Twenty-Four-Hour Ambulatory Blood Pressure Monitoring Parameters During Pregnancy: A Pilot Study

Abstract

Introduction:

Maternal blood pressure (BP) is a critical cardiovascular marker with profound implications for maternal and fetal well-being, particularly in the detection of hypertensive disorders during pregnancy. Although conventional clinic-based BP (CBP) measurements have traditionvally been used, monitoring 24-hour ambulatory BP (ABP) has emerged as a more reliable method for assessing BP levels and diagnosing conditions such as gestational hypertension and preeclampsia/eclampsia. This study aimed to assess the feasibility and acceptability of 24-hour ABP monitoring in pregnant women and report on various ABP parameters, including ambulatory blood pressure variability (ABPV).

Method:

A prospective cross-sectional study design was employed, involving 55 multipara pregnant women with and without prior adverse pregnancy outcomes (APOs). The participants underwent baseline assessments, including anthropometrics, resting CBP measurements, and the placement of ABP and actigraphy devices. Following a 24-hour period with these devices, participants shared their experiences to gauge device acceptability. Pregnancy outcomes were collected postpartum.

Results:

Twenty-four-hour ABP monitoring before 20 weeks of gestation is feasible for women with and without prior APOs. Although some inconvenience was noted, the majority of participants wore the ABP monitoring device for the entire 24-hour period. Pregnant women who later experienced APOs exhibited higher 24-hour ABP and ABPV values in the early stages of pregnancy.

Conclusion:

The study highlights the potential benefits of 24-hour ABP monitoring as a valuable tool in prenatal care, emphasizing the need for further research in this area.

Introduction

Maternal blood pressure (BP) is an important cardiovascular marker for maternal and fetal health, playing a pivotal role in detecting hypertensive disorders of pregnancy.¹ Several studies have reported associations between increased maternal BP and poor birth outcomes, such as intrauterine growth retardation,^2
–4 low birth weight,⁵ small for gestational age,^5
–7 and preterm birth.⁷ Traditionally, clinic-based blood pressure (CBP) has been used to monitor BP during pregnancy. However, reliance solely on clinic or office-based measurement introduces the potential for measurement errors. These errors may result from white coat hypertension (elevated BP in the office and normal out of the office) or masked hypertension (normal readings in the clinic but elevated out of the clinic).^8,9 Furthermore, BP measurement in a clinic setting also does not reflect the diurnal variation and nocturnal BP levels and is a poor surrogate for BP in 24-hour daily activity or work environment.

Monitoring 24-hour ambulatory BP (ABP), defined as BP measured over 24 hours while participants engage in their routine daily activities, is considered a more reliable method to quantify BP levels and diagnose gestational hypertension or preeclampsia/eclampsia than CBP.^10,11 Prior studies have shown that 24-hour ABP is superior to CBP in predicting cardiovascular morbidity and mortality.^12,13 According to Brown et al.,¹³ the greatest clinical role of 24-hour ABP in pregnancy is the potential to recognize white coat hypertension during early pregnancy, reducing the rate of inappropriate use of antihypertensive medications which are detrimental to uteroplacental perfusion. Monitoring 24-hour ABP also offers the opportunity to assess ambulatory blood pressure variability (ABPV), masked hypertension, BP nondipping, and nocturnal hypertension. These 24-hour ABP parameters can serve as an additional tool for cardiovascular and mortality risk stratification.^13

–17

Despite the aforementioned benefits of 24-hour ABP monitoring, its utilization among pregnant women has been extremely limited. Several factors contribute to this limited utilization, including the limited availability of 24-hour ABP monitoring devices, the time commitment necessary for the full 24-hour ABP monitoring process, and the inconvenience of wearing the monitoring device continuously for the entire 24-hour period.^18,19 Furthermore, data on the feasibility and acceptability of 24-hour ABP among pregnant women with a known history of adverse pregnancy outcomes ([APOs] such as preeclampsia, gestational hypertension, placental abruption, and placental infarction) and those without is limited. Moreover, the full spectrum of advantages provided by 24-hour ABP parameters, including short-term ABPV (defined as ABPV within 24 hours),¹⁵ are not yet fully comprehended. Therefore, the objectives of this study are to determine the feasibility and acceptability of 24-hour ABP monitoring and to report 24-hour ABP parameters, including ABPV, among pregnant women with and without prior APOs, as well as among those with and without current APOs in the index pregnancy.

