PREDICTIVE VALUE OF FETAL MIDDLE CEREBRAL ARTERY TO UTERINE ARTERY PULSATILITY INDEX RATIO IN PREECLAMPSIA

Document Type : Original Article

Authors

1 Department of Obstetrics and Gynecology, Faculty of Medicine, Al-Azhar University

2 Department of Obstetrics and Gynecology, Faculty of Medicine, Al Azhar University

Abstract

Background: Complicating 2–8% of pregnancies, pre-eclampsia (PE) is a major cause of maternal and perinatal morbidity and mortality worldwide, especially in developing countries. The middle cerebral artery (MCA) to uterine artery (UTA) pulsatility index (PI) ratio and MCA to umbilical artery (UA) PI ratio have been described to be good predictors of perinatal outcome in pre-eclamptic patients in the third trimester, and have been proposed to identify fetuses at risk of morbidity and mortality.
Objective: To demonstrate the predictive value of middle cerebral artery (MCA) / uterine artery (UTA) pulsatility index (PI) ratio compared with that of the MCA/umbilical artery (UA) PI ratio in the assessment of fetal well-being in pregnant women with preeclampsia.
Patients and methods: This case control study included 200 pregnant females attended the outpatient clinic at the Maternity Hospital of Al-Azhar University (Bab Elshaariya Hospital) during the period of one year, starting from January 2020 till December 2020, Cairo, Egypt. There were divided into two equal groups; Control group (100 females with normal pregnancy) and Preeclampsia group (100 pregnant females with preeclampsia). Transabdominal ultrasonography was conducted for the assessment of the pulsatility indices of MCA, UA and UTA followed by estimation of the previous ratios.
Results: The duration of pregnancy was shorter in the preeclampsia group compared to controls. Cesarean section rates were higher in cases with preeclampsia with a significant difference between the two groups. The incidence of perinatal death, preterm birth, NICU admission and IUGR was significantly higher in preeclampsia cases. The mean MCA PI, mean MCA/UA ratio and MCA/UTA ratio were statistically significantly higher, while the mean UA PI and mean UTA PI were significantly lower in the control group as compared with preeclampsia group. MCA/UTA ratio revealed better ability in prediction of all the adverse effects of preeclampsia when compared to MCA/UA ratio.
Conclusion: Low middle cerebral artery/ uterine artery pulsatility index ratio in cases with preeclampsia is significantly associated with adverse perinatal outcomes. Middle cerebral artery/ uterine artery pulsatility index ratio had significantly higher predictive value for adverse outcomes compared to middle cerebral artery/umbilical artery pulsatility index ratio.

Keywords

Main Subjects


PREDICTIVE VALUE OF FETAL MIDDLE CEREBRAL ARTERY TO UTERINE ARTERY PULSATILITY INDEX RATIO IN PREECLAMPSIA

By

Mohamed Khaled Mohamed Tawfeek, Abd El-Monsef Abd El-Hameed Sedeek and Awad Mahmoud Awad

Department of Obstetrics and Gynecology, Faculty of Medicine, Al Azhar University

Corresponding author: Mohamed Khaled Mohamed Tawfeek,

E-mail: dr.mohamedkhaledtawfeek@gmail.com

ABSTRACT

Background: Complicating 2–8% of pregnancies, pre-eclampsia (PE) is a major cause of maternal and perinatal morbidity and mortality worldwide, especially in developing countries. The middle cerebral artery (MCA) to uterine artery (UTA) pulsatility index (PI) ratio and MCA to umbilical artery (UA) PI ratio have been described to be good predictors of perinatal outcome in pre-eclamptic patients in the third trimester, and have been proposed to identify fetuses at risk of morbidity and mortality.

Objective: To demonstrate the predictive value of middle cerebral artery (MCA) / uterine artery (UTA) pulsatility index (PI) ratio compared with that of the MCA/umbilical artery (UA) PI ratio in the assessment of fetal well-being in pregnant women with preeclampsia.

Patients and methods: This case control study included 200 pregnant females attended the outpatient clinic at the Maternity Hospital of Al-Azhar University (Bab Elshaariya Hospital) during the period of one year, starting from January 2020 till December 2020, Cairo, Egypt. There were divided into two equal groups; Control group (100 females with normal pregnancy) and Preeclampsia group (100 pregnant females with preeclampsia). Transabdominal ultrasonography was conducted for the assessment of the pulsatility indices of MCA, UA and UTA followed by estimation of the previous ratios.

Results: The duration of pregnancy was shorter in the preeclampsia group compared to controls. Cesarean section rates were higher in cases with preeclampsia with a significant difference between the two groups. The incidence of perinatal death, preterm birth, NICU admission and IUGR was significantly higher in preeclampsia cases. The mean MCA PI, mean MCA/UA ratio and MCA/UTA ratio were statistically significantly higher, while the mean UA PI and mean UTA PI were significantly lower in the control group as compared with preeclampsia group. MCA/UTA ratio revealed better ability in prediction of all the adverse effects of preeclampsia when compared to MCA/UA ratio.

Conclusion: Low middle cerebral artery/ uterine artery pulsatility index ratio in cases with preeclampsia is significantly associated with adverse perinatal outcomes. Middle cerebral artery/ uterine artery pulsatility index ratio had significantly higher predictive value for adverse outcomes compared to middle cerebral artery/umbilical artery pulsatility index ratio.

Keywords: Preeclampsia, Doppler, Middle cerebral artery, Neonatal outcomes.

