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Kearney RE, Wu YW, Vargas-Calixto J, Kuzniewicz MW, Cornet MC, Forquer H, Gerstley L, Hamilton E, Warrick PA. Construction of a comprehensive fetal monitoring database for the study of perinatal hypoxic ischemic encephalopathy. MethodsX 2024; 12:102664. [PMID: 38524309 PMCID: PMC10957432 DOI: 10.1016/j.mex.2024.102664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 03/11/2024] [Indexed: 03/26/2024] Open
Abstract
This article describes the methods used to build a large-scale database of more than 250,000 electronic fetal monitoring (EFM) records linked to a comprehensive set of clinical information about the infant, the mother, the pregnancy, labor, and outcome. The database can be used to investigate how birth outcome is related to clinical and EFM features. The main steps involved in building the database were: (1) Acquiring the raw EFM recording and clinical records for each birth. (2) Assigning each birth to an objectively defined outcome class that included normal, acidosis, and hypoxic-ischemic encephalopathy. (3) Removing all personal health information from the EFM recordings and clinical records. (4) Preprocessing the deidentified EFM records to eliminate duplicates, reformat the signals, combine signals from different sensors, and bridge gaps to generate signals in a format that can be readily analyzed. (5) Post-processing the repaired EFM recordings to extract key features of the fetal heart rate, uterine activity, and their relations. (6) Populating a database that links the clinical information, EFM records, and EFM features to support easy querying and retrieval. •A multi-step process is required to build a comprehensive database linking electronic temporal fetal monitoring signals to a comprehensive set of clinical information about the infant, the mother, the pregnancy, labor, and outcome.•The current database documents more than 250,000 births including almost 4,000 acidosis and 400 HIE cases. This represents more than 80% of the births that occurred in 15 Northern California Kaiser Permanente Hospitals between 2011-2019. This is a valuable resource for studying the factors predictive of outcome.•The signal processing code and schemas for the database are freely available. The database will not be permitted to leave Kaiser firewalls, but a process is in place to allow interested investigators to access it.
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Affiliation(s)
- Robert E Kearney
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, 3775 University Street, Montreal, Quebec, H3A 2B4, Canada
| | - Yvonne W. Wu
- Departments of Neurology and Pediatrics, University of California, San Francisco, 675 Nelson Rising Lane, Ste 411, San Francisco, CA 94158, USA
| | - Johann Vargas-Calixto
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, 3775 University Street, Montreal, Quebec, H3A 2B4, Canada
| | - Michael W. Kuzniewicz
- Department of Pediatrics and Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612, USA
| | - Marie-Coralie Cornet
- Department of Pediatrics, Benioff Children's Hospital, University of California San Francisco, 550 16th St, Floor 5, San Francisco, CA 94143, USA
| | - Heather Forquer
- Department of Pediatrics and Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612, USA
| | - Lawrence Gerstley
- Kaiser Permanente, Division of Research, 2000 Broadway, Oakland, CA 94612, USA
| | - Emily Hamilton
- PeriGen Inc.100 Regency Forest Drive, Suite 200 Cary, North Carolina 27518, USA
| | - Philip A. Warrick
- PeriGen Inc.100 Regency Forest Drive, Suite 200 Cary, North Carolina 27518, USA
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2
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Steyde G, Spairani E, Magenes G, Signorini MG. Fetal heart rate spectral analysis in raw signals and PRSA-derived curve: normal and pathological fetuses discrimination. Med Biol Eng Comput 2024; 62:437-447. [PMID: 37889432 PMCID: PMC10794317 DOI: 10.1007/s11517-023-02953-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 10/16/2023] [Indexed: 10/28/2023]
Abstract
Cardiotocography (CTG) is the most common technique for electronic fetal monitoring and consists of the simultaneous recording of fetal heart rate (FHR) and uterine contractions. In analogy with the adult case, spectral analysis of the FHR signal can be used to assess the functionality of the autonomic nervous system. To do so, several methods can be employed, each of which has its strengths and limitations. This paper aims at performing a methodological investigation on FHR spectral analysis adopting 4 different spectrum estimators and a novel PRSA-based spectral method. The performances have been evaluated in terms of the ability of the various methods to detect changes in the FHR in two common pregnancy complications: intrauterine growth restriction (IUGR) and gestational diabetes. A balanced dataset containing 2178 recordings distributed between the 32nd and 38th week of gestation was used. The results show that the spectral method derived from the PRSA better differentiates high-risk pregnancies vs. controls compared to the others. Specifically, it more robustly detects an increase in power percentage within the movement frequency band and a decrease in high frequency between pregnancies at high risk in comparison to those at low risk.
