (27.5%) 243 (30.2%)
70.1 7.6 1,178 (59.3%) 28.8 6.0 1,390 (70%) 722 (36.4%) 316 (15.9%) 335 (16.9%) 417 (21%)
66.8 8.6 605 (62.8%) 30.1 6.0 795 (82.5%) 300 (31.1%) 121 (126%) 137 (14.2%) 167 (17.3%)
62.8 9.0 76 (73.8%) 30.6 6.5 97 (94.2%) 29 (28.2%) 12 (11.6%) 8 (7.8%) 22 (21.4%)
48 19 17 6 10 15 12 27 11 31 75 21 20 42 64 35 21 69 22 10 12
585 113 79 27 77 112 101 196 55 228 675 214 223 308 373 312 204 432 183 117 78
1,624 210 122 30 128 266 225 390 121 524 1,680 443 603 723 804 615 508 1,059 338 290 266
826 79 53 5 47 123 120 164 53 235 836 202 297 408 378 268 240 476 162 165 135
87 6 8 2 5 8 23 14 5 19 87 14 32 61 56 27 24 56 16 18 15
(53.3%) (21.1%) (18.9%) (6.7%) (11.1%) (16.7%) (13.3%) (30%) (12.2%) (34.4%) (83.3%) (23.3%) (26.7%) (46.7%) (71.1%) (38.9%) (28%) (76.7%) (24.4%) (11.1%) (13.3%)
31 (45.6%) 13 (19.1%) 10 (14.7%) 14 (20.6%) 1.1 0.2 1.0 0.2 4.5 0.6
(72.8%) (14.1%) (9.8%) (3.4%) (9.6%) (13.9%) (12.6%) (24.4%) (6.8%) (28.4%) (84%) (26.6%) (34.4%) (38.3%) (46.4%) (38.8%) (31.5%) (53.8%) (22.8%) (14.6%) (9.7%)
414 (70.2%) 77 (13.1%) 49 (8.3%) 50 (8.5%) 1.1 0.2 1.0 0.2 4.3 0.7
(81.8%) (10.6%) (6.1%) (1.5%) (6.5%) (13.4%) (11.3%) (19.6%) (6.1%) (26.4%) (84.6%) (22.3%) (38.6%) (36.4%) (40.5%) (31%) (32.5%) (53.4%) (17%) (14.6%) (13.4%)
1,122 (75.9%) 187 (12.7%) 114 (7.7%) 55 (3.7%) 1.1 0.2 1.0 0.2 4.3 0.6
(85.8%) (8.2%) (5.5%) (0.5%) (4.9%) (12.8%) (12.5%) (17%) (5.5%) (24.4%) (86.7%) (21%) (40.5%) (42.3%) (39.2%) (27.8%) (32.8%) (49.4%) (16.8%) (17.1%) (14%)
567 (77.6%) 89 (12.2%) 52 (7.1%) 23 (3.2%) 1.2 0.2 1.1 0.2 4.3 0.6
(84.5%) (5.8%) (7.8%) (1.9%) (4.9%) (7.8%) (22.3%) (13.6%) (4.9%) (18.5%) (84.5%) (13.6%) (41.6%) (59.2%) (54.4%) (26.2%) (31.6%) (54.4%) (15.5%) (17.5%) (14.6%)
60 (74.1%) 13 (16.1%) 5 (6.2%) 3 (3.7%) 1.2 0.2 1.1 0.2 4.2 0.7
0.0001 0.03 0.0001 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01
0.001 0.39 0.02 <0.01 0.12 0.04 0.5 0.008 0.04 <0.01 <0.01 <0.01 0.91 <0.01 0.002 0.27 0.06 <0.01
0.0001 0.0005 0.08
ACE inhibitors ¼ angiotensin-converting enzyme inhibitors; CCBs ¼ calcium channel blockers; NYHA HF class ¼ New York Heart Association heart failure class. * Echocardiographic data available for 2,948 patients (74.7% of entire study population).