Methods

Study design, setting, and participants

We used a prospective cross-sectional study design. A convenience sample of 55 multiparous pregnant women was recruited from Vanderbilt University Medical Center Clinics and the Nashville metro area. As the primary purpose of the pilot study is not hypothesis testing, we did not calculate sample size or estimate power.

Inclusion and exclusion criteria

Pregnant women who met the following criteria were included: (1) aged 18 years or older with one or more previous pregnancies (regardless of outcome), at ≤ 20 weeks of gestation, (2) English-speaking, and (3) willing to wear the ABP monitoring device and actigraphy device for 24 hours. Exclusion criteria were: (1) primiparous women, (2) pregnant women diagnosed with atrial fibrillation or other arrhythmias, arteriovenous fistula in the brachial arm, or lymphedema, (3) those with a history of angina pectoris, myocardial infarction, stroke, heart failure, peripartum cardiomyopathy, or bleeding disorders, (4) individuals currently taking antihypertensive medications or blood thinners, and (5) body mass index ≥ 40.

Procedure

After obtaining written consent, participants were scheduled for the baseline visit. During this visit, participants completed baseline questionnaires and underwent anthropometric measurements and resting CBP measurements. Subsequently, they were fitted with the ABP and actigraphy devices to measure their 24-hour ABP and sleep duration and quality, respectively. Participants returned to the clinic after wearing the ABP and actigraphy devices for 24 hours. During the second visit, participants completed a brief survey to share their experience with the 24-hour ABP monitoring device, assessing its acceptability. Two weeks after the expected date of delivery, participants were contacted, and self-reported pregnancy outcomes were collected.

Measures

Demographic questionnaire and anthropometric measures

Sociodemographic characteristics (age, race/ethnicity, marital status, income, education, insurance status), and tobacco, alcohol, and substance use, as well as comorbidities, were collected during the baseline visit using a questionnaire developed by the study team. Anthropometric measures including height, weight, and mid-upper arm circumference were also measured.

Prior APOs

Participants indicated whether they had experienced any of the following APOs during their prior pregnancy: eclampsia, gestational diabetes, placenta previa, preterm labor, premature rupture of membrane, and intensive care unit admission. The sample was categorized into two groups using the responses: those with prior APOs vs. those without prior APOs.

Objective sleep duration and efficiency

Sleep duration and efficiency were measured over a day using a wrist-worn accelerometer (ActiGraph, wGT3X-BT). The raw actigraphy data collected were processed using a software program (ActiLife), which filtered the raw data and converted them into activity counts. Bedtimes were validated using a sleep diary completed by each participant. Within the software, the sleep state from awake status was determined based on the Cole–Kripke scoring algorithm.²⁰ Using the processed data, sleep duration was defined as the total number of minutes scored asleep (total sleep time). Sleep efficiency was defined as the percentage of time asleep during time in bed and was calculated using the formula: sleep efficiency = (total sleep time/time in bed) × 100.²¹

Clinic-based blood pressure

During the baseline visit, brachial artery resting BP was measured using an Omron oscillometer device per the American Heart Association (AHA) guidelines by a trained research assistant.²² The device obtained three BP readings at 2-minute intervals, and the mean of the three measures was used for the final analysis.