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Affiliation(s)
- Giulio Steyde
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy.
| | - Edoardo Spairani
- Electrical, Computer and Biomedical Engineering Department, Università di Pavia, 27100, Pavia, Italy
| | - Giovanni Magenes
- Electrical, Computer and Biomedical Engineering Department, Università di Pavia, 27100, Pavia, Italy
| | - Maria G Signorini
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy
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3
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Hussain NM, O'Halloran M, McDermott B, Elahi MA. Fetal monitoring technologies for the detection of intrapartum hypoxia - challenges and opportunities. Biomed Phys Eng Express 2024; 10:022002. [PMID: 38118183 DOI: 10.1088/2057-1976/ad17a6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 12/20/2023] [Indexed: 12/22/2023]
Abstract
Intrapartum fetal hypoxia is related to long-term morbidity and mortality of the fetus and the mother. Fetal surveillance is extremely important to minimize the adverse outcomes arising from fetal hypoxia during labour. Several methods have been used in current clinical practice to monitor fetal well-being. For instance, biophysical technologies including cardiotocography, ST-analysis adjunct to cardiotocography, and Doppler ultrasound are used for intrapartum fetal monitoring. However, these technologies result in a high false-positive rate and increased obstetric interventions during labour. Alternatively, biochemical-based technologies including fetal scalp blood sampling and fetal pulse oximetry are used to identify metabolic acidosis and oxygen deprivation resulting from fetal hypoxia. These technologies neither improve clinical outcomes nor reduce unnecessary interventions during labour. Also, there is a need to link the physiological changes during fetal hypoxia to fetal monitoring technologies. The objective of this article is to assess the clinical background of fetal hypoxia and to review existing monitoring technologies for the detection and monitoring of fetal hypoxia. A comprehensive review has been made to predict fetal hypoxia using computational and machine-learning algorithms. The detection of more specific biomarkers or new sensing technologies is also reviewed which may help in the enhancement of the reliability of continuous fetal monitoring and may result in the accurate detection of intrapartum fetal hypoxia.
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Affiliation(s)
- Nadia Muhammad Hussain
- Discipline of Electrical & Electronic Engineering, University of Galway, Ireland
- Translational Medical Device Lab, Lambe Institute for Translational Research, University Hospital Galway, Ireland
| | - Martin O'Halloran
- Discipline of Electrical & Electronic Engineering, University of Galway, Ireland
- Translational Medical Device Lab, Lambe Institute for Translational Research, University Hospital Galway, Ireland
| | - Barry McDermott
- Translational Medical Device Lab, Lambe Institute for Translational Research, University Hospital Galway, Ireland
- College of Medicine, Nursing & Health Sciences, University of Galway, Ireland
| | - Muhammad Adnan Elahi
- Discipline of Electrical & Electronic Engineering, University of Galway, Ireland
- Translational Medical Device Lab, Lambe Institute for Translational Research, University Hospital Galway, Ireland
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4
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Vargas-Calixto J, Wu Y, Kuzniewicz M, Cornet MC, Forquer H, Gerstley L, Hamilton E, Warrick PA, Kearney RE. Timely Detection of Infants at Risk of Intrapartum Acidosis and Hypoxic-Ischemic Encephalopathy Using Cardiotocography . ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-5. [PMID: 38083649 DOI: 10.1109/embc40787.2023.10340095] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
This work aims to improve the intrapartum detection of fetuses with an increased risk of developing fetal acidosis or hypoxic-ischemic encephalopathy (HIE) using fetal heart rate (FHR) and uterine pressure (UP) signals. Our study population comprised 40,831 term births divided into 3 classes based on umbilical cord or early neonatal blood gas assessments: 374 with verified HIE, 3,047 with acidosis but no encephalopathy and 37,410 healthy babies with normal gases. We developed an intervention recommendation system based on a random forest classifier. The classifier was trained using classical and novel features extracted electronically from 20-minute epochs of FHR and UP. Then, using the predictions of the classifier on each epoch, we designed a decision rule to determine when to recommended intervention. Compared to the Caesarean rates in each study group, our system identified an additional 5.68% of babies who developed HIE (54.55% vs 60.23%, p < 0.01) with a specific alert threshold. Importantly, about 75% of these recommendations