1Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
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1Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
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Jordan P. R. McIntyre
1Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
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Alistair J. Gunn
2Department of Physiology, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
3Department of Paediatrics: Child and Youth Health, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
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Christopher A. Lear
2Department of Physiology, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
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Laura Bennet
2Department of Physiology, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
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Edwin A. Mitchell
3Department of Paediatrics: Child and Youth Health, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
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John M. D. Thompson
1Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
3Department of Paediatrics: Child and Youth Health, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
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1Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
2Department of Physiology, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
3Department of Paediatrics: Child and Youth Health, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
Peter R. Stone, Email: zn.ca.dnalkcua@enots.p.
*Corresponding author P. Stone: Department of Obstetrics and Gynaecology, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand. Email: zn.ca.dnalkcua@enots.p
Received 2016 Jul 27; Accepted 2016 Oct 25.
Copyright © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society
Abstract
Key points
Fetal behavioural state in healthy late gestation pregnancy is affected by maternal position.
Fetal state 1F is more likely to occur in maternal supine or right lateral positions.
Fetal state 4F is less likely to occur when the woman lies supine or semi‐recumbent.
Fetal state change is more likely when the woman is supine or semi‐recumbent.
Fetal heart rate variability is affected by maternal position with variability reduced in supine and semi‐recumbent positions.
Abstract
Fetal behavioural states [FBS] are measures of fetal wellbeing. In acute hypoxaemia, the human fetus adapts to a lower oxygen consuming state with changes in the cardiotocograph and reduced fetal activity. Recent studies of late gestation stillbirth described the importance of sleep position in the risk of intrauterine death. We designed this study to assess the effects of different maternal positions on FBS in healthy late gestation pregnancies under controlled conditions. Twenty‐nine healthy women had continuous fetal ECG recordings under standardized conditions in four randomly allocated positions, left lateral, right lateral, supine and semi‐recumbent. Two blinded observers, assigned fetal states in 5 min blocks. Measures of fetal heart rate variability were calculated from ECG beat to beat data. Compared to state 2F, state 4F was less likely to occur when women were semi‐recumbent [odds ratio [OR] = 0.11, 95% confidence interval [95% CI] 0.02, 0.55], and supine [OR = 0.27, 95% CI 0.07, 1.10]. State 1F was more likely on the right [OR = 2.36, 95% CI 1.11, 5.04] or supine [OR = 4.99, 95% CI 2.41, 10.43] compared to the left. State change was more likely when the mother was semi‐recumbent [OR = 2.17, 95% CI 1.19, 3.95] or supine [OR = 2.67, 95% CI 1.46, 4.85]. There was a significant association of maternal position to mean fetal heart rate. The measures of heart rate variability [SDNN and RMSSD] were reduced in both semi‐recumbent and supine positions. In healthy late gestation pregnancy, maternal position affects FBS and heart rate variability. These effects are likely fetal adaptations to positions which may produce a mild hypoxic stress.
Keywords: fetal behavioural state, fetal heart rate variability, maternal position, pregnancy, stillbirth
Abbreviations
CIconfidence intervalCTGcardiotocographFBSfetal behavioural stateFHRfetal heart rateFHRVfetal heart rate variabilityORodds ratioPaO2arterial partial pressure of oxygenRR intervalinterval between successive R waves on the electrocardiographRMSSDroot mean square of successive differences [in the RR interval]SDNNstandard deviation of the RR intervalIntroduction
The presence of fetal behavioural states [FBS] has now been established for many years [Nijhuis et al. ; Arduini et al. ] and fetal heart rate [FHR] patterns have been used to deduce the fetal state [Timor‐Tritsch et al. ; Pillai & James, a], which is reliably determined by examination of the characteristics of the baseline FHR patterns alone [Pillai & James, b]. FBS and their transitions are measures of fetal wellbeing that reflect the neurological integrity of the fetus [Romanini & Rizzo, ] and the development of autonomic nervous control of heart rate [Brandle et al. ].
