Maternal fibrinogen/fibrin degradation products to high density lipoprotein cholesterol ratio for predicting delivery of small and large for gestational age infants: a pilot study

BACKGROUND

The purpose of this pilot study was to investigate associations between fibrinogen/fibrin degradation products (FDP) to high density lipoprotein-cholesterol (HDL-C) ratio (FHR) of mothers and the risk of delivering large/small for gestational age (LGA/SGA) infants and to evaluate the predictive power of FHR on LGA/SGA.

METHODS

This study retrospectively reviewed 11,657 consecutive women whose lipid profiles and FDP levels were investigated at the time of admission for delivery at a specialized hospital. The FHR was calculated, and perinatal outcomes, including clinical parameters, were analyzed.

RESULTS

The prevalence of SGA was 9% (n = 1034), and that of LGA was 15% (n = 1806) in this cohort study. FHR was significantly lower in women who delivered SGA infants (4.0 ± 3.2 vs. 4.7 ± 3.3 mg/mmol, P < 0.01) and higher in women who delivered LGA infants (5.7 ± 3.8 vs. 4.7 ± 3.3 mg/mmol, P < 0.01) compared with those who delivered infants of normal size for their gestational age. Women in the top quartile for FHR (> 5.9 mg/mmol) had a 2.9-fold higher risk of delivering LGA infants [adjusted odds ratio (OR) = 2.9, P < 0.01] and a 47% lower risk of delivering SGA infants (adjusted OR = 0.47, P < 0.01) than those in the bottom quartile (< 2.7 mg/mmol). In addition, adding FHR to the conventional models significantly improved the area under the curve for the prediction of delivering LGA (0.725 vs. 0.739, P < 0.01) and SGA (0.717 vs. 0.727, P < 0.01) infants.

CONCLUSION

These findings suggest that the FHR calculated in late pregnancy is an innovative predictor of delivering LGA and SGA infants. Combining FHR with perinatal parameters could thus enhance the predictive ability for predicting the delivery of LGA/SGA infants.

Early Diagnosis and Classification of Fetal Health Status from a Fetal Cardiotocography Dataset Using Ensemble Learning

(1) Background: According to the World Health Organization (WHO), 6.3 million intrauterine fetal deaths occur every year. The most common method of diagnosing perinatal death and taking early precautions for maternal and fetal health is a nonstress test (NST). Data on the fetal heart rate and uterus contractions from an NST device are interpreted based on a trace printer's output, allowing for a diagnosis of fetal health to be made by an expert. (2) Methods: in this study, a predictive method based on ensemble learning is proposed for the classification of fetal health (normal, suspicious, pathology) using a cardiotocography dataset of fetal movements and fetal heart rate acceleration from NST tests. (3) Results: the proposed predictor achieved an accuracy level above 99.5% on the test dataset. (4) Conclusions: from the experimental results, it was observed that a fetal health diagnosis can be made during NST using machine learning.

Multimodal Deep Learning for Predicting Adverse Birth Outcomes Based on Early Labour Data

Cardiotocography (CTG) is a widely used technique to monitor fetal heart rate (FHR) during labour and assess the health of the baby. However, visual interpretation of CTG signals is subjective and prone to error. Automated methods that mimic clinical guidelines have been developed, but they failed to improve detection of abnormal traces. This study aims to classify CTGs with and without severe compromise at birth using routinely collected CTGs from 51,449 births at term from the first 20 min of FHR recordings. Three 1D-CNN and LSTM based architectures are compared. We also transform the FHR signal into 2D images using time-frequency representation with a spectrogram and scalogram analysis, and subsequently, the 2D images are analysed using a 2D-CNNs. In the proposed multi-modal architecture, the 2D-CNN and the 1D-CNN-LSTM are connected in parallel. The models are evaluated in terms of partial area under the curve (PAUC) between 0-10% false-positive rate; and sensitivity at 95% specificity. The 1D-CNN-LSTM parallel architecture outperformed the other models, achieving a PAUC of 0.20 and sensitivity of 20% at 95% specificity. Our future work will focus on improving the classification performance by employing a larger dataset, analysing longer FHR traces, and incorporating clinical risk factors.

