Contribution of uniparental disomy to fetal growth restriction: a whole-exome sequencing series in a prenatal setting.

Fetal growth restriction (FGR), a leading cause of perinatal morbidity and mortality, is caused by fetal, maternal, and placental factors. Uniparental disomy (UPD) is a rare condition that leads to imprinting effects, low-level mosaic aneuploidies and homozygosity for pathogenic variants. In the present study, UPD events were detected in 5 women with FGR by trio exome sequencing (trio-WES) of a cohort of 150 FGR cases. Furthermore, noninvasive prenatal testing results of the 5 patients revealed a high risk of rare autosomal trisomy. Trio-WES showed no copy-number variations (CNVs) or nondisease-causing mutations associated with FGR. Among the 5 women with FGR, two showed gene imprinting, and two exhibited confined placental mosaicism (CPM) by copy number variant sequencing (CNV-seq). The present study showed that in FGR patients with UPD, the detection of imprinted genes and CPM could enhance the genetic diagnosis of FGR.

Association between plasma brain-derived neurotrophic factor level and Alzheimer's disease: a Mendelian randomization study.

BACKGROUND: High brain-derived neurotrophic factor (BDNF) concentrations have been found to be associated with a decreased risk of Alzheimer's disease (AD) in observational studies, but the causality for this association remains unclear. Therefore, we aimed to examine the association between genetically determined plasma BDNF levels and AD using a two-sample Mendelian randomization (MR) method. METHODS: Twenty single-nucleotide polymorphisms associated with plasma BDNF concentrations were identified as genetic instruments based on a genome-wide association study with 3301 European individuals. Summary-level data on AD were obtained from the International Genomics of Alzheimer's Project, involving 21,982 AD cases and 41,944 controls of European ancestry. To evaluate the relationship between plasma BDNF concentrations and AD, we employed the inverse-variance weighted method along with a series of sensitivity analyses. RESULTS: The inverse-variance weighted MR analysis showed that genetically determined BDNF concentrations were associated with a decreased risk of AD (odds ratio per SD increase, 0.91; 95% confidence interval, 0.86-0.96; p =0.001). The association between plasma BDNF concentrations and AD was further confirmed through sensitivity analyses using different MR methods, and MR-Egger regression suggested no directional pleiotropy for this association. CONCLUSION: Genetically determined BDNF levels were associated with a decreased risk of AD, suggesting that BDNF was implicated in the development of AD and might be a promising target for the prevention of AD.

Analysis of complex chromosomal rearrangement involving chromosome 6 via the integration of optical genomic mapping and molecular cytogenetic methodologies.

Complex chromosomal rearrangements (CCRs) can result in spontaneous abortions, infertility, and malformations in newborns. In this study, we explored a familial CCR involving chromosome 6 by combining optical genomic mapping (OGM) and molecular cytogenetic methodologies. Within this family, the father and the paternal grandfather were both asymptomatic carriers of an identical balanced CCR, while the two offspring with an unbalanced paternal-origin CCR and two microdeletions presented with clinical manifestation. The first affected child, a 5-year-old boy, exhibited neurodevelopmental delay, while the second, a fetus, presented with hydrops fetalis. SNP-genotype analysis revealed a recombination event during gamete formation in the father that may have contributed to the deletion in his offspring. Meanwhile, the couple's haplotypes will facilitate the selection of normal gametes in the setting of assisted reproduction. Our study demonstrated the potential of OGM in identifying CCRs and its ability to work with current methodologies to refine precise breakpoints and construct accurate haplotypes for couples with a CCR.

[Study of a fetus with confined placental mosaicism for trisomy 2 in conjunct with fetal uniparental disomy and a literature review].

