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Evans MI, Britt DW, Evans SM, Devoe LD. Changing Perspectives of Electronic Fetal Monitoring. Reprod Sci 2022; 29:1874-1894. [PMID: 34664218 PMCID: PMC8522858 DOI: 10.1007/s43032-021-00749-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 09/24/2021] [Indexed: 12/26/2022]
Abstract
The delivery of healthy babies is the primary goal of obstetric care. Many technologies have been developed to reduce both maternal and fetal risks for poor outcomes. For 50 years, electronic fetal monitoring (EFM) has been used extensively in labor attempting to prevent a large proportion of neonatal encephalopathy and cerebral palsy. However, even key opinion leaders admit that EFM has mostly failed to achieve this goal. We believe this situation emanates from a fundamental misunderstanding of differences between screening and diagnostic tests, considerable subjectivity and inter-observer variability in EFM interpretation, failure to address the pathophysiology of fetal compromise, and a tunnel vision focus. To address these suboptimal results, several iterations of increasingly sophisticated analyses have intended to improve the situation. We believe that part of the continuing problem is that the focus of EFM has been too narrow ignoring important contextual issues such as maternal, fetal, and obstetrical risk factors, and increased uterine contraction frequency. All of these can significantly impact the application of EFM to intrapartum care. We have recently developed a new clinical approach, the Fetal Reserve Index (FRI), contextualizing EFM interpretation. Our data suggest the FRI is capable of providing higher accuracy and earlier detection of emerging fetal compromise. Over time, artificial intelligence/machine learning approaches will likely improve measurements and interpretation of FHR characteristics and other relevant variables. Such future developments will allow us to develop more comprehensive models that increase the interpretability and utility of interfaces for clinical decision making during the intrapartum period.
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Affiliation(s)
- Mark I Evans
- Fetal Medicine Foundation of America, New York, NY, USA.
- Comprehensive Genetics, PLLC, New York, NY, USA.
- Department of Obstetrics & Gynecology, Icahn School of Medicine at Mt. Sinai, New York, NY, USA.
| | - David W Britt
- Fetal Medicine Foundation of America, New York, NY, USA
| | - Shara M Evans
- Department of Maternal Child Health, Gillings School of Public Health, University of North Carolina, Chapel Hill, USA
| | - Lawrence D Devoe
- Department of Obstetrics and Gynecology, Medical College of Georgia, Augusta University, Augusta, GA, USA
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2
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Barbounaki S, Vivilaki VG. Intelligent systems in obstetrics and midwifery: Applications of machine learning. Eur J Midwifery 2022; 5:58. [PMID: 35005483 PMCID: PMC8686058 DOI: 10.18332/ejm/143166] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 10/15/2021] [Accepted: 10/18/2021] [Indexed: 12/28/2022] Open
Abstract
INTRODUCTION Machine learning is increasingly utilized over recent years in order to develop models that represent and solve problems in a variety of domains, including those of obstetrics and midwifery. The aim of this systematic review was to analyze research studies on machine learning and intelligent systems applications in midwifery and obstetrics. METHODS A thorough literature review was performed in four electronic databases (PubMed, APA PsycINFO, SCOPUS, ScienceDirect). Only articles that discussed machine learning and intelligent systems applications in midwifery and obstetrics, were considered in this review. Selected articles were critically evaluated as for their relevance and a contextual synthesis was conducted. RESULTS Thirty-two articles were included in this systematic review as they met the inclusion and methodological criteria specified in this study. The results suggest that machine learning and intelligent systems have produced successful models and systems in a broad list of midwifery and obstetrics topics, such as diagnosis, pregnancy risk assessment, fetal monitoring, bladder tumor, etc. CONCLUSIONS This systematic review suggests that machine learning represents a very promising area of artificial intelligence for the development of practical and highly effective applications that can support human experts, as well the investigation of a wide range of exciting opportunities for further research.