were made more than 200 minutes before birth. In the acidosis group, the system identified an additional 17.44% (37.15% vs 54.59%, p < 0.01) and about 2/3 of these recommendations were made more than 200 minutes before birth. Compared to the Caesarean rate in the healthy group, the associated false positive rate was increased by 1.07% (38.80% vs 39.87%, p<0.01).Clinical Relevance- This method recommended intervention in more babies affected by acidosis or HIE, than the intervention rate observed in practice and most often did so 200 minutes before delivery. This was early enough to expect that interventions would have clinical benefit and reduce the rate of HIE. Given the high burden associated with HIE, this would justify the marginal increase in the normal Cesarean rate.
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Chen T, Feng G, Heiselman C, Quirk JG, Djurić PM. IMPROVING PHASE-RECTIFIED SIGNAL AVERAGING FOR FETAL HEART RATE ANALYSIS. PROCEEDINGS OF THE ... IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING. ICASSP (CONFERENCE) 2022; 2022. [PMID: 36035505 PMCID: PMC9415860 DOI: 10.1109/icassp43922.2022.9747860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Low umbilical artery pH is a marker for neonatal acidosis and is associated with an increased risk for neonatal complications. The phase-rectified signal averaging (PRSA) features have demonstrated superior discriminatory or diagnostic ability and good interpretability in many biomedical applications including fetal heart rate analysis. However, the performance of PRSA method is sensitive to values of the selected parameters which are usually either chosen based on a grid search or empirically in the literature. In this paper, we examine PRSA method through the lens of dynamical systems theory and reveal the intrinsic connection between state space reconstruction and PRSA. From this perspective, we then introduce a new feature that can better characterize dynamical systems comparing with PRSA. Our experimental results on an open-access intrapartum Cardiotocography database demonstrate that the proposed feature outperforms state-of-the-art PRSA features in pH-based fetal heart rate analysis.
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Affiliation(s)
- Tong Chen
- Department of Electrical and Computer Engineering, Stony Brook University
| | - Guanchao Feng
- Department of Electrical and Computer Engineering, Stony Brook University
| | - Cassandra Heiselman
- Department of Obstetrics/Gynecology, Renaissance School of Medicine, Stony Brook University
| | - J Gerald Quirk
- Department of Obstetrics/Gynecology, Renaissance School of Medicine, Stony Brook University
| | - Petar M Djurić
- Department of Electrical and Computer Engineering, Stony Brook University
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Luongo G, Rees F, Nairn D, Rivolta MW, Dössel O, Sassi R, Ahlgrim C, Mayer L, Neumann FJ, Arentz T, Jadidi A, Loewe A, Müller-Edenborn B. Machine Learning Using a Single-Lead ECG to Identify Patients With Atrial Fibrillation-Induced Heart Failure. Front Cardiovasc Med 2022; 9:812719. [PMID: 35295255 PMCID: PMC8918925 DOI: 10.3389/fcvm.2022.812719] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 02/07/2022] [Indexed: 11/13/2022] Open
Abstract
Aims Atrial fibrillation (AF) and heart failure often co-exist. Early identification of AF patients at risk for AF-induced heart failure (AF-HF) is desirable to reduce both morbidity and mortality as well as health care costs. We aimed to leverage the characteristics of beat-to-beat-patterns in AF to prospectively discriminate AF patients with and without AF-HF. Methods A dataset of 10,234 5-min length RR-interval time series derived from 26 AF-HF patients and 26 control patients was extracted from single-lead Holter-ECGs. A total of 14 features were extracted, and the most informative features were selected. Then, a decision tree classifier with 5-fold cross-validation was trained, validated, and tested on the dataset randomly split. The derived algorithm was then tested on 2,261 5-min segments from six AF-HF and six control patients and validated for various time segments. Results The algorithm based on the spectral entropy of the RR-intervals, the mean value of the relative RR-interval, and the root mean square of successive differences of the relative RR-interval yielded an accuracy of 73.5%, specificity of 91.4%, sensitivity of 64.7%, and PPV of 87.0% to correctly stratify segments to AF-HF. Considering the majority vote of the segments of each patient, 10/12 patients (83.33%) were correctly classified. Conclusion Beat-to-beat-analysis using a machine learning classifier identifies patients with AF-induced heart failure with clinically relevant diagnostic properties. Application of this algorithm in routine care may improve early identification of patients at risk for AF-induced cardiomyopathy and improve the yield of targeted clinical follow-up.
