Hemodynamic Predictors of Blood Pressure Responsiveness to Continuous Aerobic Training in Postmenopausal Hypertensive Women

Abstract

Blood pressure (BP) responses to recommended aerobic training can vary widely between individuals. Although studies demonstrate the role of exercise training in regulating BP responsiveness, predictive models are still unknown. This study aimed to identify hemodynamic predictive markers for the diagnosis of BP responsiveness based on baseline characteristics and postexercise ambulatory blood pressure (ABP) before an aerobic training program in postmenopausal women. Sixty-five postmenopausal women with essential hypertension were randomly allocated into the continuous aerobic training (CAT, n = 51) and nonexercising control (CON, n = 14) groups. CAT group cycled at moderate intensity three times a week for 12 weeks. Individuals who failed to decrease systolic blood pressure (SBP) were classified as nonresponders (NRs; n = 34) based on typical error of measurement. Baseline anthropometric, metabolic, cardiovascular, hemodynamic variables, and postexercise ABP was measured to predict BP responsiveness. A logistic regression model based on Baseline SBP [odds ratio (OR) = 1.202; 95% confidence interval (CI) = 1.080–1.338], SBP Nighttime (OR = 0.889; 95% CI = 0.811–0.975), and heart rate (HR) Nighttime (OR = 1.127; 95% CI = 1.014–1.254) were able to diagnose responders and NR individuals to BP reduction in response to CAT with 92.6% accuracy (P < 0.001; Sensitivity = 94.1%; Specificity = 79.4%). The findings highlight the potential value of baseline clinical characteristics as Baseline SBP, SBP, and HR Nighttime as markers for diagnosing BP responsiveness to recommended CAT in hypertension postmenopausal women. Clinical Trial Registration number: RBR-3xnqxs8.

Introduction

Despite considerable advances in pharmacological treatments, hypertension remains a highly prevalent disease, affecting around one-third of the world's adult population.¹ Hypertension prevalence increases with age and reaches higher values in women compared to men, especially in the postmenopause, when endogenous estrogen fall negatively impacts many traditional risk factors for cardiovascular disease (CVD) development, such as increased blood pressure (BP).² Frequently, the BP control to guideline-recommended target levels is not achieved by postmenopausal women, with increased BP being the main global risk factor for CVD development and mortality in this population.^3,4

Fortunately, CVD can be delayed by engaging in appropriate lifestyle behaviors. A single aerobic exercise session reduces the average ambulatory blood pressure (ABP) below baseline levels in hypertensive individuals, with the hypotensive effects lasting up to 22 hr.^5,6 Likewise, the chronic aerobic training program can reduce an average of 5–7 mmHg of resting BP in hypertensive individuals, important magnitudes that rival those obtained by first-line antihypertensive medications and reduce the CVD risk.⁷

Previous studies indicate that acute postexercise BP reduction is related to chronic effects, suggesting that postexercise changes are an important predictor of BP responsiveness to chronic training. Liu et al. demonstrated that the magnitude of acute BP reduction after submaximal exercise (30 min) can predict the BP reduction at rest after an 8-week aerobic training program (four times a week, 30 min per session, 65% maximum oxygen consumption) in prehypertensive patients.⁸ Likewise, Hecksteden et al. reported a strong correlation (P = 0.77) between the magnitude of postexercise hypotension (1 hr) with training-induced BP decrease after a walking/running program [45 min, four times a week at 60% heart rate reserve (HRR)] performed for 4 weeks in healthy subjects.⁹ For this reason, international hypertension guidelines recommend that hypertensive individuals engage in moderate-intensity aerobic exercise for 30–60 min, most if not every day of the week.^4,10
–12

Despite recommendations, findings in the literature demonstrate an individual BP variation in response to an aerobic training program. A review of 47 studies showed that up to 25% of hypertensive individuals did not respond to exercise and did not demonstrate a decrease in BP after aerobic training.¹³ Since BP decrease is associated with the reduction of cardiovascular risk, examining how baseline characteristics could predict a magnitude of the chronic response before undergoing the exercise intervention have important clinical implications, becoming a relevant step in identifying BP responders (REs).

