Machine learning on cardiotocography data to classify fetal outcomes: A scoping review

Introduction: Uterine contractions during labour constrict maternal blood flow and oxygen delivery to the developing baby, causing transient hypoxia. While most babies are physiologically adapted to withstand such intrapartum hypoxia, those exposed to severe hypoxia or with poor physiological reserves may experience neurological injury or death during labour. Cardiotocography (CTG) monitoring was developed to identify babies at risk of hypoxia by detecting changes in fetal heart rate (FHR) patterns. CTG monitoring is in widespread use in intrapartum care for the detection of fetal hypoxia, but the clinical utility is limited by a relatively poor positive predictive value (PPV) of an abnormal CTG and significant inter and intra observer variability in CTG interpretation. Clinical risk and human factors may impact the quality of CTG interpretation. Misclassification of CTG traces may lead to both under-treatment (with the risk of fetal injury or death) or over-treatment (which may include unnecessary operative interventions that put both mother and baby at risk of complications). Machine learning (ML) has been applied to this problem since early 2000 and has shown potential to predict fetal hypoxia more accurately than visual interpretation of CTG alone. To consider how these tools might be translated for clinical practice, we conducted a review of ML techniques already applied to CTG classification and identified research gaps requiring investigation in order to progress towards clinical implementation. Materials and method: We used identified keywords to search databases for relevant publications on PubMed, EMBASE and IEEE Xplore. We used Preferred Reporting Items for Systematic Review and Meta-Analysis for Scoping Reviews (PRISMA-ScR). Title, abstract and full text were screened according to the inclusion criteria. Results: We included 36 studies that used signal processing and ML techniques to classify CTG. Most studies used an open-access CTG database and predominantly used fetal metabolic acidosis as the benchmark for hypoxia with varying pH levels. Various methods were used to process and extract CTG signals and several ML algorithms were used to classify CTG. We identified significant concerns over the practicality of using varying pH levels as the CTG classification benchmark. Furthermore, studies needed to be more generalised as most used the same database with a low number of subjects for an ML study. Conclusion: ML studies demonstrate potential in predicting fetal hypoxia from CTG. However, more diverse datasets, standardisation of hypoxia benchmarks and enhancement of algorithms and features are needed for future clinical implementation.</p

Symbolic Dynamics Analysis: a new methodology for foetal heart rate variability analysis

Cardiotocography (CTG) is a widespread foetal diagnostic methods. However, it lacks of objectivity and reproducibility since its dependence on observer's expertise. To overcome these limitations, more objective methods for CTG interpretation have been proposed. In particular, many developed techniques aim to assess the foetal heart rate variability (FHRV). Among them, some methodologies from nonlinear systems theory have been applied to the study of FHRV. All the techniques have proved to be helpful in specific cases. Nevertheless, none of them is more reliable than the others. Therefore, an in-depth study is necessary. The aim of this work is to deepen the FHRV analysis through the Symbolic Dynamics Analysis (SDA), a nonlinear technique already successfully employed for HRV analysis. Thanks to its simplicity of interpretation, it could be a useful tool for clinicians. We performed a literature study involving about 200 references on HRV and FHRV analysis; approximately 100 works were focused on non-linear techniques. Then, in order to compare linear and non-linear methods, we carried out a multiparametric study. 580 antepartum recordings of healthy fetuses were examined. Signals were processed using an updated software for CTG analysis and a new developed software for generating simulated CTG traces. Finally, statistical tests and regression analyses were carried out for estimating relationships among extracted indexes and other clinical information. Results confirm that none of the employed techniques is more reliable than the others. Moreover, in agreement with the literature, each analysis should take into account two relevant parameters, the foetal status and the week of gestation. Regarding the SDA, results show its promising capabilities in FHRV analysis. It allows recognizing foetal status, gestation week and global variability of FHR signals, even better than other methods. Nevertheless, further studies, which should involve even pathological cases, are necessary to establish its reliability.La Cardiotocografia (CTG) è una diffusa tecnica di diagnostica fetale. Nonostante ciò, la sua interpretazione soffre di forte variabilità intra- e inter- osservatore. Per superare tali limiti, sono stati proposti più oggettivi metodi di analisi. Particolare attenzione è stata rivolta alla variabilità della frequenza cardiaca fetale (FHRV). Nel presente lavoro abbiamo suddiviso le tecniche di analisi della FHRV in tradizionali, o lineari, e meno convenzionali, o non-lineari. Tutte si sono rivelate efficaci in casi specifici ma nessuna si è dimostrata più utile delle altre. Pertanto, abbiamo ritenuto necessario effettuare un’indagine più dettagliata. In particolare, scopo della tesi è stato approfondire una specifica metodologia non-lineare, la Symbolic Dynamics Analysis (SDA), data la sua notevole semplicità di interpretazione che la renderebbe un potenziale strumento di ausilio all’attività clinica. Sono stati esaminati all’incirca 200 riferimenti bibliografici sull’analisi di HRV e FHRV; di questi, circa 100 articoli specificamente incentrati sulle tecniche non-lineari. E’ stata condotta un’analisi multiparametrica su 580 tracciati CTG di feti sani per confrontare le metodologie adottate. Sono stati realizzati due software, uno per l’analisi dei segnali CTG reali e l’altro per la generazione di tracciati CTG simulati. Infine, sono state effettuate analisi statistiche e di regressione per esaminare le correlazioni tra indici calcolati e parametri di interesse clinico. I risultati dimostrano che nessuno degli indici calcolati risulta più vantaggioso rispetto agli altri. Inoltre, in accordo con la letteratura, lo stato del feto e le settimane di gestazione sono parametri di riferimento da tenere sempre in considerazione per ogni analisi effettuata. Riguardo la SDA, essa risulta utile all’analisi della FHRV, permettendo di distinguere – meglio o al pari di altre tecniche – lo stato del feto, la settimana di gestazione e la variabilità complessiva del segnale. Tuttavia, sono necessari ulteriori studi, che includano anche casi di feti patologici, per confermare queste evidenze

