Study Protocol

Changes in Maternal Heart Rate Variability in

Response to the Administration of Routine Obstetric
Medication in Hospitalized Patients: Study Protocol
for a Cohort Study (MAMA-Heart Study)
Maretha Bester 1,2, *,† , Suzanne Moors 1,3,† , Rohan Joshi 2 , Thomas J. Nichting 1,3 ,
M. Beatrijs van der Hout-van der Jagt 1,3,4 , S. Guid Oei 1,3 , Massimo Mischi 1 ,
Rik Vullings 1 and Judith O. E. H. van Laar 1,3
1 Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven,
The Netherlands; suzanne.moors@mmc.nl (S.M.); thomas.nichting@mmc.nl (T.J.N.);
M.B.v.d.Hout@tue.nl (M.B.v.d.H.-v.d.J.); guidoei@outlook.com (S.G.O.); m.mischi@tue.nl (M.M.);
R.Vullings@tue.nl (R.V.); judith.van.laar@mmc.nl (J.O.E.H.v.L.)
2 Department of Family Care Solutions, Philips Research, 5656 AE Eindhoven, The Netherlands;
rohan.joshi@philips.com
3 Department of Obstetrics and Gynecology, Máxima MC, 5504 DB Veldhoven, The Netherlands
4 Department of Biomedical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven,
The Netherlands
* Correspondence: m.bester@tue.nl
† M.B. and S.M. should be jointly considered as first authors.




Received: 29 December 2020; Accepted: 18 January 2021; Published: 21 January 2021


Abstract: Pregnancy is a period of continuous change in the maternal cardiovascular system,

partly mediated by the autonomic nervous system. Insufficient autonomic adaptation to increasing
gestation is associated with pregnancy complications, such as hypertensive disorders of pregnancy
and preterm birth (both major causes of perinatal morbidity and mortality). Consequently, maternal
heart rate variability (mHRV), which is a proxy measure for autonomic activity, is increasingly assessed
in these cohorts to investigate the pathophysiology of their complications. A better pathophysiological
understanding could facilitate the early detection of these complications, which remains challenging.
However, such studies (typically performed in pregnancies leading to hospitalization) have generated
conflicting findings. A probable reason for these conflicting findings is that these study cohorts
were likely administered routine obstetric medications during the study period of which the effects
on mHRV are largely unknown. Subsequently, we design a longitudinal, observational study to
quantifying the effect of these medications—particularly corticosteroids, which are known to affect
fetal HRV—on mHRV to improve the interpretation of past and future studies. We will enroll
61 women admitted to a tertiary obstetric unit with an indication to receive corticosteroids antenatally.
Participants’ mHRV will be continuously acquired throughout their hospitalization with wrist-worn
photoplethysmography to facilitate a within-patient comparison of the effect of corticosteroids
on mHRV.

Keywords: gynecology; pregnancy complications; medical device; biomedical engineering; heart

rate variability; photoplethysmography; corticosteroids; medications; hypertensive disorders of
pregnancy; preterm birth

Clin. Pract. 2021, 11, 13–25; doi:10.3390/clinpract11010004 www.mdpi.com/journal/clinpract