FBS may be defined as combinations of particular physiological variables which are stable over a period of time and recur [Martin, ]. In the fetus at least three distinct behavioural or activity states have been identified and correspond to the early neonatal behavioural states 1 [quiet sleep – in the fetus termed 1F], 2 [active sleep – fetal 2F], 3 [quiet awake – in the fetus this is very infrequent or not seen] and 4 [active awake – in the fetus a period of considerable fetal activity with rapid heart rate and varying baseline FHR] [Nijhuis et al. ]. During the third trimester of pregnancy, fetal activities are cycle‐ or state‐dependent, so that prolonged and often repeated recording of behaviour is necessary before any adverse conclusions can be drawn about fetal wellbeing [Pillai & James, b]. The development and stability of FBS is disturbed in adverse situations such as maternal diabetes and in chronic fetal compromise such as growth restriction [van Vliet et al. ; Mulder et al. ]. More acute compromise in a previously healthy fetus leads to suppression of fetal activity which may adapt over time in the absence of metabolic acidaemia [Martin, ]. In acute hypoxaemia, the fetus makes adaptations to a lower oxygen consuming state, with effects on electrocortical activity shown in sheep [Boddy et al. ; Richardson et al. ; Bocking & Harding, ]. The human fetus also makes adaptive changes to hypoxia [Martin, ] with changes in the cardiotocograph [CTG] and in reduced fetal activity [Bocking, ; Froen et al. ].
Behavioural state transitions have also been found to be different in length of time and characteristics in the growth‐restricted compared with the normally grown fetus [Arduini et al. ]. Measures of fetal habituation and behavioural state transitions have been proposed as methods of assessing fetal wellbeing and predicting neonatal outcome [Krasnegor et al. ].
Recent developments in transabdominal fetal ECG have permitted ambulatory recording of the beat to beat FHR [Narayan et al. ]. A conventional CTG may be derived from this and fetal behavioural state determined.
Fetal heart rate variability [FHRV] calculated from beat to beat heart rate intervals is an established marker of fetal wellbeing as it reflects the development and function of the fetal autonomic nervous system in both health and in stress such as hypoxia [Dawes et al. ; Schneider et al. ]. Reduction in FHRV is known to precede fetal distress and alterations in the inter‐beat interval may occur before any noticeable change in the heart rate itself is detected [Dalton et al. ]. The changes in fetal behavioural state may be associated with changes in FHRV [Romanini & Rizzo, ].
A recent study of factors associated with late [third trimester] stillbirth described the importance of maternal sleep position where non‐left‐sided sleeping, particularly supine, was found to be associated with an increased risk of stillbirth [Stacey et al. ]. Two further studies have confirmed adverse effects of supine sleeping [Owusu et al. ; Gordon et al. ]. The mechanisms by which a normally formed fetus in a healthy pregnancy should be at risk of stillbirth remain unclear as does the reason why maternal position should be of importance. However, a triple risk model has been proposed as a method of understanding the pathogenesis of late stillbirth involving the interplay of maternal factors, a vulnerable fetus and the imposition of a stressor [such as maternal supine position] which then produces a lethal combination [Warland & Mitchell, ]. An aim of our studies was to investigate the effects of maternal position in healthy late gestation prior to examining vulnerable pregnancies such as those in obese woman or with fetal growth restriction. Vulnerable groups at increased risk of late stillbirth have been identified as a priority area for research in high‐income countries [Flenady et al. ].
Therefore, as part of ongoing studies of stillbirth, we designed this study to assess the effects of different maternal positions in healthy late gestation pregnancies under controlled conditions on FBS as a marker of fetal wellbeing. We hypothesised that FBS would be affected by maternal position.
Methods
Ethical approval
This study was approved by the Northern Regional Human Ethics Committee [NTX/11/09/084]. All subjects gave written informed consent. All studies approved by the Northern Regional Human Ethics Committee conform to the Declaration of Helsinki.
Subjects
Twenty‐nine healthy women aged ≥ 18 years with a normal singleton pregnancy, late in the third trimester [35–38 weeks of gestation], were recruited from low risk midwifery care at National Women's Hospital, Auckland, New Zealand.
