The predictive value of sonographic placental markers for adverse pregnancy outcome in women with chronic kidney disease

Contribution of Second Trimester Sonographic Placental Morphology to Uterine Artery Doppler in the Prediction of Placenta-Mediated Pregnancy Complications

Background: Second-trimester uterine artery Doppler is a well-established tool for the prediction of preeclampsia and fetal growth restriction. At delivery, placentas from affected pregnancies may have gross pathologic findings. Some of these features are detectable by ultrasound, but the relative importance of placental morphologic assessment and uterine artery Doppler in mid-pregnancy is presently unclear. Objective: To characterize the association of second-trimester sonographic placental morphology markers with placenta-mediated complications and determine whether these markers are predictive of placental dysfunction independent of uterine artery Doppler. Methods: This was a retrospective cohort study of patients with a singleton pregnancy at high risk of placental complications who underwent a sonographic placental study at mid-gestation (160/7−246/7 weeks’ gestation) in a single tertiary referral center between 2016−2019. The sonographic placental study included assessment of placental dimensions (length, width, and thickness), placental texture appearance, umbilical cord anatomy, and uterine artery Doppler (mean pulsatility index and early diastolic notching). Placental area and volume were calculated based on placental length, width, and thickness. Continuous placental markers were converted to multiples on medians (MoM). The primary outcome was a composite of early-onset preeclampsia and birthweight < 3rd centile. Results: A total of 429 eligible patients were identified during the study period, of whom 45 (10.5%) experienced the primary outcome. The rate of the primary outcome increased progressively with decreasing placental length, width, and area, and increased progressively with increasing mean uterine artery pulsatility index (PI). By contrast, placental thickness followed a U-shaped relationship with the primary outcome. Placental length, width, and area, mean uterine artery PI and bilateral uterine artery notching were all associated with the primary outcome. However, in the adjusted analysis, the association persisted only for placenta area (adjusted odds ratio [aOR] 0.21, 95%-confidence interval [CI] 0.06−0.73) and mean uterine artery PI (aOR 11.71, 95%-CI 3.84−35.72). The area under the ROC curve was highest for mean uterine artery PI (0.80, 95%-CI 0.71−0.89) and was significantly higher than that of placental area (0.67, 95%-CI 0.57−0.76, p = 0.44). A model that included both mean uterine artery PI and placental area did not significantly increase the area under the curve (0.82, 95%-CI 0.74−0.90, p = 0.255), and was associated with a relatively minor increase in specificity for the primary outcome compared with mean uterine artery PI alone (63% [95%-CI 58−68%] vs. 52% [95%-CI 47−57%]). Conclusion: Placental area is independently associated with the risk of placenta-mediated complications yet, when combined with uterine artery Doppler, did not further improve the prediction of such complications compared with uterine artery Doppler alone.

FIGO (international Federation of Gynecology and obstetrics) initiative on fetal growth: best practice advice for screening, diagnosis, and management of fetal growth restriction

Fetal growth restriction (FGR) is defined as the failure of the fetus to meet its growth potential due to a pathological factor, most commonly placental dysfunction. Worldwide, FGR is a leading cause of stillbirth, neonatal mortality, and short- and long-term morbidity. Ongoing advances in clinical care, especially in definitions, diagnosis, and management of FGR, require efforts to effectively translate these changes to the wide range of obstetric care providers. This article highlights agreements based on current research in the diagnosis and management of FGR, and the areas that need more research to provide further clarification of recommendations. The purpose of this article is to provide a comprehensive summary of available evidence along with practical recommendations concerning the care of pregnancies at risk of or complicated by FGR, with the overall goal to decrease the risk of stillbirth and neonatal mortality and morbidity associated with this condition. To achieve these goals, FIGO (the International Federation of Gynecology and Obstetrics) brought together international experts to review and summarize current knowledge of FGR. This summary is directed at multiple stakeholders, including healthcare providers, healthcare delivery organizations and providers, FIGO member societies, and professional organizations. Recognizing the variation in the resources and expertise available for the management of FGR in different countries or regions, this article attempts to take into consideration the unique aspects of antenatal care in low-resource settings (labelled “LRS” in the recommendations). This was achieved by collaboration with authors and FIGO member societies from low-resource settings such as India, Sub-Saharan Africa, the Middle East, and Latin America.