Wearable Sensors for the Monitoring of Maternal Health-A Systematic Review

Maternal health includes health during pregnancy and childbirth. Each stage during pregnancy should be a positive experience, ensuring that women and their babies reach their full potential in health and well-being. However, this cannot always be achieved. According to UNFPA (United Nations Population Fund), approximately 800 women die every day from avoidable causes related to pregnancy and childbirth, so it is important to monitor mother and fetal health throughout the pregnancy. Many wearable sensors and devices have been developed to monitor both fetal and the mother's health and physical activities and reduce risk during pregnancy. Some wearables monitor fetal ECG or heart rate and movement, while others focus on the mother's health and physical activities. This study presents a systematic review of these analyses. Twelve scientific articles were reviewed to address three research questions oriented to (1) sensors and method of data acquisition; (2) processing methods of the acquired data; and (3) detection of the activities or movements of the fetus or the mother. Based on these findings, we discuss how sensors can help effectively monitor maternal and fetal health during pregnancy. We have observed that most of the wearable sensors were used in a controlled environment. These sensors need more testing in free-living conditions and to be employed for continuous monitoring before being recommended for mass implementation.

Evaluating the clinical utility of measuring levels of factor H and the related proteins

After years of disappointing clinical results, the tide has finally changed and complement targeted-therapies have become a validated and accepted treatment option for several diseases. These accomplishments have revitalized the field and brought renewed attention to the prospects that complement therapeutics can offer. Streamlining diagnostics and therapeutics is imperative in this new era of clinical use of complement therapeutics. However, the incredible success in therapeutics has not been accompanied by the development of novel standardized tools for complement testing. Complement biomarkers can assist in the risk assessment and diagnosis of diseases as well as the prediction of disease progression and treatment response. Recently, a group of complement proteins has been suggested to be highly relevant in various complement-associated disorders, namely the human factor H (FH) protein family. This family of closely related proteins consists of FH, FH-like protein 1, and five factor H-related proteins, and they have been linked to eye, kidney, infectious, vascular, and autoimmune diseases as well as cancer. The goal of this review is to provide a comprehensive overview of the available data on circulating levels of FH and its related proteins in different pathologies. In addition, we examined the current literature to determine the clinical utility of measuring levels of the FH protein family in health and disease. Finally, we discuss future steps that are needed to make their clinical translation a reality.

Association of fetal heart rate short term variability pattern during term labor with neonatal morbidity and small for gestational age status

OBJECTIVE

To assess the association of fetal heart rate short-term variability (STV) pattern during term labor with both neonatal composite morbidity (cord blood pH ≤ 7.10 and/or neonatal intensive care unit admission and/or Apgar score at 5 min <7) and small for gestational age (SGA) status.

STUDY DESIGN

Retrospective cohort in a single academic institution between January 2016 and December 2018. A total of 1896 women that delivered a singleton during labor in cephalic presentation after 37 weeks of gestation were included (948 women with SGA neonates and 948 women with appropriate weight for gestational age (AGA) neonates that were matched to women with SGA neonates based on maternal age, parity, induction of labor, gestational diabetes, gestational age at delivery and a history of one cesarean section using propensity score matching). STV was compared at labor onset (cervical dilation ≤ 4 cm), in the first stage of labor (cervical dilation = 6 cm) and in the second stage of labor (cervical dilation = 10 cm). A generalized linear mixed model was used to assess the association between SGA status, neonatal composite morbidity and STV.

RESULTS

After adjustment for maternal origin, term, gestational diabetes, labor length, SGA status was not associated with any change in STV during labor (mean adjusted STV: -0.20 ms, 95 %CI[-0.58-0.17], p = 0.284 at labor onset, 0.29 ms, 95 %CI[-0.1- 0.68], p = 0.155, in the first stage of labor and 0.36 ms, 95 %CI[-0.02-0.74], p = 0.065 in the second stage of labor). In case of neonatal composite morbidity mean adjusted STV was lower in the first stage of labor (mean adjusted STV: -1.29 ms, 95 %CI[-2.1 - -0.43], p = 0.003) and in the second stage of labor (mean adjusted STV: -1.15 ms, 95 %CI[-1.96 - -0.34], p = 0.005). The results were similar with the addition of delivery mode and meconium-stained amniotic fluid in the model or non-reassuring fetal heart rate and meconium-stained amniotic fluid.