Clin. Pract. 2021, 11 14

1. Introduction
Pregnancy is a period of continuous anatomical and physiological change in both mother and
fetus [1]. During this period, most maternal physiological systems undergo considerable adaptation
to support the growing fetus. Some of the most prominent changes needed to sustain the increasing
metabolic demands of the maternal-fetal dyad occur in the maternal cardiovascular system [1–3].
These maternal cardiovascular adaptations involve, amongst others, changes in blood pressure
and heart rate (HR) [1]. The main mechanisms mediating these changes are related to the endocrine
and the autonomic nervous systems (ANS) [2,4]. However, in some cases, the ANS does not sufficiently
adapt to support the increasing demands of pregnancy—a scenario which is associated with various
pregnancy complications [5]. Two prominent examples are hypertensive disorders of pregnancy
(HDP) and preterm birth (PTB), both of which are leading causes of worldwide perinatal and maternal
morbidity and mortality [6–9].
Alleviating the burden of HDP and PTB (i.e., birth before 37 weeks of gestation) remains an
important challenge in perinatology, in large part because the early detection of these complications
is challenging. The early detection of these conditions is important and actionable since effective
risk-mitigating interventions do exist [10–12]. Although their exact etiologies remain uncertain, studies
indicate that both complications are associated with dysfunctional autonomic regulation [5,13–16].
A prominent theory is that this autonomic dysfunction results in insufficient placental development in
early pregnancy, which in turn results in the development of such complications [17–19]. Therefore,
assessing ANS activity during pregnancy is relevant as it can allow for the tracking of developing
pathophysiologies, potentially enabling early detection.
Since changes in HR are closely modulated by the ANS, studying HR and, in particular,
its variability offers a window into changes in autonomic activity [17,20–22]. Consequently, maternal
heart rate variability (mHRV) has been increasingly studied to assess autonomic dysfunction in
complicated pregnancies [5,17,19,20,23–25]. However, such studies, which are typically performed in
pregnancies leading to hospitalization, have generated conflicting findings [17,19].
The onset of HDP and PTB is typically sudden, resulting in swift hospitalization to obstetric care
units (OCUs), where patients frequently receive routine obstetric medications. A probable reason for
these conflicting findings is that, during the study period, these study cohorts were likely administered
obstetric medications that potentially confounded measures of mHRV.
Typically, soon after admission to an OCU, corticosteroids and tocolytics are administered to the
patient. Corticosteroids are aimed at maturing the fetal respiratory system in the case of premature
delivery [26], while tocolytics attenuate maternal contractions to reduce the risk of preterm delivery [11].
Additionally, magnesium sulfate (MgSO4 ) and antihypertensive drugs may be administered as
needed. These medications offer maternal and fetal neuroprotection in cases of HDP and PTB,
respectively [11,12,27].
Consequently, studies assessing mHRV in hospitalized cohorts with complications, such as
HDP and threatened PTB, likely also capture the potential confounding effects of obstetric
medications. While some researchers avoid this problem by only conducting short measurements
before the administration of medications [5,20], several studies do not discuss the administration
of corticosteroids or tocolytics, even though their study populations would typically have received
these [5,11,12,23,24,27–29]. Others note the potential confounding effects of these medications as an
unavoidable part of their study design [30,31]. In fact, some even urge investigation into the effects
of obstetric medications on mHRV [19,24]. Quantifying these changes would not only enhance our
understanding of how obstetric medications affect maternal physiology but may also improve the
interpretation of past and future studies.
To our knowledge, only two studies have investigated the changes in mHRV in response to the
administration of routinely used obstetric medications. Koenen et al. found no changes to the diurnal
rhythm of mHRV in response to betamethasone administration (n = 16), although it should be noted that
only short and long-term variability (STV and LTV) were assessed [32]. Additionally, Weissman et al.
Clin. Pract. 2021, 11 15

