Abstract
To evaluate the impact of blood pressure variability (BPV) on cardiovascular outcomes in patients with acute coronary syndrome, short‐term BPV was estimated by using weighted standard deviation of 24‐hour ambulatory blood pressure monitoring readings. The primary outcome was in‐hospital major adverse cardiac events (MACE). Overall, 200 patients (mean age, 58.6 years; 27.5% women; 38% with diabetes mellitus; and 47% smokers) were divided into low and high BPV groups based on the median value (9.45). Patients in the high BPV group were more likely to have in‐hospital MACE compared with patients with low BPV (47% vs 27%, P = .003). Multivariate binary logistic regression analysis of incidence of MACE showed that BPV (odds ratio, 2.4; confidence interval, 1.2–4.5 [P = .008]) and presence of type II diabetes mellitus (odds ratio, 2.6; confidence interval, 1.2–5.3 [P = .008]) were the only independent predictors of in‐hospital MACE derived mainly by hypertensive emergencies. BPV could be an important risk factor for in‐hospital MACE in patients with acute coronary syndrome.
Keywords: acute coronary syndrome, ambulatory BP monitoring, blood pressure variability, cardiovascular outcome
1. INTRODUCTION
Hypertension and its effect on target organ damage have been extensively established in clinical practice. Overall, each increase in systolic blood pressure (SBP) of 20 mm Hg (or each 10‐mm Hg increase in diastolic blood pressure [DBP]) doubles the risk of a fatal coronary event and stroke.1, 2
Currently, blood pressure variability (BPV) is considered a novel risk factor for cardiovascular disease. BPV is multifaceted and includes both short‐term (in the range of minutes to hours) and long‐term (within days and months) variations. It can be estimated by different blood pressure (BP) devices (mainly ambulatory BP monitoring [ABPM]) using different calculation and statistical methods (mainly weighted standard deviation or average real variability).3, 4
In recent years, many clinical trials proposed that short‐ or long‐term BPV independently affects target organ damage, cardiovascular events, and mortality, not only in patients with hypertension but also in patients with diabetes mellitus, chronic kidney disease, and obstructive sleep apnea5 Consequently, amelioration of BPV has been suggested as an additional target of therapy in patients with cardiovascular diseases.6, 7 There is also increasing focus on the identification of the novel risk markers that are associated with high BPV, eg, serum uric acid level8 and locomotive syndrome.9
On the other hand, patients with acute coronary syndrome (ACS) often show vasomotor instability, which increases the tendency of exaggerated responses to antihypertensive treatment, with BP fluctuating up and down early during ACS management.10 Bearing in mind the controversial issues of the clinical significance of BPV in cardiovascular diseases and the lack of studies on the effect of BPV in patients with ACS, the aim of our work was to evaluate the impact of BPV on cardiovascular outcomes in patients with ACS.
2. PATIENTS AND METHODS
2.1. Patient selection
Patients with ACS were included in the study if they met the following criteria: (1) they presented with typical anginal pain lasting for >30 minutes; (2) there was ST‐segment elevation or depression of at least 1 mm in at least two contiguous electrocardiography leads or new onset of complete left bundle branch block; and (3) they had positive troponin elevation. Exclusion criteria were morbid obesity or handicap that inhibited the ability of ABPM placement, chronic obstructive airway disease, clinical hemodynamic or electrical instability, chronic renal impairment (estimated glomerular filtration rate <60 mL/min), history of secondary hypertension, or congestive heart failure.
2.2. Study design
Between March 2015 and June 2016, this prospective cohort study included 920 patients who were admitted to the coronary care unit of an urban university hospital in Northern Africa. A total of 300 patients were excluded because of negative troponin results (n = 190) or comorbidities (n = 110). We were not able to offer the ABPM to 200 patients for logistical reasons (eg, not enough time to prepare the protocol, busy nurses, lack of devices, study staff unavailable). Of the 320 patients who were offered the ABPM, 75 were unable to complete the study (recently experienced unusual chest pain or did not think they were able to bear the pain of cuff inflation) and 45 had incomplete data. These 120 patients were excluded because they did not complete the ABPM, leaving 200 participants for this analysis (Figure 1).