Although clinical BP is widely used as a method to assess postexercise hypotension, ABP is also a good indicator of cardiovascular prognosis.^14
–16 This is because ABP allows the indirect and intermittent recording of BP behavior 24 hr, monitoring while the patient performs his usual activities during awake and asleep time.¹⁷ Such measures also demonstrate a better correlation with cardiovascular outcomes, such as myocardial infarction and stroke,^14,18,19 being a useful clinical tool for estimate the probability of an adverse outcome occurring. However, no study to date has tried to assess the acute responses of ABP for 24 hr and its relationship with BP responsiveness.

Therefore, the aim of the present study is identified hemodynamic predictive markers for the diagnoses of BP responsiveness based on baseline characteristics and postexercise ABP in postmenopausal women. Our hypothesis is that BP changes after an acute aerobic exercise session will be predictive of BP REs and nonresponders (NRs) after chronic aerobic training.

Materials and Methods

Study population

Sixty-five sedentary hypertensive females, 60–75 years of age, volunteered to take part in the study. All participants were nonsmokers, postmenopausal (≥2 years), had systolic blood pressure (SBP) and diastolic blood pressure (DBP) lower than 160 and 100 mmHg, respectively, while medicated with antihypertensive drugs and reported no prior disease (i.e., no known history of cardiovascular, respiratory, and/or metabolic diseases). Exclusion criteria included the following: participation in a regular exercise program defined as 30 min week-1 at an energy expenditure of six METS or more in the last 6 months, limiting osteoarticular diseases, use of medications that directly affect the heart rate (HR) (i.e., beta-blockers), obesity stage 2 or greater (i.e., body mass index—BMI ≥35 kg∙m⁻²), and insulin-dependent diabetes mellitus.

Change of doses and/or type of antihypertensive drugs during the study, lack of motivation or availability to attending the training sessions with less than 90% of attendance at the training sessions and/or more than two consecutive missed sessions were considered a discontinuity criterion.²⁰

The sample size was calculated using GPower^® 3.2.1 Software and determined for BP in terms of changes expected (decrease higher than 6 mmHg) after 12 weeks of intervention, based on a pilot study, assuming large effects of Cohen's d = 0.8 for comparisons between groups (TAC vs. CON) with allocation ratio of 3:1 for t-test design,¹³ and Cohen's f = 0.4 for analysis of variance (ANOVA) one way design, type I error of 0.05 for a two side-test to reach a statistical power of at least 80%.²¹

Participants were randomly allocated using an unequal randomization strategy with a 3:1 ratio of subjects into the continuous aerobic training (CAT) and nonexercising control (CON) groups. This 3:1 ratio strategy was used to ensure adequate sample sizes for the RE and NR analyses in the intervention group,²² based on expected frequency of NR individuals in the literature.¹³

The data reported herein were collected as a part of a registered clinical trial (https://ensaiosclinicos.gov.br/rg/RBR-3xnqxs8). All participants provided written consent before participating. This study followed the principles in the Declaration of Helsinki and has been approved by the Research Ethics Committee from University of Campinas, Brazil (no. 2.474.963).

Protocol

Participants underwent four pretraining assessment sessions distributed over a week. On the first visit, body composition was assessed, followed by a maximal oxygen consumption ( $V^{∙}$ O_2max) test. Forty-eight hours after the first visit, the participants returned to the laboratory for resting BP assessment, which was repeated 24 hr later to calculate the typical error of measurement (TEM). The averages of these values were used for later analyses. Finally, after 96 hr of the ( $V^{∙}$ O_2max), the retest was conducted, with the highest oxygen consumption values recorded between the two tests and their respective time to exhaustion considered for analyses.