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Affiliation(s)
- Stavroula Barbounaki
- Department of Midwifery, School of Health and Care Sciences, University of West Attica, Athens, Greece
| | - Victoria G Vivilaki
- Department of Midwifery, School of Health and Care Sciences, University of West Attica, Athens, Greece
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3
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Vargas-Calixto J, Warrick P, Kearney R. Estimation and Discriminability of Doppler Ultrasound Fetal Heart Rate Variability Measures. Front Artif Intell 2021; 4:674238. [PMID: 34490419 PMCID: PMC8417534 DOI: 10.3389/frai.2021.674238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 07/27/2021] [Indexed: 11/20/2022] Open
Abstract
Continuous electronic fetal monitoring and the access to databases of fetal heart rate (FHR) data have sparked the application of machine learning classifiers to identify fetal pathologies. However, most fetal heart rate data are acquired using Doppler ultrasound (DUS). DUS signals use autocorrelation (AC) to estimate the average heartbeat period within a window. In consequence, DUS FHR signals loses high frequency information to an extent that depends on the length of the AC window. We examined the effect of this on the estimation bias and discriminability of frequency domain features: low frequency power (LF: 0.03–0.15 Hz), movement frequency power (MF: 0.15–0.5 Hz), high frequency power (HF: 0.5–1 Hz), the LF/(MF + HF) ratio, and the nonlinear approximate entropy (ApEn) as a function of AC window length and signal to noise ratio. We found that the average discriminability loss across all evaluated AC window lengths and SNRs was 10.99% for LF 14.23% for MF, 13.33% for the HF, 10.39% for the LF/(MF + HF) ratio, and 24.17% for ApEn. This indicates that the frequency domain features are more robust to the AC method and additive noise than the ApEn. This is likely because additive noise increases the irregularity of the signals, which results in an overestimation of ApEn. In conclusion, our study found that the LF features are the most robust to the effects of the AC method and noise. Future studies should investigate the effect of other variables such as signal drop, gestational age, and the length of the analysis window on the estimation of fHRV features and their discriminability.
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Affiliation(s)
| | - Philip Warrick
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada.,PeriGen Inc., Montreal, QC, Canada
| | - Robert Kearney
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
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Intrapartum Resuscitation Interventions for Category II Fetal Heart Rate Tracings and Improvement to Category I. Obstet Gynecol 2021; 138:409-416. [PMID: 34352857 DOI: 10.1097/aog.0000000000004508] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Accepted: 05/06/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVE To evaluate intrapartum resuscitation interventions and improvement in category II fetal heart rate (FHR) tracings. METHODS This secondary analysis of a randomized trial of intrapartum fetal electrocardiographic ST-segment analysis included all participants with category II FHR tracings undergoing intrauterine resuscitation: maternal oxygen, intravenous fluid bolus, amnioinfusion, or tocolytic administration. Fetal heart rate pattern-recognition software was used to confirm category II FHR tracings 30 minutes before intervention and to analyze the subsequent 60 minutes. The primary outcome was improvement to category I within 60 minutes. Secondary outcomes included FHR tracing improvement to category I 30-60 minutes after the intervention and composite neonatal outcome. RESULTS Of 11,108 randomized participants, 2,251 (20.3%) had at least one qualifying intervention for category II FHR tracings: 63.7% improved to category I within 60 minutes and 50.5% improved at 30-60 minutes. Only 3.4% underwent cesarean delivery and 4.1% an operative vaginal delivery for nonreassuring fetal status within 60 minutes after the intervention. Oxygen administration was the most common intervention (75.4%). Among American College of Obstetricians and Gynecologists-defined subgroups that received oxygen, the absent FHR accelerations and absent-minimal FHR variability subgroup (n=332) was more likely to convert to category I within 60 minutes than the FHR accelerations or "moderate FHR variability" subgroup (n=1,919) (77.0% vs 63.0%, odds ratio [OR] 2.0, 95% CI 1.4-2.7). The incidence of composite neonatal adverse outcome for category II tracings was 2.9% (95% CI 2.2-3.7%) overall; 2.8% (95% CI 2.0-3.8%) for improvement to category I within 60 minutes (n=1,433); and 3.2% (95% CI 2.1-4.6%) for no improvement within 60 minutes (n=818). However, the group with improvement had 29% lower odds for higher level neonatal care (11.8% vs 15.9%, OR 0.71, 95% CI 0.55-0.91). CONCLUSION Nearly two thirds of category II FHR tracings improved to category I within 60 minutes of intervention with a relatively low overall rate of the composite neonatal adverse outcome. FUNDING SOURCE Funded in part by Neoventa Medical.