Apgar alternatifi olarak doğum öncesi sınıflandırma yaklaşımları

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Hızlı ve etkin bir yöntem olan apgar skorlaması yeni doğan bebeklerin sağlıklı olup olmadığının anlaşılması için kullanılır. Bebeğe herhangi bir müdahalenin (resusitasyon veya entübasyon) yapılıp yapılmayacağına apgar skorlaması ve çeşitli fizyolojik verilerin incelenmesi sonucunda karar verilmektedir. Müdahale süresinin kısalması bebek için hayati önem taşımaktadır. Bu çalışmada, anne ve fetüsten alınan fizyolojik veriler ile FHR (fetal kalp atım hızı) ve UC (rahim kasılması) sinyallerinden çıkartılan öznitelikler, yeni doğan bebeğe bir müdahale gerekip gerekmeyeceğinin doğumdan önce belirlenmesi için incelenmiş ve apgar skorlamasına yönelik çalışma yapılmıştır. Çalışmada müdahale gerekir ve müdahale gerekmez şeklinde iki sınıf kullanılmıştır. Veriler Mann-Whitney U testi kullanılarak analiz edilmiştir. Bu sınıflar istatistiksel veriler, FHR ve UC sinyalleri açısından karşılaştırılmış, elde edilen sonuçlara göre k en yakın komşu sınıflandırma algoritması kullanılarak bebekler müdahale gerekir ve müdahale gerekmez sınıflarına ayrılmıştır.Apgar scoring is a method which is a fast and a effective way of understanding whether newborn babies are healthy or not. Any intervention to the baby such as resuscitation or intubation is done, if necessary, after evaluating the Apgar score and examining various physiological data. Shortening the response time for medical support is vitally important for babies. In this study, the physiological data gathered from mother and fetus along with the features extracted from FHR (fetal heart rate) and UC (uterus contraction) signals were examined in order to determine whether the newborn will have any immediate problems that will need medical support before the baby was actually born and a study towards Apgar scoring was made. There were two classes (intervention, non-intervention) used in this study. Data was analyzed by using Mann-Whitney U test. The classes were compared in terms of statistical data, FHR and UC signals and according to the obtained the results, intervention and non-intervention classes have been devoted using k nearest neighbor classification algorithm

Machine learning algorithms combining slope deceleration and fetal heart rate features to predict acidemia