CONCLUSIONS

This work suggests that STV decrease during term labor is associated with fetal well-being, independently of fetal weight. This suggests that further prospective studies should consider the evaluation of this parameter in the prediction of neonatal compromise.

Low Levels of Factor H Family Proteins During Meningococcal Disease Indicate Systemic Processes Rather Than Specific Depletion by Neisseria meningitidis

Neisseria meningitidis, the causative agent of meningococcal disease (MD), evades complement-mediated clearance upon infection by ‘hijacking’ the human complement regulator factor H (FH). The FH protein family also comprises the homologous FH-related (FHR) proteins, hypothesized to act as antagonists of FH, and FHR-3 has recently been implicated to play a major role in MD susceptibility. Here, we show that the circulating levels of all FH family proteins, not only FH and FHR-3, are equally decreased during the acute illness. We did neither observe specific consumption of FH or FHR-3 by N. meningitidis, nor of any of the other FH family proteins, suggesting that the globally reduced levels are due to systemic processes including dilution by fluid administration upon admission and vascular leakage. MD severity associated predominantly with a loss of FH rather than FHRs. Additionally, low FH levels associated with renal failure, suggesting insufficient protection of host tissue by the active protection by the FH protein family, which is reminiscent of reduced FH activity in hemolytic uremic syndrome. Retaining higher levels of FH may thus limit tissue injury during MD.

Heart rate estimation and validation algorithm for fetal phonocardiography

Fetal heart rate (FHR) is an important parameter for assessing fetal well-being and is usually measured by doppler ultrasound. Fetal phonocardiography can provide non-invasive, easy-to-use and passive alternative for fetal monitoring method if reliable FHR measurements can be made even in noisy clinical environments. In this work we present an automatic algorithm to determine fetal heart rate from the fetal heart sound recordings in a noisy clinical environment. Using an electronic stethoscope fetal heart sounds were recorded from the expecting mother's abdomen, during weeks 30-40 of their pregnancy. Of these, 60 recordings were analyzed manually by two observers to obtain reference heart rate measurement. An algorithm was developed to determine FHR using envelope detection and autocorrelation of the signals. Algorithm performance was improved by implementing peak validation algorithm utilizing knowledge of valid FHR from prior windows and power spectral density function. The improvements in accuracy and reliability of algorithm were measured by mean absolute error and positive precent agreement. By including the validation step, the mean absolute error reduced from 11.50 to 7.54 beats per minute and positive percent agreement improved from 81% to 87%. The proposed algorithms provide good accuracy overall but are sensitive to the noises in recording environment that influence the quality of the signals.

Early Biomarkers and Intervention Programs for the Infant Exposed to Prenatal Stress

Functional development of affective and reward circuits, cognition and response inhibition later in life exhibits vulnerability periods during gestation and early childhood. Extensive evidence supports the model that exposure to stressors in the gestational period and early postnatal life increases an individual's susceptibility to future impairments of functional development. Recent versions of this model integrate epigenetic mechanisms of the developmental response. Their understanding will guide the future treatment of the associated neuropsychiatric disorders. A combination of non-invasively obtainable physiological signals and epigenetic biomarkers related to the principal systems of the stress response, the Hypothalamic-Pituitary axis (HPA) and the Autonomic Nervous System (ANS), are emerging as the key predictors of neurodevelopmental outcomes. Such electrophysiological and epigenetic biomarkers can prove to timely identify children benefiting most from early intervention programs. Such programs should ameliorate future disorders in otherwise healthy children. The recently developed Early Family-Centered Intervention Programs aim to influence the care and stimuli provided daily by the family and improving parent/child attachment, a key element for healthy socio-emotional adult life. Although frequently underestimated, such biomarker-guided early intervention strategy represents a crucial first step in the prevention of future neuropsychiatric problems and in reducing their personal and societal impact.