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Garcia-Canadilla P, Sanchez-Martinez S, Crispi F, Bijnens B. Machine Learning in Fetal Cardiology: What to Expect. Fetal Diagn Ther 2020; 47:363-372. [PMID: 31910421 DOI: 10.1159/000505021] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Accepted: 11/25/2019] [Indexed: 11/19/2022]
Abstract
In fetal cardiology, imaging (especially echocardiography) has demonstrated to help in the diagnosis and monitoring of fetuses with a compromised cardiovascular system potentially associated with several fetal conditions. Different ultrasound approaches are currently used to evaluate fetal cardiac structure and function, including conventional 2-D imaging and M-mode and tissue Doppler imaging among others. However, assessment of the fetal heart is still challenging mainly due to involuntary movements of the fetus, the small size of the heart, and the lack of expertise in fetal echocardiography of some sonographers. Therefore, the use of new technologies to improve the primary acquired images, to help extract measurements, or to aid in the diagnosis of cardiac abnormalities is of great importance for optimal assessment of the fetal heart. Machine leaning (ML) is a computer science discipline focused on teaching a computer to perform tasks with specific goals without explicitly programming the rules on how to perform this task. In this review we provide a brief overview on the potential of ML techniques to improve the evaluation of fetal cardiac function by optimizing image acquisition and quantification/segmentation, as well as aid in improving the prenatal diagnoses of fetal cardiac remodeling and abnormalities.
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Affiliation(s)
- Patricia Garcia-Canadilla
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain, .,Institute of Cardiovascular Science, University College London, London, United Kingdom,
| | | | - Fatima Crispi
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain.,Fetal Medicine Research Center, BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), Institut Clínic de Ginecologia Obstetricia i Neonatologia, Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Bart Bijnens
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain.,Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium.,ICREA, Barcelona, Spain
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Chauhan SP, Weiner SJ, Saade GR, Belfort MA, Reddy UM, Thorp JM, Tita ATN, Miller RS, Dinsmoor MJ, McKenna DS, Stetzer B, Rouse DJ, Gibbs RS, El-Sayed YY, Sorokin Y, Caritis SN. Intrapartum Fetal Heart Rate Tracing Among Small-for-Gestational Age Compared With Appropriate-for-Gestational-Age Neonates. Obstet Gynecol 2018; 132:1019-1025. [PMID: 30204687 PMCID: PMC6247114 DOI: 10.1097/aog.0000000000002855] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE To compare fetal heart rate (FHR) patterns during the last hour of labor between small-for-gestational-age (SGA; birth weight less than the 10th percentile for gestational age) and appropriate-for-gestational-age (AGA; birth weight at the 10-90th percentile) neonates at 36 weeks of gestation or greater. We also compared the rate of cesarean delivery and composite neonatal morbidity among SGA and AGA newborns. METHODS This is a secondary analysis of a randomized trial of intrapartum fetal electrocardiographic ST-segment analysis. We excluded women with chorioamnionitis, insufficient duration of FHR tracing in the hour before delivery, and anomalous newborns. Fetal heart rate patterns were categorized by computerized pattern recognition software (PeriCALM Patterns). Composite neonatal morbidity was defined as any of the following: intrapartum fetal death, Apgar score 3 or less at 5 minutes, cord artery pH 7.05 or less, base deficit 12 mmol/L or greater, neonatal seizure, intubation at delivery, neonatal encephalopathy, and neonatal death. Logistic regression was used to evaluate the association between FHR patterns and SGA adjusted for magnesium sulfate exposure and stage of labor. RESULTS Of the 11,108 women randomized, 85% (n=9,402) met inclusion criteria, of whom 9% were SGA. In the last hour, the likelihood of accelerations was significantly lower among SGA than AGA neonates (72.4% vs 66.8%; P=.001). Variable decelerations lasting greater than 60 seconds, with depth greater than 60 beats per minute (bpm) or nadir less than 60 bpm, were significantly more common with SGA than AGA (all P<.001). The rate of late decelerations, prolonged decelerations, or bradycardia were similar between SGA and AGA (all P>.05). Cesarean delivery for fetal indications was significantly more common with SGA (7.0%) than AGA (4.0%; P<.001). The composite neonatal morbidity was 1.4% among SGA and 1.0% among AGA (odds ratio 1.40, 95% CI 0.74-2.64). CONCLUSION Although the FHR patterns in the last hour of labor differ among SGA and AGA neonates, as does the rate of cesarean delivery, the composite neonatal morbidity was similar.