OBJECTIVE: To carry out genetic analysis for a fetus with confined placental mosaicism (CPM) for trisomy 2 (T2) in conjunct with fetal uniparental disomy (UPD). METHODS: Amniocentesis and chromosomal karyotyping was carried out for a pregnant woman with a high risk for chromosome 2 anomalies indicated by non-invasive prenatal testing (NIPT). Single nucleotide polymorphism array (SNP-array) and trio-whole exome sequencing (Trio-WES) were carried out. Ultrasonography was used to closely monitor the fetal growth. Multifocal sampling of the placenta was performed after delivery for copy number variation sequencing (CNV-seq). RESULTS: The fetus was found to have a normal chromosomal karyotype. SNP-array has revealed multiple regions with loss of heterozygosity (LOH) on chromosome 2. Trio-WES confirmed the presence of maternal UPD for chromosome 2. Ultrasonography has revealed intrauterine growth restriction and oligohydramnios. Intrauterine fetal demise had occurred at 23+4 weeks of gestation. Pathological examination had failed to find salient visceral abnormality. The placenta was proved to contain complete T2 by CNV-seq. CONCLUSION: T2 CPM can cause false positive result for NIPT and may be complicated with fetal UPD, leading to adverse obstetric outcomes such as intrauterine growth restriction, oligohydramnios and intrauterine fetal demise.

Detection of Mosaic Absence of Heterozygosity (AOH) Using Low-Pass Whole Genome Sequencing in Prenatal Diagnosis: A Preliminary Report.

Objective: Mosaicism is a common biological phenomenon in organisms and has been reported in many types of chromosome abnormalities, including the absence of heterozygosity (AOH). Due to the detection limitations of the sequencing approach, mosaic AOH events are rarely assessed in clinical cases. Herein, we report the performance of mosaic AOH identification using a low-pass (5~8-fold) WGS method (termed 'CMA-seq', an abbreviation for 'Chromosome Analysis by Sequencing') in fetal genetic diagnosis. Methods: Thirty AOH-negative, eleven constitutional AOH, and three mosaic AOH samples were collected as training data sets to develop the algorithm and evaluate the suitable thresholds for distinguishing mosaic AOH. Twenty-four new chromosomal aberrant cases, along with sixteen constitutional AOH samples, which were previously ascertained via the SNP-array-based method, were used as a validation data set to measure the performance in terms of sensitivity and specificity of this algorithm. Results: A new statistic, 'D-value', was implemented to identify and distinguish constitutional and mosaic AOH events. The reporting thresholds for constitutional and mosaic AOH were also established. In the validation set consisting of 24 new cases, seven constitutional AOH cases and 1 mosaic AOH case were successfully identified, indicating that the results were consistent with those of the SNP-array-based method. The results of all sixteen constitutional AOH validation samples also met the threshold requirements. Conclusions: In this study, we developed a new bioinformatic algorithm to accurately distinguish mosaic AOH from constitutional AOH by low-pass WGS. However, due to the small sample size of the training data set, the algorithm proposed in this manuscript still needs further refinements.

Prenatal genetic diagnosis of disseminated infantile myofibromatosis: a case report and literature review.

BACKGROUND: Infantile myofibromatosis (IM) is a rare disorder characterized by the formation of nodules in the skin, muscle, bone, and, more rarely, visceral organs. Very few cases are detected prenatally, and the final diagnosis cannot be made until pathology is completed after birth. Here, we present a case of disseminated form IM (DFIM) with a diagnosis established on prenatal genetic grounds. CASE PRESENTATION: A woman at 23 weeks of gestation was referred for ultrasound evaluation of fetal kidney abnormality. Generalized masses in the skin and muscle of the fetus developed at 28 weeks. Prenatal genetic testing identified the pathogenic heterozygous variant c.1681C > T (p.R561C) of the PDGFRB gene inherited from the asymptomatic father. Intrauterine demise occurred at 31 weeks. Autopsy confirmed DFIM with involvement of the heart and kidney. All cases of prenatally detected IM were reviewed, revealing an association of high mortality with DFIM. CONCLUSIONS: Prenatal IM diagnosis is difficult. Initial detection is always based on ultrasound. DFIM has high mortality. The germline p.R561C mutation in PDGFRB may cause fetal demise due to severe visceral involvement of IM. Prenatal genetic testing provides a diagnosis before pathological results are available, leading to better counseling and management of pregnancy with a fetus with IM.

Evaluation and Analysis of Absence of Homozygosity (AOH) Using Chromosome Analysis by Medium Coverage Whole Genome Sequencing (CMA-seq) in Prenatal Diagnosis.