 

 

INTRODUCTION

     Hypertension in pregnancy is diagnosed when the pregnant lady has a systolic blood pressure > 140 mmHg and a diastolic blood pressure > 90 mmHg on at least two time points, six hours apart. The term “hypertension in pregnancy” encompasses three clinical entities; gestational hypertension, preeclampsia, and eclampsia. A previous Egyptian study reported that the prevalence of pregnancy induced hypertension was 4.2, whereas the prevalence of preeclampsia and eclampsia was 3.8 and 0.3% respectively (Amaral et al., 2017).

     Preeclampsia is strongly associated with adverse obstetric and neonatal outcomes including intrauterine growth restriction (IUGR), abruptio placenta, and still birth (Dymara-Konopka et al., 2018). The pathogenesis of preeclampsia is mediated through vascular endothelial damage and vasospasm which have a negative impact on fetal hemodynamics (Dhariwal and Lynde, 2017). Kramer reported that these adverse outcomes are more encountered in developing countries compared to developed ones. Therefore, it is crucial for obstetricians to consider appropriate antenatal surveillance and to choose the optimum therapeutic intervention (Snead et al., 2020).

     Recently, the great development in medical technology has made doppler velocity study of critical importance in clinical obstetric practice as it can provide information about both placental and fetal circulations. Various doppler indices have been developed to assess the status of uteroplacental flow (Raj et al., 2017).

     Multiple studies have reported that middle cerebral artery (MCA) to umbilical artery (UA) ratio is more beneficial than MCA indices alone in the detection of placental abnormality in females with high-risk pregnancy (Eser et al., 2011). As placental insufficiency develops, compensatory mechanisms occur to the fetal circulation to keep blood supply to the more important organs like brain and heart and thus, maximizing the brain sparing effect (Stefopoulou et al., 2020).

     Others have found that uterine artery  (UTA) doppler indices are good indicators for both placental perfusion and fetal status in in the 3rd trimester of high-risk pregnancies, making it more beneficial more than UA doppler that can only assess the placental pathology (Ukah et al., 2017).

     The current study was conducted to calculate third trimester MCA/UTA PI ratio and to compare its predictive value with that of the MCA/UA PI ratio regarding perinatal adverse effects in pregnant ladies presented with preeclampsia.

PATIENTS AND METHODS

     This prospective case control study was conducted at Maternity Hospital of Al-Azhar University (Bab Elshaariya Hospital) during the period of one year, starting from January 2020 till December 2020, after gaining approval from the local ethical committee of Al-Azhar University. We included a total of 200 pregnant ladies who were classified into two groups; Group A included 100 females with normal pregnancy, and Group B that included the remaining 100 ladies diagnosed with preeclampsia. Preeclampsia was defined according to the “National Blood High Pressure Education Program Working Group” on high blood pressure in pregnancy (Lucero et al., 2019).

     All of the included subjects had singleton pregnancy with gestational age ≥ 28 weeks. Conversely, females with history of preexisting hypertension, uncontrolled systemic comorbidities (like diabetes), receiving medications during pregnancy rather than iron therapy, in active labor, or with membrane rupture were excluded.

     Before evaluation, an informed consent was obtained from all ladies after explaining the benefits, steps and drawbacks of each intervention. Then, all of the included participants were subjected to detailed history taking, general examination (including blood pressure measurement and lower limb examination for edema), and complete obstetric examination. In addition, pelviabdominal ultrasound examination was performed using GE (voluson E6) ultrasound machine equipped with color doppler options (a 3.5 MHz curved transducer).

     US examination was performed when the lady was at the semi recumbent position to avoid caval compression. The pulsatility index of the UA was estimated on a free-floating umbilical cord loop in the absence of breathing and movement. To estimate the MCA PI, the circle of Willis was identified after obtaining an axial view of the fetal head. The MCA was identified as a major anterolateral branch that runs towards the lateral orbital edge. The doppler sample volume was estimated about 1 cm distal to its origin. Besides, the mean PI of the right and left uterine arteries was estimated as well.

     MCA to UTA PI ratio together with MCA to UA were estimated. The former was plotted on a specific chart, and any value less than the 5th percentile was considered abnormal, while the latter was considered as abnormal or to have brain sparing effect, when the ratio was less than 1.08 (Simanaviciute and Gudmundsson, 2010). All cases had regular follow up till delivery and the perinatal outcome was evaluated and recorded. Our outcomes included mode of delivery, birth weight, gestational age at delivery, APGAR score, incidence of small for gestational age newborn (SGA), and need for neonatal intensive care unit admission (NICU). With the follow up, 23 females dropped out (lack of follow up), so the final number included was 89 females in the normal pregnancy group and 88 females in the PE group.

Statistical analysis:

     Collection and analysis of the data was conducted using statistical package of social science (SPSS, IBM Chicago-USA) version 24. Data were either expressed in the form of number and percentage (with categorical data) while the quantitative data were expressed as mean ± SD with parametric data or median and range for non-parametric data. We used chi-square or Fischer’s exact tests to compare two independent groups of categorical data. While comparing the quantitative data within two independent groups, independent samples t-test was used for parametric data and Mann-Whitney U test for non-parametric data. Diagnostic ability of predictors variable in relation to categorical outcome were expressed in terms of sensitivity, specificity, negative predictive value and post predictive value. Odd’s ratio was also used to express diagnostic ability of predictive variables. For all used statistical tests, the cut-off point below 0.05 for probability (P value) was considered to be a statistically significant.


RESULTS

 

 

     The mean age of the females in the control group was 26.89 years while in females with preeclampsia was 30.27 years. The age of the participants was significantly older in the preeclampsia group. Nevertheless, BMI was not significantly different between the two groups as it had mean values of 28.35 and 27.83 kg/m2 in control and preeclampsia groups respectively. Both gravidity and parity did not constitute a significant difference between the study groups (Table 1).