Figure 1.
Flow chart of the study. ABPM indicates ambulatory blood pressure monitoring; ACS, acute coronary syndrome; Pts, patients
2.3. Study population
We enrolled 200 consecutive patients who fulfilled the inclusion and exclusion criteria for this study. Demographic characteristics, medical history, and smoking status were assessed. We measured weight, resting BP, and heart rate. All patients included in the study were treated according to the recent European Society of Cardiology guidelines for the management of ST‐segment elevation myocardial infarction (STEMI)11and non‐STEMI.12 After the initial event, all patients received acetyl salicylic acid (150 mg/d) indefinitely, clopidogrel (75 mg/d) for 1 year, and other medications, including β‐blockers, angiotensin‐converting enzyme inhibitors, nitrates, and statins, were prescribed according to standard guidelines. The study protocol was approved by the ethical committee of Assiut University Faculty of Medicine and written informed consent was obtained from all participants. The consent form was designed with an explanation on the purpose and conduction of this research study. In the present study, diabetes mellitus was defined as having a fasting glucose level ≥126 mg/dL and/or a glycated hemoglobin level ≥6.5% (in National Glycohemoglobin Standardization Program units) or being treated with one or more antidiabetic medications. Hyperlipidemia was defined as having a total cholesterol level ≥240 mg/dL or being treated with one or more antihyperlipidemic medications. A history of cardiovascular disease was defined as having had one or more of the following: angina pectoris, myocardial infarction, heart failure, aortic dissection, or stroke. Chronic kidney disease was defined as estimated glomerular filtration rate (<60 mL/min/1.73 m2 and/or the presence of proteinuria. Current smoking was defined as smoking at the time of study enrollment or within the prior year.
2.4. Ambulatory BP monitoring
All 200 patients were fitted with the ABPM devices (Contec model ABPM 50, Germany and Reynolds ABPM) for 24 hours within the first 2 days after cardiac care unit admission. The device was programmed to obtain BP readings at 30‐minute intervals during the day (6 am–11 pm) and at 45‐minute interval during the night (11 pm–6 am). Mean SBP, DBP, mean arterial pressure, and BP load values were obtained for the full 24‐hour, daytime, and nighttime periods.13 Hypertension was diagnosed when office SBP was ≥140 mm Hg and/or DBP was ≥90 mm Hg on at least two separate occasions, or by a previous diagnosis of hypertension with current antihypertensive medication use. The criteria for good‐quality ABPM to be included in the study were the following: (1) approximately 75% to 80% valid readings should be obtained with the other traditional criteria and the ABPM device should be calibrated against a mercury‐column sphygmomanometer to verify that the SBP and DBP agree within about 5 mm Hg; and (2) patients should be educated regarding the use of the ABPM at device hookup. For example, the patient needs to be aware that when the actual readings are being measured, the arm should be held motionless to avoid artifact and repetitive readings.
2.5. Calculation of BPV indices
2.5.1. Dipping status
Normal dippers are defined as patients with an average night BP decrease of 10% to 20% of the average daytime BP. Nondippers are those with an average night BP decrease of 0% to 10% of the average daytime BP. Extreme dippers are patients with an average night BP decrease of >20% of the average daytime BP. Meanwhile, reversed dippers are patients with an average night BP higher than the average daytime BP.14
2.5.2. BPV index
BPV index was defined as the weighted standard deviation (SD) of 24‐hour BP, daytime BP, and nighttime BP (SBP and DBP). As measures of short‐term reading‐to‐reading BPV, we used the SD over 24 hours weighted for the time interval between consecutive readings (SD24) and the average of the daytime and nighttime SDs weighted for the duration of the daytime and nighttime interval (SDdn). The SDdn is the mean of day and night SD values corrected for the number of hours included in each of these two periods, according to the following formula: SDdn = ([day SD × hours included in the daytime] + [night SD × hours included in the nighttime])/(hours included in daytime+nighttime).This method removes the influence of the day‐night BP difference from the estimate of BPV.3 All ABPM data were entered into an Excel file for each patient separately to calculate the formula by an independent investigator who was not aware of the clinical data of each patient.