After completion of pretraining assessments and with 3 days of intervals, subjects assigned in the training group underwent 12 weeks of aerobic training. Controls were advised to perform their normal activities of daily living and not to engage in exercise training. In the first exercise session, after resting BP assessment, participants performed an acute exercise session (50 min at 60%–70% HRR) followed by 24 hr ABP measurement. At the end of the training period, all assessments were repeated in the same order and at the same time of the day (07:00–12:00 am). The experimental design of the study is shown in Fig. 1.

FIG. 1.

Experimental design of the study. ABP, ambulatory blood pressure; BC, body composition; BP, blood pressure; CAT, continuous aerobic training; CON, control; NRs, nonresponders; RE, responders; TEM, typical error of measurement; VO_2max, maximal oxygen consumption.

The program was supervised by study researchers, who monitored the adequate adherence to exercise intensity through an HR monitor watch (Polar 810i; Polar Electro Oy, Kempele, Finland). Participants were instructed to avoid alcohol, coffee, or other caffeinated beverages for 12 hr, fast for 2 hr before sessions, sleep well, and abstain from vigorous exercise for 72 hr before assessments.

Body composition

Participants were asked to drink only water and not to eat or exercise for 2 hr before the assessment. Height was measured using a stadiometer with a precision of 0.1 cm, and weight was taken using a calibrated digital scale (BOD POD; Cosmed, Chicago) without shoes or outer garments. Body density was assessed using air displacement plethysmography (BOD POD Body Composition Tracking System; Cosmed) calibrated according to manufacturer guidelines. Body density was converted to body fat percentage using the Siri equation.²³

Cardiorespiratory test

Participants performed a cardiorespiratory test and retest on a cycle ergometer (Corival CPET, Lode BV, Groningen, Netherlands) using a ramp protocol, which started with a 5 min of rest on the bike, followed by a 3 min warm-up at 25 W and workload increments of 25 W every minute until the exhaustion.²⁴ A 3-min recovery period with no load was allowed. Minute ventilation and gas exchange were measured breath-by-breath and registered by an automated metabolic cart (CPX Medical Graphics, St. Paul, MN) at an ambient temperature of 23°C.

Participants were instructed to maintain a 60–70 rpm cadence throughout the test and exhaustion was defined as the incapacity to maintain a cadence of at least 60 rpm with the current workload despite verbal encouragement. HR was measured during the whole test with a cardiac monitor (S810, Polar, Kepler, Finland) and maximal heart rate (HR_max) was obtained from the mean values in the final 10 sec of the test. During the last 15 sec of each exercise stage, perceived exertion was recorded with the Borg's scale and all participants reported ratings of perceived exertion ≥17 at end of the test.²⁵

The validity of each maximal exercise test was determined based on the attendance of at least three out of the four following criteria: (1) maximum voluntary exhaustion defined by attaining a 17 on the Borg's scale, (2) 90% of the predicted HR_max (220-age),²⁶ (3) presence of a $V^{∙}$ O₂ plateau (Δ $V^{∙}$ O₂ between two consecutive work rates of <2.1 mL∙kg⁻¹ min⁻¹), and (4) respiratory exchange ratio >1.10.²⁷ The highest 30-sec mean value of oxygen consumption was expressed as the peak oxygen consumption ( $V^{∙}$ O_2peak) because a plateau of $V^{∙}$ O₂ was invariably not observed during the test.²⁸

Blood sampling

Blood samples (20 mL) were obtained from the antecubital vein and collected into Vacutainer^® tubes (Becton Dickinson Ltd., Oxford, UK) for serum or plasma samples (containing anticoagulant EDTA) by a trained phlebotomist, in the morning (07:00–09:00 am) and after a 12-hr overnight fast. The collections took place before, at the end of 12 (first intervention phase), and 24 weeks (second intervention phase) of the physical training program (Stage 2), with a minimum interval of 72 hr after the last training session. All samples were collected, processed, divided into serum or plasma aliquots, and stored at −80°C for subsequent analysis. Serum samples were used to measure triglycerides, total cholesterol, high-density lipoprotein, and low-intensity lipoprotein cholesterol. Plasma samples were used for fasting glucose analysis.

