Second trimester uterine arteries pulsatility index is a function of placental pathology and provides insights on stillbirth aetiology: A multicenter matched case-control study

Amodeo, Silvia; Cavoretto, Paolo; Seidenari, Anna; Paci, Giuseppe; Germano, Chiara; Monari, Francesca; Donno, Valeria; Giambanco, Laura; Avagliano, Laura; Martino, Daniela Di; Fusè, F.; Masturzo, Bianca; Chiàntera, Vito; Facchinetti, Fabio; Ferrazzi, E.; Candiani, Massimo; Bulfamante, Gaetano; Farina, Antonio

doi:10.1016/j.placenta.2022.02.021

Cited by 21 publications

(15 citation statements)

References 27 publications

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“…Ultrasound can be used to measure Doppler velocimetry in the uterine artery, which is associated with development of preeclampsia and placental pathology 21 , 22 , but when it comes to morphological markers of impaired placental function, reliable indicators are scarce. It is well-documented that placental volume is often smaller in hypertensive pregnancies and cases with growth restriction 23 , 24 .…”

Section: Discussionmentioning

confidence: 99%

Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization

Andreasen

Feragen

Christensen

et al. 2023

Sci Rep

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The placenta is crucial to fetal well-being and it plays a significant role in the pathogenesis of hypertensive pregnancy disorders. Moreover, a timely diagnosis of placenta previa may save lives. Ultrasound is the primary imaging modality in pregnancy, but high-quality imaging depends on the access to equipment and staff, which is not possible in all settings. Convolutional neural networks may help standardize the acquisition of images for fetal diagnostics. Our aim was to develop a deep learning based model for classification and segmentation of the placenta in ultrasound images. We trained a model based on manual annotations of 7,500 ultrasound images to identify and segment the placenta. The model's performance was compared to annotations made by 25 clinicians (experts, trainees, midwives). The overall image classification accuracy was 81%. The average intersection over union score (IoU) reached 0.78. The model’s accuracy was lower than experts’ and trainees’, but it outperformed all clinicians at delineating the placenta, IoU = 0.75 vs 0.69, 0.66, 0.59. The model was cross validated on 100 2nd trimester images from Barcelona, yielding an accuracy of 76%, IoU 0.68. In conclusion, we developed a model for automatic classification and segmentation of the placenta with consistent performance across different patient populations. It may be used for automated detection of placenta previa and enable future deep learning research in placental dysfunction.

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Section: Discussionmentioning

confidence: 99%

Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization

Andreasen

Feragen

Christensen

et al. 2023

Sci Rep

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“…Genetic variations between patients and ethnic origin could be attributed in part to variations in microRNAs. The search for an association between biomarkers or sonographic findings with specific diseases or pathological conditions including preeclampsia, stillbirth and IUGR is underway [ 26 , 27 ]. Studies have shown an association between specific biomarkers and severity of adhesions in endometriosis and sonographic findings associated with the severity of adhesions in repeat CDs [ 28 , 29 ].…”

Section: Discussionmentioning

confidence: 99%

Repeat low order caesarean delivery, risk factors for complications: A retrospective, longitudinal study

et al. 2023

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One-third of cesarean deliveries (CDs) are repeat operations, of which the majority are low-order, second (CD2) and third (CD3). The study objectives were to identify risk factors for a complicated maternal CD among women undergoing a repeat low-order CD and to develop a predictive model for at-risk women. A retrospective longitudinal follow-up study was conducted in a single medical center, during 2005–2016. Women who underwent both CD2 and CD3 at the site were included. Those with placenta accreta or a caesarean hysterectomy were excluded. A composite complicated maternal CD was defined by either uterine rupture/dehiscence, blood transfusion, relaparotomy, admission to the intensive care unit or prolonged operative time >90th percentile. Data was analyzed comparing between CD2 to CD3, each woman served as her own control. Univariate analysis followed by a multivariate logistic regression modeling were performed with an OR of 95% CI defining significance. The study group comprised of 1,331 women. A complicated CD occurred in 159 (12%) vs. 226 (17%) of CD2 vs. CD3 respectively, (p<0.001). Women with a complicated CD2 were at higher risk for complications in CD3, aOR 2.3 (95% CI 1.5, 3.3). Sub-Saharan African origin and preterm delivery at CD3 were both risk factors for a complicated CD3, aOR 3.7 (95% CI 1.9, 7.3) and aOR 1.7 (95% CI 1.1, 2.7), respectively. The multivariate regression model included 1328 cases, was statistically significant, χ2(7) = 50.760, p <0.001, explained 6.3% of the variance of composite complicated maternal CD3 and correctly classified 82.9% of cases. Although a complicated CD2, Sub-Saharan African origin and preterm delivery are risk factors for maternal complications in CD3, it is hard to predict which specific women will experience complications. Sensitivity, specificity, positive and negative predictive value of a complicated CD2 for detecting complications in CD3 were 21%, 90%, 30% and 85% respectively.

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“…Recently, the COVID-19 lockdown contributed to a higher proportion of weight gain than in previous years [28]. The BMI can contribute to many other pregnancy complications such as increased risk of stillbirth, altered glucose tolerance, endocrine dysfunctions and its associated gynecological and obstetric outcomes during pregnancy [29,30].…”

Section: Discussionmentioning

confidence: 99%

Effect of body mass index on pregnancy outcomes: a prospective observational study from a rural south Indian tertiary care setting

Venkataraman¹,

Yadav²,

Pukal³

2023

Ital J Gynaecol Obstet

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Introduction. The effect of body mass index (BMI) on pregnancy outcome is not well established especially in a south Indian population. This study aimed to assess the link between maternal BMI and pregnancy outcomes. Materials and Methods.A prospective observational study was conducted among 150 pregnant women subjects in a south Indian tertiary care center for a period of 6 months after obtaining ethical M a n u s c r i p t a c c e p t e d f o r p u b l i c a t i o n 2 approval. Pregnant women aged 18 or above who were accepted and willing to provide written informed consent were included in the study. The relevant data were collected from patients and analyzed using SPSS version 16.Results. A higher proportion of participants (65.3%) had normal BMI, followed by overweight or obese (32%) and only 2.7% were underweight. Being overweight was significantly associated with depression (p = 0.032) and gestational diabetes (p = 0.000), but not with gestational hypertension and pre-eclampsia (p > 0.05) in the pregnant woman.Conclusions. The overweight and obesity were significantly associated with gestational diabetes and depression among pregnant women.

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Second trimester uterine arteries pulsatility index is a function of placental pathology and provides insights on stillbirth aetiology: A multicenter matched case-control study

Cited by 21 publications

References 27 publications

Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization

Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization

Repeat low order caesarean delivery, risk factors for complications: A retrospective, longitudinal study

Effect of body mass index on pregnancy outcomes: a prospective observational study from a rural south Indian tertiary care setting

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