Acquisition and Analysis of Electrohysterogram Signal

Electrohysterogram (EHG) signal is the signal related to action potentials propagating through smooth muscle cells of the uterus (myometrium) to the abdomen of pregnant women which is also known as uterine contraction signal. Cardiotocography (CTG) is the most common method used for monitoring fetal heart rate (FHR) and uterine contractions during pregnancy and labor. This method detects mechanical activity of fetal heart and uterus, however, it provides low accuracy and sensibility and hence more accurate methods are required. The abdominal electrode method of FECG monitoring and Electrohysterography (EHG) are alternative noninvasive method to monitor the FHR and uterine contractions during pregnancy which provides better results compared to CTG. Each information such as the frequency of uterine contractions, length of the contraction and contraction power of uterus, indicates the condition of the uterus which will help the obstetricians to identify the progress of labor. All these above mentioned parameters can be identified from the EHG signal acquired non-invasively by placing the electrodes on the abdomen of the pregnant women. In this work the acquisition of EHG signal as well as analysis of EHG signal in both antepartum condition and labor condition have been carried out and parameters such as number of contractions, contraction duration, amplitude, power of contraction are computed and the quantitative analysis of EHG signals in both above mentioned conditions are performed and it is compared with the simultaneously recorded uterine contraction signal parameters from Cardiotocography (CTG).

Complement dysregulation in glomerulonephritis

Glomerulonephritis (GN) refers to a group of renal diseases affecting the glomeruli due to the damage mediated by immunological mechanisms. A large proportion of the disease manifestations are caused by disturbances in the complement system. They can be due to genetic errors, autoimmunity, microbes or abnormal immunoglobulins, like modified IgA or paraproteins. The common denominator in most of the problems is an overactive or misdirected alternative pathway complement activation. An assessment of kidney function, amount of proteinuria and hematuria are crucial elements to evaluate, when glomerulonephritis is suspected. However, the cornerstones of the diagnoses are renal biopsy and careful examination of the complement abnormality. Differential diagnostics between the various forms of GN is not possible based on clinical features, as they may vary greatly. This review describes the known mechanisms of complement dysfunction leading to different forms of primary GN (like IgA glomerulonephritis, dense deposit disease, C3 glomerulonephritis, post-infectious GN, membranous GN) and differences to atypical hemolytic uremic syndrome. It also covers the basic elements of etiology-directed therapy and prognosis of the most common forms of GN. Common principles in the management of GN include treatment of hypertension and reduction of proteinuria, some require immunomodulating treatment. Complement inhibition is an emerging treatment option. A thorough understanding of the basic disease mechanism and a careful follow-up are needed for optimal therapy.

Prenatal identification of CHD murmur using four segment phonocardiographic signal analysis

Congenital heart defects (CHD) are one of the utmost birth defects present in the neonatal after birth and a big challenge for the researchers to identify the structural abnormality during the antepartum period. An algorithm is presented here to identify the presence of CHD through foetal phonocardiographic (fPCG) signals. The recorded fPCG is decomposed using Daubechies4 wavelet with sub-level threshold to remove the noise in the signal. The Shannon energy is used to identify the different peaks of signals and then S1 and S2 according to the intervals between adjacent peaks. The signal is segmented into four important parts: S1, S1S2, S2 and S2S1. The FFT is used to identify the frequency component present in four segments which in turn indicates the presence of pathological murmur that may turn into CHD. The algorithm is tested on 25 samples with accuracy rate 88% in identifying the presence of a murmur.

[Does the paper speed in fetal heart monitoring during labour influence the variability in the interpretation by professionals?]

OBJECTIVE

Assessing inter- and intra- observer agreement in the reading of fetal heart rate (FHR) between two different paper speeds (1 and 2cm/min) using FIGO classification.

MATERIAL AND METHODS

Single-centre experimental study consisting in reading 60minutes FHR tracings by six readers (3 midwives and 3 obstetricians) during 1cm and 2cm/min sessions within a period of three weeks. The reading guideline was based on FIGO classification. Inter- and intra-observer agreement was assessed thanks to Kappa coefficient (K) and percentage of agreement (PA) using the classification of FHR tracings drawn up by readers.