Clin. Pract. 2021, 11, FOR PEER REVIEW 3

found that a tocolytic drug (atosiban) did not affect mHRV in hospitalized patients [33]. Even though
little is knownaffect
significantly on how mHRV
fHRV is affected,
[35–38]. the effect
Therefore, we of obstetric medications
investigate whether mHRV on fetal HRV (fHRV)
changes has been
in response to
more widely investigated.
administering Similar to Weissman’s findings on mHRV, administering tocolytic drugs did
corticosteroids.
not significantly alter
Investigating thefHRV [34].
effect of However, corticosteroids
routine obstetric are known
medications, suchtoas
significantly affect and
corticosteroids fHRVtocolytic
[35–38].
Therefore, we investigate whether mHRV changes in response to administering corticosteroids.
drugs on mHRV, should contribute to understanding the impact of these medications. Subsequently,
in thisInvestigating
paper, we the effect of
describe routinetoobstetric
a study medications,
investigate changes such as corticosteroids
in mHRV in responseandto tocolytic drugs
administering
on mHRV, should contribute to understanding the impact of these medications. Subsequently,
routinely administered obstetric medications in a cohort of patients hospitalized with pregnancy in this
paper, we describe a study to investigate changes in mHRV in response to administering routinely
complications.
administered obstetric medications in a cohort of patients hospitalized with pregnancy complications.
2. Materials and Methods
2. Materials and Methods
2.1. Aim of the Study
2.1. Aim of the Study
This study aims to investigate the effect of routinely administered obstetric medications on
This study aims to investigate the effect of routinely administered obstetric medications on mHRV
mHRV in patients hospitalized due to pregnancy complications.
in patients hospitalized due to pregnancy complications.
2.2.
2.2. Clinical
Clinical Setting
Setting
This
This longitudinal,
longitudinal, observational
observational cohort
cohort study
study will
will be
be conducted
conducted at at the
the OCU
OCU of of Máxima
Máxima Medical
Medical
Center (Máxima MC), Veldhoven, The Netherlands. The study cohort will
Center (Máxima MC), Veldhoven, The Netherlands. The study cohort will comprise patients admitted comprise patients
admitted
to the OCU tobetween
the OCU23between
5/7 and 33 23 6/7
5/7weeks
and 33 of 6/7 weekswith
gestation of gestation with to
an indication anreceive
indication to receive
corticosteroids
corticosteroids antenatally.
antenatally. Since Máxima MC SinceisMáxima MC
a tertiary is a tertiary
obstetric obstetric
referral center,referral center,ofthe
the majority majority
the of the
study cohort
study cohort will comprise high-risk patients transferred to Máxima MC from neighboring
will comprise high-risk patients transferred to Máxima MC from neighboring secondary care hospitals. secondary
care hospitals.
2.3. Clinical Data Acquisition
2.3. Clinical Data Acquisition
Longitudinal PPG measurements will be continuously acquired with the Philips Data Logger
(PDL, Longitudinal PPG measurements
Philips Research, Eindhoven, The will Netherlands,
be continuously acquired
where two of withthethe Philipsare
authors Data Logger
affiliated).
(PDL, Philips Research,
The PDL—shown Eindhoven,
in Figure The Netherlands,
1—is a non-invasive wheredevice
wrist-worn two of(CE-marked)
the authors are thataffiliated).
acquires PPG The
PDL—shown in Figure 1—is a non-invasive wrist-worn device (CE-marked)
data (sampled at 32 Hz) through optical sensing that measure changes in blood volume. Previous that acquires PPG data
(sampled at 32
studies have Hz)and
used through optical
validated sensing that
a predecessor measure
of this device changes in PPG
to collect blood volume. Previous
measurements studies
in free-living
have used and validated
conditions [39–41]. a predecessor of this device to collect PPG measurements in free-living
conditions [39–41].

Figure 1. The Philips Data Logger (worn on the author’s hand). This
This device
device will
will be employed in this
The device
study to acquire PPG and accelerometer data. The device does
does not
not display
display this
this PPG
PPG and
and accelerometer
accelerometer
data, it only displays the time.

PPG measurements capture the time intervals between pulses resulting from subsequent
heartbeats, serving as a measure of HR, from which HRV can be calculated [42]. Furthermore, the
PDL also records movement data using a tri-axial accelerometer (range: ± 8 G, sampled at 32 Hz),
which can aid in filtering out motion artifacts. The PDL offloads acquired data to a mobile phone via
Bluetooth. Data are not displayed on either the PDL or the mobile phone, ensuring that acquired data
cannot influence clinical decision making.
Clin. Pract. 2021, 11 16

PPG measurements capture the time intervals between pulses resulting from subsequent heartbeats,
serving as a measure of HR, from which HRV can be calculated [42]. Furthermore, the PDL also
records movement data using a tri-axial accelerometer (range: ±8 G, sampled at 32 Hz), which can
aid in filtering out motion artifacts. The PDL offloads acquired data to a mobile phone via Bluetooth.
Data are not displayed on either the PDL or the mobile phone, ensuring that acquired data cannot
influence clinical decision making.
In addition to PPG measurements, the study utilizes patient data routinely collected in electronic
patient files. These data—detailed in the Study Parameter section—include maternal–fetal health
parameters and routine measurements.