24-hour ambulatory blood pressure monitoring

The 24-hour ABP monitoring device (Mobil-O-Graph, IEM GmbH, Stolberg, Germany) was programmed to measure BP every 30 minutes during the day (awake time) and every 1 hour during the nighttime (sleep time), based on participant-reported wake and sleep times. Participants were blinded from seeing actual BP readings in real-time until the end of the 24-hour measurement cycle. An appropriately sized cuff was selected based on the participant’s nondominant mid-upper arm circumference, following the AHA guidelines for BP measurement.²² Participants were instructed to maintain their usual daily activities during the measurement period and to keep their arm still and extended at the time of cuff inflation. Once the device was returned by participants, and all ABP parameters (24-hour ambulatory brachial and aortic BP, mean arterial pressure, augmentation index, pulse wave velocity [PWV], and other related parameters) were downloaded from the device into a software program (HMS Client Server). Using the exported data, we computed the means of 24-hour ABP parameters and the means of the most commonly used arterial stiffness indices, including augmentation index (a surrogate measure of arterial stiffness that is calculated as augmentation pressure divided by pulse pressure × 100) and PWV (a measure of how fast the pulse wave travels in a defined arterial segment). To assess the impact of gestation on office BP, 2-hour ABP parameters, and 24-hour ABPV indices, we compared these parameters by gestational age at the time ABP measurement (before 15 weeks of gestation vs 15 to 20 weeks gestation). In addition, we calculated ABPV indices, including standard deviation (SD), coefficient of variation (CoV), weighted standard variation (wSD),²³ average real variability (ARV),^24,25 and successive variation (SV).²⁶ Nocturnal BP dipping was determined by calculating the percentage of BP drop using the following formula: dipping (%) = (mean daytime BP − mean nighttime BP) × 100/mean daytime BP.²⁷ The percentage was dichotomized into two groups: non-dipping BP (defined as <10% decrease) versus dipping (10% to 20% decrease).

Pregnancy outcome data

Participants were asked about APOs during the index pregnancy (preeclampsia, eclampsia, gestational hypertension, postpartum preeclampsia, gestational diabetes, placenta accreta, placenta previa, placenta abruption, preterm labor, premature rupture of membrane, stillbirth, abortion, and intensive care unit admission), place of delivery, gestation, mode of delivery, length of hospital stay, neonatal intensive care unit admission, birth weight, and baby’s sex.

Data analysis

To assess feasibility, we calculated the recruitment rate as the number of pregnant women enrolled divided by the number of eligible participants and then multiplied by 100 (see Equation 1):²⁸

Recruitment rate = \frac{Number of pregnant women enrolled}{Number of eligible participants approached} \times 100 .

(1)

Retention was calculated as the percentage of mothers completing both the baseline and follow-up surveys and in-person visits divided by those who completed only the baseline surveys (see Equation 2):²⁸

Retention = \frac{\begin{matrix} Number of pregnant women who completed \\ baseline and follow-up surveys \end{matrix}}{\begin{matrix} Number of participants who completed \\ baseline survey \end{matrix}} \times 100 .

(2)

Adherence/compliance to 24-hour ABP monitoring was assessed by calculating the percentage of participants completing the measurement over 24 hours and the number of valid BP readings obtained over the period (see Equation 3). Participants who had at least 70% of the expected number of valid BP readings within the 24-hour period were considered compliant and included in the analysis.²⁹

ABP measure compliance = \frac{\begin{matrix} Number of participants with the minimum required \\ percent of ABP readings during the 24-hour cycle \end{matrix}}{\begin{matrix} Number of participants who initiated 24-hour \\ ABP measurement cycle \end{matrix}} \times 100 .

(3)

Acceptability was determined by calculating the percentage of participants’ levels of comfort, pain, noise disturbance, interference with daily activity, and sleep interference.

