Abstract
Background
There is a close association between sleep-disordered breathing (SDB) and preeclampsia. Both conditions have poor pregnancy outcomes.
Methods
Forty women with new-onset hypertension of pregnancy and 60 age-matched normotensive pregnant women were subjected to polysomnography. The maternal and fetal outcomes of all the subjects were noted.
Results
SDB occurs more frequently (p = 0.018; OR 13.1) and with more severity (p 0.001; OR 1.8) in women with hypertensive disorders of pregnancy even after controlling for pre-pregnancy body mass index (BMI). Furthermore, the BMI significantly correlated with both the Apnea–Hypopnea Index (AHI; r = 0.745; p < 0.001) and the blood pressure (r = 0.617; p < 0.001) highlighting the contribution of obesity in the causation of hypertension and SDB. We also found a significant correlation between AHI and blood pressure even after adjustment for BMI pointing toward an independent role of SDB in the development of hypertension (r = 0.612; p = 0.01). Maternal and fetal complications significantly correlated with different parameters of SDB–AHI, Arousal Index and minimum oxygen saturation, in the cases and with the fetal complications in the controls as well.
Conclusion
SDB occurs more frequently and with more severity in women with pregnancy-induced hypertension and is associated with more severe preeclampsia and adverse feto-maternal outcomes.
Keywords: Sleep-disordered breathing, Preeclampsia, Gestational hypertension, New-onset pregnancy hypertension, Poor maternal outcomes, Poor fetal outcomes
Introduction
Preeclampsia is a hypertensive disorder unique to pregnancy which is characterized by hypertension, proteinuria and/or severe features like pulmonary edema, raised liver enzymes, thrombocytopenia, elevated creatinine levels and cerebral features. Gestational hypertension is also a new-onset hypertensive disorder of pregnancy, but without proteinuria, which can develop into preeclampsia during the course of pregnancy [1]. Hypertensive disorders of pregnancy affect about 6.9% of all pregnant women as demonstrated in a recent community-based Indian study [2].
Preeclampsia is one of the leading causes of maternal morbidity and mortality, ICU admissions and neonatal morbidity [3]. The adverse maternal outcomes include antepartum and postpartum hemorrhage, seizures, need for induction of labor, preterm birth and operative deliveries. These women are also at risk of developing coronary artery disease and stroke later in life [4]. The notable adverse fetal outcomes are intrauterine growth restriction, low birth weight, low APGAR at birth and prolonged nursery stay [5, 6].
The exact pathogenesis of these hypertensive disorders is not certain; however, most research points toward the central role of placenta, as placenta is necessary for the development of preeclampsia and not the fetus; besides, the definitive treatment of preeclampsia is termination of pregnancy. It is postulated that defective trophoblastic invasion or differentiation results in production of reactive oxygen species and other inflammatory mediators, which ultimately lead to endothelial dysfunction affecting all the systems of the body [7].
Sleep-disordered breathing (SDB) is a condition which is characterized by repeated episodes of partial or complete obstruction of upper airway leading to impairment of normal ventilation, intermittent hypoxemia and frequent arousals [8]. The epidemiological risk factors are obesity, male gender and increasing age [9]. The pathogenesis of SDB may be related to anatomical factors leading to small pharyngeal airway or a central ventilatory control disorder [9]. SDB is associated with several cardiovascular complications including hypertension [10]. The intermittent episodes of hypoxia and arousals are associated with oxidative stress, inflammation and increased sympathetic activity leading to high blood pressure and endothelial dysfunction [11].
It has been seen that pregnant women are prone to develop SDB due to anatomical, physiological and hormonal changes. Snoring, which is considered as a hallmark of SDB, is much more common in the pregnant population and has been observed in 14–46% of pregnant women [12, 13]. In studies conducted on Indian population, snoring and SDB were found in 18–27.5 and 7–9.5% of pregnant women, respectively [14, 15].
Recent studies have found a close association between SDB and preeclampsia [16, 17]. It is possible that, among pregnant women with SDB, intermittent hypoxia leading to abnormal sympathovagal balance and endothelial dysfunction may contribute to the development of new-onset hypertension. Thus, this common pathogenic pathway of the two conditions can explain the strong association of snoring and SDB with pregnancy-induced hypertension demonstrated by a growing body of evidence [16, 17]. Both are associated with similar long-term cardiovascular and metabolic consequences. Moreover, both preeclampsia and SDB are seen more often in the third trimester and are associated with poor fetal and maternal outcomes [16, 18]. The outcomes of SDB in preeclamptic women have not been studied extensively. However, preliminary evidence shows a worsening of maternal and fetal outcomes as the severity of SDB increases [17].