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Affiliation(s)
- Suneet P Chauhan
- Departments of Obstetrics and Gynecology, University of Texas Health Science Center at Houston, McGovern Medical School-Children's Memorial Hermann Hospital, Houston, Texas; University of Texas Medical Branch, Galveston, Texas; University of Utah Health Sciences Center, Salt Lake City, Utah; University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; University of Alabama at Birmingham, Birmingham, Alabama; Columbia University, New York, New York; Northwestern University, Chicago, Illinois; The Ohio State University, Columbus, Ohio; MetroHealth Medical Center-Case Western Reserve University, Cleveland, Ohio; Brown University, Providence, Rhode Island; University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, Colorado; Stanford University, Stanford, California; Wayne State University, Detroit, Michigan; and University of Pittsburgh, Pittsburgh, Pennsylvania; the George Washington University Biostatistics Center, Washington, DC; and the Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland
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Marzbanrad F, Stroux L, Clifford GD. Cardiotocography and beyond: a review of one-dimensional Doppler ultrasound application in fetal monitoring. Physiol Meas 2018; 39:08TR01. [PMID: 30027897 PMCID: PMC6237616 DOI: 10.1088/1361-6579/aad4d1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
One-dimensional Doppler ultrasound (1D-DUS) provides a low-cost and simple method for acquiring a rich signal for use in cardiovascular screening. However, despite the use of 1D-DUS in cardiotocography (CTG) for decades, there are still challenges that limit the effectiveness of its users in reducing fetal and neonatal morbidities and mortalities. This is partly due to the noisy, transient, complex and nonstationary nature of the 1D-DUS signals. Current challenges also include lack of efficient signal quality metrics, insufficient signal processing techniques for extraction of fetal heart rate and other vital parameters with adequate temporal resolution, and lack of appropriate clinical decision support for CTG and Doppler interpretation. Moreover, the almost complete lack of open research in both hardware and software in this field, as well as commercial pressures to market the much more expensive and difficult to use Doppler imaging devices, has hampered innovation. This paper reviews the basics of fetal cardiac function, 1D-DUS signal generation and processing, its application in fetal monitoring and assessment of fetal development and wellbeing. It also provides recommendations for future development of signal processing and modeling approaches, to improve the application of 1D-DUS in fetal monitoring, as well as the need for annotated open databases.
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Affiliation(s)
- Faezeh Marzbanrad
- Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC, Australia
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A Comprehensive Evaluation of the Predictive Abilities of Fetal Electrocardiogram-Derived Parameters during Labor in Newborn Acidemia: Our Institutional Experience. BIOMED RESEARCH INTERNATIONAL 2018; 2018:3478925. [PMID: 29888259 PMCID: PMC5985095 DOI: 10.1155/2018/3478925] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Revised: 03/20/2018] [Accepted: 04/17/2018] [Indexed: 11/17/2022]
Abstract
This study aimed to identify cardiotocography patterns that discriminate fetal acidemia newborns by comprehensively evaluating the parameters obtained from Holter monitoring during delivery. Between June 1, 2015, and August 1, 2016, a prospective observational study of 85 patients was conducted using fetal Holter monitoring at the Beijing Obstetrics and Gynecology Hospital, Capital Medical University, China. Umbilical cord blood was sampled immediately after delivery and fetal acidemia was defined as umbilical cord arterial blood pH < 7.20. Fetal electrocardiogram- (FECG-) derived parameters, including basal fetal heart rate (BFHR), short-term variation (STV), large acceleration (LA), deceleration capacity (DC), acceleration capacity (AC), proportion of episodes of high variation (PEHV), and proportion of episodes of low variation (PELV), were compared between 16 fetuses with acidemia and 47 without. The areas under the curve (AUC) of receiver operating characteristics (ROC) were calculated. Although all the computerized parameters showed predictive values for acidemia (all AUC > 0.50), STV (AUC = 0.84, P < 0.001), DC (AUC = 0.84, P < 0.001), AC (AUC = 0.80, P < 0.001), and PELV (AUC = 0.71, P = 0.012) were more strongly associated with fetal acidemia. Our institutional experience suggests that FECG-derived parameters from Holter monitoring are beneficial in reducing the incidence of neonatal acidemia.