We used mean (SD) or frequency (percentage) and independent t-test or chi-square test, where appropriate, to summarize and compare the demographic characteristics, health behaviors, comorbidity, and sleep duration and quality between the groups with and without prior APOs. We also performed independent t-test or chi-square tests to examine whether there is a difference in 24-hour ABP parameters, including mean 24-hour SBP and variability indices (SD, CoV, wSD, ARV, SV, and dipping), and clinic-based SBP between pregnant women with and without prior APOs and between groups with and without APOs in the index pregnancy. Table 1 provides the list of ABPV indices along with their definitions and formulas used to calculate the value for each index using 24-hour ABP monitoring measures. A p value of 0.05 was used to determine statistical significance. Data analysis was conducted using IBM SPSS Statistics software version 29.0 (IBM SPSS Inc., Chicago). The study was approved by the institutional review board of the respective institution.

TABLE 1.

Blood Pressure Variability Indices Calculated Using 24-Hour Ambulatory Blood Pressure Monitoring Measures

BPV index	Definition	Formula
SD	SD of BP readings over 24 hours; dispersion of values around the mean	$\sqrt{[\sum \frac{{(individual readings - sample mean)}^{2}}{n - 1}]}$
COV	SD divided by mean BP; adjust for mean BP but not consider the order of BP readings	$(24-hour SD / mean BP) \times 100$
wSD²³	The mean of day and night SD values corrected for the number of hours included in each period (daytime, nighttime)	$\frac{(daytime S D * number o f daytime readings) + (nighttime S D * number o f nighttime readings)}{number o f B P readings over 24 hours}$
ARV^24,25	The mean of absolute differences between consecutive BP measurements over 24 hours; consider the order of BP readings and remove influence of overlapping circadian variation	$\frac{1}{n - 1} \sum_{k = 1}^{n - 1} \| B P_{k + 1} - B P_{k} \|$ n denotes the number of valid BP measurements in the ABPM data and k is the order of measurements.
SV²⁶	Dispersion between successive BP readings, measured as square root of average squared differences between successive readings; similar to ARV	$\sqrt{(1 / (n - 1) \sum_{k = 1}^{n - 1} {(B P_{k + 1} - B P_{k})}^{2}}$ n denotes the number of valid BP measurements in the ABPM data and k is the order of measurements.

ABPM, ambulatory blood pressure monitoring; BPV, blood pressure variability; ARV, average real variability; BP, blood pressure; COV, coefficient of variation; SD, standard deviation; SV, successive variation; wSD, weighted standard variation.

Results

Participant characteristics

Among the total of 55 pregnant women (≤20 weeks of gestation) recruited in the study, the majority were non-Hispanic whites (83.6%) with a mean age of 33 ± 3.9. Thirty-three participants (60%) had a history of prior APOs. The distribution of demographics (age, race, ethnicity, marital status, household income, insurance status), behavioral characteristics (tobacco and substance/alcohol use), and comorbidities between women with and without prior APOs was not different at baseline (Table 2).

TABLE 2.

Sample Characteristics by Prior Adverse Pregnancy Outcome Status (n = 55)

