Umbilical cord blood gas analysis at the time of delivery.

AIMS: it is now recommended that cord blood acid-base measurement is performed routinely at time of delivery in the UK as a measure of fetal response to labour. However, there remains some uncertainty about the value of this procedure. In this paper our experience of cord blood analysis is described and the literature is reviewed to: (1) provide an overview of the physiological basis of cord blood acid-base assessment; (2) describe the appropriate methodology and identify issues which have contributed to confusion and undermined the value of cord blood sampling; and (3) address the practical issues of cord blood sampling. CONCLUSIONS: cord blood acid-base measurement has a sound physiological basis. It provides objective information which is a useful adjunct to subjective methods of newborn assessment, enables babies at risk of neonatal morbidity to be identified, can be helpful in litigation cases and is a prerequisite for clinical audit. However, to be of benefit the information must be correct and correctly interpreted.

A multicentre comparative study of 17 experts and an intelligent computer system for managing labour using the cardiotocogram.

OBJECTIVES: To investigate 1. whether an intelligent computer system could obtain a performance in labour management comparable with experts when using cardiotocograms (CTGs), patient information, and fetal blood sampling and 2. whether experts could be consistent and agree in their management of labour. SUBJECTS: An intelligent computer system and 17 clinicians experienced in fetal monitoring from 16 centres in the UK. DESIGN: Fifty cases with complete intrapartum CTGs and clinical data were reviewed by each expert and the system independently on two occasions, at least one month apart. Each CTG was scored in 15 min segments according to a protocol and estimates of the cervical dilatation and fetal scalp blood pH were given when requested. MAIN OUTCOME MEASURES: Consistency and agreement in the recorded scores, agreement and timing of cases recommended for caesarean sections, fetal blood sampling rates, intervention in cases with poor outcome and intervention in cases with good clinical outcome. RESULTS: The system: 1. Agreed with experts well and significantly better than chance (67.33%, kappa = 0.31, P << 0.001). 2. Was highly consistent (99.16%, kappa = 0.98, P << 0.001) when used by two operators independently. 3. Recommended no unnecessary intervention in cases with normal delivery and good condition (cord artery pH > 7.15, vein pH > 7.20, 5 min Apgar > or = 9 and no resuscitation). This was better than all but two of the experts. 4. Recommended delivery by caesarean section in 11 cases; at least 15 of the 17 experts in each review also recommended caesarean section delivery in these cases. The majority did so within 15 min of the system and two-thirds did so within 30 min. 5. Identified as many of the birth asphyxiated cases (cord arterial pH < 7.05 and BDecf > or = 12, and Apgar score at 5 min < or = 7 with neonatal morbidity) as the majority of experts and one more than was acted upon clinically. The experts were found to be consistent and to agree. There was good agreement in the cases and the timing of caesarean section recommendations. The majority of experts did not recommend operative intervention in cases which had a normal delivery and good outcome, but did recommend operative interventions in 10 of 12 cases delivered with cord arterial pH < 7.05. However, in one of the cases delivered with birth asphyxia, 14 of the 17 experts and the system failed to recommend intervention. CONCLUSIONS: The system's performance was found to be indistinguishable from the experts' in the 50 cases examined, but it was more consistent. This demonstrates the potential for an intelligent computer system to improve the interpretation of the CTG and decrease intervention. Furthermore, the good performance of most experts in this study demonstrates the potential effectiveness of the CTG and raises important questions regarding why the CTG has fallen short of expectations in current practice.

Development, evaluation and validation of an intelligent system for the management of labour.

Over the past 4 years our group has developed a prototype intelligent system which applies captured expert knowledge to support clinical decision-making during labour. This chapter presents a review of the system and the progress made to date. The system classifies the same features from the CTG as experienced clinicians using numerical algorithms and a small neural network. This hybrid approach has been shown to obtain a comparable performance with experts. The CTG information, together with the patient information and labour events, are collectively passed to an expert system for processing. The expert system interprets this combined data using a database of over 400 rules which are used to recommend action. Importantly, as the knowledge is rule-based, it allows the system to explain the reasoning which led it to recommend a certain action. In this way, the clinician is not expected to blindly follow the system's recommendations but can reach an informed judgement in the same way they might by discussing the case with an experienced informed colleague. After two internal evaluations had found the system obtained a performance comparable with local experts, an extensive external validation was undertaken. This study involved 17 experts from 16 leading centres within the UK. Each expert and the system reviewed 50 cases twice, at least one month apart which contained those CTGs considered most difficult to interpret selected from a database of 2400 high-risk labours. This study found that the majority of experts agreed well and were consistent in their management of the cases. The system obtained a performance that was indistinguishable from the experts, except it was more consistent, even when used by an engineer with little knowledge of labour management. This study demonstrates the potential for intelligent systems to transform the cardiotocograph from a difficult-to-use, ineffective recorder of fetal heart rate, to an interactive and effective decision support tool capable of raising the skills of staff.