2.4. Routinely Administered Medications in Obstetric Care Settings

Owing to their clinical state, the patient cohort participating in this study will be administered
one or more obstetric medication as part of their standard clinical care. All medications administered
during this study are part of standard care and not influenced by study participation.
When pregnancy complications are diagnosed before 34 weeks of gestation, patients receive
corticosteroids (specifically betamethasone) [11]. Owing to its frequent use and its effects on fHRV,
our study design focuses on this medication. A course of betamethasone (Celestone Chrondose® ,
Schering AG, Berlin, Germany) consists of two 11.4 mg injections administered intramuscularly,
each consisting of 50% betamethasone phosphate for quick uptake (≈1 h) and 50% betamethasone
acetate for slow release to facilitate sustained exposure [43–45]. Although the pharmacokinetics of
betamethasone in the maternal system is not fully known, the maximum effect and terminal half-life of
betamethasone (i.e., time until the drug concentration in plasma reduces by 50%) are believed to lie
within 0.5–3 h and within 6–12 h after administration, respectively [45–48]. Betamethasone’s biological
half-life—which relates to its effect on the hypothalamus-pituitary-adrenal axis—is 36–59 h [49,50],
and is cleared from the maternal system within 48 h [46].
Patients will typically receive other obstetric medications in addition to corticosteroids; this is
unavoidable in these cohorts [11,12,27]. In cases of threatened PTB, patients are likely to receive tocolytic
drugs, such as nifedipine or atosiban, to attenuate uterine contractions [11]. Furthermore, patients in the
study population can also receive MgSO4 , which is prescribed for either fetal neuroprotection (in case of
PTB < 30 weeks’ gestation) or maternal neuroprotection (in the case of severe HDP) [11,12,27]. Patients
with HDP might also be administered anti-hypertensive medications, such as labetalol, methyldopa,
nifedipine, or nicardipine.

2.5. Study Design

The study comprises two periods of PPG measurements in the same study population. The primary
phase will assess the effect of obstetric medications on mHRV, based on PPG data gathered throughout
subjects’ hospitalization in the OCU. The secondary phase—added to compare cardiovascular features
between the antenatal and postpartum periods—consists of 24 h PPG measurements at six weeks
postpartum, acquired in free-living conditions at home.

2.5.1. Primary Phase

We specify a series of measurement epochs from our continuous measurements, as visualized in
Figure 2. Our active measurement epochs (i.e., measurements to capture the effect of betamethasone)
are defined on day 1 and day 2 (dark red in Figure 2). Similar studies assessing fHRV have typically
found a slight increase in variability parameters on day 1, followed by a significant decrease in
parameters on day 2. Hence, we will assess both active epochs against baseline measurements. We will
exclude and replace subjects for whom reliable PPG data are not available in both active epochs.
We define possible baseline measurements on day 0 (i.e., before betamethasone administration)
and day 4 (i.e., 72 h after the second betamethasone injection), depicted as light blue in Figure 2. Due to
the typically speedy administration of betamethasone after admission, PPG measurements with the
Clin. Pract. 2021, 11 17

PDL will start as soon as possible to capture premedication measurements on day 0. However, many
subjects will only be included on day 1 since the majority of our cohort will comprise transfers who have
already received their first injection. Subsequently, we specify an additional baseline measurement on
day 4 when the pharmacological effects of betamethasone will have diminished [45–50]. We will also
exclude
Clin. Pract.and
2021,replace
11, FOR subjects for whom no baseline epoch with reliable PPG data are available.
PEER REVIEW 5