It was hypothesized that sleep-disordered breathing would be more prevalent in women with preeclampsia and gestational hypertension. Further, it was hypothesized that increasing severity of SDB would correlate with the severity of hypertension and the adverse pregnancy outcomes in these women. To test these hypotheses, this study was carried on a cohort of 40 patients with pregnancy-induced hypertension and 60 normotensive pregnant controls.
Methods
Participants
This was a prospective, case control study in which patients with preeclampsia or gestational hypertension in the age group, 18–35 years, who attended the antenatal OPD or admitted as inpatients at Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, were serially screened and those who met the inclusion criteria were offered to be part of the study. Ethical clearance from the institutional ethical committee was taken before commencing the study.
A total of 75 patients fulfilled the criteria; of these, 40 gave their consent to be part of the study; 20 patients did not give their consent and 15 patients had to be induced the same day because of the severity of the condition. The demographic and clinical profile of the women who did not give their consent was similar to that of the others.
Women with chronic or acute respiratory diseases, overt or gestational diabetes, renal disease, liver disease, heart disease, essential hypertension or any other medical or obstetrical condition known to have poor pregnancy outcomes were excluded from the study.
Gestational hypertension was defined as a blood pressure of ≥ 140/90 mmHg on two or more occasions 6 h apart, detected first after 20 weeks of pregnancy, whereas preeclampsia was diagnosed when hypertension was accompanied by albuminuria of 1 + or more on dipstick examination [1].
The control group consisted of pregnant women with no medical disease, attending the antenatal OPD. Eighty-eight women fulfilled the criteria out of which 60 agreed to undergo an overnight polysomnography (PSG).
Subject Evaluation
All the women underwent a detailed general physical, systemic and obstetric examination. The blood pressure was measured in the sitting position on the right arm; the procedure was repeated after 6 h if the initial value was ≥ 140/90 mm Hg. The patients were treated for pregnancy-induced hypertension as per the institutional protocol. The Berlin Sleep Questionnaire was used for the evaluation of SDB and was filled by one of the authors after directly questioning the subject. Daytime sleepiness was measured by using the Epworth Sleepiness Scale (ESS), and the subjects were asked to rate their probability of falling asleep in eight different situations on a score of 0–3. An ESS score of more than 10 was considered to be diagnostic of abnormal sleepiness [19, 20].
All the cases and controls were followed for maternal and fetal outcomes through pregnancy, labor and the postnatal period. The maternal and fetal outcome measures recorded were: preterm labor, antepartum hemorrhage, postpartum hemorrhage, eclampsia, intrauterine growth restriction, birth weight of neonate, APGAR score, mode and route of delivery and requirement for nursery admission.
Polysomnography
All the cases and controls underwent a whole-night polysomnography (PSG) in the hospital. A three-channel electroencephalography (F3M2, C3M2 and O1M2); two-channel electrooculography; anterior tibialis and submental electromyography; nasal airflow by thermistor; nasal pressure by pressure cannula; thoracic and abdominal efforts by strain gauges; oxygen saturation by pulse oximeter; and tracheal sound with microphone attached to the neck were recorded for all the subjects undergoing PSG. ALICE 5 digital polysomnography system (Respironics, Inc, Murrysville, PA) was used for recording and storing all the signals. All the PSG records were scored by an experienced sleep medicine specialist.
Definitions of Respiratory Parameters
Apnea was defined when there was a drop in the peak thermal sensor excursion by > 90% of the baseline lasting for ≥ 10 s. Hypopnea was defined as the drop of nasal pressure signal excursions by > 30% of the baseline lasting for ≥ 10 s, when accompanied by a drop in 3% or more of oxygen saturation from the pre-event baseline or an arousal. An arousal was scored when there was an abrupt shift of EEG frequency including alpha, theta and/or frequencies > 16 Hz that lasted at least 3 s with at least 10 s of stable sleep preceding the change. Apnea–Hypopnea Index (AHI) was defined as the number of obstructive apneas and hypopneas per hour of sleep. This was calculated by dividing total number of respiratory events with total sleep time in hours. SDB was defined as an AHI of 5 or more along with symptoms such as EDS or an AHI > 15 with or without associated symptoms [21]. The severity of SDB was defined according to the AHI as mild, 5–15/h; moderate, 16–30/h; and severe > 30/h [21]. Arousal Index was defined as number of arousals per hour of sleep. Minimum oxygen saturation was the lowest level oxygen saturation recorded during sleep study.