Sample characteristics	Total	With prior APO (n = 18)	With no prior APO (n = 37)	p value
Sample characteristics	M ± SD/n (%)	M ± SD/n (%)	M ± SD/n (%)	p value
Age, years*	33.19 ± 3.90	34.35 ± 3.86	32.54 ± 3.83	0.114
Race
White	46 (83.6)	13 (72.2)	33 (89.2)	0.135
Non-White	9 (16.4)	5 (27.8)	4 (10.8)
Ethnicity*
Hispanic	3 (5.6)	1 (5.9)	2 (5.4)	1.000
Non-Hispanic	51 (94.4)	16 (94.1)	35 (94.6)
Marital status
Married or living with partner	52 (94.5)	16 (88.9)	36 (97.3)	0.247
Divorced or separated and not living with partner	3 (5.5)	2 (11.1)	1 (2.7)
Income
<$74,999	16 (29.1)	7 (38.9)	9 (24.3)	0.200
$75,000–$99,999	10 (18.2)	1 (5.6)	9 (24.3)
≥$100,000	29 (52.7)	10 (55.6)	19 (51.4)
Education
High school graduate, vocational school, some college, college graduate	26 (47.3)	7 (38.9)	19 (51.4)	0.407
Some graduate/professional school, graduate/professional degree	29 (52.7)	11 (61.1)	18 (48.6)
Insurance
Private insurance	42 (76.4)	15 (83.3)	27 (73.0)	0.278
Medicaid	4 (7.3)	2 (11.1)	2 (5.4)
Multiple sources	9 (16.4)	1 (5.6)	8 (21.6)
Smoking
Past smoker	3 (5.5)	1 (5.6)	2 (5.4)	1.000
Never smoker	52 (94.5)	17 (94.4)	35 (94.6)
Substance or alcohol use during pregnancy
Yes	3 (5.5)	0 (0.0)	3 (8.1)	0.543
No	52 (94.5)	18 (100.0)	34 (91.9)
Comorbidities
Yes	25 (45.5)	7 (38.9)	18 (48.6)	0.572
No	30 (54.5)	11 (61.1)	19 (51.4)
Sleep duration**	458.57 ± 76.26	446.75 ± 81.12	464.30 ± 74.39	0.456
Sleep efficiency**	90.15 ± 5.05	87.05 ± 6.03	91.65 ± 3.75	0.011

*missing = 1; **missing = 6.

APOs, adverse pregnancy outcomes; SD, standard deviation.

Feasibility and acceptability of 24-hour ABP monitoring at ≤20 weeks of gestation

We approached 65 women deemed eligible based on the prescreening questionnaire, and 55 of them were enrolled, translating to a recruitment rate was 84.6%. Out of the 55 participants recruited, 51 completed the study by providing pregnancy outcome data after childbirth (retention rate of 92.7%). Fifty-three (96.4%) participants provided valid 24-hour ABP readings, which accounted for ≥70% of the expected number of readings over a 24-hour period. Figure 1 presents a summary of responses related to the acceptability of the 24-hour ABP monitoring. Among those who completed the study, 61.8% and 5.5% of participants reported that the 24-hour ABP monitoring interfered with their own or their partner’s sleep, respectively. Pain from inflation of the cuff (7.3%), others disturbed by noise from the BP device (10.9%), embarrassment in public (30.9%), and interference with daily activity (41.8%) while wearing the device were also reported.

FIG. 1.

Summary of participants’ experience wearing the 24-hour ABP monitoring devices at ≤ 20 weeks of gestation. ABPM, ambulatory blood pressure monitoring.

24-hour ABP parameters and ABPV indices by prior APOs status among pregnant women at ≤20 weeks of gestation

Table 3 summarizes the distribution of CBP and 24-hour ABP parameters, and ABPV indices in pregnant women ≤20 weeks of gestation by prior APO status. The mean systolic and diastolic 24-hour, day, and night ABP, as well as 24-hour ABPV indices including SD, CoV, wSD, ARV, and SV and nocturnal dipping, were not significantly different between the groups with and without prior APOs. However, it is important to note that 72.2% of women with prior APOs and 48.6% of those without prior APOs had non-dipping BP. The average systolic and diastolic 24-hour, day, and night ABP for the total sample was 113.53 ± 7.95, 66.81 ± 6.31, 116.23 ± 8.16, 69.47 ± 6.67, and 105.44 ± 9.63, 59.08 ± 6.54, respectively. When stratified by prior APOs status, the average systolic and diastolic 24-hour, day, and night ABP, augmentation index, PWV, and ABPV indices were higher in the group with APOs compared to those without APOs but were not statistically significantly different (Table 3). The mean 24-hour SBP for those with prior APOs was 2 mmHg higher than those without prior APOs, although the difference was not statistically significant. In our sample, systolic 24-hour ABPV indices range from 10.03 ± 2.00 (ARV) to 13.37 ± 2.87 (SV) and diastolic 24-hour ABPV indices range from 8.63 ± 1.78 (ARV) to 15.43 ± 3.22 (CoV) (Table 3).