 

Table (1):  Demographic and clinical parameters in the study groups

Groups

Variables

Control

(N=100)

Preeclampsia

(N=100)

P value

Age (years)

Mean ± SD

26.89 ± 4.88

30.27 ± 5.86

0.001

BMI (kg/m2)

Mean ± SD

28.35± 6.59

27.83±5.77

0.375

Gravidity

Median (min-max)

3 (1 – 5)

2 (1 – 5)

0.322

Parity

Median (min-max)

1 (0 – 3)

2 (0 – 4)

0.274

SBP (mmHg)

Mean ± SD

121.33 ± 10.14

151.66 ± 7.94

< 0.001

DBP (mmHg)

Mean ± SD

81.51 ± 8.12

93.66 ± 7.18

< 0.001

GA (weeks)

Median (min-max)

30 (27 – 32)

31 (27 – 32)

0.216

BMI: Body mass index. DBP: Diastolic blood pressure. GA: Gestational age. SBP: Systolic blood pressure.

 

 

     The mean MCA PI in the control group was 1.65 ± 0.39 which was statistically significant higher as compared with the preeclampsia group (1.31 ± 0.27) (p = 0.035). the mean UA PI in the control group was 0.98 ± 0.17 which was statistically significant lower as compared with the preeclampsia group (1.22 ± 0.25) (p = 0.021). the mean UTA PI in the control group was 0.81 ± 0.11 which was statistically significant lower as compared with the preeclampsia group (1.25 ± 0.22) (p = 0.009). The mean MCA/UA ratio in the control group was 1.68 ± 2.29 which was statistically significant higher as compared with the preeclampsia group (1.07 ± 1.08) (p = 0.001). The mean MCA/UTA ratio in the control group was 2.02 ± 2.69 which was statistically significant higher as compared with the preeclampsia group (1.08 ± 1.14) (p < 0.001) (Table 2).

 

 

 

 

 

 

 

 

 

Table (2):  Doppler indices in the study groups

Groups

Variables

Control

(N=100)

Preeclampsia

(N=100)

P value

MCA PI

Mean ± SD

1.65 ± 0.39

1.31 ± 0.27

0.035

UA PI

Mean ± SD

0.98 ± 0.17

1.22 ± 0.25

0.021

UTA PI

Mean ± SD

0.81 ± 0.11

1.25 ± 0.22

0.009

MCA/UA ratio 

Mean ± SD

1.68 ± 2.29

1.07 ± 1.08

0.001

MCA/UTA ratio 

Mean ± SD

2.02 ± 2.69

1.08 ± 1.14

< 0.001

MCA: Middle cerebral artery. UA: umbilical artery. UTA: Uterine artery. PI: Pulsatility index.

 

 

     In the control group, vaginal delivery was conducted in 27 females (30.3%) and CS in 62 females (69.7%), the percentage of the CS was higher in cases with preeclampsia (79.6%) (p = 0.009). The duration of pregnancy was shorter in the preeclampsia group as compared with controls (p = 0.018). Additionally, the birth weight was significantly lower in the preeclampsia cases compared to controls (P < 0.001). the median 5-min APGAR score was statistically significantly lower in the preeclampsia group as compared with the control group (p= 0.024). The incidence of IUGR, preterm birth, perinatal death, and NICU admission was statistically significant higher in the preeclampsia group as compared to controls (P < 0.001) (Table 3).

 

 

Table (3):  Pregnancy and neonatal outcomes of the study groups

Groups

Variables

Control

(N=89)

Preeclampsia

(N=88)

P value

Mode of delivery

-Vaginal

-CS

 

27 (30.3%)

62 (69.7%)

 

18 (20.4%)

70 (79.6%)

0.009

GA at delivery (weeks)

Median (min-max)

38 (36 – 40)

34 (31 – 38)

0.018

Birth weight (gm)

Mean ± SD

2906.22 ± 419.42

1938.84 ± 368.23

< 0.001

5 min APGAR score

Median (min-max)

9 (6 – 10)

7 (4 – 9)

0.024

Perinatal death

1 (1.1%)

14 (15.9%)

0.009

Preterm birth

5 (5.6%)

42 (47.7%)

< 0.001

NICU admission

7 (7.8%)

32 (36.4%)

< 0.001

IUGR

4 (4.4%)

22 (25%)

0.001

CS: Cesarean section. IUGR: Intrauterine growth retardation. NICU: Neonatal intensive care unit.

 

 

     Normal and abnormal MCA/UA ratios and MCA/UTA ratio in relation to adverse outcomes in preeclampsia were compared. The odds ratio (OR) for abnormal MCA/UTA ratio was higher compared to the OR of MCA/UA ratio in prediction of the adverse neonatal outcomes including decreased 5-min APGAR score (< 6), preterm infants, NICU, IUGR and perinatal death (Table 4).


Table (4):  Normal and abnormal MCA/UA ratio and MCA/UTA ratio in relation to adverse outcomes in preeclampsia

Outcome

MCA/UA ratio

MCA/UTA ratio

Total

(n=44)

Normal (n=58)

Abnormal (n=30)

OR

Normal (n=52)

Abnormal (n=36)

OR

Decreased 5-min APGAR score (<6)

24 (41.4%)

20 (66.7%)

0.83

18 (34.6%)

26 (72.2%)

1.44

44 (50%)

Preterm

22(37.9%)

20 (66.7%)

0.91

16 (30.8%)

26 (72.2%)

1.63

42 (47.7%)

NICU

16 (27.6%)

16 (53.3%)

1

12 (23.1%)

20 (55.6%)

1.67

32 (36.4%)

IUGR

8 (13.8%)

14 (46.7%)

1.75

4 (7.6%)

18 (50%)

4.5

22 (25%)

Perinatal death

6 (10.3%)

8 (26.7%)

1.33

2 (3.8%)

12 (33.3%)

6

14 (15.9%)

IUGR: Intrauterine growth retardation. MCA: Middle cerebral artery. NICU: Neonatal intensive care unit. UA: Umbilical artery. UTA: Uterine artery.