Statistical Evaluation
Comparison of blood pressure, demographic and PSG parameters was done between cases and controls using the using t test and Chi-square test, which showed the univariate association of pregnancy-induced hypertension with the covariates. To study the associations of demographic parameters, BP, PSG parameters with pregnancy-induced hypertension after eliminating the confounding effect of pre-pregnancy BMI, regression analysis technique was used. Association of PSG parameters with blood pressure was also found out using the Carl Pearson correlation coefficient. Regression analysis was used to check these associations adjusting for the pre-pregnancy BMI. Comparison of maternal and fetal complications between cases and controls was done using Chi-square test. Correlation of maternal and fetal complications among cases and controls separately, with PSG parameters, was also seen using coefficient of correlation and t test.
Results
The mean age of the cases (25.3 ± 3.9 years) and controls (25 ± 3.5 years) was comparable (p = 0.687). Both the pre-pregnancy and the present BMI were significantly higher in cases; however, the weight gain in both the groups was comparable (p = 0.298). The mean gestational age of the cases was 34.9 ± 1.7 weeks and that of controls was 35.7 ± 2.0 weeks (p = 0.03). The systolic, diastolic and mean blood pressures were significantly higher in the cases as compared to the controls (Table 1).
Table 1.
Comparison of demographic parameters and blood pressure between cases and controls
| Cases n = 40 (mean ± SD) | Controls n = 60 (mean ± SD) | p value | |
|---|---|---|---|
| Age (years) | 25.3 ± 3.9 | 25 ± 3.5 | 0.687 |
| BMI pre-pregnancy (kg/m2) | 22.4 ± 2.1 | 20.9 ± 1.0 | < 0.001 |
| Present BMI (kg/m2) | 26.1 ± 2.4 | 24.6 ± 1.3 | < 0.001 |
| Weight gain during pregnancy (kg) | 9.3 ± 1.4 | 9.0 ± 1.5 | 0.298 |
| POG at presentation (weeks) | 34.9 ± 1.7 | 35.7 ± 2.0 | 0.03 |
| SBP (mm Hg) | 143.6 ± 6.0 | 106.5 ± 6.4 | < 0.001 |
| DBP (mm Hg) | 93.8 ± 4.1 | 69.3 ± 5.4 | < 0.001 |
| MBP (mm Hg) | 110.2 ± 4.0 | 82.0 ± 5.3 | < 0.001 |
BMI body mass index, POG period of gestation, SBP, systolic blood pressure, DBP diastolic blood pressure, MBP mean blood pressure
Both snoring and SDB were significantly higher in the cases as compared to the control group even after controlling for the BMI (p < 0.001; OR 74.4 and p = 0.018; OR 13.1, respectively). The cases had a significantly higher AHI (11.3 ± 3.7) as compared to controls (4.6 ± 1.9) indicating more severe disease in them (Table 2). The majority of the cases had mild-to-moderate disease, whereas most of the controls had mild disease. The Arousal Index (AI) was significantly higher (13.3 ± 3.9 vs. 7.6 ± 2.7; p < 0.001), and the minimum oxygen saturation was lower in the cases (94.1 ± 2.0 vs. 94.9 ± 1.0; p = 0.028) (Table 2).
Table 2.
Comparison of polysomnography parameters between cases and controls
| Polysomnography parameters | Cases N = 40 (mean ± SD) | Controls N = 60 (mean ± SD) | p value | p value after adjustment for BMI pre-pregnancy (using regression analysis technique) | |
|---|---|---|---|---|---|
| Snoring | 90% | 12.5% | < 0.001 (OR 63) | < 0.001 (OR 74.4) | |
| SDB (AHI > 5 + EDS; and AHI > 15) | 38.3% | 2.5% | < 0.001 (OR 24.2) | 0.018 (OR 13.1) | |
| AHI | 11.3 ± 3.7 | 4.6 ± 1.9 | < 0.001 | < 0.001 (OR 1.84) | |
| AHI category | < 5 (normal) | 13.0% | 91.4% | < 0.001 | |
| 5–14.99 (mild) | 68.5% | 8.6% | |||
| 15–29.99 (moderate) | 18.5% | 0% | |||
| AI (per hour) | 13.3 ± 3.9 | 7.6 ± 2.7 | < 0.001 | ||
| Minimum oxygen saturation (%) | 94.1 ± 2.0 | 94.9 ± 1.0 | 0.028 | ||
AHI Apnea–Hypopnea Index, AI Arousal Index, SDB Sleep-disordered breathing
On correlating the pre-pregnancy BMI with the blood pressure and AHI, it was seen that there was a significant correlation of the pre-pregnancy BMI with the SBP, DBP and MBP as well as AHI signifying the important role of pre-pregnancy BMI in the causation of both hypertension and SDB (Table 3, Fig. 1).