Figure 2. Baseline and active measurements epochs acquired in the primary phase of the study.
Figure 2. Baseline and active measurements epochs acquired in the primary phase of the study. The
The baseline measurements epochs are defined on day 0 and/or day 4 (light blue), while active
baseline measurements epochs are defined on day 0 and/or day 4 (light blue), while active
measurements epochs are defined on day 1 and day 2 (dark red).
measurements epochs are defined on day 1 and day 2 (dark red).
If baseline measurements from both day 0 and day 4 are available, the mean of these is taken as
We define
the baseline possible
[35,38]. baseline
Epochs that measurements
are compared for on the
dayprimary
0 (i.e., before betamethasone
analysis administration)
will be 24 (±4) hours apart
and day 4 (i.e., 72 h after the second betamethasone injection), depicted as light blue in
to minimize diurnal effects [38]. Selected epochs will contain at least 5 min of PPG data of quality Figure 2. Due
that is sufficient to continuously determine HR [51]. Additionally, epochs will be selected fromwith
to the typically speedy administration of betamethasone after admission, PPG measurements rest
the PDL(i.e.,
periods willperiods
start aswithout
soon asmotion
possible to capture
artefacts) premedication
where possible, sincemeasurements
PPG are most on day 0.
reliable However,
under these
many subjects
conditions will only be included on day 1 since the majority of our cohort will comprise transfers
[41,52].
who have already received their first injection. Subsequently, we specify an additional baseline
2.5.2. Secondary
measurement onPhase
day 4 when the pharmacological effects of betamethasone will have diminished [45–
50]. We will also exclude and replace subjects for whom no baseline epoch with reliable PPG data are
Participants will wear the PDL at six weeks postpartum for a 24-h monitoring period in free-living
available.
conditions at home. Participants are not excluded if they refuse to participate in the secondary phase.
If baseline measurements from both day 0 and day 4 are available, the mean of these is taken as
the baseline
2.6. Primary and [35,38]. Epochs
Secondary that are compared for the primary analysis will be 24 (±4) hours apart to
Analyses
minimize diurnal effects [38]. Selected epochs will contain at least 5 min of PPG data of quality that
2.6.1. PrimarytoPhase
is sufficient continuously determine HR [51]. Additionally, epochs will be selected from rest
periods (i.e., periods
The primary analysis without motion
will artefacts)
determine whereof
the effect possible, since PPG
administering are most reliable
betamethasone under
on mHRV.
these conditions
Secondary analyses [41,52].
will, as far as possible, explore the effect of other medications on mHRV, compare
cardiovascular parameters between subgroups (e.g., stratified by diagnosis), assess cardiovascular
2.5.2. Secondary Phase
parameters during delivery, and evaluate similarities between trends in PPG and routinely acquired
CTG Participants
measurements.
will wear the PDL at six weeks postpartum for a 24-h monitoring period in free-
living conditions at home. Participants are not excluded if they refuse to participate in the secondary
2.6.2.
phase.Secondary Phase
PPG measurements acquired in the secondary phase will further facilitate secondary analyses,
including a and
2.6. Primary Secondary Analyses
within-patient comparison of cardiovascular parameters between the antenatal and
postpartum periods. If the eventual sample population allows, we will also compare postpartum
2.6.1. Primary
parameters Phase subgroups (stratified by diagnosis).
between
The primary analysis will determine the effect of administering betamethasone on mHRV.
2.7.
SecondaryParameters
Study analyses will, as far as possible, explore the effect of other medications on mHRV, compare
cardiovascular parameters
We will assess between
cardiovascular subgroupsderived
parameters (e.g., stratified
from theby diagnosis),
PPG assess to
measurements cardiovascular
perform our
analyses. These include HR, HRV features (e.g., SDNN, RMSSD, HF, LF, and pNN50) and acquired
parameters during delivery, and evaluate similarities between trends in PPG and routinely features
CTG measurements.

2.6.2. Secondary Phase

PPG measurements acquired in the secondary phase will further facilitate secondary analyses,
including a within-patient comparison of cardiovascular parameters between the antenatal and
postpartum periods. If the eventual sample population allows, we will also compare postpartum
Clin. Pract. 2021, 11 18

based on the morphology of the PPG waveform (e.g., pulse area and large artery stiffness index [53]).
To describe the study cohort, we will also collect the following data from patient records:

• Maternal condition:

o Patient characteristics, including age, BMI, and ethnicity.

o Pregnancy characteristics, including gestational age, results of prenatal screening,
and complications in pregnancy.
o Obstetric history, including gravidity, parity, and previous pregnancy or labor complications.
o Family history, including genetic or congenital diseases or a history of hypertension
or preeclampsia.
o Medical condition, including preexisting diseases (i.e., cardiovascular disease, pre-existing
hypertension, autoimmune disorders, neurologic disorders).
o Routine measurements, including blood pressure, laboratory test results, physical
examination results, ultrasound results.
• Fetal/neonatal condition, including fetal growth, congenital diseases, birth weight, APGAR score,
CTG measurements, and umbilical cord blood gases.
• Labor and delivery, including mode of delivery and clinical notes.
• Administration of medications, including timing, dosage, and reasons for administration.