Baseline characteristics of the study population were compared across the SBP and DBP groups by the chi-square test for categorical variables and the 1-way analysis of variance or the Kruskal-Wallis test for continuous variables, depending on the distribution of the variable. We hypothesized that if a J- or U-shaped relation is discovered between BP and outcome, it is more likely to be seen with average on-treatment follow-up BP (which is closer to the patient’s “actual” long-term BP) rather than a single baseline BP value.4 We also conducted formal tests of linearity for the relation between BP and outcomes. The R2 of the quadratic model of SBP was significantly better than that of the linear model of SBP (p <0.001). Thus, the model with SBP as a quadratic function gives a better fit. Similar results were obtained using DBP and for secondary outcome as well. Hence, we decided to define the relation between average on-treatment BP and outcomes as a quadratic
nonlinear relation. A nadir BP was calculated with the delta method, which is equal to coefficient of the linear term divided by 2 times the coefficient of the quadratic (square) term.21 The value of nadir BP was then used to determine the range of SBP and DBP at which the event rate would be the lowest, and this range of SBP (130e140 mmHg) and DBP (70e80 mmHg) was subsequently used as the referent group in the Cox proportional hazards models. We created 2 separate adjusted models using baseline BP and average on-treatment follow-up BP. The predictive value for each model was calculated using Harrell’s concordance index (C index), and a comparison was drawn between them using bootstrapping. Because the predictive value of models with average on-treatment BP was significantly better than that of baseline BP models, all subsequent mention of BP relates to average follow-up BP and not to baseline BP.
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Figure 1. Relation between blood pressure and primary outcome in the overall population. (A) Adjusted HR of the primary outcome as a function of average followup SBP categories. (B) Adjusted HR of the primary outcome as a function of average follow-up DBP categories. (C) Adjusted restricted cubic spline of the primary outcome as a function of average follow-up SBP. (D) Adjusted restricted cubic spline of the primary outcome as a function of average follow-up DBP.
Univariate Cox proportional hazards analysis was performed to investigate individual variables significantly associated with primary and secondary outcomes. Variables with p <0.2 in the initial univariate screen and those believed to be clinically relevant were included in the multivariate model.22 Initially, we constructed multivariate Cox proportional hazards models incorporating all potential confounding variables. Subsequently, we created reduced models including only variables with p <0.05 using backward regression techniques. These reduced models showed similar results and adjusted hazard ratio (HR) values compared with the full model. We decided to use the reduced model for our analysis to avoid “overfitting.” The variables included in the final multivariate models were BP group, age, history of hypertension, history of congestive heart failure (CHF), history of myocardial infarction, history of revascularization, history of stroke, history of diabetes, smoking status, use of warfarin, lipid-lowering therapy, diuretics, and randomized (rate vs rhythm) treatment group. This analysis was performed for the complete cohort and was also performed separately for the rate and the rhythm control arms. The adjusted HR for each category of BP was calculated in reference to the SBP and DBP range in which the event rate was the lowest, that is, for that group, the HR was considered as 1. We thoroughly checked for interactions and tested for collinearity using variance inflation factor, with variance inflation factor >10 signifying collinearity. No significant interactions or multicollinearity was observed. The variance inflation factor for all variables in the model was <10. To evaluate the relation between SBP (in a continuous manner) and HR of primary and secondary outcomes, we performed restricted cubic spline analysis for the Cox