Resting blood pressure

After 15 min of supine resting, participants' BP was measured by the same evaluator in the left arm with a calibrated sphygmomanometer (Narcosul, Brazil), defining phases I and V of Korotkoff sounds for the identification of SBP and DBP, respectively. The measurement was performed according the Brazilian Guidelines of Hypertension.¹² The cuff size was adapted to the circumference of the arm of each participant according to the manufacturer's instructions. Mean blood pressure (MBP) was calculated using the formula [(SBP−DBP)/3+DBP].

Ambulatory blood pressure

The 24-hr BP measurement was performed on the nondominant arm after an exercise session (postexercise) using an oscillometric device (Spacelabs 90207; Spacelabs, Inc., Redmond, WA). The device was set to take readings every 15 min during the day (7:00 am to 10:00 pm) and every 30 min during the night (10:00 pm to 7:00 am), and a new measurement was obtained after 2 min if the first one was unsuccessful. All 24-hr BP measurements were taken during the week (i.e., Monday through Friday) and started between 8:00 and 11:00 am.

All subjects were instructed to avoid exercise and maintain similar daily routines during assessments. Only records with more than 85% success measures were analyzed. For the analyses, data were calculated overtime to provide the following measurements: 24 hr (all measurements), daytime (all measurements taken while subjects reported being awake), and nighttime (all measurements taken while subjects reported being sleeping).

Continuous aerobic training

The CAT protocol consisted of three 50-min cycling sessions per week on alternate days (Mondays, Wednesdays, and Fridays) for 12 weeks, at an intensity customized for each participant based on the HRR, calculated as the difference between resting and maximum HR values.²⁷. The intensity of training was 60% HRR for 50 min in the first 6 weeks and 70% HRR for 50 min in the last 6 weeks.¹⁰

All exercise sessions were supervised to ensure that the target HR (monitored by the Polar watch and band) and cycling cadence (60–70 rpm) were maintained. Subjects were required to reach their target HR in the first 5 min and the power output of the cycle ergometer was adjusted manually in response to HR variability of each participant at all training sessions. To minimize possible cardiovascular drift effects due to dehydration and increased body temperature, all subjects were encouraged to drink water which was offered ad libitum during each exercise session, whereas environmental temperature was kept throughout training sessions (21°C–23°C).

Classification of REs and NRs

To classify the participants as responders (RE) and NRs based on decreases in SBP, the TEM between BP test-retest at rest was calculated using the following equation: SD_diff/√2, where SD_diff is the standard deviation of the different scores observed between two tests performed within 24 hr at baseline as previously described.²⁹ NR were defined as individuals who failed to demonstrate a decrease greater than one time the TEM away from zero.^30
–32 This value corresponded to −6 mmHg in the present study.

Statistical analysis

For all variables, the normal distribution of data was checked and verified. When appropriate (skewness values >3.0), logarithmic transformations (log²) were applied to improve normal distribution. All transformed data were presented in their original scale for ease of interpretation. To identify differences between the two groups (CAT vs. CON) at baseline and after a single exercise session, unpaired t-tests were performed. To compare variables among the three groups (RE, NR, and CON) at baseline and after a single exercise session we used a one-way ANOVA followed by a Sidak's adjustment. Models for diagnosing BP response were developed from binary logistic regression analysis with the forward method (Wald) for variable selection, assuming the level of responsiveness [RE (1) or NR (0)] as the dependent variable.

Age, BMI, body fat, Baseline BP, and Postexercise 24 hr ABP were considered predicted variables. The model's goodness of fit was confirmed by the Hosmer-Lemeshow test. The accuracy of the predictive model was analyzed by the receiver operating characteristics curve (ROC curve), with the area under the curve, sensitivity (SEN), specificity (ESP), and odds ratio (OR) calculated. Discriminant cutoff values between RE and NR individuals were obtained from the Youden Index Analyses. Data were analyzed using SPSS^® statistics 25.0 software (SPSS, Inc., Chicago, IL). Statistical significance was defined as P ≤ 0.05.