 

 

     The predictive ability of MCA/UA ratio and MCA/UTA ratio in relation to adverse outcomes in preeclampsia. The MCA/UTA ratio revealed better ability in prediction of all the adverse effects of preeclampsia when compared to MCA/UA ratio (Table 5).

 

 

Table (5):  Predictive ability of MCA/UA ratio and MCA/UTA ratio in relation to adverse outcomes in preeclampsia

 

Sensitivity (%)

Specificity (%)

PPV (%)

NPV (%)

MCA/UA ratio

Decreased 5-min APGAR score (<6)

45.4

77.3

66.7

58.6

Preterm

47.6

56.3

66.7

62.1

NICU

50

75

53.3

72.4

IUGR

63.6

75.7

46.7

86.2

Perinatal death

57.1

70.3

26.7

89.7

MCA/UTA ratio

Decreased 5-min APGAR score (<6)

59.1

77.3

72.2

65.4

Preterm

61.9

78.2

72.2

69.2

NICU

62.5

62.5

55.6

71.4

IUGR

81.8

72.7

50

92.3

Perinatal death

85.7

67.6

33.3

96.2

IUGR: Intrauterine growth retardation. MCA: Middle cerebral artery. NICU: Neonatal intensive care unit. UA: Umbilical artery. UTA: uterine artery.

 

 

 

 

 

 

DISCUSSION

     In the recent era, doppler US is a very useful tool for monitoring high-risk pregnancy. Multiple studies have established the relationship between abnormal doppler findings and adverse pregnancy outcomes in cases with preeclampsia (Eser et al., 2011 and Adiga et al., 2015). Both MCA PI/UA PI and MCA PI/UTA PI ratio have been proposed as predictors for adverse obstetric and perinatal outcomes in such cases (Shahinaj et al., 2010 and Eser et al., 2011).

     This study was conducted to calculate third trimester MCA/UTA PI ratio and to compare its predictive value with that of the MCA/UA PI ratio regarding perinatal adverse effects in pregnant ladies presented with preeclampsia. This case control study included 200 pregnant females who were classified into two groups; group A that included 100 pregnant females with normal pregnancy and group B that included 100 pregnant females with preeclampsia. In this study, age was significantly older in cases with preeclampsia compared to controls (30.27 vs. 26.86 years respectively – p < 0.05).

     This came in accordance with Gabal et al. (2017) who reported that there was a significant positive correlation between age and blood pressure of the pregnant participants. The included cases had mean ages of 29.1 and 25.4 years in the preeclampsia and control groups respectively. Also, Eldeeb and his associates reported, in their epidemiological study, that the highest incidence of preeclampsia was noted in ladies older than 40 years (El Deeb et al., 2015).

     In this study, no significant difference was detected between the two groups regarding either parity or gravidity. This came in accordance with Gabal et al. (2010) who showed no significant relation between parity and preeclampsia. Nevertheless, another study conducted in Sweden reported that primiparous females were more prone to develop preeclampsia compared to multiparous women (≥ 3 deliveries). Another study reported that both nulliparous and high multiparous women were at increased risk of developing that condition (Al-Shaikh et al., 2017). The disparity between different studies could be attributed to different patient criteria, sample size and statistical tests between different studies. Also, the economic status of the included cases could play a role as a previous study has confirmed that low socioeconomic status is a risk factor for preeclampsia during pregnancy (Ganesh et al., 2010).

     In this study, the mean values of SBP and DBP were statistically significant higher in the preeclampsia group as compared with the control group (p < 0.001). This came in line with the results published by Simanaviciute and Gudmundsson (2010), Eser et al. (2011) and Orabona et al. (2015).

     In this study, the duration of pregnancy was shorter in the preeclampsia group as compared with the control group indicating early termination of pregnancy (p = 0.018). This came in accordance with Eser et al. (2011) who showed that cases with preeclampsia had significantly lower GA compared to controls.

     In this study, in the control group, vaginal delivery occurred in 27 females (30.3%) and CS in 62 females (69.7%), the percentage of the CS was higher in cases with preeclampsia (79.6%). Statistical analysis showed a significant difference between the two groups (p = 0.009). The higher prevalence of CS could be explained by the unavailability of facilities required for maternal and fetal monitoring during delivery, along with the increased rates of on-demand CS. Of note, previous studies have reported an increased complication rates on performing CS in cases with preeclampsia (Mahran et al., 2017).

     In this study, the birth weight was statistically significant lower in cases with preeclampsia compared to controls (P < 0.001). The median 5-min APGAR score had significantly lower values in cases compared to controls (p= 0.024). Moreover, the incidence of perinatal death, preterm birth, NICU and IUGR was statistically significant higher in cases versus controls (P < 0.001). This came in accordance with Mayrink et al. (2019) who reported that cases with preeclampsia had a 3.97-fold increased risk for preterm delivery compared to controls. Also, neonates showed higher incidence of low birth weight, small for gestational age, and NICU admission compared to controls. In addition, the same group had significantly lower APGAR score after 5 minutes of delivery. This also agreed with Hoffman et al. (2018) who showed that mothers with preeclampsia had significantly increased incidence of preterm delivery, low birth weight, and post-partum complications (p < 0.001).