Electronic fetal monitoring (EFM) is widely used in intrapartum care as the standard method for monitoring fetal well-being. Our objective was to employ machine learning algorithms to predict acidemia by analyzing specific features extracted from the fetal heart signal within a 30 min window, with a focus on the last deceleration occurring closest to delivery. To achieve this, we conducted a case–control study involving 502 infants born at Miguel Servet University Hospital in Spain, maintaining a 1:1 ratio between cases and controls. Neonatal acidemia was defined as a pH level below 7.10 in the umbilical arterial blood. We constructed logistic regression, classification trees, random forest, and neural network models by combining EFM features to predict acidemia. Model validation included assessments of discrimination, calibration, and clinical utility. Our findings revealed that the random forest model achieved the highest area under the receiver characteristic curve (AUC) of 0.971, but logistic regression had the best specificity, 0.879, for a sensitivity of 0.95. In terms of clinical utility, implementing a cutoff point of 31% in the logistic regression model would prevent unnecessary cesarean sections in 51% of cases while missing only 5% of acidotic cases. By combining the extracted variables from EFM recordings, we provide a practical tool to assist in avoiding unnecessary cesarean sections

Classification of Foetal Distress and Hypoxia Using Machine Learning

Foetal distress and hypoxia (oxygen deprivation) is considered a serious condition and one of the main factors for caesarean section in the obstetrics and gynaecology department. It is considered to be the third most common cause of death in new-born babies. Foetal distress occurs in about 1 in 20 pregnancies. Many foetuses that experience some sort of hypoxic effects can have series risks such as damage to the cells of the central nervous system that may lead to life-long disability (cerebral palsy) or even death. Continuous labour monitoring is essential to observe foetal wellbeing during labour. Many studies have used data from foetal surveillance by monitoring the foetal heart rate with a cardiotocography, which has succeeded traditional methods for foetal monitoring since 1960. Despite the indication of normal results, these results are not reassuring, and a small proportion of these foetuses are actually hypoxic. This study investigates the use of machine learning classifiers for classification of foetal hypoxic cases using a novel method, in which we are not only considering the classification performance only, but also investigating the worth of each participating parameter to the classification as seen by medical literature. The main parameters that are included in this study as indicators of metabolic acidosis are: pH level (which is a measure of the hydrogen ion concentration of blood to specify the acidity or alkalinity), as an indicator of respiratory acidosis; Base Deficit of extra-cellular fluid level and Base Excess (BE) (which is the measure of the total concentration of blood buffer base that indicates metabolic acidosis or compensated respiratory alkalosis). In addition to other parameters such as the PCO2 (partial pressure of carbon dioxide can reflect the hypoxic state of the foetus) and the Apgar scores (which shows the foetal physical activity within a specific time interval after birth). The provided data was an open-source partum clinical data obtained by Physionet, including both hypoxic cases and normal cases. Six well known machine learning classifier are used for the classification; each model was presented with a set of selected features derived from the clinical data. Classifier evaluation is performed using the receiver operating characteristic curve analysis, area under the curve plots, as well as confusion matrix. The simulation results indicate that machine learning classifiers provide good results in diagnosis of foetal hypoxia, in addition to acceptable results of different combinations of parameters to differentiate the cases

Leitura automatizada do cardiotocograma : Contribuição para o seu desenvolvimento e avaliação

Dissertação de Doutoramento em Medicina, área de especialização em Ginecologia e Obstetrícia, apresentada à Faculdade de Medicina da Universidade do Port

Effectiveness of clinical pathway for parturient mothers upon knowledge and practice of nurses and maternal outcome