Results

There were 363 participants assessed for eligibility. Of these, 102 meet the inclusion criteria and signed the informed consent to participate in the intervention. Fourteen participants dropped out during the initial evaluation. Therefore, 88 participants were randomized into the groups. During the interventions, 15 participants from CAT and 8 participants from CON declined over the course of the study. At the end, a total of 65 participants (CAT = 51 and CON = 14) were analyzed.

The average adherence to CAT was 98% ± 3%. In the CAT, 17 (33.0%) of the 51 hypertension women were classified as RE, having a BP reduction equal or higher than 6 mmHg. Supplementary Data presents the individual differences of BP changes after 12 weeks in CON (Supplementary Fig. S1). At baseline, CAT and CON were comparable for general, anthropometric, metabolic, and cardiovascular characteristics. Likewise, there were no significant differences between RE, NR, and CON for general, anthropometric, metabolic, and cardiovascular characteristics at baseline (Table 1).

Table 1.

Baseline Characteristics of Continuous Aerobic Training Group (Entire Group and Stratified by Blood Pressure Response) and Control Group

	REs (n = 17)	NRs (n = 34)	CON (n = 14)	CAT (n = 51)
General
Age (years)	57.8 ± 6.5	57.6 ± 6.5	60.3 ± 5.1	57.7 ± 6.4
Anthropometry
Height (cm)	159 ± 8	161 ± 6	161 ± 8	160 ± 7
Body weight (kg)	78.2 ± 14.2	77.6 ± 17.3	80.1 ± 14.8	77.8 ± 16.2
BMI (kg·m⁻²)	30.9 ± 5.1	29.9 ± 5.9	31.0 ± 4.6	30.2 ± 5.6
Fat mass (%)	43.6 ± 7.0	41.7 ± 9.7	45.8 ± 7.8	42.3 ± 8.9
Metabolic
Fasting glucose (mg·dL⁻¹)	105 ± 9	96 ± 21	98 ± 12	99 ± 18
Total cholesterol (mg·dL⁻¹)	194 ± 46	199 ± 41	188 ± 34	197 ± 43
LDL cholesterol (mg·dL⁻¹)	113 ± 37	120 ± 39	108 ± 26	118 ± 38
HDL cholesterol (mg·dL⁻¹)	55 ± 12	57 ± 16	54 ± 21	56 ± 14
Triglycerides (mg·dL⁻¹)	143 ± 70	131 ± 48	141 ± 55	135 ± 56
Cardiovascular
$V^{∙}$ O_2peak (mL·kg⁻¹·min⁻¹)	17.7 ± 2.8	18.8 ± 3.2	17.2 ± 3.6	18.4 ± 3.0
$V^{∙}$ O_2peak (L·min⁻¹)	1.36 ± 0.24	1.41 ± 0.30	1.33 ± 0.33	1.39 ± 0.28
PPO_peak (W)	107 ± 21	111 ± 24	104 ± 19	110 ± 23
HR_max (beats min⁻¹)	154 ± 13	149 ± 12	145 ± 23	151 ± 13

Values expressed as mean and SD.

Unpaired t-test: Comparisons between CON versus CAT—P ≤ 0.05 versus CON.

One-way ANOVA: Comparison between RE versus NR versus CON—P ≤ 0.05 versus RE; P ≤ 0.05 versus NR; P ≤ 0.05 versus CON.

ANOVA, analysis of variance; BMI, body mass index; CAT, continuous aerobic training; HDL, high-density lipoprotein; HR_max, maximal heart rate; LDL, low-density lipoprotein; NRs, nonresponders; PPO_peak, peak power output; RE, responders; SD, standard deviation; $V^{∙}$ O_2peak, peak oxygen consumption.