OBJECTIVE: Absence of homozygosity (AOH) is a genetic characteristic known to cause human diseases mainly through autosomal recessive or imprinting mechanisms. The importance and necessity of accurate AOH detection has become more clinically significant in recent years. However, it remains a challenging task for sequencing-based methods thus far. METHODS: In this study, we developed and optimized a new bioinformatic algorithm based on the assessment of minimum sequencing coverage, optimal bin size, the Z-score threshold of four types of allele count and the frequency for accurate genotyping using 28 AOH negative samples, and redefined the AOH detection cutoff value. We showed the performance of chromosome analysis by five-fold coverage whole genome sequencing (CMA-seq) for AOH identification in 27 typical prenatal/postnatal AOH positive samples, which were previously confirmed by chromosomal microarray analysis with single nucleotide polymorphism array (CMA/SNP array). RESULTS: The blinded study indicated that for all three forms of AOH, including whole genomic AOH, single chromosomal AOH and segmental AOH, and all kinds of sample types, including chorionic villus sampling, amniotic fluid, cord blood, peripheral blood and abortive tissue, CMA-seq showed equivalent detection power to that of routine CMA/SNP arrays (750K). The subtle difference between the two methods is that CMA-seq is prone to detect small inconsecutive AOHs, while CMA/SNP array reports it as a whole. CONCLUSION: Based on our newly developed bioinformatic algorithm, it is feasible to detect clinically significant AOH using CMA-seq in prenatal diagnosis.

Ex utero intrapartum therapy in infants with congenital diaphragmatic hernia: a propensity score matching analysis.

Objective: Previous studies have shown that ex utero intrapartum therapy (EXIT) is safe and feasible for newborns with congenital diaphragmatic hernia (CDH). This study reports our experience with EXIT in fetuses with CDH in an attempt to explore the efficacy of EXIT on the survival rate of this population. Methods: A retrospective analysis of the clinical data of 116 children with CDH was conducted. The children were assigned to EXIT and non-EXIT groups. Propensity score matching (PSM) toward clinical data was performed, and the clinical characteristics and outcomes were compared. Taking survival at discharge as the main outcome, logistic regression analysis was carried out to explore the efficacy of EXIT on survival. Results: During the study period, 30 of 116 children received EXIT. After PSM, the survival rates of the EXIT group and the non-EXIT group were 82.76% (24/29) and 48.28% (14/29), respectively (p=0.006). EXIT (OR=0.083, 95% CI=0.013to 0.525, p=0.008), liver herniation (OR=16.955, 95% CI=2.342 to 122.767, p=0.005), and gestational age at diagnosis (OR=0.662, 95% CI=0.497 to 0.881, p=0.005) were independent mortality-related risk factors of all children with CDH. Ninety-nine of 116 children underwent surgery. After PSM, the postoperative survival rates of the EXIT group and non-EXIT group were 84.6% (22/26) and 76.9% (20/26), respectively (p=0.754). Liver herniation (OR=10.451, 95% CI=1.641 to 66.544, p=0.013) and gestational age at diagnosis (OR=0.736, 95% CI=0.577 to 0.938, p=0.013) were independent mortality-related risk factors of children after surgery. Conclusion: EXIT can be performed safely for selected prenatally diagnosed CDH neonates with potentially better survival and does not cause more maternal complications compared with traditional cesarean section.

Impact of the COVID-19 pandemic on congenital diaphragmatic hernia patients: a single-center retrospective study.

PURPOSE: To investigate the impact of COVID-19 on the treatment of children with congenital diaphragmatic hernia (CDH). METHODS: We retrospectively collected and compared the data of patients with CDH admitted between January 1, 2020 and December 31, 2021(study group) with the CDH patients admitted before the pandemic between January 1, 2018 and December 31, 2019 (control group). RESULTS: During the pandemic, 41 patients with CDH diagnosed prenatally were transferred to our hospital, and 40 underwent surgical repair. The number of patients treated in our hospital increased by 24.2% compared with the 33 patients before the pandemic. During the pandemic, the overall survival rate, postoperative survival rate and recurrence rate were 85.4%, 87.5% and 7.3%, respectively, and there were no significant differences compared with the control group (75.8%, 83.3% and 9.1%, respectively). The average length of hospital stay in patients admitted during the pandemic was longer than that in the control group (31 days vs. 16 days, P < 0.001), and the incidence of nosocomial infection was higher than that in the control group (19.5% vs. 3%, P = 0.037). CONCLUSIONS: CDH patients confirmed to be SARS-CoV-2 infection-free can receive routine treatment. Our data indicate that the implementation of protective measures during the COVID-19 pandemic, along with appropriate screening and case evaluation, do not have a negative impact on the prognosis of children.