A Quasi Experimental Study to Assess the Effectiveness of Clinical pathway for Parturient Mothers upon the Knowledge and Practice of Nurses and Maternal outcome at Apollo First Med Hospitals, Chennai. The Objectives of the Study 1. To assess the pre and post-test level of knowledge and practice of nurses regarding clinical pathway for parturient mothers. 2. To evaluate the effectiveness of clinical pathway for parturient mothers upon the knowledge and practice of nurses. 3. To assess and compare the maternal outcome in control and experimental group of parturient mothers. 4. To determine the level of satisfaction of nursing care in the control and experimental groups of parturient mothers. 5. To determine the association between the selected demographic variables of nurses with their pre and post-test level of knowledge of parturient mothers. 6. To determine the association between the selected demographic variables with maternal outcome and level of satisfaction in control and experimental groups of parturient mothers. 7. To determine the association between the selected obstetric variables with maternal outcome and level of satisfaction in control and experimental groups of parturient mothers. The conceptual frame work of the study was based on “King’s Goal Attainment Theory”. The study variables were effectiveness of clinical pathway for parturient mother. Null hypotheses were formulated. The level of significance selected was p<0.001. An extensive review of literature was made based on the opinions of the experts. A Quasi experimental study of one group pre-test and post-test design was used. The study included 12 nurses and 60 parturient mothers with selected purposive sampling technique out of which 30 were in the control group and were 30 in the experimental group. The study was conducted at Apollo First Med Hospitals, Chennai. Demographic variable Proforma for nurses, demographic variable proforma for parturient mothers, obstetric variable proforma for parturient mothers, structured knowledge questionnaire, practice checklist, rating scale to assess the level of satisfaction and rating scale for maternal outcome for parturient mothers were the various tools used by the researcher. The validity was obtained from various experts and reliability was obtained through inter rater evaluation and found to be highly reliable. After pilot study the data for the main study was collected. Structured knowledge questionnaire and practice check list was used for the nurses. The rating scale for level of satisfaction and maternal outcome were used for parturient mothers. Pre-test structured knowledge questionnaire regarding clinical pathway for parturient mothers was administered to the nurses and observed the level of existing nursing practice through checklist. Assessed the maternal outcome for parturient mothers through checklist and their level of satisfaction with existing nursing practice through rating scale in control group. Then clinical pathway was implemented. After 7 days post- test structured knowledge questionnaire was administered to the same nurses and nursing practice was observed through checklist and the maternal outcome and their level of satisfaction was assessed through rating scale among experimental group of parturient mothers. The data obtained were analyzed using descriptive and inferential statistics

The effects of obstetric medication on newborn behaviour

In a study of the effects of obstetric medication on the neonate, 145 mothers and their offspring were studied from 36 weeks of pregnancy to six weeks after the birth. Fifty-one mothers requested intramuscular pethidine, 59 chose epidural bupivacaine and 35 decided not to have drugs. Data were collected during the antenatal period on health, psychological state, and expectations of the coming birth and baby. In the delivery room, observations were made of the infant and his parents, and selected assessments from the Brazelton Neonatal Behavioural Assessment Scale (BNBAS) were performed. The full BNBAS was carried out on days 1, 3, 7, 21, and 42. The Prechtl Neurological Examination (PNE) was done by a paediatrician on day 6. Records were kept by the mother over the first week of her infant's feeding and sleeping pattern, and for 24 hours after the 21 and 42 day visits. A series of questionnaires were also given to the mother during these first six weeks, covering the experience of labour, her mood, and perceptions of the baby. A multiple regression analysis using "dummy variables" for pethidine and bupivacaine indicated that the mere presence or absence of pain-relief during labour generally had no effect on the neonatal measured used. However, when biochemical indices of drug metabolism in the infant (maternal dose, cord blood concentration in the infant, half-life, and pre- and post-delivery "exposure") were entered into the equation then maternal analgesia and anaesthesia were shown to have consistent and long-lasting effects on the infant. Higher cord levels of pethidine were associated with babies who were more prone to respiratory difficulties, and drowsy and unresponsive immediately after delivery. In the following six weeks depressed attention and social responsiveness were found in connection with high drug levels, as were difficulties in state control at 3 and 6 weeks. After greater exposure to bupivacaine in utero infants were more likely to be cyanotic and unresponsive to their surroundings in the delivery room. Visual skills and alertness decreased significantly with increases in the cord blood concentration of bupivacaine, particularly on the first day but also throughout the next six weeks. Adverse effects of bupivacaine levels were seen on motor organisation, state control and physiological response to stress. However, the changes involved were relatively subtle, and the failure to find "between-groups" differences suggests that many mothers who received either bupivacaine or pethidine had babies who performed as well, and sometimes better, than those who had not been given drugs. Sleep and feed patterns and the neurological status of the infant were relatively unaffected by obstetric or medication variables. There were some modest associations between maternal psychological variables and neonatal and parental behaviour in the delivery room, but not over the next six weeks. Neither jaundice nor sex of the baby determined performance on the BNBAS. Discussion focuses on the interpretation of drug effects and the interdependence of psychosocial, obstetric and ecological variables in the management of childbirth.<p