TABLE 3.

Ambulatory Blood Pressure Profiles and Ambulatory Blood Pressure Variability Indices by Adverse Pregnancy Outcome Status in the Index Pregnancy (n = 53)

Blood pressure parametersand indices	Total	With prior APOs(n = 18)	With no prior APOs(n = 35)	p value
Blood pressure parametersand indices	M ± SD/n (%)	M ± SD/n (%)	M ± SD/n (%)	p value
SBP
Office BP*	115.33 ± 10.06	117.00 ± 11.92	115.13 ± 9.85	0.552
ABP-24 hours	113.53 ± 7.95	113.85 ± 7.15	113.36 ± 8.43	0.833
ABP-day	116.23 ± 8.16	115.85 ± 7.15	116.42 ± 8.73	0.811
ABP-night	105.44 ± 9.63	107.79 ± 9.64	104.23 ± 9.53	0.206
SD	12.04 ± 2.52	11.38 ± 1.90	12.38 ± 2.75	0.175
COV	10.61 ± 2.00	10.00 ± 1.60	10.92 ± 2.14	0.115
wSD	10.60 ± 2.05	10.26 ± 1.75	10.77 ± 2.19	0.395
ARV	10.03 ± 2.00	10.36 ± 2.11	9.87 ± 1.94	0.404
SV	13.37 ± 2.87	13.52 ± 2.65	13.29 ± 3.02	0.782
Dipping
<10%	30 (56.6)	13 (72.2)	17 (48.6)	0.145
≥10%	23 (43.4)	5 (27.8)	18 (51.4)
DBP
Office BP*	71.02 ± 8.09	69.67 ± 8.755	71.78 ± 7.74	0.380
ABP-24 hours	66.81 ± 6.31	66.12 ± 6.08	67.17 ± 6.49	0.574
ABP-day	69.47 ± 6.67	68.38 ± 6.28	70.02 ± 6.89	0.401
ABP-night	59.08 ± 6.54	59.61 ± 6.72	58.81 ± 6.53	0.677
SD	10.26 ± 2.20	9.85 ± 1.79	10.47 ± 2.37	0.337
COV	15.43 ± 3.22	15.05 ± 3.22	15.62 ± 3.25	0.544
wSD	8.87 ± 1.82	8.63 ± 1.75	8.99 ± 1.87	0.507
ARV	8.63 ± 1.78	8.62 ± 1.73	8.64 ± 1.82	0.965
SV	11.59 ± 2.85	11.30 ± 2.64	11.73 ± 2.98	0.605
Dipping
<10%	15 (28.3)	6 (33.3)	9 (25.7)	0.748
≥10%	38 (71.7)	12 (66.7)	26 (74.3)
ABP measures of arterial stiffness
AIx75**	22.47 ± 5.53	23.48 ± 6.79	21.95 ± 4.79	0.344
PWV**	5.29 ± 0.37	5.41 ± 0.38	5.23 ± 0.35	0.108

*missing = 5; **missing = 4.

AI, augmentation index; APOs, adverse pregnancy outcomes; ABP, ambulatory blood pressure; ARV, average real variability; BP, blood pressure; COV, coefficient of variation; DBP, diastolic blood pressure; PWV, pulse wave velocity; SBP, systolic blood pressure; SD, standard deviation; SV, successive variation; wSD, weighted standard variation.

Early pregnancy (≤20 weeks of gestation) 24-hour ABP measures and ABPV indices by APOs status in the index pregnancy

When compared with women with normal pregnancy outcomes, systolic 24-hour ABP, augmentation index, PWV, and systolic and diastolic ABPV (SD, CoV, wSD, ARV, and SV) measures at ≤20 weeks of gestation were higher in women who later developed APOs, although the association did not reach a statistical significance (Fig. 2A, C, and D; Fig. 3A and B). When the systolic 24-hour ABP was stratified by day versus night, only the night systolic BP was higher in those who later developed APOs. A similar relationship was observed with the diastolic BP measures with one exception (wSD). One participant had white coat hypertension (higher clinic BP compared to 24-hour ABP).