The electronic medical records from the hospital only contain information relevant to a patient’s
hospitalization or appointments at Máxima MC. Subsequently, we will contact subjects who did not
deliver at Máxima MC to retrieve basic details of their delivery (i.e., birth weight and gestational age).
For subjects who participate in the secondary phase and have their postpartum appointments at
Máxima MC, information on their postpartum condition (e.g., postpartum complications and standard
checkup measurements) will also be collected from their electronic medical records.

2.8. Subject Inclusion and Exclusion Criteria

Patients admitted to the OCU at Máxima MC who are going to receive one or both dosages
of betamethasone injection(s) are eligible for inclusion. Table 1 outlines the entire inclusion and
exclusion criteria.

Table 1. Inclusion and exclusion criteria for MAMA-hart study.

Inclusion Criteria Exclusion Criteria

− History of severe arrhythmia and/or maternal

congenital heart disease
− Diseases with known effects on ANS Known
allergies to hard plastic (e.g., used in sport
− Age 18 years and above watches) or elastic band material
− Gestational age 23 5/7 to 33 6/7 weeks − Wounds, injuries, or infectious diseases on the
− Yet to receive the second wrist where the PDL will be worn
betamethasone injection − Tattoo location on wrist interfering with the
− Proficient in Dutch or English positioning of the PDL
− Both wrists unavailable for wearing the PDL
(e.g., owing to intravenous lines)
− Dexamethasone (another brand of
corticosteroid) administered instead
of betamethasone
PDL = Philips Data Logger.

Retrospectively, if subjects are identified to be incorrectly enrolled (i.e., not meeting the full
eligibility criteria), they will be excluded from the study analysis and replaced with a new subject.
Clin. Pract. 2021, 11 19

2.9. Sample Size

We designed the study to detect the differences in mHRV indices between the active and baseline
measurement epochs (in line with our primary analysis). Since we will assess multiple HRV indices,
we base our sample size calculation on detecting a difference in mean NN intervals (i.e., the time
between heartbeats). NN intervals form the basis for calculating HRV indices and are also a less
sensitive measure than HRV, therefore, resulting in a conservative sample size estimation. Subsequently,
we calculated the sample size using a two-sided t-test for a confidence interval of 95% and a power
assumption of 80%. The expected variation in NN-interval measurements was estimated from studies
assessing NN intervals in pregnant populations [14,54,55]. No prior research was available to guide
the decision concerning effect size but given the heterogeneity of the cohort we would like to be able to
detect a small effect. Subsequently, we selected an effect size of 10%.
Based on these parameters, we calculated a sample size of 43 using the built-in power function for
a paired t-test in R (version 3.5.3, RStudio Inc., Boston, MA, USA). Adding in a safety margin of 20%
to the expected variation, the sample size increases to 61. We will perform an interim analysis after
including 43 subjects to assess whether further inclusions are necessary. The study is powered for the
primary analysis, and not specifically powered for secondary analyses.

2.10. Statistical Analysis

Our study cohort has various diagnoses, which can result in different baseline measurements for
mHRV. Owing to this, a within-subject comparison of mHRV features will be performed for the primary
analysis to minimize the effect of this heterogeneity. For each participant, the active measurement
epochs on day 1 and day 2 will, respectively, be compared to the baseline measurement epoch.
Since the treatment of this study cohort is guided by standard clinical management,
the co-administration of medications is unavoidable [11,12,27]. To this end, we will perform variance
analyses to understand whether this co-administration affects our results. For secondary analyses in
both phases, we will perform within-subject as well as between-group comparisons.
We will test normality assumptions with a Shapiro-Wilk test and subsequently compare continuous
variables using a paired t-test or a Wilcoxon matched-pairs test, and categorical variables using a
χ2-test or Fisher’s exact test, chosen as appropriate. p < 0.05 is considered significant for a two-tailed
test. Effect sizes will be reported along with the p values [56].