     Furthermore, Akinlade et al. (2015) reported that birth weight, infant length, Apgar score, and head circumference were significantly lower in neonates of women with preeclampsia when compared with the controls. The observed low birth weight, low gestational age, small infant length, low ponderal index, and small head circumference in infants of women with preeclampsia is in line with the report of Onyiriuka and Okolo (2010).

     This was attributed to the degree of hypoxia, which accompanies preeclampsia, especially when there is placental abruption which deprives the fetus of oxygen and nourishment and as a consequence, the fetus dies (Armaly et al., 2018).

     In this study, the mean MCA PI, mean MCA/UA ratio and MCA/UTA ratio had significantly higher values in controls compared to the preeclampsia group while the mean UA PI and mean UTA PI had significantly lower values. Eser et al. (2011) confirmed our findings.

     In this study, the odds ratio (OR) for abnormal MCA/UTA ratio was higher as compared with the OR of MCA/UA ratio in prediction of the adverse neonatal outcomes including decreased 5-min APGAR score (<6) (1.44 vs 0.83), preterm infants (1.63 vs 0.91), NICU (1.67 vs 1), IUGR (4.5 vs 1.75) and perinatal death (6 vs 1.33).

     This came in agreement with Simanaviciute and Gudmundsson (2010) who reported that the low MCA/UTA PI ratio was associated with a higher incidence of SGA newborns (57.8% vs. 25.7%), preterm labor (100% vs. 81.8%) and CS rates (90.7% vs. 66.7%) compared to cases who had higher values of the same ratio. This also came in accordance with Eser et al. (2011) who reported that 42.3% of cases with preeclampsia had their MCA/UTA ratio below the 5th percentile. Cases who expressed MCA/UTA PI ratio showed higher rates of preterm delivery, CS, and NICU admission. However, cases with low MCA/UA PI ratio, only higher rates of CS and NICU admission were noted.

     In this study, the MCA/UTA ratio revealed better ability in prediction of all the adverse effects of preeclampsia when compared to MCA/UA ratio PI. This came in agreement with Orabona et al. (2015) who showed that the MCA/UTA PI ratio had a higher predictive value for perinatal outcome when compared to MCA PI/UA PI. Multiple studies also confirmed the previous findings (Arduini and Rizzo, 2010, Arbeille et al., 2010 and Arias, 2010), and the predictive value of MCA/UTA  PI  ratio  has been found to be more accurate before 34 weeks of gestation (McCowan and Naden, 2010 and Arias, 2011). The superiority of uterine artery to umbilical artery could be explained by the fact that UA doppler indices basically reflect placental abnormalities, while being deficient in evaluating patient status. On the other hand, UTA doppler indices could reflect both placental as well as fetal abnormalities (Hernandez-Andrade et al., 2012).

     In contrast to our results, Simanaviciute and Gudmundsson (2010) reported that both ratios had comparable predictive value regarding the same parameter.

     Our study has some limitations, first of all, it is a single center study that included a relatively sample size. Also, the long-term neonatal outcomes should have been assessed as well. These cons should be covered in the upcoming studies.

CONCLUSION

     All in all, abnormally low MCA/UTA PI ratio in preeclamptic patients is significantly related to adverse perinatal outcomes. MCA/UTA PI ratio has significantly higher predictive value for adverse outcomes compared to MCA/UA PI ratio.