Suitability of artificial neural networks for feature extraction from cardiotocogram during labour.

Fetal condition during labour is inferred from a continuous display of fetal heart rate and uterine contractions called the cardiotocogram (CTG). The CTG requires a considerable expertise for correct interpretation, which is not always available. We are developing an intelligent system to support clinical decision-making during labour. The system's performance depends on its ability to classify features from the CTG similarly to experts. Artificial neural networks (NNs) can be taught by experts for such tasks, and so may be particularly suitable. We found NNs suitable for feature extraction when the problem was reduced to small well defined tasks, and numerical algorithms were used to pre-process the raw data before application to the NNs. A NN with optimised dimensions was used in this way to classify the magnitude of decelerations, a feature clinicians find particularly difficult. The NN was compared with the algorithm used in a commercial antenatal monitor and six reviewers which included two CTG experts. The experts were consistent (89.7% and 97.0%) and agreed well with each other (81.0%), whereas the non-experts were less consistent and agreed less well. The NN agreed well with the experts (75.0% and 81.9%) but the algorithm agreed poorly (56.5% and 68.9%). It was found that the algorithm's performance could be improved (72.1% and 76.7%) when modified to use additional information. Our earlier attempts to fully classify the raw CTG using a single NN were unsuccessful because of the large number of data patterns. A simplified approach to classify the magnitude and timing of decelerations was also unsuitable when contraction data was of poor quality or absent.(ABSTRACT TRUNCATED AT 250 WORDS)

Preliminary evaluation of an intelligent system for the management of labour.

Over the past 10-15 years, workers using conventional computing approaches have attempted to provide an accurate assessment of fetal condition during labour based on the cardiotocogram (CTG) alone. These have not proved successful perhaps because the correct interpretation of fetal condition also requires physiological knowledge, specific patient information, knowledge of events during labour and considerable practical experience. An intelligent system which considers all the relevant information and embodies expertise may better diagnose fetal condition and support decision making. This study reports the preliminary evaluation of such a system and investigates whether this approach can attain a performance comparable with experienced local clinicians. From a database of 200 high risk labour records, 30 cases were selected; the 9 cases which received clinical intervention for 'fetal-distress' and a further 21 cases selected randomly. The management specified by the system, 3 experienced clinicians (A, B and C) and the actual clinical management were compared in a retrospective blinded review. The experts were found to agree well with each other. Expert A reviewed the cases five months later and was found to be entirely consistent in the management of 28 of the 30 cases. The system's actions were indistinguishable from the experts' and in no case did the system recommend an action not also recommended by at least one experienced reviewer. This study demonstrates the potential of an intelligent system to assist in the management of labour.

Suitability of fetal scalp electrodes for monitoring the fetal electrocardiogram during labour.

As the limitations of heart-rate based intrapartum monitoring have become apparent, there is renewed interest in analysis of the fetal electrocardiographic waveform as obtained from a fetal scalp electrode. A high quality ECG signal is necessary for waveform analysis. This study examined the suitability of five commonly available scalp electrodes for collecting this signal by examining their physical and electrical characteristics, together with a randomised clinical trial in which the ECG trace quality was assessed in 50 patients. The frequency response of Copeland electrodes was such that they attenuate the ECG signal more than the baseline noise. Difficulties were experienced in obtaining optimum attachment and the long, semi-rigid design increased movement artefact resulting in significantly poorer quality ECG signals. Whilst the Hewlett-Packard double spiral electrode had a near ideal frequency response, certain design features made it difficult to apply and remain secure so the clinical signals were of intermediate quality. The Corometrics and Cetro single spirals had the most stable attachment to the scalp and a near ideal frequency response, so produced significantly better signal quality in the clinical trial. Currently, single spiral electrodes are the most suitable for electrocardiographic data collection.