2.11. Data Handling and Storage

We will adhere to the European General Data Protection Regulation (GDPR) and the Dutch
Personal Data Protection Act (“Uitvoeringswet AVG”) for data processing and analyses. Subsequently,
subject data will be de-identified.
We will use Research Manager (version 5.51.0, Research Manager, Deventer, The Netherlands) for
the case report form and data handling. Personal data will be stored according to Good Clinical Practice
guidelines. Analyses are carried out under the Eindhoven MedTech Innovation Center framework,
in collaboration between Máxima MC, Philips Research, and the Eindhoven University of Technology.

2.12. Ethics and Dissemination

The Medical Ethics Committee of Máxima MC, Veldhoven, The Netherlands, confirmed that the
study neither imposes any changes in general practice nor does it burden participants. Therefore, in
line with the Declaration of Helsinki, a waiver for ethical approval was granted (N19.112; 02/12/2019).
The study is registered in the Dutch Trial Register (NL8204; 06/12/2019).
All investigators agree to publish the study results in an international peer-reviewed journal,
regardless of whether the outcomes align with the stated hypotheses. The full study protocol is available
upon request.
Clin. Pract. 2021, 11 20

3. Discussion
The autonomic dysfunction associated with pregnancy complications has increasingly been
studied by investigating mHRV [17,19]. However, the mHRV features obtained in these cohorts are
possibly confounded by routinely administered obstetric medications—in particular, corticosteroids.
This likely impedes the accurate interpretation of such results and could explain why they are often
conflicting. Therefore, quantifying changes in mHRV in response to obstetric medications would
not only enhance our understanding of how these medications affect maternal physiology, but also
improve the interpretation of past and future studies.
Our study is one of only a few to explore the effect of administering routine obstetric medications
on mHRV [33,57], and the first to focus on investigating changes in mHRV resulting from the
antenatal administration of corticosteroids (betamethasone). Apart from a small number of human
and animal studies [32,58–60], research has focused on assessing changes in fHRV—demonstrating
that administering betamethasone significantly decreases fHRV parameters [35,38,61]. Since fHRV
is not continuously monitored in cohorts hospitalized due to pregnancy complications, these fetal
studies (such as that of Verdurmen et al.) had to deliberately incorporate fHRV measurements into
clinical workflow, which can be logistically challenging [38]. Since our clinical setting and protocol
are comparable to theirs, we implement unobtrusive monitoring to ensure that our study fits more
seamlessly into standard clinical workflow.
For collecting mHRV in our study, we selected a wristwatch-like device (the PDL) owing to its
ease of use and limited interference with clinical workflow. The traditional alternative would be an
ECG Holter monitor, as it might offer higher accuracy in determining mHRV. However, this approach
is more obtrusive and cumbersome for both the patient and clinical staff. Furthermore, in addition to
high participant compliance in wrist-worn monitoring in pregnant populations [62], HRV determined
from PPG measurements, sampled above 25 Hz (PDL: 32 Hz), can be as reliable as that calculated from
ECG [63]. Epochs used for analyses will be selected from rest periods where possible since this is when
PPG measures are generally most reliable. Still, since frequency domain features may be less reliable
when calculated from PPG measurements, we will interpret these features with caution [52].
The unobtrusive nature of wrist-worn PPG measurements also offers opportunities for additional
exploratory analyses: firstly, a continuous dataset representing the complete period of hospitalization of
participants can be collected; secondly, it enables us to collect 24 h of postpartum at-home measurements
for these same participants (i.e., the secondary phase). Incorporating all these measurements could
allow for the analysis of mHRV throughout the perinatal period (i.e., antepartum, intrapartum, and
postpartum), which—to our knowledge—has not yet been assessed. Insights into the postpartum
period could be particularly useful, since literature on how autonomic regulation changes in this period
is limited [64–66].
Defining a baseline measurement epoch is another important challenge in assessing the effect of
betamethasone on mHRV. The presumptive ideal is the epoch leading up to the first betamethasone
injection (i.e., day 0 in Figure 2), but this is impractical given that most of our study cohort will be
transfers who have already received their first injection. Furthermore, since admission is typically
urgent and unexpected, patients are likely physiologically stressed during day 0, which can affect HRV
parameters [67]. Therefore, an alternative baseline measurement is necessary. Guided by the available
literature and the pharmacokinetics of betamethasone, we define our alternative baseline measurement
on day 4. Koenen et al. found that, while administering betamethasone suppresses the diurnal rhythm
of maternal cortisol and ACTH levels, this rhythm returns by day 4 [32]. This aligns with what is known
concerning the pharmacokinetics of the medication in the maternal system, with studies showing the
maternal terminal half-life of betamethasone as 6 to 12 h [45–48], and the corresponding biological
half-life as 36 to 59 h [49,50]. Several studies have also shown that the effect of betamethasone on fHRV
ceases by day 4 [35,37,38]. Factoring in that Ballard et al. have demonstrated that the medication’s
terminal half-life in the maternal system is half of that in the fetus [46], it is reasonable to assume that
Clin. Pract. 2021, 11 21