REFERENCES

  1. Adiga P, Kantharaja I, Hebbar S, Rai L, Guruvare S and Mundkur A. (2015): Predictive value of middle cerebral artery to uterine artery pulsatility index ratio in hypertensive disorders of pregnancy. International Journal of Reproductive Medicine. 15: 102-108.
  2. Akinlade KS, Adediji IO, Rahamon SK, Fawole AO and Tongo OO. (2015): Serum copeptin and pregnancy outcome in preeclampsia. Nigerian Medical Journal, 56(5):362-66.
  3. Al-Shaikh GK, Ibrahim GH, Fayed AA and AlMandeel H. (2017): Grand multiparity and the possible risks of of adverse maternal and neonatal outcomes: A dilemma to be deciphered. BMC Pregnancy and Childbirth, 17:310-316.
  4. Amaral LM, Wallace K, Owens M and LaMarca B. (2017): Pathophysiology and current clinical management of preeclampsia. Current Hypertension Reports, 19(8):61-66.
  5. Arbeille P, Roncin A, Berson M, Patat F and Pourcelot L. (2010): Exploration of the fetal cerebral blood flow by duplex Doppler—linear array system in normal and pathological pregnancies. Ultrasound in Medicine and Biology, 13(6):329-37.
  6. Arduini D and Rizzo G. (2010): Prediction of fetal outcome in small for gestational age fetuses: comparison of Doppler measurements obtained from different fetal vessels. Journal of Perinatal Medicine-Official Journal of the WAPM, 20(1):29-38.
  7. Arias F. (2011): Accuracy of the middle-cerebral-to-umbilical-artery resistance index ratio in the prediction of neonatal outcome in patients at high risk for fetal and neonatal complications. American Journal of Obstetrics and Gynecology, 171(6):1541-5.
  8. Armaly Z, Jadaon JE, Jabbour A and Abassi ZA. (2018): Preeclampsia: novel mechanisms and potential therapeutic approaches. Frontiers in Physiology, 9:973-78.
  9. Dhariwal NK and Lynde GC. (2017): Update in the management of patients with preeclampsia. Anesthesiology Clinics, 35(1):95-106.
  10. Dymara-Konopka W, Laskowska M and Oleszczuk J. (2018): Preeclampsia-current management and future approach. Current Pharmaceutical Biotechnology, 19(10):786-96.
  11. El Deeb SIH, El-Bakry MM, Nouh AAA and Mohamed SME. (2015): prevalence of pregnancy induced hypertension Zagazig university Hospital. Zagazig University Medical Journal, 36: 96-104.
  12. Eser A, Zulfıkaroglu E, Eserdag S, Kılıc S and Danısman N. (2011): Predictive value of middle cerebral artery to uterine artery pulsatility index ratio in preeclampsia. Archives of Gynecology and Obstetrics, 284(2):307-11.
  13. Gabal MS, Abousaif HA, Salah-Eldin W and Abdelaziz AM. (2017): Frequency of Hypertension Associated with Pregnancy among The Pregnant Women Attending Maternal and Child Care Centers in Belbeis City. Egyptian Journal of Community Medicine, 35(3): 58-63.
  14. Ganesh KS, Unnikrishnan B, Nagaraj K and Jayaram S. (2010): Determinants of pre-eclampsia: a case–control study in a district hospital in South India. Indian journal of community medicine: official publication of Indian Association of Preventive and Social Medicine, 35(4):502-506.
  15. Hernandez-Andrade E, Brodszki J, Lingman G, Gudmundsson S, Molin J and Maršál K. (2012): Uterine artery score and perinatal outcome. Ultrasound in Obstetrics and Gynecology: The Official Journal of the International Society of Ultrasound in Obstetrics and Gynecology, 19(5):438-42.
  16. Hoffman K, Patel A, Tang A and Poornima I. (2018): A case-control study of preeclampsia and the future development of cardiovascular risk factors. Journal of the American College of Cardiology, 71(11): 1861-66.
  17. Lucero JM, Peterson-Layne C and Smith KA. (2019): Update in diagnosis and management of preeclampsia. ASA Newsletter., 83(4):20-3.
  18. Mahran A, Fares H and Elkhateeb R. (2017): Risk factors and outcome of patients with eclampsia at a tertiary hospital in Egypt. BMC Pregnancy and Childbirth, 17(1):435-442.
  19. Mayrink J, Souza RT and Feitosa FE. (2019): Incidence and risk factors for Preeclampsia in a cohort of healthy nulliparous pregnant women: a nested case-control study. Scientific Reports, 9(1):1-9.
  20. McCowan LM and Naden RP. (2010): Doppler ultrasound in pregnancies with hypertension. Australian and New Zealand Journal of Obstetrics and Gynaecology, 32(3):225-30.
  21. Onyiriuka AN and Okolo AA. (2010): Perinatal outcome in patients with pre-eclampsia in Benin City, Nigeria. Tropical Journal of Obstetrics and Gynaecology, 21(2):148-52.
  22. Orabona R, Gerosa V and Gregorini ME. (2015): The prognostic role of various indices and ratios of Doppler velocimetry in patients with pre-eclampsia. Clinical and Experimental Hypertension, 37(1):57-62.
  23. Raj A, Bhat RK, Prajwal S and Rao P. (2017): Foetal umbilical artery doppler versus NST as predictors of adverse perinatal outcome in severe preeclampsia and foetal growth restriction. International Journal of Reproduction, Contraception, Obstetrics and Gynecology, 6(5):2061-67.
  24. Shahinaj R, Manoku N, Kroi E and Tasha I. (2010): The value of the middle cerebral to umbilical artery Doppler ratio in the prediction of neonatal outcome in patient with preeclampsia and gestational hypertension. Journal of Prenatal Medicine, 4(2):17-23.
  25. Simanaviciute D and Gudmundsson S. (2010): Fetal middle cerebral to uterine artery pulsatility index ratios in normal and pre-eclamptic pregnancies. Ultrasound in Obstetrics and Gynecology: The Official Journal of the International Society of Ultrasound in Obstetrics and Gynecology, 28(6):794-801.
  26. Snead CM, Strassberg E and Overcash R. (2020): Obstetricians’ knowledge and practices regarding the management of preeclampsia. The Journal of Maternal-Fetal and Neonatal Medicine, 33(17):2970-5.
  27. Stefopoulou M, Johnson J and Wilsgaard T. (2020): Volume blood flow-based indices of fetal brain sparing in the second half of pregnancy: A longitudinal study. Acta Obstetricia et Gynecologica Scandinavica., 99(12):1717-27.
  28. Ukah U, Payne B, Côté A, Hoodbhoy Z and von Dadelszen P. (2017): Placental growth factor as a prognostic tool in women with hypertensive disorders of pregnancy. Hypertension, 70:1228–1237.
  29. Wikström A-K, Stephansson O and Cnattingius S. (2010): Tobacco use during pregnancy and preeclampsia risk: effects of cigarette smoking and snuff. Hypertension, 55(5):1254-9.


القيمه التنبؤيه للشريان الدماغي الأوسط الجنيني إلي نسبه مؤشر نبضات الشريان الرحمي في حالات تسمم الحمل

محمد خالد محمد توفيق، عبد المنصف عبد الحميد صديق، عوض محمود عوض

قسم التوليد وأمراض النساء، کلية الطب، جامعة الأزهر

Corresponding author: Mohamed Khaled Mohamed Tawfeek,

E-mail: dr.mohamedkhaledtawfeek@gmail.com

خلفية البحث: تسمم الحمل مسؤولا عن حدوث مضاعفات في 2-8% من حالات الحمل، تسمم الحمل يعد سببًا رئيسيًا لإصابة ووفيات الأمهات في فترة الخصوبة في جميع أنحاء العالم، خاصة في البلدان النامية. يرتبط إجهاد الجنين بنقص التأکسد بمؤشرات دوبلر غير طبيعية للشريان السري، ويؤدي توسع الأوعية الدماغية التعويضيه إلى الانخفاض في نبض الشريان الدماغي الأوسط. تم وصف نسبة مؤشر النبض للشريان الدماغي الأوسط إلى الشريان الرحمي ونسبة الشريان الدماغي الأوسط إلى الشريان السري على أنها تنبئ جيدًا بنتائج الولادة في مرضى تسمم الحمل في الفترة الأخيرة من الحمل.