Maternal exclusion criteria included: current smoking or alcohol use, early pregnancy body mass index > 30, any medical or obstetric complications [e.g. pre‐eclampsia, any known cardiovascular disorder including hypertension or use of antihypertensive treatments, respiratory or renal disorders, all forms of diabetes], not regularly attending scheduled obstetric appointments, any orthopaedic or musculoskeletal conditions which would make adopting different maternal positions difficult and inadequate English speaking to give consent. Fetal exclusion criteria included: abnormal biometry for the gestation, reduced amniotic fluid volume, abnormal umbilical arterial Doppler measurements and multiple pregnancy.
A maternal echocardiogram and ECG were performed immediately prior to the study to ensure normal maternal cardiac anatomy and function.
Fetal biometry using customized centile charts [McCowan et al. ] and fetal Doppler measures of the umbilical and middle cerebral arteries were also recorded using standard methodologies. Fetal biometry 5th centile on reference charts [Ebbing et al. ] were considered normal and were required for inclusion in the study. In addition, a measurement of the single deepest pool of amniotic fluid was performed, all assessments being performed to confirm normal fetal wellbeing. Birth outcome data were collected to confirm the health status of the mother and neonate.
Procedures
Participants were told to abstain from alcohol, caffeine, chocolate and strenuous exercise on the day of the assessment, and not eat within 2 h of the assessment. All assessments were performed in the afternoon between 14.00 and 15.00 h.
Four maternal positions, supine, semi‐recumbent, left lateral and right lateral, were studied. In supine the woman lay on her back with one pillow. The semi‐recumbent position was defined as having the woman supine with the cephalad end of the examination couch raised to a measured 30 deg from the horizontal and one pillow was provided. The lateral positions involved the women being placed lying on their side and at least 30 deg from supine, with the head of the couch flat and one or two pillows provided.
On arrival in the laboratory, the participants were randomised to the order of maternal positions from a computer‐generated list created in MS Excel. Each woman was monitored for 30 min in each position. The participant would move directly from one position to the next unless she needed to use the bathroom. Assessments were all performed in the same room, by the same investigators [PS, JM].
A continuous fetal ECG, electrohysterogram and maternal heart rate were recorded using the Monica AN24 ambulatory transabdominal fetal ECG device [Monica Healthcare, Nottingham, UK]. Skin preparation, electrode placement and impedance testing were performed as per the manufacturer's instructions. This device enabled monitoring of the fetus without need to reposition bulky transducers when the mothers moved between each position. In addition, in contrast to conventional CTG, the device recorded a fetal ECG with true beat to beat intervals in 1 min epochs without autocorrelation as used in commercial CTG machines.
Data processing
The data from the Monica device were uploaded to a PC computer with the Monica [VS] analysis software. The Monica VS software uses beat to beat data to construct a fetal cardiograph, which when combined with the hysterogram produced a printout analogous to a standard CTG suitable for interpreting FBS.
The Monica device has a built in proprietary algorithm to deal with signal loss [any epoch with > 30 s signal loss in the 1 min epochs used for the analysis of the raw ECG signal is disregarded and no result is given for that epoch]. The manufacturer's analysis program [Monica DK v1.9] was used to calculate FHRV. Mean FHR was assessed for each minute analysed, giving up to 30 samples [30 1 min epochs] per position in each subject. Each epoch was quantified by the mean FHR, the standard deviation of RR intervals [SDNN] and the root mean square of successive RR intervals [RMSSD]. The left lateral position was used as the referent from which the other positions were compared. For analysis of the relationship of these variables in relation to fetal state, the observations over each block of time were averaged to correspond with the block of time in which the fetal state had been determined.
Fetal state was based on the classic features of the CTG as described by Pillai & James [ a]. The CTGs were scored independently by two obstetricians [PS, WB], blinded to maternal position. Each block was scored for fetal state as either 1F, 2F, 4F, transition or indeterminate using the methods of Pillai & James [ a]. Consistent heart rate patterns were defined as a state when the duration was at least 3 min. Comparison of the scoring found a kappa of 0.68, which is considered substantial, with complete agreement in 82% of observations. When the agreement analysis was limited to observations where a fetal state had been defined by both scorers kappa was 0.86 [considered almost perfect] and there was complete agreement for 95% of observations. For observations where there was disagreement, the scorers reviewed the observations together, blinded to the original scoring and reached a consensus view. These observations are those used in the analysis.