2.6. Outcome ascertainment
All patients were followed up for an average of 7 days during their hospital stay. Clinical outcome was evaluated through the monitoring of major adverse cardiac events (MACE) occurring at any time during in‐hospital follow‐up. Only the most serious event of MACE was used to calculate the cumulative MACE per patient according to the following sequence: death >myocardial reinfarction>shock>cerebrovascular stroke>heart failure>hypertensive crisis>life‐threatening arrhythmia. Death was defined as all‐cause death at follow‐up. Myocardial reinfarction during follow‐up was defined as a troponin T increase >0.03 μg/L with symptoms or percutaneous coronary intervention, or a re‐rise of troponin T > 25% after recent myocardial infarction in the presence of symptoms or re‐PCI, or the development of new Q waves on electrocardiography.15 Heart failure during follow‐up was defined as either the presence of rales in more than one third of the lung fields that did not clear with coughing or evidence of pulmonary edema on chest x‐ray.11 Cardiogenic shock was defined by sustained low BP with tissue hypoperfusion.16 Cerebrovascular stroke, either ischemic or hemorrhagic, was defined as poor blood flow to the brain resulting in cell death.17 Hypertensive crisis was defined as severely elevated BP >180/110 mm Hg in the sitting of ACS.18 Life‐threatening arrhythmias included ventricular tachycardia, ventricular fibrillation, and complete heart block.15
3. STATISTICAL ANALYSIS
Categorical data are presented as counts and proportions (percentages) and compared by Pearson chi‐square analysis or Fisher exact test if the expected cell count for a 2 × 2 table was <5. Normal distribution of continuous data was tested using a Kolmogorov‐Smirnov test. Continuous and normally distributed data are presented as mean ± 1 SD and were compared by two‐tailed unpaired t tests. Correlations were performed by Spearman correlation coefficient test. Univariable and multivariable binary logistic regression models were performed to characterize predictors of MACE. Multivariable regression was performed using only variables with a probability value <.05 at univariable regression analysis. Univariable regression analyses were performed using all clinical and ABPM indices. The cutoff value of BPV index that identifies, with the highest sensitivity and specificity, patients with high risk of MACE was analyzed by receiver operating characteristic curve. All P values were 2‐tailed, and statistical significance was defined as P < .05. All analyses were performed with SPSS version 16.0 (SPSS Inc).
4. RESULTS
We divided the 200 patients into low and high BPV groups based on our study group median value (median value of BPV = 9.45 mm Hg). Each group was comprised of 100 patients. The difference between the two groups in demographic data is shown in Table 1. Patients with high BPV more frequently had hypertension with NSTEMI and more frequently took diuretic and angiotensin receptor blocker therapy. BPV index was higher in the high BPV group than in the low BPV group (12.7 vs 7.3, respectively; P < .001) (Table 2).
Table 1.