الهدف من البحث: هو حساب نسبة مؤشر النبض للشريان الدماغي الأوسط إلى الشريان الرحمي في الثلث الثالث من الحمل وإثبات قيمتها التنبؤية للمخرجات الخاصة بالجنين مقارنة مع نسبة نسبة مؤشر النبض للشريان الدماغي الأوسط إلي الشريان السري في حالات الحمل المعقدة مع تسمم الحمل.

المريضات وطرق البحث: تضمنت دراسة الحالة هذه 200 امرأة حامل حضرن إلى العيادة الخارجية بمستشفى الولادة بجامعة الأزهر (مستشفى باب الشعرية) خلال فترة عام واحد، بدءًا من يناير 2020 حتى ديسمبر 2020، القاهرة، مصر. تم تقسيمهم إلى مجموعتين متساويتين. وتم تصنيفها إلى مجموعتين، المجموعة (أ) التي ضمت الإناث الحوامل بحمل طبيعي، والمجموعة (ب) والتي ضمت الإناث الحوامل مصابات بتسمم الحمل. في الزيارة الأولى، خضعت الحالات لأخذ التاريخ المرضي الکامل، وفحص عام وفحص مفصل للبطن مع الترکيز على فحص الرحم للکشف عن مستوى الرحم. تم إجراء التصوير بالموجات فوق الصوتية عبر البطن لتأکيد وجود الحمل وللتأکد من عمر الحمل. تبع ذلک تقييم لمؤشرات النبض للشريان السري والشريان الرحمي والشريان الدماغي الأوسط.

نتائج البحث: کانت مدة الحمل أقصر في مجموعة تسمم الحمل مقارنة مع مجموعة التحکم التي تشير إلى الإنهاء المبکر للحمل. وکانت النسبة المئوية للولادة القيصرية أعلى في مجموعة تسمم الحمل (79.6٪) مع اختلاف معتد به إحصائياً بين المجموعتين. وکان معدل حدوث وفيات الفترة المحيطة بالولادة والولادة قبل الموعد ودخول وحدة العناية المرکزة لحديثي الولادة وتأخر النمو داخل الرحم أعلى بشکل معتد به إحصائياً في مجموعة السيدات المصابات بتسمم الحمل مقارنة بالمجموعة الضابطة. وکان متوسط نسبة مؤشر النبض للشريان الدماغي الأوسط، ونسبة الشريان الدماغي الأوسط إلى الشريان السري ونسبة للشريان الدماغي الأوسط إلى الشريان الرحمي أعلى بفرق ذو دلالة إحصائية في المجموعة الضابطة مقارنة بمجموعة تسمم الحمل. وکان متوسط مؤشر النبض إلي الشريان السري ومتوسط مؤشر النبض إلي نسبة الشريان الدماغي الأوسط أقل بفرق ذو دلالة إحصائية في المجموعة الضابطة. وکشفت نسبة الشريان الدماغي الأوسط إلي الشريان الرحمي عن قدرة أفضل في التنبؤ بجميع الآثار الضارة لمقدمات تسمم الحمل (الإرتعاج) بالمقارنة مع نسبة الشريان السري إلي الشريان الدماغي الأوسط.

الإستنتاج: إنخفاض نسبة مؤشر نبض الشريان الدماغي الأوسط/ الشريان الرحمي في حالات مقدمات الارتعاج يرتبط بشکل کبير بنتائج الفترة المحيطة بالولادة الضائرة. کان لنسبة مؤشر نبض الشريان الدماغي الأوسط/ الشريان الرحمي قيمة تنبؤية أعلى بشکل ملحوظ للنتائج الضائرة مقارنة بنسبة مؤشر نبض الشريان الدماغي الأوسط/ الشريان السري.

الکلمات الدالة: تسمم الحمل، دوبلر، الشريان الدماغي الأوسط، نتائج حديثي الولادة.