Assessment of Features between Multichannel Electrohysterogram for Differentiation of Labors.

Electrohysterogram (EHG) is a promising method for noninvasive monitoring of uterine electrical activity. The main purpose of this study was to characterize the multichannel EHG signals to distinguish between term delivery and preterm birth, as well as deliveries within and beyond 24 h. A total of 219 pregnant women were grouped in two ways: (1) term delivery (TD), threatened preterm labor (TPL) with the outcome of preterm birth (TPL_PB), and TPL with the outcome of term delivery (TPL_TD); (2) EHG recording time to delivery (TTD) ≤ 24 h and TTD > 24 h. Three bipolar EHG signals were analyzed for the 30 min recording. Six EHG features between multiple channels, including multivariate sample entropy, mutual information, correlation coefficient, coherence, direct partial Granger causality, and direct transfer entropy, were extracted to characterize the coupling and information flow between channels. Significant differences were found for these six features between TPL and TD, and between TTD ≤ 24 h and TTD > 24 h. No significant difference was found between TPL_PB and TPL_TD. The results indicated that EHG signals of TD were more regular and synchronized than TPL, and stronger coupling between multichannel EHG signals was exhibited as delivery approaches. In addition, EHG signals propagate downward for the majority of pregnant women regardless of different labors. In conclusion, the coupling and propagation features extracted from multichannel EHG signals could be used to differentiate term delivery and preterm birth and may predict delivery within and beyond 24 h.

Recognition of uterine contractions with electrohysterogram and exploring the best electrode combination.

BACKGROUND: As an essential indicator of labour and delivery, uterine contraction (UC) can be detected by manual palpation, external tocodynamometry and internal uterine pressure catheter. However, these methods are not applicable for long-term monitoring. OBJECTIVE: This paper aims to recognize UCs with electrohysterogram (EHG) and find the best electrode combination with fewer electrodes. METHODS: 112 EHG recordings were collected by our bespoke device in our study. Thirteen features were extracted from EHG segments of UC and non-UC. Four classifiers of the decision tree, support vector machine (SVM), artificial neural network, and convolutional neural network were established to identify UCs. The optimal classifier among them was determined by comparing their classification results. The optimal classifier was applied to evaluate all the possible electrode combinations with one to eight electrodes. RESULTS: The results showed that SVM achieved the best classification capability. With SVM, the combination of electrodes on the right part of the uterine fundus and around the uterine body's median axis achieved the overall best performance. CONCLUSIONS: The optimal electrode combination with fewer electrodes was confirmed to improve the clinical application for long-term monitoring of UCs.

Association of a unicornuate uterus with adverse obstetric outcomes: A retrospective cohort study.

OBJECTIVE: To estimate the association of unicornuate uterus (UU) with adverse obstetric outcomes. METHODS: Using data from 26 737 singleton childbirths from a tertiary hospital from 1999 to 2019, we identified 44 births from women with a UU. A total of 367 births from women with a normal uterus were randomly selected as controls. The outcome measures were preterm birth (PTB), breech presentation, and cesarean delivery. The subdivisions of PTB and indications for cesarean delivery were described. RESULTS: The presence of UU was associated with an increased risk of PTB (adjusted risk ratio [aRR], 2.3; 95% confidence interval [CI], 1.1-4.9), breech presentation (aRR, 6.2; 95% CI, 2.9-13.2), and cesarean delivery (aRR, 2.1; 95% CI, 1.8-2.7). For women with a UU, most PTBs (7/9) were moderate to late PTBs, and approximately half of the PTBs (4/9) were iatrogenic due to preeclampsia (PE). Breech presentation, PE, and prior surgery for rudimentary horn resection were UU-related indications for cesarean delivery. CONCLUSIONS: Women with a UU have a higher risk of PTB, breech presentation, and cesarean delivery. Understanding of the subdivisions of PTBs and indications for cesarean delivery might help clinicians when counseling women with pregnancy complicated by a UU.