Baseline characteristics of the study population
| Variable | All patients (N = 200) | Low BPV group (n = 100) | High BPV group (n = 100) | P valuea |
|---|---|---|---|---|
| Age, mean±SD, y | 58.6 ± 10.4 | 57.7 ± 10.9 | 59.5 ± 9.9 | .23 |
| Women, No. (%) | 55 (27.5) | 24 (24) | 31 (31) | .26 |
| Smoking | 94 (47) | 44 (44) | 50 (50) | .34 |
| DM | 77 (38) | 36 (36) | 41 (41) | .46 |
| Known hypertension | 100 (50) | 41 (41) | 59 (59) | .011b |
| Dyslipidemia | 50 (25) | 24 (24) | 26 (26) | .43 |
| Family history | 40 (20) | 23 (23) | 17 (17) | .43 |
| Known IHD | 79 (39) | 35 (35) | 44 (44) | .19 |
| Presenting with ACS, No. (%) | ||||
| STEMI | 124 (62) | 70 (70) | 54 (54) | .02b |
| Non‐STEMI | 76 (38) | 30 (30) | 46 (46) | |
| Weight, kg | 73.9 ± 9.4 | 73.9 ± 7 | 72.7 ± 5 | .56 |
| Systolic BP, mm Hg | 133 ± 34 | 132 ± 29 | 129 ± 32 | .46 |
| Diastolic BP, mm Hg | 78 ± 25 | 80 ± 24 | 77 ± 33 | .52 |
| Pulse rate, beats per min | 88 ± 24 | 89 ± 18 | 86 ± 21 | .44 |
| Antihypertensive drug, No. (%) | ||||
| No treatment | 30 (15) | 14 (14) | 16 (16) | .56 |
| Diuretics | 40 (20) | 8 (8) | 32 (32) | .004b |
| β‐Blocker | 46 (23) | 16 (16) | 30 (30) | .07 |
| CCBs | 20 (10) | 10 (10) | 10 (10) | .98 |
| ACEIs | 78 (39) | 40 (40) | 38 (38) | .88 |
| ARBs | 36 (18) | 10 (10) | 26 (26) | .04b |
Data are presented as mean ± standard deviation, number (percentage) of patients, or median (interquartile range) (n = 100 for each group).
Abbreviations: ACEIs, angiotensin‐converting enzyme inhibitors; ACS, acute coronary syndrome; ARBs, angiotensin receptor blockers; CCBs, calcium channel blockers; DM, diabetes mellitus; IHD, ischemic heart disease; STEMI, ST‐segment elevation myocardial infarction.
Between low and high blood pressure (BP) variability (BPV) groups.
Statistically significant difference.
Table 2.
BPV indices and MACE in the study groups
| Variable | All patients (N = 200) | Low BPV group | High BPV group | P valuea |
|---|---|---|---|---|
| BPV index (weighted systolic SD day‐night) | 9.9 ± 3.6 | 7.3 ± 1.6 | 12.7 ± 3.1 | <.001b |
| SD of day systolic readings | 11.4 ± 4.9 | 8.7 ± 2.8 | 13.5 ± 5.3 | .001b |
| SD of day diastolic readings | 7.8 ± 2.9 | 7.0 ± 1.9 | 8.5 ± 3.4 | .11 |
| SD of night systolic readings | 10.5 ± 4.6 | 8.2 ± 3.1 | 12.4 ± 4.8 | .003b |
| SD of night diastolic readings | 7.7 ± 2.9 | 6.0 ± 1.8 | 9.0 ± 3.1 | .001b |
| SD of total systolic readings | 11.9 ± 3.9 | 9.3 ± 2.9 | 14.0 ± 3.4 | .0001b |
| SD of total diastolic readings | 8.2 ± 2.6 | 6.8 ± 1.4 | 9.3 ± 2.8 | .001b |
| MACE, No. (%) | ||||
| Cumulative MACE | 74 (37) | 27 (27) | 47 (47) | .003b |
| Mortality | 9 (4.5) | 6 (6) | 3 (3) | .30 |
| Shock | 14 (7) | 7 (7) | 7 (7) | 1 |
| Cerebrovascular stroke | 4 (2) | 2 (2) | 2 (2) | 1 |
| Hypertensive crisis | 18 (9) | 0 (0) | 18 (18) | <.001b |
| Pulmonary edema | 28 (14) | 14 (14) | 14 (14) | 1 |
| Arrhythmia | 25 (12.5) | 12 (12) | 13 (13) | .83 |
| LV dysfunction | 18 (9) | 9 (9) | 9 (9) | 1 |
| Reinfarction | 9 (4.5) | 7 (7) | 2 (2) | .08 |
Data are presented as mean ± standard deviation (SD) or number (percentage) of patients (n = 100 for each group).