proportional hazards model using the covariates listed previously. Separate subgroup analyses were also performed in important subgroups. A p value of <0.05 was considered statistically significant. All analyses were performed using the Stata software, version 11.0 (StataCorp LP, College Station, Texas). Results The baseline characteristics of the study population, stratified by average SBP and DBP ranges, are listed in Tables 1 and 2. Participants with a lower mean SBP were likely to be younger, men, and have a lower body mass index, history of CAD, and history of myocardial infarction and/or CHF. Participants with a lower mean DBP were more likely to be older, leaner, and have a history of CAD, myocardial infarction, peripheral vascular disease, and diabetes. Lower SBP and DBP were significantly associated with a decreased left ventricular ejection fraction (LVEF; <30%). Higher SBP and DBP were significantly associated with a normal LVEF (>50%). Use of angiotensinconverting enzyme inhibitors, diuretics, calcium channel blockers, and other antihypertensive drugs was associated with a higher SBP. Use of diuretics, other antihypertensive drugs, digoxin, and/or amiodarone was associated with lower DBP. The mean follow-up period was 42.4 14.7 months. C indexes of average and baseline SBP models were 0.73 (95% confidence interval [CI] 0.71 to 0.74) and 0.71 (95% CI 0.69 to 0.73), respectively. Similarly, C indexes of average and baseline DBP models were 0.72 (95% CI 0.70 to 0.74) and 0.71 (95% CI 0.69 to 0.73), respectively. The C indexes of the models with average on-treatment BP were
Table 3 Hazard ratio of primary and secondary outcomes in various subgroups compared with the reference range (130 to 140/80 to 90 mm Hg) Subgroups
Rhythm control (1,973) CAD absent (2,442) CAD present (1,505) Hypertension absent (1,139) Hypertension present (2,808) CHF absent (3,046) CHF present (901) EF 30% (2,803) EF < 30% (145)
Secondary Outcome (Hazards Ratio, (CI) p Value)
*SBP < 110
*SBP > 160
*DBP < 60
*DBP > 90
SBP < 110
SBP > 160
DBP < 60
DBP > 90
3.9 (2.9e5.4), p <0.001 4.2 (2.7e6.7), p <0.001 3.6 (2.3e5.7), p <0.001 3.0 (1.7e5.3), p <0.001 4.7 (3.1e7.0), p <0.001 3.3 (1.8e5.9), p <0.001 4.7 (3.2e6.9), p <0.001 3.3 (1.9e5.7), p <0.001 4.2 (2.7e6.4), p <0.001 4.0 (2.6e6.4), p <0.001 1.8 (0.7e4.5), p ¼ 0.22
1.9 (1.4e2.7), p <0.001 2.8 (1.7e4.6), p <0.001 1.4 (0.9e2.3), p ¼ 0.13 1.6 (0.9e2.6), p ¼ 0.09 2.3 (1.4e3.7), p <0.001 7.2 (3.2e16), p <0.001 1.6 (1.1e2.3), p ¼ 0.02 1.9 (1.2e2.9), p ¼ 0.01 2.0 (1.1e3.4), p ¼ 0.01 1.9 (1.2e2.8), p <0.001 0.7 (0.1e6.7), p ¼ 0.75
3.9 (2.8e5.3), p <0.001 4.2 (2.6e6.8), p <0.001 3.6 (2.4e5.6), p <0.001 4.8 (2.7e8.5), p <0.001 3.9 (2.6e5.6), p <0.001 2.9 (1.6e5.5), p <0.001 4.6 (3.1e6.6), p <0.001 4.7 (2.9e7.9), p <0.001 4.0 (2.6e6.1), p <0.001 3.7 (2.4e5.6), p <0.001 5.0 (2.0e13), p <0.001
1.8 (1.1e3.0), p ¼ 0.02 3.5 (1.8e6.7), p <0.001 0.9 (0.4e2.2), p ¼ 0.8 1.5 (0.7e3.3), p ¼ 0.28 2.1 (1.0e4.3), p ¼ 0.03 2.0 (0.3e15), p ¼ 0.5 1.9 (1.1e3.2), p ¼ 0.02 1.8 (0.9e3.4), p ¼ 0.07 1.8 (0.7e4.3), p ¼ 0.16 1.8 (1.0e3.4), p ¼ 0.07 6.5 (1.1e36), p ¼ 0.04
2.5 (1.9e3.3), p <0.001 2.5 (1.7e3.7), p <0.001 2.4 (1.6e3.7), p <0.001 1.9 (1.1e3.1), p ¼ 0.01 2.9 (2.0e4.2), p <0.001 2.5 (1.5e3.9), p <0.001 2.8 (1.9e4.0), p <0.001 2.1 (1.3e3.3), p <0.001 2.8 (1.9e4.1), p <0.001 2.9 (1.9e4.2), p <0.001 1.8 (0.8e4.2), p ¼ 0.16
1.4 (1.0e1.9), p ¼ 0.03 1.5 (1.0e2.3), p ¼ 0.08 1.4 (0.9e2.1), p ¼ 0.09 1.2 (0.8e1.9), p ¼ 0.33 1.6 (1.0e2.4), p ¼ 0.02 4.6 (2.1e9.8), p <0.001 1.2 (0.9e1.7), p ¼ 0.2 1.3 (0.9e1.9), p ¼ 0.12 1.5 (0.9e2.5), p ¼ 0.08 1.5 (1.0e2.1), p ¼ 0.04 0.8 (0.1e6.9), p ¼ 0.84