FIG. 2.

(A–D) Box plots summarizing 24-hour mean-systolic BP (A), 24-hour mean diastolic BP (B), augmentation index @75 (C), and pulse wave velocity (D) before 20 weeks of gestation by adverse pregnancy outcome status during the index pregnancy. BP, blood pressure.

FIG. 3.

(A) Box plots summarizing systolic ambulatory blood pressure variability indices before 20 weeks of gestation by adverse pregnancy outcome status during the index pregnancy. (B) Box plots summarizing diastolic ambulatory blood pressure variability indices before 20 weeks of gestation by adverse pregnancy outcome status during the index pregnancy. ARV, average real variability; BP, blood pressure; COV, coefficient of variation; SD, standard deviation; SV, successive variation; wSD, weighted standard variation.

In the analysis stratified by gestational age at the time of 24-hour ABP measurements, we found that SBP-night, office diastolic BP, diastolic ABP-24 hours, diastolic ABP-day, and diastolic ABP-night were significantly higher values in participants who underwent the measurements before 15 weeks of gestation compared to those measured between 15 and 20 weeks of gestation (Supplemental Table S1).

Discussion

The main findings of this prospective pilot study were as follows: (1) 24-hour ABP monitoring at ≤20 weeks of gestation in women with and without prior APOs is feasible; (2) 24-hour ABP monitoring causes some level of inconvenience, yet the majority of the study participants wore the device for the entire 24-hours; and (3) participants who went on to develop APOs exhibited higher 24-hour ABP and ABPV measures at ≤20 weeks of gestation. This finding underscores the importance of early 24-hour ABP monitoring during pregnancy or even during preconception to mitigate the risk of APOs.

The feasibility of the study protocol, including recruitment and retention rates, indicated successful implementation. The high recruitment (84.6%) and retention rates (92.7%) represent the participants’ commitment to the study. Moreover, most participants (96.4%) provided valid 24-hour ABP readings, further affirming the feasibility of implementing this monitoring technique in early pregnancy. Despite its feasibility, certain challenges were encountered in the form of reported disturbances caused by the monitoring device. Sleep interference, device-related pain, embarrassment in public, and disruption of daily activities were some of the reported issues. In future research, these concerns need to be addressed to improve the acceptability of 24-hour ABP monitoring.

The investigation into 24-hour ABP parameters and ABPV indices in relation to prior APOs status revealed no significant differences in the mean systolic and diastolic 24-hour ABP, daytime and nighttime ABP, or ABPV indices between women with and without prior APOs. This finding suggests that, during the early stage of pregnancy (≤20 weeks of gestation), a history of prior APOs may not strongly correlate with alterations in 24-hour ABP profiles and ABPV indices before the 20-week gestational mark. It is worth noting that during the first trimester, systemic vascular resistance tends to be lower due to normal physiological responses, and maternal BP reaches its lowest point around 16 to 18 weeks of gestation before gradually returning to pre-pregnancy levels during the third trimester.³⁰ This aligns with the current study’s finding of higher 24-hour ABP parameters in women measured before 15 weeks of gestation as compared with those measured at 15 to 20 weeks of gestation. Despite this well-known physiological phenomenon, clinical practice typically defines hypertension during pregnancy as BP ≥ 140/90 mmHg, regardless of gestational age. Since we did not collect prepregnancy BP data, we cannot tell whether this phenomenon has impacted the findings of the current study. For future research, it may be valuable to compare the BP levels of women with and without prior APOs during the late second trimester and third trimester to investigate possible associations between prior APOs and BP levels in subsequent pregnancies. We believe it is time for the scientific community to consider the development and implementation of gestational age-specific BP criteria for defining hypertension in pregnancy.³¹