RESULTS

Intra-observer agreement reached 60% between the two paper speeds, and PA ranged from 48 to 67%. Inter-observer agreement was poor to moderate (K=0.42 for 1cm/min sessions and K=0.38 for 2cm/min sessions). Inter-observer agreement was significantly higher for normal tracings (PA ranged from 55.2% for 2cm/min sessions to 57.4% for 1cm/min sessions). The preterminal category had the lowest concordance rates (PA=19% for 1cm/min sessions and 20, 7% for 2cm/min sessions).

CONCLUSION

This study did not highlight significant differences in intra- and inter-observer variability between the two FHR paper speeds. The 1cm/min paper speed, which is commonly used in France, is more economical and gives a better bedside overview of FHR. Therefore, it should be recommended.

Adaptive shut-down of EEG activity predicts critical acidemia in the near-term ovine fetus

In fetal sheep, the electrocorticogram (ECOG) recorded directly from the cortex during repetitive heart rate (FHR) decelerations induced by umbilical cord occlusions (UCO) predictably correlates with worsening hypoxic-acidemia. In human fetal monitoring during labor, the equivalent electroencephalogram (EEG) can be recorded noninvasively from the scalp. We tested the hypothesis that combined fetal EEG – FHR monitoring allows for early detection of worsening hypoxic-acidemia similar to that shown for ECOG-FHR monitoring. Near-term fetal sheep (n = 9) were chronically instrumented with arterial and venous catheters, ECG, ECOG, and EEG electrodes and umbilical cord occluder, followed by 4 days of recovery. Repetitive UCOs of 1 min duration and increasing strength (with regard to the degree of reduction in umbilical blood flow) were induced each 2.5 min until pH dropped to <7.00. Repetitive UCOs led to marked acidosis (arterial pH 7.35 ± 0.01 to 7.00 ± 0.03). At pH of 7.22 ± 0.03 (range 7.32–7.07), and 45 ± 9 min (range 1 h 33 min–20 min) prior to attaining pH < 7.00, both ECOG and EEG amplitudes began to decrease ∼fourfold during each FHR deceleration in a synchronized manner. Confirming our hypothesis, these findings support fetal EEG as a useful adjunct to FHR monitoring during human labor for early detection of incipient fetal acidemia.

Magnetophysiologic and echocardiographic comparison of blocked atrial bigeminy and 2:1 atrioventricular block in the fetus

BACKGROUND

Blocked atrial bigeminy (BAB) and second-degree atrioventricular block with 2:1 conduction block (2:1 AVB) both present as ventricular bradycardia and can be difficult to distinguish by echocardiography. Since the prognosis and clinical management of these rhythms are different, an accurate diagnosis is essential.

OBJECTIVE

To identify magnetic and mechanical heart rate and rhythm parameters that could reliably distinguish BAB from 2:1 AVB.

METHODS

A retrospective study of ten BAB and seven 2:1 AVB subjects was performed, using fMCG and pulsed Doppler ultrasound.

RESULTS

Distinguishing BAB from 2:1 AVB by using fMCG was relatively straightforward because in BAB the ectopic P wave (P') occurred early, resulting in a bigeminal (short-long) atrial rhythm. The normalized coupling interval of the ectopic beat (PP' of the blocked beat to PP of the conducted beat) was 0.29 ± 0.03. In contrast, the echocardiographic assessment of inflow-outflow gave a normalized mechanical coupling interval (AA'/AA) near 0.5, which made it difficult to distinguish BAB from 2:1 AVB. Heart rate distinguished most subjects with BAB from those with 2:1 AVB (82 ± 5.7 beats/min vs 69 ± 4.2 beats/min), but was not a completely reliable indicator. In most subjects, BAB alternated with sinus rhythm or other rhythms, resulting in complex heart rate and rhythm patterns.

CONCLUSIONS

Fetal BAB and 2:1 AV block can be difficult to distinguish using echocardiography because in many fetuses with BAB the mechanical rhythm does not accurately reflect the magnetic rhythm. fMCG provides a more reliable means of making a differential diagnosis.