Factors associated with test failure in pregnant women undergoing cell-free DNA-based testing for fetal trisomy.

OBJECTIVE: To investigate the factors associated with cell-free DNA test failure, and the optimal subsequent management of these pregnancies. METHODS: This was a retrospective study of 27,363 singleton pregnancies undergoing cell-free DNA testing. Women with cell-free DNA test failure were divided into a high-risk group and a low-risk group according to their indications. The subsequent management and pregnancy outcomes of these women were followed up. RESULTS: The rate of cell-free DNA test failure at the first sampling was 1.49%, and 78.4% of failures were due to a low fetal fraction. Of the 66 women who refused any subsequent management, an adverse pregnancy outcome was seen in 5 cases, all belonging to the high-risk group. Of the 13 low-risk women who chose second-trimester maternal serum screening, all obtained a low-risk maternal serum screening result and an unaffected pregnancy outcome. A redraw was chosen by 171 women, which yielded a result in 75.4% and their pregnancy outcomes were unaffected; 42 women had an uninformative result again and received an amniocentesis. As 158 women had an amniocentesis after the first sampling, this procedure was offered in 200 cases altogether. Abnormal genetic testing results were shown in six (3%, 6/200) cases, all in the high-risk group. CONCLUSIONS: High-risk pregnant women with cell-free DNA test failure are at increased risk of adverse pregnancy outcomes. A second sampling for cell-free DNA test or maternal serum screening might be suggested to low-risk women. Invasive prenatal diagnosis should be offered to the high-risk patients, especially those with a second cell-free DNA test failure.

A Rapid PCR-Free Next-Generation Sequencing Method for the Detection of Copy Number Variations in Prenatal Samples.

Next-generation sequencing (NGS) is emerging as a new method for the detection of clinically significant copy number variants (CNVs). In this study, we developed and validated rapid CNV-sequencing (rCNV-seq) for clinical application in prenatal diagnosis. Low-pass whole-genome sequencing was performed on PCR libraries prepared from amniocyte genomic DNA. From 10-40 ng of input DNA, PCR-free libraries consistently produced sequencing data with high unique read mapping ratios, low read redundancy, low coefficient of variation for all chromosomes and high genomic coverage. In validation studies, reliable and accurate CNV detection using PCR-free-based rCNV-seq was demonstrated for a range of common trisomies and sex chromosome aneuploidies as well as microdeletion and duplication syndromes. In reproducibility studies, CNV copy number and genomic intervals closely matched those defined by chromosome microarray analysis. Clinical testing of genomic DNA samples from 217 women referred for prenatal diagnosis identified eight samples (3.7%) with known chromosome disorders. We conclude that PCR-free-based rCNV-seq is a sensitive, specific, reproducible and efficient method that can be used in any NGS-based diagnostic laboratory for detection of clinically significant CNVs.

Automatic recognition of uterine contractions with electrohysterogram signals based on the zero-crossing rate.

Uterine contraction (UC) is an essential clinical indicator in the progress of labour and delivery. Electrohysterogram (EHG) signals recorded on the abdomen of pregnant women reflect the uterine electrical activity. This study proposes a novel algorithm for automatic recognition of UCs with EHG signals to improve the accuracy of detecting UCs. EHG signals by electrodes, the tension of the abdominal wall by tocodynamometry (TOCO) and maternal perception were recorded simultaneously in 54 pregnant women. The zero-crossing rate (ZCR) of the EHG signal and its power were calculated to modulate the raw EHG signal and highlight the EHG bursts. Then the envelope was extracted from the modulated EHG for UC recognition. Besides, UC was also detected by the conventional TOCO signal. Taking maternal perception as a reference, the UCs recognized by EHG and TOCO were evaluated with the sensitivity, positive predictive value (PPV), and UC parameters. The results show that the sensitivity and PPV are 87.8% and 93.18% for EHG, and 84.04% and 90.89% for TOCO. EHG detected a larger number of UCs than TOCO, which is closer to maternal perception. The duration and frequency of UC obtained from EHG and TOCO were not significantly different (p > 0.05). In conclusion, the proposed UC recognition algorithm has high accuracy and simple calculation which could be used for real-time analysis of EHG signals and long-term monitoring of UCs.