2.5 (1.9e3.3), p <0.001 2.2 (1.4e3.5), p <0.001 2.7 (1.8e4.0), p <0.001 2.7 (1.6e4.6), p <0.001 2.6 (1.8e3.7), p <0.001 1.9 (1.1e3.4), p ¼ 0.02 3.0 (2.1e4.2), p <0.001 2.4 (1.5e3.9), p <0.001 2.9 (2.0e4.2), p <0.001 2.4 (1.6e3.6), p <0.001 5.2 (2.2e12), p <0.001
1.5 (1.0e2.3), p ¼ 0.04 2.1 (1.2e3.6), p ¼ 0.01 1.2 (0.6e2.2), p ¼ 0.61 1.2 (0.6e2.1), p ¼ 0.62 2.0 (1.1e3.6), p ¼ 0.01 5.3 (1.6e17), p ¼ 0.01 1.4 (0.9e2.2), p ¼ 0.01 1.3 (0.8e2.2), p ¼ 0.28 2.1 (1.0e4.3), p ¼ 0.03 1.7 (1.0e2.7), p ¼ 0.04 3.6 (0.7e19), p ¼ 0.12
Systemic Hypertension/Blood Pressure Control and Atrial Fibrillation
Complete cohort (3,947) Rate control (1,974)
All-Cause Mortality (Hazards Ratio, (CI) p Value)
Model was adjusted for age, history of hypertension, history of congestive heart failure, history of myocardial infarction, history of revascularization, history of stroke, history of diabetes, smoking status, use of warfarin, lipid-lowering therapy, diuretics, and randomized (rate vs rhythm) treatment group. We did not include the subgroup variable in the model while carrying out the multivariate model for particular subgroup of interest, for example, history of CAD was not included in the model for subgroup analysis in CAD present and CAD absent subgroups. CAD ¼ coronary artery disease; CHF ¼ congestive heart failure; DBP ¼ diastolic blood pressure; EF ¼ ejection fraction; SBP ¼ systolic blood pressure. * Referent groups for systolic and diastolic blood pressures were 130 to 140 mm Hg and 70 to 80 mm Hg, respectively.
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Figure 2. Relation between blood pressure and secondary outcome in the overall population. (A) Adjusted HR of the secondary outcome as a function of average followup SBP categories. (B) Adjusted HR of the secondary outcome as a function of average follow-up DBP categories. (C) Adjusted restricted cubic spline of the secondary outcome as a function of average follow-up SBP. (D) Adjusted restricted cubic spline of the secondary outcome as a function of average follow-up DBP.
Figure 3. Figure showing the relation between BP and primary outcome in the rate control group. (A) Adjusted HR of the primary outcome as a function of average follow-up SBP categories in the rate control group. (B) Adjusted HR of the primary outcome as a function of average follow-up DBP categories in the rate control group. (C) Adjusted restricted cubic spline of the primary outcome as a function of average follow-up SBP in the rate control group. (D) Adjusted restricted cubic spline of the primary outcome as a function of average follow-up DBP in the rate control group.
significantly better than those of models with baseline BP (p values of 0.02 and 0.007 for SBP and DBP, respectively). The nadir BP (SBP and/or DBP) for the complete cohort resulting in the lowest ACM was calculated to be 140/ 78 mm Hg.
Of the 3,947 participants, ACM was observed in 614 participants (15.6%). The relation between average SBP and ACM followed a U-shaped relation with increased event rates at the low and high SBP ranges (Figure 1 and Table 3). After adjusting for baseline covariates compared with the
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Figure 4. Figure showing the relation between BP and primary outcome in the rhythm control group. (A) Adjusted HR of the primary outcome as a function of average follow-up SBP categories in the rhythm control group. (B) Adjusted HR of the primary outcome as a function of average follow-up DBP categories in the rhythm control group. (C) Adjusted restricted cubic spline of primary outcome as a function of average follow-up SBP in the rhythm control group. (D) Adjusted restricted cubic spline of primary outcome as a function of average follow-up DBP in the rhythm control group.