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Silberstein T, Sheiner E, Salem SY, Hamou B, Aricha B, Baumfeld Y, Yohay Z, Elharar D, Idan I, Yohay D. Fetal heart rate monitoring category 3 during the 2nd stage of labor is an independent predictor of fetal acidosis. J Matern Fetal Neonatal Med 2016; 30:257-260. [DOI: 10.3109/14767058.2016.1172064] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- Tali Silberstein
- Department of Obstetrics and Gynecology, Soroka University Medical Center, Beersheba, Israel
| | - Eyal Sheiner
- Department of Obstetrics and Gynecology, Soroka University Medical Center, Beersheba, Israel
| | - Shimrit Yaniv Salem
- Department of Obstetrics and Gynecology, Soroka University Medical Center, Beersheba, Israel
| | - Batel Hamou
- Department of Obstetrics and Gynecology, Soroka University Medical Center, Beersheba, Israel
| | - Barak Aricha
- Department of Obstetrics and Gynecology, Soroka University Medical Center, Beersheba, Israel
| | - Yael Baumfeld
- Department of Obstetrics and Gynecology, Soroka University Medical Center, Beersheba, Israel
| | - Zehava Yohay
- Department of Obstetrics and Gynecology, Soroka University Medical Center, Beersheba, Israel
| | - Debora Elharar
- Department of Obstetrics and Gynecology, Soroka University Medical Center, Beersheba, Israel
| | - Inbal Idan
- Department of Obstetrics and Gynecology, Soroka University Medical Center, Beersheba, Israel
| | - David Yohay
- Department of Obstetrics and Gynecology, Soroka University Medical Center, Beersheba, Israel
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Sholapurkar SL. Imperative for improvements and international convergence of intrapartum fetal monitoring: A bird’s eye view. World J Obstet Gynecol 2016; 5:102-109. [DOI: 10.5317/wjog.v5.i1.102] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2015] [Revised: 10/25/2015] [Accepted: 11/25/2015] [Indexed: 02/05/2023] Open
Abstract
Intrapartum fetal monitoring has been criticized for the lack of evidence of improvement in fetal outcome despite causing increased operative intervention. Paradoxically, cardiotocography (CTG) has been a major driver for litigation for neonatal neurological injury. This analytical review tries to explore why extensive clinical studies and trials over 50 years have failed to demonstrate or bring about significant improvement in intrapartum fetal monitoring. There seems a need for significant reform. International congruence on most aspects of CTG interpretation [definitions of fetal heart rate (FHR) parameters, CTG recording speed, 3-tier systems, etc.] is highly desirable to facilitate future meaningful clinical studies, evaluation and progress in this field. The FHR changes are non-specific and poor surrogate for fetal well-being. As a compromise for maintaining low false-negative results for fetal acidemia, a high false-positive value may have to be accepted. The need for redefining the place of adjuvant tests of fetal well-being like fetal blood sampling or fetal electrocardiography (ECG) is discussed. The FHR decelerations are often deterministic (center-stage) in CTG interpretation and 3-tier categorization. It is discussed if their scientific and physiological classification (avoiding framing and confirmation biases) may be best based on time relationship to uterine contractions alone. This may provide a more sound foundation which could improve the reliability and further evolution of 3-tier systems. Results of several trials of fetal ECG (STAN) have been inconclusive and a need for a fresh approach or strategy is considered. It is hoped that the long anticipated Computer-aided analysis of CTG will be more objective and reliable (overcome human factors) and will offer valuable support or may eventually replace visual CTG interpretation. In any case, the recording and archiving all CTGs digitally and testing cord blood gases routinely in every delivery would be highly desirable for future research. This would facilitate well designed retrospective studies which can be very informative especially when prospective randomised controlled trials are often difficult and resource-intensive.
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Karmakar C, Kimura Y, Palaniswami M, Khandoker A. Analysis of fetal heart rate asymmetry before and after 35 weeks of gestation. Biomed Signal Process Control 2015. [DOI: 10.1016/j.bspc.2015.05.010] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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12
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Hruban L, Spilka J, Chudáček V, Janků P, Huptych M, Burša M, Hudec A, Kacerovský M, Koucký M, Procházka M, Korečko V, Seget'a J, Šimetka O, Měchurová A, Lhotská L. Agreement on intrapartum cardiotocogram recordings between expert obstetricians. J Eval Clin Pract 2015; 21:694-702. [PMID: 26011725 DOI: 10.1111/jep.12368] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/10/2015] [Indexed: 12/26/2022]
Abstract
RATIONALE, AIMS AND OBJECTIVES To evaluate obstetricians' inter- and intra-observer agreement on intrapartum cardiotocogram (CTG) recordings and to examine obstetricians' evaluations with respect to umbilical artery pH and base deficit. METHODS Nine experienced obstetricians annotated 634 intrapartum CTG recordings. The evaluation of each recording was divided into four steps: evaluation of two 30-minute windows in the first stage of labour, evaluation of one window in the second stage of labour and labour outcome prediction. The complete set of evaluations used for this experiment is available online. The inter- and intra-observer agreement was evaluated using proportion of agreement and kappa coefficient. Clinicians' sensitivity and specificity was computed with respect to umbilical artery pH, base deficit and to Apgar score at the fifth minute. RESULTS The overall proportion of agreement between clinicians reached 48% with 95% confidence intervals (CI) (CI: 47-50). Regarding the different classes, proportion of agreement ranged from 57% (CI: 54-60) for normal to 41% (CI: 36-46) for pathological class. The sensitivity of clinicians' majority vote to objective outcome was 39% (CI: 16-63) for the umbilical artery base deficit and 27% (CI: 16-42) for pH. The specificity was 89% (CI: 86-92) for both types of objective outcome. CONCLUSIONS The reported inter-/intra-observer variability is large and this holds irrespective of clinicians' experience or work place. The results support the need of modernized guidelines for CTG evaluation and/or objectivization and repeatability by introduction of a computerized approach that could standardize the process of CTG evaluation within the delivery ward.