Comparisons of Baseline BP and ABP (SBP, DBP, MBP, and HR values in 24-hr, Daytime, and Nighttime) after a single exercise session between groups (CAT vs. CON; RE vs. NR. vs. CON) are presented in Table 2. Statically significant difference was observed in Baseline SBP, Baseline MBP, and Nighttime HR, with RE presenting higher values compared to NR (P < 0.05 for all).

Table 2.

Baseline Blood Pressure and Ambulatory Blood Pressure Response After a Single Exercise Session Based on Continuous Aerobic Training Group (Entire Group and Stratified by Blood Pressure Response) and Control Group

	REs (n = 17)	NRs (n = 34)	CON (n = 14)	CAT (n = 51)
Baseline sphygmomanometer
SBP	133.6 ± 13.0^a	119.9 ± 10.4	129.3 ± 13.3	124.4 ± 13.0
DBP	84.2 ± 9.3	80.1 ± 6.1	82.8 ± 5.6	81.5 ± 7.5
Mean BP	100.7 ± 9.6^a	93.3 ± 6.9	94.5 ± 13.5	95.7 ± 8.6
Acute ABP 24 hr
SBP (mmHg)	122.8 ± 11.5	124.8 ± 10.1	128.7 ± 10.0	124.2 ± 10.5
DBP (mmHg)	73.8 ± 8.0	76.0 ± 8.6	74.6 ± 8.9	75.3 ± 8.4
Mean BP (mmHg)	91.2 ± 7.7	93.1 ± 8.6	93.4 ± 8.1	92.5 ± 8.3
HR (bpm)	80.5 ± 11.3	76.6 ± 8.2	79.9 ± 8.8	77.9 ± 9.4
Acute ABP daytime
SBP (mmHg)	124.9 ± 11.5	126.5 ± 10.0	130.5 ± 10.9	126.0 ± 10.5
DBP (mmHg)	75.9 ± 8.2	77.6 ± 8.5	75.7 ± 9.5	77.0 ± 8.3
Mean BP (mmHg)	93.5 ± 8.0	94.7 ± 8.5	94.8 ± 8.8	94.3 ± 8.3
HR (bpm)	82.4 ± 10.5	78.9 ± 8.8	82.6 ± 9.1	80.1 ± 9.4
Acute ABP Nighttime
SBP (mmHg)	114.9 ± 12.2	118.9 ± 12.7	122.4 ± 8.8	117.5 ± 12.5
DBP (mmHg)	66.6 ± 7.5	70.0 ± 10.2	70.0 ± 7.3	68.9 ± 9.4
Mean BP (mmHg)	83.6 ± 8.3	87.3 ± 10.9	88.5 ± 7.2	86.1 ± 10.2
HR (bpm)	75.4 ± 14.9^a	66.1 ± 7.8	70.7 ± 7.1	69.2 ± 11.4

Values expressed as mean and SD.

Unpaired t-test: Comparisons between CON versus CAT—P ≤ 0.05 versus CON.

One-way ANOVA: Comparison between RE versus NR versus CON—P ≤ 0.05 versus RE; ^a P ≤ 0.05 versus NR; P ≤ 0.05 versus CON.

ABP, ambulatory blood pressure; BP, blood pressure; DBP, diastolic blood pressure; SBP, systolic blood pressure.

A binary logistic regression was performed to verify predictors of BP responsiveness (Table 3). In the analysis, anthropometric, metabolic, cardiovascular and hemodynamic variables were characterized and quantified. From these variables, three models were created: Model 1 [χ ² (1) = 14,069; P < 0.001, R ² Negelkerke = 0.335], Model 2 [χ ² (2) = 23,550; P < 0.001, R ² Negelkerke = 0.514] and Model 3 [χ ² (3) = 32.878; P < 0.001, R ² Negelkerke = 0.660].

Table 3.