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Affiliation(s)
- Giorgio Luongo
- Institute of Biomedical Engineering (IBT), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
- *Correspondence: Giorgio Luongo
| | - Felix Rees
- Division of Cardiology and Angiology II, University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany
| | - Deborah Nairn
- Institute of Biomedical Engineering (IBT), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Massimo W. Rivolta
- Dipartimento di Informatica, Università degli Studi di Milano, Milan, Italy
| | - Olaf Dössel
- Institute of Biomedical Engineering (IBT), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Roberto Sassi
- Dipartimento di Informatica, Università degli Studi di Milano, Milan, Italy
| | - Christoph Ahlgrim
- Division of Cardiology and Angiology II, University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany
| | - Louisa Mayer
- Division of Cardiology and Angiology II, University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany
| | - Franz-Josef Neumann
- Division of Cardiology and Angiology II, University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany
| | - Thomas Arentz
- Division of Cardiology and Angiology II, University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany
| | - Amir Jadidi
- Division of Cardiology and Angiology II, University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany
| | - Axel Loewe
- Institute of Biomedical Engineering (IBT), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Björn Müller-Edenborn
- Division of Cardiology and Angiology II, University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany
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López-Justo C, Pliego-Carrillo AC, Ledesma-Ramírez CI, Mendieta-Zerón H, Peña-Castillo MÁ, Echeverría JC, Rodríguez-Arce J, Reyes-Lagos JJ. Differences in the Asymmetry of Beat-to-Beat Fetal Heart Rate Accelerations and Decelerations at Preterm and Term Active Labor. SENSORS 2021; 21:s21248249. [PMID: 34960343 PMCID: PMC8704786 DOI: 10.3390/s21248249] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 11/30/2021] [Accepted: 12/06/2021] [Indexed: 11/29/2022]
Abstract
The fetal autonomic nervous system responds to uterine contractions during active labor as identified by changes in the accelerations and decelerations of fetal heart rate (FHR). Thus, this exploratory study aimed to characterize the asymmetry differences of beat-to-beat FHR accelerations and decelerations in preterm and term fetuses during active labor. In an observational study, we analyzed 10 min of fetal R-R series collected from women during active preterm labor (32–36 weeks of pregnancy, n = 17) and active term labor (38–40 weeks of pregnancy, n = 27). These data were used to calculate the Deceleration Reserve (DR), which is a novel parameter that quantifies the asymmetry of the average acceleration and deceleration capacity of the heart. In addition, relevant multiscale asymmetric indices of FHR were also computed. Lower values of DR, calculated with the input parameters of T = 50 and s = 10, were associated with labor occurring at the preterm condition (p = 0.0131). Multiscale asymmetry indices also confirmed significant (p < 0.05) differences in the asymmetry of FHR. Fetuses during moderate premature labor may experience more decaying R-R trends and a lower magnitude of decelerations compared to term fetuses. These differences of FHR dynamics might be related to the immaturity of the fetal cardiac autonomic nervous system as identified by this system response to the intense uterine activity at active labor.