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Affiliation(s)
- Lukáš Hruban
- Department of Gynecology and Obstetrics, Masaryk University Hospital, Brno, Czech Republic
| | - Jiří Spilka
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.,Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Prague, Czech Republic
| | - Václav Chudáček
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.,Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Prague, Czech Republic
| | - Petr Janků
- Department of Gynecology and Obstetrics, Masaryk University Hospital, Brno, Czech Republic
| | - Michal Huptych
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Miroslav Burša
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Adam Hudec
- Department of Gynecology and Obstetrics, University Hospital in Plzeň, Plzeň, Czech Republic
| | - Marian Kacerovský
- Department of Gynecology and Obstetrics, University Hospital in Hradec Králové, Hradec Králové, Czech Republic
| | - Michal Koucký
- Department of Gynecology and Obstetrics, University Hospital in Prague, Prague, Czech Republic
| | - Martin Procházka
- Department of Gynecology and Obstetrics, University Hospital in Olomouc, Olomouc, Czech Republic
| | - Vladimír Korečko
- Department of Gynecology and Obstetrics, University Hospital in Plzeň, Plzeň, Czech Republic
| | - Jan Seget'a
- Department of Gynecology and Obstetrics, University Hospital Ostrava, Ostrava, Czech Republic
| | - Ondřej Šimetka
- Department of Gynecology and Obstetrics, University Hospital Ostrava, Ostrava, Czech Republic.,Department of Surgical Studies, Ostrava University, Ostrava, Czech Republic
| | - Alena Měchurová
- Department for Mother and Child Care, Prague Podolí, Prague, Czech Republic
| | - Lenka Lhotská
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
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Pladys P, Vandenbroucke L, Hernandez A, Beuchée A. Intérêt des mesures de variabilité du rythme cardiaque dans le sepsis. MEDECINE INTENSIVE REANIMATION 2015. [DOI: 10.1007/s13546-014-1013-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Dong S, Boashash B, Azemi G, Lingwood BE, Colditz PB. Automated detection of perinatal hypoxia using time-frequency-based heart rate variability features. Med Biol Eng Comput 2013; 52:183-91. [PMID: 24272142 DOI: 10.1007/s11517-013-1129-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2013] [Accepted: 11/08/2013] [Indexed: 11/29/2022]
Abstract
Perinatal hypoxia is a cause of cerebral injury in foetuses and neonates. Detection of foetal hypoxia during labour based on the pattern recognition of heart rate signals suffers from high observer variability and low specificity. We describe a new automated hypoxia detection method using time-frequency analysis of heart rate variability (HRV) signals. This approach uses features extracted from the instantaneous frequency and instantaneous amplitude of HRV signal components as well as features based on matrix decomposition of the signals' time-frequency distributions using singular value decomposition and non-negative matrix factorization. The classification between hypoxia and non-hypoxia data is performed using a support vector machine classifier. The proposed method is tested on a dataset obtained from a newborn piglet model with a controlled hypoxic insult. The chosen HRV features show strong performance compared to conventional spectral features and other existing methods of hypoxia detection with a sensitivity 93.3 %, specificity 98.3 % and accuracy 95.8 %. The high predictive value of this approach to detecting hypoxia is a substantial step towards developing a more accurate and reliable hypoxia detection method for use in human foetal monitoring.
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Affiliation(s)
- Shiying Dong
- UQ Centre for Clinical Research, The University of Queensland, Herston, QLD, Australia,
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