Simultaneous Detection of CNVs and SNVs Improves the Diagnostic Yield of Fetuses with Ultrasound Anomalies and Normal Karyotypes.

The routine assessment to determine the genetic etiology for fetal ultrasound anomalies follows a sequential approach, which usually takes about 6-8 weeks turnaround time (TAT). We evaluated the clinical utility of simultaneous detection of copy number variations (CNVs) and single nucleotide variants (SNVs)/small insertion-deletions (indels) in fetuses with a normal karyotype with ultrasound anomalies. We performed CNV detection by chromosomal microarray analysis (CMA) or low pass CNV-sequencing (CNV-seq), and in parallel SNVs/indels detection by trio-based clinical exome sequencing (CES) or whole exome sequencing (WES). Eight-three singleton pregnancies with a normal fetal karyotype were enrolled in this prospective observational study. Pathogenic or likely pathogenic variations were identified in 30 cases (CNVs in 3 cases, SNVs/indels in 27 cases), indicating an overall molecular diagnostic rate of 36.1% (30/83). Two cases had both a CNV of uncertain significance (VOUS) and likely pathogenic SNV, and one case carried both a VOUS CNV and an SNV. We demonstrated that simultaneous analysis of CNVs and SNVs/indels can improve the diagnostic yield of prenatal diagnosis with shortened reporting time, namely, 2-3 weeks. Due to the relatively long TAT for sequential procedure for prenatal genetic diagnosis, as well as recent sequencing technology advancements, it is clinically necessary to consider the simultaneous evaluation of CNVs and SNVs/indels to enhance the diagnostic yield and timely TAT, especially for cases in the late second trimester or third trimester.

Application of decision tree in determining the importance of surface electrohysterography signal characteristics for recognizing uterine contractions.

The aims of this study were to apply decision tree to classify uterine activities (contractions and non-contractions) using the waveform characteristics derived from different channels of electrohysterogram (EHG) signals and then rank the importance of these characteristics. Both the tocodynamometer (TOCO) and 8-channel EHG signals were simultaneously recorded from 34 healthy pregnant women within 24 h before delivery. After preprocessing of EHG signals, EHG segments corresponding to the uterine contractions and non-contractions were manually extracted from both original and normalized EHG signals according to the TOCO signals and the human marks. 24 waveform characteristics of the EHG segments were derived separately from each channel to train the decision tree and classify the uterine activities. The results showed the Power and sample entropy (SamEn) extracted from the un-normalized EHG segments played the most important roles in recognizing uterine activities. In addition, the EHG signal characteristics from channel 1 produced better classification results (AUC = 0.75, Sensitivity = 0.84, Specificity = 0.78, Accuracy = 0.81) than the others. In conclusion, decision tree could be used to classify the uterine activities, and the Power and SamEn of un-normalized EHG segments were the most important characteristics in uterine contraction classification.

Preliminary Study on the Efficient Electrohysterogram Segments for Recognizing Uterine Contractions with Convolutional Neural Networks.

BACKGROUND: Uterine contraction (UC) is the tightening and shortening of the uterine muscles which can indicate the progress of pregnancy towards delivery. Electrohysterogram (EHG), which reflects uterine electrical activities, has recently been studied for UC monitoring. In this paper, we aimed to evaluate different EHG segments for recognizing UCs using the convolutional neural network (CNN). MATERIALS AND METHODS: In the open-access Icelandic 16-electrode EHG database (122 recordings from 45 pregnant women), 7136 UC and 7136 non-UC EHG segments with the duration of 60 s were manually extracted from 107 recordings of 40 pregnant women to develop a CNN model. A fivefold cross-validation was applied to evaluate the CNN based on sensitivity (SE), specificity (SP), and accuracy (ACC). Then, 1056 UC and 1056 non-UC EHG segments were extracted from the other 15 recordings of 5 pregnant women. Furthermore, the developed CNN model was applied to identify UCs using different EHG segments with the durations of 10 s, 20 s, and 30 s. RESULTS: The CNN achieved the average SE, SP, and ACC of 0.82, 0.93, and 0.88 for a 60 s EHG segment. The EHG segments of 10 s, 20 s, and 30 s around the TOCO peak achieved higher SE and ACC than the other segments with the same duration. The values of SE from 20 s EHG segments around the TOCO peak were higher than those from 10 s to 30 s EHG segments on the same side of the TOCO peak. CONCLUSION: The proposed method could be used to determine the efficient EHG segments for recognizing UC with the CNN.