  1. REFERENCES

    1. Adiga P, Kantharaja I, Hebbar S, Rai L, Guruvare S and Mundkur A. (2015): Predictive value of middle cerebral artery to uterine artery pulsatility index ratio in hypertensive disorders of pregnancy. International Journal of Reproductive Medicine. 15: 102-108.
    2. Akinlade KS, Adediji IO, Rahamon SK, Fawole AO and Tongo OO. (2015): Serum copeptin and pregnancy outcome in preeclampsia. Nigerian Medical Journal, 56(5):362-66.
    3. Al-Shaikh GK, Ibrahim GH, Fayed AA and AlMandeel H. (2017): Grand multiparity and the possible risks of of adverse maternal and neonatal outcomes: A dilemma to be deciphered. BMC Pregnancy and Childbirth, 17:310-316.
    4. Amaral LM, Wallace K, Owens M and LaMarca B. (2017): Pathophysiology and current clinical management of preeclampsia. Current Hypertension Reports, 19(8):61-66.
    5. Arbeille P, Roncin A, Berson M, Patat F and Pourcelot L. (2010): Exploration of the fetal cerebral blood flow by duplex Doppler—linear array system in normal and pathological pregnancies. Ultrasound in Medicine and Biology, 13(6):329-37.
    6. Arduini D and Rizzo G. (2010): Prediction of fetal outcome in small for gestational age fetuses: comparison of Doppler measurements obtained from different fetal vessels. Journal of Perinatal Medicine-Official Journal of the WAPM, 20(1):29-38.
    7. Arias F. (2011): Accuracy of the middle-cerebral-to-umbilical-artery resistance index ratio in the prediction of neonatal outcome in patients at high risk for fetal and neonatal complications. American Journal of Obstetrics and Gynecology, 171(6):1541-5.
    8. Armaly Z, Jadaon JE, Jabbour A and Abassi ZA. (2018): Preeclampsia: novel mechanisms and potential therapeutic approaches. Frontiers in Physiology, 9:973-78.
    9. Dhariwal NK and Lynde GC. (2017): Update in the management of patients with preeclampsia. Anesthesiology Clinics, 35(1):95-106.
    10. Dymara-Konopka W, Laskowska M and Oleszczuk J. (2018): Preeclampsia-current management and future approach. Current Pharmaceutical Biotechnology, 19(10):786-96.
    11. El Deeb SIH, El-Bakry MM, Nouh AAA and Mohamed SME. (2015): prevalence of pregnancy induced hypertension Zagazig university Hospital. Zagazig University Medical Journal, 36: 96-104.
    12. Eser A, Zulfıkaroglu E, Eserdag S, Kılıc S and Danısman N. (2011): Predictive value of middle cerebral artery to uterine artery pulsatility index ratio in preeclampsia. Archives of Gynecology and Obstetrics, 284(2):307-11.
    13. Gabal MS, Abousaif HA, Salah-Eldin W and Abdelaziz AM. (2017): Frequency of Hypertension Associated with Pregnancy among The Pregnant Women Attending Maternal and Child Care Centers in Belbeis City. Egyptian Journal of Community Medicine, 35(3): 58-63.
    14. Ganesh KS, Unnikrishnan B, Nagaraj K and Jayaram S. (2010): Determinants of pre-eclampsia: a case–control study in a district hospital in South India. Indian journal of community medicine: official publication of Indian Association of Preventive and Social Medicine, 35(4):502-506.
    15. Hernandez-Andrade E, Brodszki J, Lingman G, Gudmundsson S, Molin J and Maršál K. (2012): Uterine artery score and perinatal outcome. Ultrasound in Obstetrics and Gynecology: The Official Journal of the International Society of Ultrasound in Obstetrics and Gynecology, 19(5):438-42.
    16. Hoffman K, Patel A, Tang A and Poornima I. (2018): A case-control study of preeclampsia and the future development of cardiovascular risk factors. Journal of the American College of Cardiology, 71(11): 1861-66.
    17. Lucero JM, Peterson-Layne C and Smith KA. (2019): Update in diagnosis and management of preeclampsia. ASA Newsletter., 83(4):20-3.
    18. Mahran A, Fares H and Elkhateeb R. (2017): Risk factors and outcome of patients with eclampsia at a tertiary hospital in Egypt. BMC Pregnancy and Childbirth, 17(1):435-442.
    19. Mayrink J, Souza RT and Feitosa FE. (2019): Incidence and risk factors for Preeclampsia in a cohort of healthy nulliparous pregnant women: a nested case-control study. Scientific Reports, 9(1):1-9.
    20. McCowan LM and Naden RP. (2010): Doppler ultrasound in pregnancies with hypertension. Australian and New Zealand Journal of Obstetrics and Gynaecology, 32(3):225-30.
    21. Onyiriuka AN and Okolo AA. (2010): Perinatal outcome in patients with pre-eclampsia in Benin City, Nigeria. Tropical Journal of Obstetrics and Gynaecology, 21(2):148-52.
    22. Orabona R, Gerosa V and Gregorini ME. (2015): The prognostic role of various indices and ratios of Doppler velocimetry in patients with pre-eclampsia. Clinical and Experimental Hypertension, 37(1):57-62.
    23. Raj A, Bhat RK, Prajwal S and Rao P. (2017): Foetal umbilical artery doppler versus NST as predictors of adverse perinatal outcome in severe preeclampsia and foetal growth restriction. International Journal of Reproduction, Contraception, Obstetrics and Gynecology, 6(5):2061-67.
    24. Shahinaj R, Manoku N, Kroi E and Tasha I. (2010): The value of the middle cerebral to umbilical artery Doppler ratio in the prediction of neonatal outcome in patient with preeclampsia and gestational hypertension. Journal of Prenatal Medicine, 4(2):17-23.
    25. Simanaviciute D and Gudmundsson S. (2010): Fetal middle cerebral to uterine artery pulsatility index ratios in normal and pre-eclamptic pregnancies. Ultrasound in Obstetrics and Gynecology: The Official Journal of the International Society of Ultrasound in Obstetrics and Gynecology, 28(6):794-801.
    26. Snead CM, Strassberg E and Overcash R. (2020): Obstetricians’ knowledge and practices regarding the management of preeclampsia. The Journal of Maternal-Fetal and Neonatal Medicine, 33(17):2970-5.
    27. Stefopoulou M, Johnson J and Wilsgaard T. (2020): Volume blood flow-based indices of fetal brain sparing in the second half of pregnancy: A longitudinal study. Acta Obstetricia et Gynecologica Scandinavica., 99(12):1717-27.
    28. Ukah U, Payne B, Côté A, Hoodbhoy Z and von Dadelszen P. (2017): Placental growth factor as a prognostic tool in women with hypertensive disorders of pregnancy. Hypertension, 70:1228–1237.
    29. Wikström A-K, Stephansson O and Cnattingius S. (2010): Tobacco use during pregnancy and preeclampsia risk: effects of cigarette smoking and snuff. Hypertension, 55(5):1254-9.