Binary Logistic Regression Models for the Diagnosis of Blood Pressure Responders

Models	Predictive variable	B	P	OR	95% CI
Model 1 (n = 51)	Baseline SBP	0.10	0.002	1.11	1.04–1.18
	Constant	−13.57	0.001	0.000	—
Model 2 (n = 51)	Baseline SBP	0.16	0.001	1.18	1.07–1.29
	SBP Nighttime	−0.99	0.008	0.91	0.84–0.97
	Constant	−9.58	0.051	0.000	—
Model 3 (n = 51)	Baseline SBP	0.18	0.001	1.20	1.08–1.34
	SBP Nighttime	−0.12	0.012	0.89	0.81–0.97
	HR Nighttime	0.12	0.027	1.13	1.01–1.25
	Constant	−18.58	0.009	0.000	—

OR indicates the chance of occurrence of RE individuals from the predictive variables.

95% CI, 95% confidence interval; OR, odds ratio.

In Model 1, Baseline SBP [OR = 1.107; 95% confidence interval (CI) = 1.040–1.179] was a significant predictor of BP responsiveness. In Model 2, Baseline SBP (OR = 1.176; 95% CI = 1.072–1.290) and SBP Nighttime (OR = 0.906; 95% CI = 0.843–0.974) were significant predictors of BP responsiveness. In Model 3, Baseline SBP (OR = 1.202; 95% CI = 1.080–1.338), SBP Nighttime (OR = 0.889; 95% CI = 0.811–0.975), and HR Nighttime (OR = 1.127; 95% CI = 1.014–1.254) were significant predictors of BP responsiveness. There were no significant effects of anthropometric, metabolic, and cardiovascular variables on BP responsiveness for any of the models (P > 0.05 for all).

Figure 2 compares the ROC curve produced for each model. In the Model 1, Baseline SBP diagnosed RE and NR with 78.3% accuracy (P = 0.001; SEN = 58.8%; ESP = 88.2%). In the Model 2, Baseline SBP and SBP Nighttime diagnosed RE and NR with 85.1% accuracy (P < 0.001; SEN = 70.6%; ESP = 94.1%). In the Model 3, Baseline SBP, SBP Nighttime and HR Nighttime diagnosed RE and NR with 92.6% accuracy (P < 0.001; SEN = 94.1%; ESP = 79.4%). All the models had a good diagnostic ability to identify RE to training, with Model 3 being the most promising one.

FIG. 2.

The AUC for predicting the diagnosis of RE individuals to BP reduction in response to CAT, tested through a binary logistic regression model. AUC, area under the receiver operating characteristic curve.

Discussion

The main purpose of the present study was to identify hemodynamic predictive markers for the diagnoses of BP responsiveness in postmenopausal hypertension women. Our logistic regression analysis suggests a positive impact of Baseline SBP, SBP, and HR Nighttime to diagnose RE and NR individuals to BP reduction in response to CAT with 92.6% accuracy.

Despite the proven beneficial effects of aerobic training, the magnitude of hypotensive response can vary widely,^7,13 with some studies demonstrating significant BP reductions^33
–35 and others no change.^7,36,37 These findings illustrate the critical need to identify factors that explain the variability in the BP response to training so that exercise can be more effectively prescribed as antihypertensive therapy.³⁸

Several factors can influence the BP responses to an aerobic training program, and among them, the characteristics of the studied individuals must be considered. A review suggested that factors such as initial BP level, physical fitness, and the individual's gender are important.⁷ Regarding BP level, it has been reported that BP reduction after aerobic training is directly related to baseline BP, with the greatest reductions seen in those with the highest baseline levels.⁶ This effect is in line with Wilder's well-known principle that states that “the direction of the body's function response to any agent largely depends on the initial value of that function.”³⁹