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Affiliation(s)
- Carolina López-Justo
- Facultad de Medicina (School of Medicine), Universidad Autónoma del Estado de México (Autonomous University of Mexico State), Toluca de Lerdo 50180, Mexico; (C.L.-J.); (A.C.P.-C.); (C.I.L.-R.); (H.M.-Z.)
| | - Adriana Cristina Pliego-Carrillo
- Facultad de Medicina (School of Medicine), Universidad Autónoma del Estado de México (Autonomous University of Mexico State), Toluca de Lerdo 50180, Mexico; (C.L.-J.); (A.C.P.-C.); (C.I.L.-R.); (H.M.-Z.)
| | - Claudia Ivette Ledesma-Ramírez
- Facultad de Medicina (School of Medicine), Universidad Autónoma del Estado de México (Autonomous University of Mexico State), Toluca de Lerdo 50180, Mexico; (C.L.-J.); (A.C.P.-C.); (C.I.L.-R.); (H.M.-Z.)
| | - Hugo Mendieta-Zerón
- Facultad de Medicina (School of Medicine), Universidad Autónoma del Estado de México (Autonomous University of Mexico State), Toluca de Lerdo 50180, Mexico; (C.L.-J.); (A.C.P.-C.); (C.I.L.-R.); (H.M.-Z.)
- Hospital Materno Perinatal Mónica Pretelini Sáenz, Instituto de Salud del Estado de México (Health Institute of Mexico State), Toluca de Lerdo 50010, Mexico
| | - Miguel Ángel Peña-Castillo
- División de Ciencias Básicas e Ingeniería (Basic Science and Engineering Division), Universidad Autónoma Metropolitana Unidad Iztapalapa (Metropolitan Autonomous University Campus Iztapalapa), Iztapalapa 09340, Mexico; (M.Á.P.-C.); (J.C.E.)
| | - Juan Carlos Echeverría
- División de Ciencias Básicas e Ingeniería (Basic Science and Engineering Division), Universidad Autónoma Metropolitana Unidad Iztapalapa (Metropolitan Autonomous University Campus Iztapalapa), Iztapalapa 09340, Mexico; (M.Á.P.-C.); (J.C.E.)
| | - Jorge Rodríguez-Arce
- Facultad de Ingeniería (School of Engineering), Universidad Autónoma del Estado de México (Autonomous University of Mexico State), Toluca de Lerdo 50100, Mexico;
| | - José Javier Reyes-Lagos
- Facultad de Medicina (School of Medicine), Universidad Autónoma del Estado de México (Autonomous University of Mexico State), Toluca de Lerdo 50180, Mexico; (C.L.-J.); (A.C.P.-C.); (C.I.L.-R.); (H.M.-Z.)
- Correspondence:
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8
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Rivolta MW, Barbieri M, Stampalija T, Sassi R, Frasch MG. Relationship Between Deceleration Morphology and Phase Rectified Signal Averaging-Based Parameters During Labor. Front Med (Lausanne) 2021; 8:626450. [PMID: 34901040 PMCID: PMC8655232 DOI: 10.3389/fmed.2021.626450] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 10/31/2021] [Indexed: 01/03/2023] Open
Abstract
During labor, uterine contractions trigger the response of the autonomic nervous system (ANS) of the fetus, producing sawtooth-like decelerations in the fetal heart rate (FHR) series. Under chronic hypoxia, ANS is known to regulate FHR differently with respect to healthy fetuses. In this study, we hypothesized that such different ANS regulation might also lead to a change in the FHR deceleration morphology. The hypothesis was tested in an animal model comprising nine normoxic and five chronically hypoxic fetuses that underwent a protocol of umbilical cord occlusions (UCOs). Deceleration morphologies in the fetal inter-beat time interval (FRR) series were modeled using a trapezoid with four parameters, i.e., baseline b, deceleration depth a, UCO response time τ u and recovery time τ r . Comparing normoxic and hypoxic sheep, we found a clear difference for τ u (24.8±9.4 vs. 39.8±9.7 s; p < 0.05), a (268.1±109.5 vs. 373.0±46.0 ms; p < 0.1) and Δτ = τ u - τ r (13.2±6.9 vs. 23.9±7.5 s; p < 0.05). Therefore, the animal model supported the hypothesis that hypoxic fetuses have a longer response time τ u and larger asymmetry Δτ as a response to UCOs. Assessing these morphological parameters during labor is challenging due to non-stationarity, phase desynchronization and noise. For this reason, in the second part of the study, we quantified whether acceleration capacity (AC), deceleration capacity (DC), and deceleration reserve (DR), computed through Phase-Rectified Signal Averaging (PRSA, known to be robust to noise), were correlated with the morphological parameters. DC, AC and DR were correlated with τ u , τ r and Δτ for a wide range of the PRSA parameter T (Pearson's correlation ρ > 0.8, p < 0.05). In conclusion, deceleration morphologies have been found to differ between normoxic and hypoxic sheep fetuses during UCOs. The same difference can be assessed through PRSA based parameters, further motivating future investigations on the translational potential of this methodology on human data.