reference group (average SBP ¼ 130 to 140 mm Hg), the risk of ACM (complete cohort) increased by 3.9 fold (p <0.001) in the group with SBP 110 mm Hg and by 1.9 fold (p <0.001) in the group with SBP >160 mm Hg. This U-shaped relation was not observed only when the baseline SBP was used (Supplementary Figure 1). This relation remained unchanged when the analysis was repeated for patients after accounting for LVEF (Supplementary Table 1). The group with average SBP <110 mm Hg actually had greater mortality than the group with average SBP >160 mm Hg (HR 3.9, p <0.001). The relation between average DBP and ACM also followed a U-shaped relation with increased event rates at both the low and high DBP ranges. After adjusting for baseline covariates compared with the reference group (average DBP >80 to 90 mm Hg), the risk of ACM (complete cohort) increased by 3.9 fold (p <0.001) in the group with DBP 60 mm Hg and by 1.8 fold (p ¼ 0.02) in the group with DBP >90 mm Hg. The U-shaped relation was not observed only when the baseline DBP was used (Supplementary Figure 1). The group with average DBP 60 mm Hg actually had greater ACM than the group with average DBP >90 mm Hg (HR 3.9, p <0.001). Of the 3,947 participants, at least one of the composite end points comprising the secondary outcome was observed in 971 subjects (24.6%). A similar U-shaped relation with secondary outcome was found for average SBP and DBP (Figure 2). After adjusting for baseline covariates, compared with the reference group (average SBP ¼ 130 to 140 mm Hg, DBP ¼ 80 to 90 mm Hg), the risk of secondary outcome (complete cohort) increased by 2.4 fold (p <0.001) in the group with SBP 110 mm Hg and by 1.5 fold (p ¼ 0.02) in the group with SBP >160 mm Hg. Similarly, the risk of secondary outcome
(complete cohort) increased by 2.5 fold (p <0.001) in the group with DBP 60 mm Hg and by 1.5 fold (p ¼ 0.04) in the group with DBP >90 mm Hg (Figure 2). Subgroup analyses were performed on the rate and rhythm control arms (Table 3 and Figures 3 and 4). Additionally, subgroup analyses were performed on patients stratified by the presence or absence of CAD, hypertension, and CHF. A subgroup analysis was also performed on patients stratified by ejection fraction (EF) <30% versus those with EF 30% (Table 3). SBP: In patients with average SBP <110 mm Hg, all subgroups showed a statistically significant increase in ACM (HR range 3.0 to 4.7) except for those with EF <30% in which there was a nonstatistical trend toward increase in mortality (Table 3). In patients with average SBP >160 mm Hg, all subgroups, except for those assigned to rhythm control, those without CAD, and those with EF <30%, showed a statistically significant increase in ACM (HR 1.6 to 7.2; Table 3). DBP: In patients with average DBP <60 mm Hg, the ACM was significantly increased for all patient subgroups (Table 3). In patients with average DBP >90 mm Hg, there was a significant increase in ACM in the following subgroups: rate control, CAD, hypertension, and EF <30% (Table 3). Discussion The main finding of this study is the demonstration of a U-shaped relation between average BP (SBP and DBP) and ACM in patients with AF. This U-shaped relation was also observed with the composite secondary end points.
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Additionally, this study demonstrated significantly increased mortality and secondary events in patients with average SBP <110 mm Hg and DBP <60 mm Hg; this finding has implications for lower boundaries of BP, which may serve to limit pharmacologic rate and rhythm control drug therapies. Based on this post hoc analysis of the AFFIRM data set, the optimal BP associated with the lowest mortality (nadir) was 140/78 mm Hg. The “optimal” or “goal” BP in AF has never been studied in the past and had not been addressed in the Joint National Committee-8 guidelines.13 The current guidelines on hypertension therapy recommend tight control of BP.1,13,23,24 However, it has been recognized that tight control of BP (SBP <130 mm Hg) over a standard control of BP (SBP 130 to 140 mm Hg) has no benefit in patients with CAD or diabetes.25 Our study was based on a population of patients with AF who were elderly or are believed to have at least 1 risk factor for thromboembolic events.14,15 There was a significantly greater mortality for patients with average BP (SBP/DBP) <110/60 mm Hg compared with average BPs in the range of 130 to 140/70 to 80 mm Hg, which was the optimal range of BPs in this study. This finding has implications guiding the use and dosing of calcium channel blockers and b blockers, including sotalol, which may cause a significant BP decrease.14,15 Because there are no clinical practice guidelines recommending the lower boundary of BP that should limit rate and/or rhythm control use, the practitioner will rely on clinical judgment when using and dosing these drugs. These medications may be titrated to BPs <110/60 mm Hg to achieve the goal of rate or rhythm control. Across the cohort and almost all subgroups (Figures 1 to 4 and Table 3), there was a greater HR observed for the very low BPs (SBP/DBP <110/60 mm Hg) compared with optimal BP control. Because many of our therapies for AF include BP-lowering medications (rate or rhythm control), and many patients have concomitant hypertension requiring therapy, this raises the question as to whether we may be harming some patients with excessive pharmacologic therapy. Strict rate control has not been shown to be superior to lenient rate control.26 Perhaps, it can be speculated that lower BPs associated with the increased use of rate