Table 3.
Correlation of pre-pregnancy BMI with BP and AHI
| BMI | ||
|---|---|---|
| SBP | Pearson correlation | 0.517** |
| Sig. (2-tailed) | < 0.001 | |
| DBP | Pearson correlation | 0.554** |
| Sig. (2-tailed) | < 0.001 | |
| MBP | Pearson correlation | 0.617 |
| Sig. (2-tailed) | < 0.001 | |
| AHI | Pearson correlation | 0.745** |
| Sig. (2-tailed) | < 0.001 |
BMI body mass index, SBP systolic blood pressure, DBP diastolic blood pressure, MBP mean blood pressure, AHI Apnea–Hypopnea Index
**p < 0.001
Fig. 1.
Correlation of pre-pregnancy BMI and polysomnography AHI
When the association between the SDB parameters was studied with blood pressure, it was observed that SBP, DBP and MBP correlated positively with AHI and Arousal Index which remained significant even after adjustment for BMI for AHI using regression analysis. There was a negative correlation of minimum oxygen saturation with SBP, DBP and MBP (r = − 0.506, p < 0.001; r = − 0.475, p < 0.001; r = − 0.567, p < 0.001, respectively). It was also observed that the cases with proteinuria had a higher AHI (15.4 ± 1.8 vs. 10.1 ± 3.1; p < 0.001); higher AI (17.1 ± 1.4 vs. 12.1 ± 3.6, p < 0.001); and lower minimum oxygen saturation (92.2 ± 2.3 vs. 94.7 ± 1.2, p = 0.003; Table 4, Figs. 1, 2, 3). A similar association was found between the blood pressure and PSG parameters (AHI and Arousal Index) in controls (Figs. 2, 3, 4, 5).
Table 4.
Correlation of polysomnography parameters with blood pressure and proteinuria
| SBP | DBP | Mean BP | Proteinuria | |||
|---|---|---|---|---|---|---|
| Pearson correlation (r) (p value) | Pearson correlation (r) (p value) | Pearson correlation (r) (p value) | Yes | No | p value | |
| AHI | 0.545 (< 0.001) | 0.518 (< 0.001) | 0.612 (< 0.001) | 15.4 ± 1.8 | 10.1 ± 3.1 | < 0.001 |
| AI | 0.483 (< 0.001) | 0.395 (− 0.003) | 0.5 (− 0.003) | 17.1 ± 1.4 | 12.1 ± 3.6 | < 0.001 |
| Minimum oxygen saturation | − 0.506 (< 0.001) | − 0.475 (< 0.001) | − 0.567 (< 0.001) | 92.2 ± 2.3 | 94.7 ± 1.2 | 0.003 |
SBP systolic blood pressure, DBP diastolic blood pressure, MBP mean blood pressure, AHI Apnea–Hypopnea Index, AI Arousal Index
Fig. 2.
Correlation of systolic BP and AHI in cases and controls
Fig. 3.
Correlation of diastolic BP and polysomnography AHI in cases and controls
Fig. 4.
Correlation of systolic BP and Arousal Index in cases and controls
Fig. 5.
Correlation of diastolic BP and Arousal Index in cases and controls
To determine the contribution of SDB in the causation of maternal and fetal complications, the PSG parameters were correlated with these outcomes. It was observed that the mean AHI and mean AI were significantly higher in the cases who had induced delivery, LSCS and preterm labor, whereas the minimum oxygen saturation was lower in them. The mean AHI and mean AI were found to be higher in cases with PPH though it was not significant. However, the minimum oxygen saturation was significantly lower in women with PPH (p = 0.009). When the PSG parameters were correlated with the outcomes in controls, we did not find any significant correlation (Table 5).