Statistical analyses
Odds ratios [ORs] were determined to estimate the risk of the fetus being in state 1F or state 4F compared to the predominant state 2F by maternal position. This was carried out using repeated measures analyses [i.e. the repeated measures over the 30 min in each position of fetal state] in the GLIMMIX procedure in SAS. The models used a binary outcome with a logit link and a random intercept term.
Differences in FHR and FHRV were assessed using the GLIMMIX procedure to compare differences in these measures when the fetus was in 1F or 4F compared to the referent 2F group. The analyses to compare FHR and FHRV by maternal position [with referent left position] for state 1F and 2F were carried out in the same manner. The sample size did not allow for this analysis to be carried out for data where the fetus was in state 4F [n = 24].
All analyses were carried out in SAS for Windows v9.3 [SAS Institute, Cary, NC, USA].
Results
There were analysable data for 511 [88.1%] of the observations [blocks of time]; data loss was due to loss of signal [8.3%], fetus in transition [1.7%] or indeterminable state [1.9%]. Visual analysis of the FHR data showed that there were no decelerations at times of state change, nor periods of fetal bradycardia.
Distribution of fetal state
The distribution of FBS by maternal position is shown in Table 1. As would be expected, the primary FBS was 2F [74.0% of the time] followed by 1F [21.3%] and 4F [4.7%].
Table 1
Number [%] of blocks of time in relation to maternal position and fetal state
Maternal positionState 1FState 2FState 4FLeft13 [11.3]91 [79.1]11 [9.6]Right28 [22.0]91 [71.7]8 [6.3]Semi‐recumbent23 [16.3]113 [81.9]2 [1.4]Supine45 [34.4]83 [63.3]3 [2.3]
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Effect of maternal position on fetal state
In Table 2, the likelihood of being in a state other than 2F related to maternal position is shown. In comparing state 2F to 1F, those on the right [OR = 2.36, 95% confidence interval [CI] 1.11, 5.04] or supine [OR = 4.99, 95% CI 2.41, 10.43] were significantly more likely to be in 1F compared to those on the left. Compared to state 2F, state 4F was less likely to occur when the women were in the semi‐recumbent position [OR = 0.11, 95% CI 0.02, 0.55]. In the supine position, the likelihood of being in 4F was also reduced but did not reach statistical significance [OR = 0.27, 95% CI 0.07, 1.10].
Table 2
Univariable odds ratios [95% CI] associated with being in fetal state 1F and 4F compared to state 2F according to maternal position [left lateral position referent]
PositionFetal state 1 vs. 2Fetal state 4 vs. 2State changeP = 0.0001P = 0.033P = 0.0005LeftrefrefrefRight2.36 [1.11, 5.04]0.57 [0.19, 1.71]0.96 [0.49, 1.85]Semi‐recumbent1.60 [0.74, 3.46]0.11 [0.02, 0.55]2.17 [1.19, 3.95]Supine4.99 [2.41, 10.43]0.27 [0.07, 1.10]2.67 [1.46, 4.85]
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Figures in bold show significant differences from referent position.
In comparison with the left lateral position, when mothers were placed semi‐recumbent or supine, the fetus was significantly more likely to change behavioural state [OR = 2.17, 95% CI 1.19, 3.95 and OR = 2.67, 95% CI 1.46, 4.85, respectively]. There was no pattern as to what state change took place.
Effect of fetal state on measures of FHRV
In Table 3 the effect of fetal state on FHR and FHRV is shown. Compared with state 2F, in state 1F there was a significant reduction in FHR, SDNN and RMSSD. In state 4F the mean FHR was higher with significant reduction in RMSSD.
Table 3
Differences in measures of FHR according to fetal state
Fetal stateFHRSDNNRMSSDP