control drugs to achieve strict rate control may have negated any potential actual benefit of a stricter rate control strategy. Although future prospective studies may provide the actual optimal BP control in patients with AF, this study raises the question of whether rate and/or rhythm control drug therapies should be limited to avoid SBPs <100 to 110 mm Hg and DBPs <60 to 70 mm Hg. Given the findings that strict rate control is not superior to lenient rate control26 and that strict rate control is not recommended by the recent guidelines on AF treatment,27 the use of less rate control medication should facilitate avoidance of relative hypotension. The subgroup analysis of the rate and rhythm control arms demonstrated similar results. Those with the lowest BPs appeared to have the highest mortality and incidence of secondary outcomes regardless of the strategy used to control the AF. The possible explanation for the adverse events and low DBP may be related to the diminished coronary blood flow to the myocardial and subendocardial layers in the setting of AF (limited coronary reserve). This may increase the risk of ventricular ischemia and
mortality.28,29 We found a low DBP associated with increased ACM in patients regardless of CAD (Table 3). In patients with low average DBP, all subgroups showed an increase in ACM or a trend in increase in ACM in the subgroups without hypertension or CHF. Secondary outcomes were increased for all patient subgroups with average DBP <60 mm Hg (Table 3), thereby supporting the notion that excessively low DBPs may be associated with adverse outcomes in patients with AF. The relation between low SBP and mortality seems more complex. Increased risk of ischemic stroke may occur with low SBP.7 Potential confounders such as CAD and hypertension may also contribute to this finding. However, the U-shaped relations in AF were independent of the history of CAD and hypertension (Table 3). Lower SBP in CHF has been shown to be associated with a greater mortality.30 We found an increase in ACM and secondary outcomes in those patients with a history of CHF and low SBP. There was a trend toward increased ACM or secondary outcomes for those patients with EF <30%. The threshold for low SBP of 110 mm Hg may not have been sufficiently low to identify a high-risk group in those with EF <30%. Also because of a lack of LVEF data in the entire cohort, only 145 patients had reported EF <30%, which limits the power of a statistical analysis. In contrast, the low average DBP threshold of 60 mm Hg did identify a group of patients with clinical CHF and patients with low EF with increased ACM and secondary outcomes. Although low BPs were associated with adverse outcomes in both the rate and rhythm control groups, the higher BPs were associated with disparate responses. In the rhythm control arm, there were nonsignificant trends of increase in ACM and composite secondary outcomes for SBP >160 mm Hg and no difference in ACM or secondary outcomes for DBP >90 mm Hg (Table 3). In contrast, in the rate control arm, there was an increase in ACM in patients with SBP >160 and DBP >90 mm Hg and an increase in secondary outcomes in patients with DBP >90 mm Hg. The results from this study cannot explain this discrepancy in association between rate and rhythm control and the higher BPs. It is possible that higher BPs lead to more adverse outcomes in patients who are more likely to be in AF (rate control) compared with patients more likely to be in sinus rhythm (rhythm control). Alternatively, the higher BPs may reflect increased sympathetic tone and/or inadequate rate control in a sicker subgroup more susceptible to adverse outcomes. Although there was discrepancy in associations between high BPs and ACM in the rate and rhythm control, clearly, the lower BPs were associated with deleterious outcomes in both groups. As the findings were generated from a post hoc analysis, any causal relation cannot be proved from these results. Therefore, there were a significant number of patients in sinus rhythm for long periods in either rate or rhythm control arms. This could have also caused an error in the calculation of the average BP measurement as the presence of sinus rhythm has been shown to lower BP reading in patients with AF. Because of the limited number of patients in the group EF <30% (n ¼ 145) and other subgroups, the power for statistical analysis was limited with wide CIs observed in most of these subgroups. Despite the
Systemic Hypertension/Blood Pressure Control and Atrial Fibrillation
comprehensive analysis adjusting for several possible confounders in the relation between BP and outcomes, it is still possible that the statistical adjustments may not have accounted for some unknown confounders, leading to a possibility of residual confounding. Acknowledgment: The authors acknowledge Dr. George Wyse, MD, PhD, University of Calgary, Alberta, Canada, and Dr. Albert L. Waldo, MD, Case Western Reserve University, Cleveland, Ohio, regarding the help on accessing the “AFFIRM Manual of Operations on recording of BP.” The authors also acknowledge Dr. Sean Coady, MD, and Dr Kevin Purkiser, PhD, from the National Heart Lung and Blood Institute (NHLBI). None of the authors are affiliated with the NHLBI or were part of the AFFIRM trial.
11. 12.
13.
14.
15.
Disclosures Dr. Mitrani has consultant relationship with Medtronic (modest) and St. Jude Medical (modest), neither of which is relevant to this article. None of the other listed authors have any disclosures or potential conflict of interest.
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