Table 5.
Associations of maternal complications with polysomnography parameters in cases and controls
| Maternal complications | Cases | Controls | ||||
|---|---|---|---|---|---|---|
| AHI | AI | Minimum oxygen saturation | AHI | AI | Minimum oxygen saturation | |
| Mean ± SD | Mean ± SD | Mean ± SD | Mean ± SD | Mean ± SD | Mean ± SD | |
| Labor onset | ||||||
| Spontaneous | 8.27 ± 3.76 | 10.17 ± 4.81 | 95.30 ± . 999 | 4.6 ± 2.1 | 7.3 ± 2.4 | 95.0 ± 0.9 |
| Induced | 12.23 ± 3.15 | 14.29 ± 2.99 | 93.83 ± 2.02 | 4.3 ± 0.3 | 7.5 ± 2.0 | 94.5 ± 1.4 |
| p value | 0.004 | 0.001 | 0.002 | 0.707 | 0.853 | 0.238 |
| PPH | ||||||
| No | 11.22 ± 3.62 | 13.22 ± 3.83 | 94.29 ± 1.57 | |||
| Yes | 13.63 ± 4.36 | 16.10 ± 3.46 | 91.33 ± 5.03 | |||
| p value | − 0.439 | 0.284 | 0.009 | |||
| Preterm labor | ||||||
| Yes | 14.94 ± 2.43 | 16.34 ± 2.53 | 91.56 ± 2.506 | |||
| No | 10.63 ± 3.45 | 12.79 ± 3.79 | 94.65 ± 1.31 | |||
| p value | < 0.001 | 0.003 | < 0.001 | |||
| Type of delivery | ||||||
| Vaginal | 9.58 ± 3.34 | 11.68 ± 3.96 | 94.93 ± 1.107 | 4.5 ± 1.9 | 7.2 ± 2.1 | 95.1 ± 0.85 |
| LSCS | 13.55 ± 2.87 | 15.41 ± 2.61 | 93.13 ± 2.25 | 5.1 ± 2.2 | 8.3 ± 2.8 | 94.6 ± 1.3 |
| p value | < 0.001 | < 0.001 | 0.002 | 0.661 | 0.406 | 0.06 |
AHI Apnea–Hypopnea Index, AI Arousal Index, LSCS lower segment cesarean section, PPH postpartum hemorrhage
When the parameters of SDB were correlated with fetal complications, it was observed that AHI and AI were significantly higher and minimum oxygen saturation was lower in infants with APGAR score less than 7, IUGR and those with nursery admission. The birth weights correlated negatively with the AHI and AI and positively with minimum oxygen saturation. Similar results were found in control subjects for fetal complications with AHI and AI but not with minimum oxygen saturation (Table 6, Fig. 6).
Table 6.
Correlation of fetal complications with polysomnography parameters among cases and controls
| Fetal complications | Cases | Controls | ||||
|---|---|---|---|---|---|---|
| AHI | AI | Minimum oxygen saturation | AHI | AI | Minimum oxygen saturation | |
| APGAR score (mean ± SD) | ||||||
| < 7 | 13.5 ± 2.4 | 15.5 ± 2.4 | 6.7 ± 3.6 | 10.1 ± 3.4 | 94.6 ± 0.8 | 93.3 ± 2.1 |
| > − 7 | 8.9 ± 3.3 | 10.9 ± 3.8 | 4.0 ± 0.5 | 6.7 ± 1.1 | 95.0 ± 1.0 | 95.2 ± 1.1 |
| p value | < 0.001 | < 0.001 | < 0.001 | < 0.001 | 0.217 | < 0.001 |
| Birth Wt | ||||||
| Pearson correlation (r) (p value) | − 0.647 (< 0.001) | − 0.569 (< 0.001) | − 0.426 (0.011) | − 0.308 (0.07) | 0.091 (0.602) | 0.683 (< 0.001) |
| IUGR (mean ± SD) | ||||||
| Yes | 13.168 ± 3.5015 | 14.976 ± 3.7223 | 7.0 ± 3.8 | 9.8 ± 3.9 | 94.8 ± 0.98 | 93.12 ± 2.205 |
| No | 9.786 ± 3.0630 | 12.007 ± 3.4247 | 4.1 ± 0.51 | 6.8 ± 1.4 | 95.0 ± 1.0 | 95.04 ± 1.055 |
| p value | < 0.001 | 0.004 | < 0.001 | 0.002 | 0.774 | < 0.001 |
| Nursery admission (mean ± SD) | ||||||
| Yes | 14.954 ± 2.6384 | 16.446 ± 2.5032 | 6.7 ± 4.2 | 9.8 ± 4.1 | 94.6 ± 0.89 | 91.85 ± 2.267 |
| No | 10.210 ± 3.1813 | 12.410 ± 3.6854 | 4.2 ± 0.97 | 7.0 ± 1.6 | 95.0 ± 1.0 | 94.87 ± 1.056 |
| p value | < 0.001 | < 0.001 | 0.005 | 0.008 | 0.400 | < 0.001 |
AHI Apnea–Hypopnea Index, AI Arousal Index, IUGR intrauterine growth restriction
Fig. 6.