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Affiliation(s)
- Massimo W. Rivolta
- Dipartimento di Informatica, Università degli Studi di Milano, Milan, Italy
| | - Moira Barbieri
- Unit of Fetal Medicine and Prenatal Diagnosis, Institute for Maternal and Child Health IRCCS Burlo Garofolo, Trieste, Italy
| | - Tamara Stampalija
- Unit of Fetal Medicine and Prenatal Diagnosis, Institute for Maternal and Child Health IRCCS Burlo Garofolo, Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Roberto Sassi
- Dipartimento di Informatica, Università degli Studi di Milano, Milan, Italy
| | - Martin G. Frasch
- Department of Obstetrics and Gynecology and Center on Human Development and Disability (CHDD), School of Medicine, University of Washington, Seattle, WA, United States
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9
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Vargas-Calixto J, Wu Y, Kuzniewicz M, Cornet MC, Forquer H, Gerstley L, Hamilton E, Warrick P, Kearney R. Temporal Evolution of Intrapartum Fetal Heart Rate Features. COMPUTING IN CARDIOLOGY 2021; 48:10.23919/cinc53138.2021.9662865. [PMID: 38013902 PMCID: PMC10681033 DOI: 10.23919/cinc53138.2021.9662865] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Our research goal is to improve the intrapartum identification of tracings associated with severe acidosis at birth and subsequent hypoxic-ischemic encephalopathy so that timely interventions could avoid such complications without causing excessive unnecessary interventions in births with normal outcomes. The present study examines the evolution of fetal heart rate (FHR) features over the course of labor. We analyzed FHR signals collected in the last 6 hours before delivery in 21,853 births with normal neonatal outcomes and in 163 that developed hypoxic-ischemic encephalopathy (HIE) from 15 hospitals of Kaiser Permanente Northern California. We divided these six hours into 18 nonoverlapping 20-minute epochs. The power spectral density of each epoch was divided into three bands: low frequency (LF, 30-150 mHz), movement frequency (MF, 150-500 mHz), and high frequency (HF, 500-1000 mHz). We also estimated the LF/(MF+HF) ratio, the mean and standard deviation of the FHR signal, the approximate entropy (ApEn), and the deceleration capacity (DC). In our results, ApEn, the standard deviation, and DC showed a promising ability to detect risk of HIE as early as 120 minutes before birth, which gives enough leading time for timely interventions.