Deep convolutional neural network for chronic kidney disease prediction using ultrasound imaging

Objectives

Chronic kidney disease (CKD) is a common disease and it is related to a higher risk of cardiovascular disease and end-stage renal disease that can be prevented by the earlier recognition and diagnosis of individuals at risk. Even though risk factors for CKD have been recognized, the effectiveness of CKD risk classification via prediction models remains uncertain. This paper intends to introduce a new predictive model for CKD using US image.

Methods

The proposed model includes three main phases “(1) preprocessing, (2) feature extraction, (3) and classification.” In the first phase, the input image is subjected to preprocessing, which deploys image inpainting and median filtering processes. After preprocessing, feature extraction takes place under four cases; (a) texture analysis to detect the characteristics of texture, (b) proposed high-level feature enabled local binary pattern (LBP) extraction, (c) area based feature extraction, and (d) mean intensity based feature extraction. These extracted features are then subjected for classification, where “optimized deep convolutional neural network (DCNN)” is used. In order to make the prediction more accurate, the weight and the activation function of DCNN are optimally chosen by a new hybrid model termed as diversity maintained hybrid whale moth flame optimization (DM-HWM) model.

Results

The accuracy of adopted model at 40th training percentage was 44.72, 11.02, 5.59, 3.92, 3.92, 3.57, 2.59, 1.71, 1.68, and 0.42% superior to traditional artificial neural networks (ANN), support vector machine (SVM), NB, J48, NB-tree, LR, composite hypercube on iterated random projection (CHIRP), CNN, moth flame optimization (MFO), and whale optimization algorithm (WOA) models.

Conclusions

Finally, the superiority of the adopted scheme is validated over other conventional models in terms of various measures.

Role of sFlt-1/PIGF ratio and uterine Doppler in pregnancies with chronic kidney disease suspected with Pre-eclampsia or HELLP syndrome

PURPOSE

Pregnancies of women with chronic kidney disease (CKD) are at higher risk of experiencing adverse perinatal (APO) and maternal outcome (AMO). Mean uterine artery pulsatility index (mUtA-PI) as well as the ratio of soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PlGF) are helpful tools in diagnosing pre-eclampsia (PE) in women with CKD. The aim of the study was to evaluate the role of sFlt-1/PIGF ratio and mUtA-PI as predictors for APO, AMO, preterm delivery and decline of kidney function in CKD pregnancies.

METHODS

A total of 28 CKD pregnancies with suspected PE/HELLP syndrome were retrospectively included, in whom both sFlt-1/PIGF and mUtA-PI were determined during the third trimester. APO was defined as fetal growth restriction, respiratory distress syndrome, intubation, admission to NICU, 5 min Apgar <7 and intracerebral hemorrhage. AMO was defined as the development of PE, HELLP syndrome or resistant hypertension. Decline of kidney function was defined as a 25% increase of creatinine level after delivery.

RESULTS

Of all included women, eight (28.6%) developed a PE/HELLP syndrome. AMO (28.6%) and APO (32.1%) were frequently observed. ROC analyses revealed a predictive value for AMO and sFlt-1/PIGF or mUtA-PI. Neither sFlt-1/PIGF nor mUtA-PI could predict APO or decline of postnatal kidney function. mUtA-PI was a predictor for preterm delivery.

CONCLUSION

Uterine Doppler and sFlt-1/PIGF are predictors of AMO in CKD pregnancies. Therefore, both markers might be helpful for an improved risk assessment. However, neither sFlt-1/PIGF nor mUtA-PI were able to predict a decline of postnatal kidney function or APO.