Correlation of baby birth weight and AHI in cases and controls
Discussion
The results of the current study show that SDB occurs more frequently and with more severity in women with hypertensive disorders of pregnancy, as compared to normotensive pregnant women suggesting a strong association of both conditions. The pre-pregnancy BMI significantly correlated with both the AHI and the blood pressure indicating the contribution of obesity in the causation of hypertension and SDB. We also found a significant correlation between AHI and blood pressure parameters in both cases and controls even after adjustment for BMI pointing toward an independent role of SDB in the development of hypertension. Maternal and fetal complications were significantly associated with different parameters of SDB in cases, whereas fetal complications were also seen to correlate with some polysomnographic parameters in controls.
A high prevalence of increased SDB events and oxygen desaturations in preeclamptic women has been reported in a number of previous studies [16]. In these studies, the patients were much more obese (BMI 32.6 ± 9.5) than the patients in our study (BMI 26.1 ± 2.4), indicating the role of craniofacial features in our patients. Several studies including one conducted by the authors have noted that women with SDB are at increased risk of developing preeclampsia [15–18].
A number of factors may be associated with frequent occurrence of SDB in preeclampsia women. First, the physiological and anatomical changes during pregnancy which make a gravid woman more prone to sleep-disordered breathing [22–24] are more pronounced in preeclampsia due to alterations in the upper airway patency which may be related to the fluid shifts from the lower limbs to the neck area. This may explain the increased occurrence of SDB in preeclamptic women even after controlling for BMI which is one of the major risk factors for the development of SDB. Secondly, obesity has been reported to be a risk factor for SDB. It has been shown that BMI and central fat patterning may independently contribute to SDB [24, 25]. It is noteworthy that even though the cases in our study had a significantly higher pre-pregnancy BMI making them more susceptible to develop SDB, the weight gain in both the groups was comparable. The weight gain in the preeclamptic women may be contributed more by the presence of third space fluid rather than by the developing feto-placental unit, as most of these patients had IUGR. Increased third space fluid can result in remarkable fluid shifts from the lower limbs to the neck area leading to more severe upper airway narrowing in women with anatomical predispositions. This was further confirmed by our finding moderate-to-severe SDB disease in cases as against mild disease in controls. It would be interesting to study the craniofacial features of preeclamptic women to determine their role in the development of SDB. Finally, another notable feature is that preeclampsia typically presents toward the later part of the third trimester, which was also the case in our study. This may be due to the fact that the physiological changes which predispose a pregnant woman to SDB are at its peak during this time further strengthening the association of preeclampsia with SDB [23].
Whether SDB contributes to the development of preeclampsia or preeclampsia leads to the development of SDB is difficult to conclude confidently from our findings. It has been seen in the non-pregnant population that the cardiovascular manifestations of SDB may take several years to develop. However, pregnancy being a state of physiological stress can have an accelerated development of SDB. It could be possible that progesterone may augment the blood pressure responses to respiratory events which may result in rapid evolution of cardiovascular manifestations over a 9-month period. In our study too, we found that AHI, AI and minimum oxygen saturation correlated positively with blood pressure as well proteinuria, which persisted even after adjustment for BMI, signifying the contribution of SDB to the increasing severity of preeclampsia. Similar relationship between SDB and blood pressure was also observed in control subjects suggesting the significant role of SDB in the development of hypertension (Figs. 2, 3, 4, 5). There may be a likely bidirectional relationship between SDB and preeclampsia where one condition may perpetuate the other. There is a need to conduct prospective longitudinal and interventional studies with continuous positive airway pressure (CPAP) therapy to understand this complex relationship.