Abbreviations: LV, left ventricular; MACE, major adverse cardiovascular events.
Between low and high blood pressure variability (BPV) groups.
Statistically significant difference.
All parameters of ABPM were significantly higher in the high BPV group, and 21 patients (10.5%) were normal dippers. Nine patients (4%) died and 74 patients (37%) had in‐hospital MACE (Table 2).
There was a significantly positive correlation between BPV index and the incidence of MACE (r = .56, P = .003) (Figure 2). This correlation was found in both patients with and without hypertension separately (Table 3).
Figure 2.
Direct proportion between blood pressure variability index and incidence of in‐hospital major adverse cardiac events. BP indicates blood pressure; MACE, major adverse cardiovascular events
Table 3.
BPV index and MACE in patients with and without hypertension
| Nonhypertension (n = 100) | Hypertension (n = 100) | |||
|---|---|---|---|---|
| No MACE (n = 72) | MACE (n = 28) | No MACE (n = 54) | MACE (n = 46) | |
| BPV index | 8.63 ± 2.47 | 11.84 ± 4.43 | 9.19 ± 2.34 | 11.87 ± 4.67 |
| P value | <.001a | <.001a | ||
Abbreviations: BPV, blood pressure variability; MACE, major adverse cardiovascular events.
Statistically significant difference.
All variables that could affect in‐hospital MACE were examined using univariate analysis, then only age, sex, diabetes mellitus, hypertension, ischemic heart disease, ACS presentation, and nondipping status were included in the multivariate binary logistic regression analysis for the whole group to identify the best predictor. Further covariate subanalysis of the effect of BPV on MACE in patients presenting with STEMI and non‐STEMI separately are shown in Table 4. Multivariate binary logistic regression analysis of incidence of MACE showed that BPV (odds ratio, 2.4; confidence interval, 1.2–4.5 [P = .008]) and presence of type II diabetes mellitus (odds ratio, 2.6; confidence interval, 1.2–5.3 [P = .008]) were the only independent predictors of in‐hospital MACE either in patients with STEMI or those with non‐STEMI, not only in patients with hypertension but also in patients without hypertension.
Table 4.
Predictors of MACE in the study group, determined by multivariate binary logistic regression analysis: subgroup analysis of patients with NSTEMI and STEMI
| Beta (SE) | 95% CI for odds ratio | P value | |||
|---|---|---|---|---|---|
| Lower | Odds ratio | Upper | |||
| Age | 0.04 (0.02) | 1.004 | 1.038 | 1.073 | .028a |
| Sex | 0.04 (0.37) | 0.501 | 1.036 | 2.143 | .924 |
| DM | 0.96 (0.36) | 1.291 | 2.623 | 5.330 | .008b |
| Hypertension | 0.01 (0.38) | 0.482 | 1.010 | 2.116 | .979 |
| Known IHD | 0.75 (0.39) | 0.993 | 2.122 | 4.535 | .052 |
| Presenting with ACS | 0.28 (0.39) | 0.619 | 1.318 | 2.808 | .474 |
| Absent dipping | 0.13 (0.52) | 0.409 | 1.141 | 3.182 | .800 |
| Day systolic BP >140 mm Hg | 1.22 (0.69) | 0.865 | 3.401 | 13.36 | .079 |
| Early morning surge >50 mm Hg | −0.37 (0.46) | 0.276 | 0.686 | 1.704 | .417 |
| BPV index | 0.88 (0.33) | 1.255 | 2.401 | 4.590 | .008b |
| NSTEMI patients only | |||||
| Age | 0.07 (0.03) | 1.002 | 1.073 | 1.149 | .041a |
| DM | 1.30 (0.61) | 1.113 | 3.688 | 12.220 | .032a |
| BPV index | 1.52 (0.61) | 1.383 | 4.570 | 15.097 | .012a |
| STEMI patients only | |||||
| DM | 1.02 (0.50) | 1.037 | 2.777 | 7.437 | .042a |
| Known IHD | 1.04 (0.49) | 1.079 | 2.84 | 7.473 | .034a |
| BPV index | 0.91 (0.45) | 1.020 | 2.497 | 6.116 | .0451a |
Abbreviations: ACS, acute coronary syndrome; Beta, beta coefficients; BP, blood pressure; BPV, blood pressure variability; CI, confidence interval; DM, diabetes mellitus; IHD, ischemic heart disease; MACE, major adverse cardiovascular events; NSTEMI, non–ST‐segment elevation myocardial infarction; STEMI, ST‐segment elevation myocardial infarction.