day 4 is a conservative baseline measurement. In the case that both baseline epochs are available,
we use their mean [35,38].
For the results of the study to be applicable in clinical practice, participants will represent a cohort
of women who typically receive corticosteroids, i.e., patients with varying characteristics and diagnoses
(e.g., HDP, threatened PTB), and who subsequently receive multiple medications. The heterogeneity
in characteristics and diagnoses could serve as limitations, as they will likely also influence mHRV.
We account for this heterogeneity by focusing on within-patient comparisons when assessing the effect
of betamethasone on mHRV, emphasizing the relative change between the active and baseline epochs,
and averaging results across subjects. Hence, the effect of the heterogeneity on the study results will
be reduced.
Another limitation is the possible confounding effect of co-administration of medications. This is
unavoidable in this study design and cohort [11,12,27]. As previously mentioned, little literature exists
on the effect of obstetric medications on mHRV, aside from one study, which determined that a tocolytic
drug had no significant effect on mHRV [33]. We aim to assess the impact of this co-administration by
doing variance analyses when multiple medications have been administered.
Still, the most prominent knowledge gap concerns betamethasone, and we subsequently focus on
investigating the effect of this medication on mHRV. Results from this study could identify the possible
confounding effect of betamethasone on mHRV, thereby improving the interpretation of existing and
future studies assessing the autonomic dysregulation associated with pregnancy complications, such as
HDP or threatened PTB. An improved interpretation of the changes in mHRV in these cohorts could
facilitate earlier diagnosis through tracking deteriorations in mHRV. In turn, early detection could
enable the prevention or better management of these complications, alleviating some of the burdens
they place on women, families, and society.

Author Contributions: Conceptualization, M.B., S.M., R.J., M.B.v.d.H.-v.d.J., M.M. and R.V., and J.O.E.H.v.L.;
methodology, M.B., S.M., R.J., R.V. and J.O.E.H.v.L.; investigation, M.B., T.J.N. and J.O.E.H.v.L.; writing—original
draft preparation, M.B. and S.M.; writing—review and editing, all authors; project administration, M.M., S.G.O.
and J.O.E.H.v.L. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.

Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration
of Helsinki. The Medical Ethics Committee of Máxima MC, Veldhoven, The Netherlands, confirmed that our
study does not impose any changes in general practice or puts any burden on the patients. Therefore, in line with
the Declaration of Helsinki, a waiver for ethical approval was granted (N19.112; 02/12/2019). Máxima MC Board
of Management, Veldhoven, The Netherlands, approved the conduct of this study at their hospital. The study is
registered in the Dutch Trial Register (NL8204; 06/12/2019).

Informed Consent Statement: Informed consent will be obtained from all subjects involved in the study.

Data Availability Statement: The data associated with this study is publicly unavailable. Upon reasonable
request, in accordance with patient consent and with permission of relevant parties, the de-identified data might
be made available to others by the corresponding author. Additionally, the full study protocol is available
upon request.
Conflicts of Interest: R.V. is a shareholder in Nemo Healthcare BV, The Netherlands. The other authors have no
competing interest to declare.

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