While we did not observe any group differences in BP levels before 20 weeks of gestation in pregnant women with and without prior APOs, monitoring ABP during the first trimester should still be employed because it is critical to accurately classify different phenotypes of hypertensive disorders of pregnancy. Espeche et al.,³² recently found that 59% of women initially diagnosed with hypertensive disorders of pregnancy actually had masked chronic hypertension. This underscores the importance of conducting 24-hour ABP monitoring before 20 weeks of gestation. Ideally, incorporating 24-hour ABP data from the preconception period is essential. Without preconception data, the interpretation of ABP during pregnancy may be incomplete.³²

The examination of ABP measures and ABPV indices before 20 weeks of gestation in women who later experienced APOs compared with those with normal pregnancy outcomes has yielded valuable insights. We observed that women who later developed APOs exhibited higher systolic 24-hour ABP and ABPV indices, particularly during nighttime measurements. Although these differences did not reach statistical significance (potentially due to limited statistical power), our findings strongly suggest that monitoring nocturnal BP levels may hold predictive value for APOs. This highlights the potential importance of close monitoring and intervention during nighttime hours. It’s worth noting that previous reports have indicated that as many as 20% of pregnant women with normal 24-hour ABPM may experience nocturnal hypertension (masked hypertension).¹⁶ Nocturnal hypertension has been consistently identified as a robust predictor of preeclampsia,^33,34 emphasizing the possible clinical significance of our findings. A recent cross-sectional study of 161 pregnant women reported that both systolic and diastolic 24-hour, daytime, and nighttime ABP measures were higher in women with hypertensive disorders of pregnancy.³⁵ Although the observed increase in arterial stiffness measures (augmentation index and PWV) among women with APOs did not reach statistical significance, the trend aligns with previous research linking arterial stiffness to APOs.³⁶

Several limitations should be acknowledged in interpreting the results of this study. The sample size was small, which led to the results not sufficiently powered to detect differences in the outcomes measured, and the study was conducted at a single center, potentially limiting the generalizability of the findings. In addition, the study focused on associations of early pregnancy (≤20 weeks of gestation) ABP profiles and ABPV with APOs in the index pregnancy. The impact of mid-to-late gestation (>20 weeks) ABP profile and ABPV indices on APOs of the index pregnancy and subsequent pregnancies remains to be explored. We did not have data on the pre-pregnancy BP of participants, which also limits our ability to interpret the 24-hour ABP parameters measured at or before 20 weeks of gestation.

In conclusion, this study contributes valuable insights into the feasibility, acceptability, and potential associations between 24-hour ABP measures during the early stages of gestation and APOs. Despite the challenges posed by device-related discomfort and disturbances, the implementation of 24-hour ABP monitoring was successful. The absence of significant differences in ABP profiles between women with and without prior APOs could be attributed to the small sample size, or it is also possible that ABP profile and ABPV indices measures to predict APOs should be considered later in gestation (>20 weeks). More research is needed to confirm the benefit and timing of ABP profile and ABPV measures during gestation and their ability to predict APOs. The elevated nocturnal ABP and ABPV indices observed in women who later developed APOs provide a basis for further investigation into the role of nighttime BP monitoring as a potential predictive tool. Future studies with larger, diverse samples and longitudinal designs are warranted to confirm these findings and elucidate the complex interactions between ABP and APOs. In the current study, we detected white coat hypertension in a single participant. To accurately determine the prevalence of white coat- and masked-hypertension among pregnant women, both with and without current and/or prior APOs, future investigators should incorporate 24-hour ABP monitoring in conjunction with clinic BP assessments. This approach will provide a more comprehensive understanding of hypertensive conditions during pregnancy.

Footnotes

Acknowledgment

We thank Riya Chinni and Joshua H van der Eerden for help in recruitment and data collection.

Author Disclosure Statement

All authors report no conflict of interest.

Supplementary Material

Supplementary Table S1

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