Maternal Serum Angiogenic Factor sFlt-1 to PlGF Ratio in Preeclampsia: A Useful Marker for Differential Diagnosis and Prognosis Evaluation in Chinese Women.

The ratio of soluble fms-like tyrosine kinase-1 to placental growth factor (sFlt-1/PlGF) is elevated and proved to be useful in preeclampsia (PE) diagnosis. Its value in differential diagnosis with other pregnancy complications and prediction of pregnancy duration has yet to be clarified in Chinese population. We retrospectively analyzed 118 singleton pregnancies with suspected or diagnosed PE at the Peking Union Medical College Hospital (PUMCH) in China. Among these, 62 pregnancies were diagnosed as PE (48 early onsets and 14 late onsets, with 39 and 5 severe PE, respectively), 12 gestational hypertension (GH), 15 chronic hypertension (chrHTN), 16 autoimmune diseases, and 13 pregnancies with uncomplicated proteinuria. And 76 normal pregnancies were included as control. The results showed (1) the sFlt-1/PlGF ratio in early onset PE subgroup was significantly higher than that in GH, chrHTN, and control groups; the sFlt-1/PlGF ratio in late onset PE subgroup was significantly higher than that in chrHTN and control groups, but similar as GH group; the sFlt-1/PlGF ratio was similar among GH, chrHTN, and control groups. (2) The sFlt-1/PlGF ratio was significantly increased in the PE group compared with autoimmune disease and uncomplicated proteinuria pregnancies. (3) By ROC curve analysis, the cutoff value of the sFlt-1/PlGF ratio was less than 21.5 to rule out PE and higher than 97.2 to confirm the diagnosis of PE. (4) The sFlt-1/PlGF ratio was higher in PE pregnancies delivering within 7 days than those more than 7 days, either in early onset PE or severe PE. In conclusion, we show that maternal sFlt-1/PlGF ratio is an efficient biomarker in the diagnosis and differential diagnosis of PE. This ratio can be used to predict the timing of delivery for PE pregnancies.

Evaluation of convolutional neural network for recognizing uterine contractions with electrohysterogram.

Uterine contraction (UC) activity is commonly used to monitor the approach of labour and delivery. Electrohysterograms (EHGs) have recently been used to monitor UC and distinguish between efficient and inefficient contractions. In this study, we aimed to identify UC in EHG signals using a convolutional neural network (CNN). An open-access database (Icelandic 16-electrode EHG database from 45 pregnant women with 122 recordings, DB1) was used to develop a CNN model, and 14000 segments with a length of 45 s (7000 from UCs and 7000 from non-UCs, which were determined with reference to the simultaneously recorded tocography signals) were manually extracted from the 122 EHG recordings. Five-fold cross-validation was applied to evaluate the ability of the CNN to identify UC based on its sensitivity (SE), specificity (SP), accuracy (ACC), and area under the receiver operating characteristic curve (AUC). The CNN model developed using DB1 was then applied to an independent clinical database (DB2) to further test its generalisation for recognizing UCs. The EHG signals in DB2 were recorded from 20 pregnant women using our multi-channel system, and 308 segments (154 from UCs and 154 from non-UCs) were extracted. The CNN model from five-fold cross-validation achieved average SE, SP, ACC, and AUC of 0.87, 0.98, 0.93, and 0.92 for DB1, and 0.88, 0.97, 0.93, and 0.87 for DB2, respectively. In summary, we demonstrated that CNN could effectively identify UCs using EHG signals and could be used as a tool for monitoring maternal and foetal health.