It is notable that the maternal and fetal outcomes in the cases correlated with all the PSG parameters highlighting the important role of SDB in worsening the pregnancy complications of preeclampsia. Louis et al. also found significant maternal and fetal complications in their patients of preeclampsia [26]. The mechanism for adverse outcomes may be explained by the fact that SDB triggers a worsening of the peripheral vasoconstriction and decreased cardiac output in these women. This further compromises the already reduced placental perfusion leading to poor fetal circulation. It was interestingly observed that adverse fetal outcomes in the control group also correlated with AHI further strengthening the primary role of SDB in the causation of these complications. However, the maternal outcomes in the control group were not significantly associated with AHI. This suggests that fetal outcomes are more vulnerable to even milder disease observed in controls than the maternal outcomes. Some preliminary data do show the positive effect of CPAP treatment on preeclampsia [27]. Besides an improvement in maternal outcomes, there is some preliminary evidence about improved fetal outcomes in preeclamptic women using CPAP [28].
The strength of this study lies in the large number of cases studied. Furthermore, all the preeclamptic women and controls underwent a whole-night, in-lab polysomnography which is considered the gold standard for diagnosis of SDB. Being a longitudinal study, the maternal and fetal outcomes could also be assessed.
However, there were few limitations in our study. First, majority of cases we studied had mild preeclampsia, as the women with severe disease had to undergo urgent obstetric intervention. Secondly, all our patients were above 30 weeks of gestation period with a range of 30–37 weeks and this group may be quite different from those develop preeclampsia early, i.e., before 30 weeks, as preterm preeclampsia is associated with higher maternal and fetal morbidity. So our results cannot be extrapolated to all groups of preeclampsia patients. Thirdly, we did not repeat the PSG of the women with SDB after 6–12 weeks of delivery when all the pregnancy changes are considered to reverse. These data could help us in determining the representation of women with SDB antedating pregnancy. Lastly, we did not record the upper airway anatomical features contributing to the development of SDB in these patients.
As the prevalence of preeclampsia is quite high (5–7%) and the consequences on the maternal and fetal morbidity are significantly high, the results of our study strongly suggest the need for screening of all preeclamptic women for SDB. Since the availability of full PSG is limited in the resource-limited countries, there is an urgent need to develop simpler and effective methods to screen and diagnose these patients.
To summarize the findings of this study, it was seen that SDB occurred more frequently and with more severity in women with pregnancy-induced hypertension as compared to normotensive, pregnant women even after controlling for BMI. The increased prevalence and severity of SDB in preeclampsia could be due to the altered fluid dynamics and more severe neck and laryngeal edema in preeclamptics as compared to the normal pregnant women. There was a significant correlation between the parameters of SDB and pregnancy-induced hypertension and proteinuria independent of BMI, suggesting the role of SDB in the increasing severity of preeclampsia. Further, it was observed that AHI correlated with poor maternal and fetal outcomes in the cases and poor fetal outcomes even in the controls suggesting a strong contribution of SDB in the poor pregnancy outcomes.
Dr. Jyotsna Suri
Professor at the Department of Obstetrics and Gynaecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi. She has a special interest in obstetric critical care and gynae-endocrinology. She is a WHO Fellow in Reproductive Endocrinology. She has organized and conducted several workshops on Obstetric Critical Care in different parts of the country. She is currently the Chairperson of the Multidiscplinary Patient Care Committee of Association of Obstetricians and Gynaecologists of Delhi and was also Chief Editor of AOGD in 2015–2016. She has several original research papers in International and National journals and has co-authored a book titled “Practical Approach to Critical Care in Obstetrics.”
Compliance with Ethical Standards
Conflict of interest
There is no conflict of interest of any of the author involved in this research work.
Human and Animals Rights
This was an observational study with no intervention. The study was approved by the institutional ethical committee.
Informed Consent
Informed consent was taken from all the participants included in the study.
Footnotes
Jyotsna Suri, Professor at Department of Obstetrics and Gynaecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi; Jagdish Chander Suri, Professor and Head, Department of Pulmonary, Critical Care and Sleep Medicine, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi; Renu Arora, Professor, Department of Obstetrics and Gynaecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi; Megha Gupta, Junior Resident, Department of Obstetrics and Gynaecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi; Tulsi Adhikari, Scientist, Indian Council of Medical Research, New Delhi.
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