Results are presented as mean ± standard error (SE).
Statistically significant difference (P < .05).
Statistically significant difference (P < .01).
Using receiver operating characteristic curves, the highest specificity (98.4%) for the identification of patients with high in‐hospital MACE risk were attained for BPV index (weighted SDdn) value of 12.6 mm Hg. The sensitivity for this cutoff value was 47.3% and the area under the curve was 0.86 (95% confidence limit, 0.77–0.95).
To assess the relationship between BPV and each complication included in MACE, we performed additional analysis on our data using a cutoff value between the low and high BPV groups (>12.6 mm Hg from our receiver operating characteristic curve analysis). This showed that there were a significant difference between high and low BPV in patients with hypertensive crisis, LV dysfunction, and pulmonary edema (Table 5).
Table 5.
BPV indices and MACE in the study groups
| Variable | All patients (N = 200) | Low BPV group (<12.6 mm Hg) (n = 163) | High BPV group (>12.6 mm Hg) (n = 37) | P valuea |
|---|---|---|---|---|
| Cumulative MACE | 74 (37) | 39 (23) | 35 (94.6) | <.001b |
| Mortality | 9 (4.5) | 8 (5) | 1 (2.7) | .561 |
| Shock | 14 (7) | 11 (6.7) | 3 (8.1) | .771 |
| Cerebrovascular stroke | 4 (2) | 3 (1.8) | 1 (2.7) | .727 |
| Hypertensive crisis | 18 (9) | 1 (0.6) | 17 (45.9) | <.001b |
| Pulmonary edema | 28 (14) | 19 (11.6) | 9 (24.3) | .045c |
| Arrhythmia | 25 (12.5) | 19 (11.6) | 6 (16.2) | .447 |
| LV dysfunction | 18 (9) | 10 (6.1) | 8 (21.6) | .002b |
| Reinfarction | 9 (4.5) | 8 (4.9) | 1 (2.7) | .561 |
Abbreviations: LV, left ventricular; MACE, major adverse cardiovascular events.
Data are expressed as number (percentage) of patients (n = 100 for each group).
Between the low and high blood pressure variability (BPV) groups.
Statistically significant difference.
5. DISCUSSION
To our knowledge, this is one of the first studies to investigate the impact of BPV measured by ABPM in patients with ACS. In this study, we found that short‐term BPV is an independent predictor of in‐hospital MACE in patients with ACS, either with STEMI or non‐STEMI, not only in those with hypertension but also in those without hypertension.
The BP fluctuation and variability during ACS has been presented as a finding during management of these critically ill patients.10 Therefore, in our study, we investigated the impact of BPV analysis using ABPM during first 2 days of admission as a new risk factor for in‐hospital MACE.