These explanations agree with our findings, which demonstrate that Baseline SBP is an important predictor of BP reduction with training. Other studies also confirm these results, demonstrating that the efficacy of exercise in lowering BP is greater in people with high BP status. A meta-analytic review found significantly greater absolute reductions in resting SBP (6 vs. 2 mmHg) and DBP (5 vs. 1 mmHg) in hypertensive compared to normotensive adults.⁴⁰ In the same way, another systematic review and meta-analysis showed that aerobic training decreases SBP by an average of 0.75 mmHg in normotensive, 4.3 mmHg in prehypertensive, and 8.3 mmHg in people with hypertension.⁷

Another important predictor of BP responsiveness presented in this study was BP Nighttime. Few studies have sought to investigate the 24-hr BP response after a bout of exercise.⁴¹ However, evaluating the effect of exercise on 24 hr BP has clinical implications, as it can establish whether the BP reduction is sustained over time (possibly up to 24 hr) or represents only a short-term postexercise effect.⁴² In this sense, it has already been reported that a single session of aerobic exercise was able to induce a sustained reduction in systolic and DBP maintained for up to 22 hr in hypertensive individuals.^5,6 This result has been confirmed in other studies, which demonstrate sustained BP reduction for several hours after continuous moderate-intensity aerobic exercise.^43

–46 Considering the association between acute and chronic BP, postexercise BP reduction may be predictive of the chronic antihypertensive effect of a physical training program.⁸

In line with these findings, the regression models presented in this study showed an inverse relationship between BP Nighttime and the prediction of BP REs. Since the pattern of nocturnal BP elevation is significantly and independently associated with cardiovascular events and mortality risk,⁴⁷ antihypertensive strategies aimed at reducing nocturnal BP, such as aerobic exercise, have potential clinical relevance.

Finally, HR Nighttime was also included in the model for predicting BP reduction in postmenopausal women. A good representation of habitual HR can be obtained through ABP measurement, associated with BP, providing more reliable information than office measurement.⁴⁸ Data from prospective cohort studies state that nocturnal HR, obtained through outpatient measurement, had better predictive value for CVD compared to daytime HR.⁴⁹ Other studies confirm this finding, demonstrating that elevated HR at night, but not during waking hours, was associated with increased noncardiovascular mortality.⁵⁰

The findings of the present study have important practical implications. The identification of baseline variables that can predict response to intervention is clinically useful, as it allows estimating the probability of an outcome occurring. This can be used to identify patients who experience adverse outcomes so that preventive measures can be initiated in the context of exercise medicine, assisting in decision-making about which intervention is appropriate for patients at an individual level.

Finally, we recognize some limitations. Participants were using antihypertensive medication to control BP but they maintained the type, brand, and dosage of medication throughout the study. Diet was not controlled in this study, but participants were asked to maintain their normal eating habits. Participants' ABP was not assessed on a nonexercise control day, without exercise effects. However, we also highlight strengths of our study like the substantial sample size, the supervision of physical training sessions with great control of exercise intensity, and the adherence of 98% of the training sessions by the participants, besides the rigorous criterion adopted to define RE and NR.

In conclusion, findings of this study highlight the potential value of baseline clinical characteristics as Baseline SBP, SBP, and HR Nighttime as markers for diagnosing BP responsiveness to CAT programs in hypertension postmenopausal women. The identification of these moderators would allow more specific selection and prioritization of patients likely to experience the greatest reductions in BP following an exercise-based treatment.

Footnotes

Authors' Contributions

The study was designed by M.L.V.F. and A.C. Data collection was performed by M.L.V.F., S.G.O.N., and M.V.M.A.S. Data were interpreted by M.L.V.F., A.C., C.R.C., and M.P.T.C.M. M.L.V.F. wrote the first draft of the article. All authors contributed to article revision and approved the final version.

Author Disclosure Statement

No conflicting financial interests exist.

Funding Information

M.L.V.F. was funded by Coordination for the Improvement of Higher Education Personnel (grant no. 88887.467522/2019–00). A.C. was funded by the São Paulo Research Foundation (grant no. 2020/13939–7). M.P.T.C.M. was funded by the National Council for Scientific and Technological (grant no. 305604/2018–0).

Supplementary Material

Supplementary Figure S1

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