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      A study of an intelligent system to support decision making in the management of labour using the cardiotocograph – the INFANT study protocol

      research-article
      , on behalf of The INFANT Collaborative Group
      BMC Pregnancy and Childbirth
      BioMed Central
      Monitoring, Labour, Computerised, Interpretation, Decision support, Cardiotocogram, Continuous electronic fetal monitoring

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          Abstract

          Background

          Continuous electronic fetal heart rate monitoring in labour is widely used but its potential for improving fetal and neonatal outcomes has not been realised. The most likely reason is the difficulty of interpreting the fetal heart rate trace correctly during labour. Computerised interpretation of the fetal heart rate and intelligent decision-support has the potential to deliver this improvement in care.

          This trial will test whether the addition of decision support software to aid the interpretation of the cardiotocogram (CTG) during labour will reduce the number of ‘poor neonatal outcomes’ in those women judged to require continuous electronic fetal heart rate monitoring.

          Methods and design

          An individually randomised controlled trial of 46,000 women who are judged to require continuous electronic fetal monitoring in labour.

          Eligibility criteria: Women admitted to a participating labour ward who are judged to require continuous electronic fetal monitoring, have a singleton or twin pregnancy, are ≥ 35 weeks’ gestation, have no known gross fetal abnormality and are ≥ 16 years of age.

          Exclusion criteria: Triplets or higher order pregnancy, elective caesarean section prior to the onset of labour, planned admission to NICU.

          Trial interventions: Computerised interpretation of the CTG with decision-support.

          Primary outcomes: Short term: A composite of ‘poor neonatal outcome’ including stillbirth after trial entry, early neonatal death except deaths due to congenital anomalies, significant morbidity: neonatal encephalopathy, admissions to the neonatal unit with 48 h for > 48 h with evidence of feeding difficulties, respiratory illness or encephalopathy where there is evidence of compromise at birth. Long term: Developmental assessment at the age of 2 years in a subset of 7000 surviving babies.

          Data Collection: For all participating women and babies, labour variables and outcomes will be stored automatically and contemporaneously onto the Guardian® system.

          Discussion

          The results of this trial will have importance for pregnant women and for health professionals who provide care for them.

          Trial registration

          Current Controlled Trials ISRCTN98680152 assigned 30.09.2008

          Related collections

          Most cited references61

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          Error, stress, and teamwork in medicine and aviation: cross sectional surveys.

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            Design and analysis of randomized clinical trials requiring prolonged observation of each patient. I. Introduction and design.

            The Medical Research Council has for some years encouraged collaborative clinical trials in leukaemia and other cancers, reporting the results in the medical literature. One unreported result which deserves such publication is the development of the expertise to design and analyse such trials. This report was prepared by a group of British and American statisticians, but it is intended for people without any statistical expertise. Part I, which appears in this issue, discusses the design of such trials; Part II, which will appear separately in the January 1977 issue of the Journal, gives full instructions for the statistical analysis of such trials by means of life tables and the logrank test, including a worked example, and discusses the interpretation of trial results, including brief reports of 2 particular trials. Both parts of this report are relevant to all clinical trials which study time to death, and wound be equally relevant to clinical trials which study time to other particular classes of untoward event: first stroke, perhaps, or first relapse, metastasis, disease recurrence, thrombosis, transplant rejection, or death from a particular cause. Part I, in this issue, collects together ideas that have mostly already appeared in the medical literature, but Part II, next month, is the first simple account yet published for non-statistical physicians of how to analyse efficiently data from clinical trials of survival duration. Such trials include the majority of all clinical trials of cancer therapy; in cancer trials,however, it may be preferable to use these statistical methods to study time to local recurrence of tumour, or to study time to detectable metastatic spread, in addition to studying total survival. Solid tumours can be staged at diagnosis; if this, or any other available information in some other disease is an important determinant of outcome, it can be used to make the overall logrank test for the whole heterogeneous trial population more sensitive, and more intuitively satisfactory, for it will then only be necessary to compare like with like, and not, by chance, Stage I with Stage III.
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              Analysis of cost data in randomized trials: an application of the non-parametric bootstrap.

              Health economic evaluations are now more commonly being included in pragmatic randomized trials. However a variety of methods are being used for the presentation and analysis of the resulting cost data, and in many cases the approaches taken are inappropriate. In order to inform health care policy decisions, analysis needs to focus on arithmetic mean costs, since these will reflect the total cost of treating all patients with the disease. Thus, despite the often highly skewed distribution of cost data, standard non-parametric methods or use of normalizing transformations are not appropriate. Although standard parametric methods of comparing arithmetic means may be robust to non-normality for some data sets, this is not guaranteed. While the randomization test can be used to overcome assumptions of normality, its use for comparing means is still restricted by the need for similarly shaped distributions in the two groups. In this paper we show how the non-parametric bootstrap provides a more flexible alternative for comparing arithmetic mean costs between randomized groups, avoiding the assumptions which limit other methods. Details of several bootstrap methods for hypothesis tests and confidence intervals are described and applied to cost data from two randomized trials. The preferred bootstrap approaches are the bootstrap-t or variance stabilized bootstrap-t and the bias corrected and accelerated percentile methods. We conclude that such bootstrap techniques can be recommended either as a check on the robustness of standard parametric methods, or to provide the primary statistical analysis when making inferences about arithmetic means for moderately sized samples of highly skewed data such as costs.
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                Author and article information

                Contributors
                p.brocklehurst@ucl.ac.uk
                Journal
                BMC Pregnancy Childbirth
                BMC Pregnancy Childbirth
                BMC Pregnancy and Childbirth
                BioMed Central (London )
                1471-2393
                20 January 2016
                20 January 2016
                2016
                : 16
                : 10
                Affiliations
                UCL EGA Institute for Women’s Health, 74 Huntley Street, WC1E 6 AU London, UK
                Article
                780
                10.1186/s12884-015-0780-0
                4719576
                26791569
                ddbad47b-364a-4970-8cc3-4d31d5979af0
                © Brocklehurst. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 30 October 2014
                : 8 December 2015
                Categories
                Study Protocol
                Custom metadata
                © The Author(s) 2016

                Obstetrics & Gynecology
                monitoring,labour,computerised,interpretation,decision support,cardiotocogram,continuous electronic fetal monitoring

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