The results of our study are in agreement with those of Frattola and colleagues19 in 1993, which constituted the first evidence that the cardiovascular complications of hypertension may depend on the degree of 24‐hour PBV. In 2000, Kikuya and coworkers20 found that BPV obtained every 30 minutes by ABPM was an independent predictor for cardiovascular mortality in the general population. More recently, a multicenter study in 2011 by Cay and colleagues21 showed that increased short‐term BPV assessed by ABPM was associated with a higher risk of restenosis after percutaneous coronary intervention in patients with normotension. A meta‐analysis of 13 prospective studies was conducted by Tai and colleagues22 to evaluate the prognostic value of visit‐to‐visit systolic BPV by different parameters in 77 299 patients with a mean follow‐up of 6.3 years. It found that a 1‐mm Hg increase in SBP SD was significantly associated with stroke, with a hazard ratio of 1.02 (95% confidence interval, 1.01–1.03; P < .001). Moreover, visit‐to‐visit systolic BPV, independent of age and mean SBP, is a predictor of cardiovascular and all‐cause mortality and stroke. More recently, a post hoc analysis of the COURAGE (Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation) trial by Sidhu and colleagues23 presented a nonlinear association between systolic BPV and long‐term survival. The subgroup that showed the largest systolic BPV had the highest mortality.
In contrast to other studies such as Verdecchia and associates24 in 1996, who stated that the adverse prognostic significance of increased BPV was no longer detectable in multivariate analysis, Arashi and colleagues25 in 2015 found that there was no relationship between variability of SBP and the incidence of MACE in patients with hypertension and CAD.
In our study, this correlation between BPV and complications was found in both arms of patients with hypertension those without hypertension separately. Our findings agree with Weiss and investigators,26 who included 39 502 individuals 65 years and older, of whom 31 737 (80.3%) had hypertension, in a cohort study and found that following adjustment for sex, age, Charlson comorbidity index, and initial SBP, mortality was higher in the fourth systolic BPV coefficient of variation quartile (BPV ≥17.95 mm Hg) compared with the first BPV coefficient of variation quartile (BPV ≤10.56 mm Hg) in both patients with and without hypertension.
In our study, we found that there was a significant correlation between BPV index and complications. This result was in agreement with Parati and colleagues,27 who stated that for any given 24‐hour mean BP value, the prevalence and severity of target organ damage were linearly related to the extent of short‐term BPV.
The weighted 24‐hour SD of BP removes the mathematical interference from nighttime BP fall and correlates better with end‐organ damage; therefore, it may be considered as a simple index of 24‐hour BPV superior to conventional 24‐hour SD.3 This concept is in agreement with our results, with the increasing incidence of complication in patients with high BPV index measured by weighted SD.
In our study, we found that BPV index value >12.6 is the best prognostic value, with high specificity, to discriminate patents with high risk of MACE during hospital admission.
The prognostic ability of BPV has been previously suggested. Abdel‐Rheim and colleagues28 used a cutoff value of 14.23 mm Hg with a sensitivity and specificity of 100% and 96%, respectively; however, we found the different values can be explained by the different study design, as we used the SD method compared with the average real variability method used in Abdel‐Rheim and colleagues.
In our study, multivariate binary logistic regression analysis of the incidence of MACE versus eight independent factors indicated that BPV is an independent predictor of MACE. This result was in agreement with Ichihara and colleagues,29 who showed that multiple regression analysis for five explanatory variables including 24‐hour or daytime SBP parameters indicated significant associations between vascular damage (changes in pulse wave velocity) and changes in 24‐hour or daytime systolic BPV.
5.1. Study limitations
The limitations of our study included its small sample size, short duration of follow‐up, and use of old versions of ABPM devices, which prevented the use of the real coefficient variability (average real variability) method. However, we used the weighted SD method, which is not affected by the dipping phenomenon. Finally, the effect of abnormal dipping on MACE was not statistically significant in our results. This can be explained by the high rates of abnormal dipping in our study (89.5% vs 10.5%).
6. CONCLUSIONS
BPV could be an important risk factor for in‐hospital MACE in patients with ACS with either STEMI or non‐STEMI.
CONFLICTS OF INTEREST
The authors have declared that no competing interests exist.
Hassan AKM, Abd–El Rahman H, Mohsen K, Dimitry SR. Impact of in‐hospital blood pressure variability on cardiovascular outcomes in patients with acute coronary syndrome. J Clin Hypertens. 2017;19:1252–1259. 10.1111/jch.13107
All authors take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation.
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