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Affiliation(s)
| | - Yvonne Wu
- University of California, San Francisco, USA
| | | | | | | | | | - Emily Hamilton
- McGill University, Montreal, Canada
- PeriGen Inc., Montreal, Canada
| | - Philip Warrick
- McGill University, Montreal, Canada
- PeriGen Inc., Montreal, Canada
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10
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Roux SG, Garnier NB, Abry P, Gold N, Frasch MG. Distance to Healthy Metabolic and Cardiovascular Dynamics From Fetal Heart Rate Scale-Dependent Features in Pregnant Sheep Model of Human Labor Predicts the Evolution of Acidemia and Cardiovascular Decompensation. Front Pediatr 2021; 9:660476. [PMID: 34414140 PMCID: PMC8369259 DOI: 10.3389/fped.2021.660476] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Accepted: 06/21/2021] [Indexed: 01/27/2023] Open
Abstract
The overarching goal of the present work is to contribute to the understanding of the relations between fetal heart rate (FHR) temporal dynamics and the well-being of the fetus, notably in terms of predicting the evolution of lactate, pH and cardiovascular decompensation (CVD). It makes uses of an established animal model of human labor, where 14 near-term ovine fetuses subjected to umbilical cord occlusions (UCO) were instrumented to permit regular intermittent measurements of metabolites lactate and base excess, pH, and continuous recording of electrocardiogram (ECG) and systemic arterial blood pressure (to identify CVD) during UCO. ECG-derived FHR was digitized at the sampling rate of 1,000 Hz and resampled to 4 Hz, as used in clinical routine. We focused on four FHR variability features which are tunable to temporal scales of FHR dynamics, robustly computable from FHR sampled at 4 Hz and within short-time sliding windows, hence permitting a time-dependent, or local, analysis of FHR which helps dealing with signal noise. Results show the sensitivity of the proposed features for early detection of CVD, correlation to metabolites and pH, useful for early acidosis detection and the importance of coarse time scales (2.5-8 s) which are not disturbed by the low FHR sampling rate. Further, we introduce the performance of an individualized self-referencing metric of the distance to healthy state, based on a combination of the four features. We demonstrate that this novel metric, applied to clinically available FHR temporal dynamics alone, accurately predicts the time occurrence of CVD which heralds a clinically significant degradation of the fetal health reserve to tolerate the trial of labor.
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Affiliation(s)
- Stephane G. Roux
- Laboratoire de Physique, Université Lyon, Ens de Lyon, Université Claude Bernard, CNRS, Lyon, France
| | - Nicolas B. Garnier
- Laboratoire de Physique, Université Lyon, Ens de Lyon, Université Claude Bernard, CNRS, Lyon, France
| | - Patrice Abry
- Laboratoire de Physique, Université Lyon, Ens de Lyon, Université Claude Bernard, CNRS, Lyon, France
| | - Nathan Gold
- Department of Mathematics and Statistics, York University, Toronto, ON, Canada
- Centre for Quantitative Analysis and Modelling, Fields Institute, Toronto, ON, Canada
| | - Martin G. Frasch
- Department of OBGYN, Center on Human Development and Disability, University of Washington, Seattle, WA, United States
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Pini N, Lucchini M, Esposito G, Tagliaferri S, Campanile M, Magenes G, Signorini MG. A Machine Learning Approach to Monitor the Emergence of Late Intrauterine Growth Restriction. Front Artif Intell 2021; 4:622616. [PMID: 33889841 PMCID: PMC8057109 DOI: 10.3389/frai.2021.622616] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 01/18/2021] [Indexed: 01/18/2023] Open
Abstract
Late intrauterine growth restriction (IUGR) is a fetal pathological condition characterized by chronic hypoxia secondary to placental insufficiency, resulting in an abnormal rate of fetal growth. This pathology has been associated with increased fetal and neonatal morbidity and mortality. In standard clinical practice, late IUGR diagnosis can only be suspected in the third trimester and ultimately confirmed at birth. This study presents a radial basis function support vector machine (RBF-SVM) classification based on quantitative features extracted from fetal heart rate (FHR) signals acquired using routine cardiotocography (CTG) in a population of 160 healthy and 102 late IUGR fetuses. First, the individual performance of each time, frequency, and nonlinear feature was tested. To improve the unsatisfactory results of univariate analysis we firstly adopted a Recursive Feature Elimination approach to select the best subset of FHR-based parameters contributing to the discrimination of healthy vs. late IUGR fetuses. A fine tuning of the RBF-SVM model parameters resulted in a satisfactory classification performance in the training set (accuracy 0.93, sensitivity 0.93, specificity 0.84). Comparable results were obtained when applying the model on a totally independent testing set. This investigation supports the use of a multivariate approach for the in utero identification of late IUGR condition based on quantitative FHR features encompassing different domains. The proposed model allows describing the relationships among features beyond the traditional linear approaches, thus improving the classification performance. This framework has the potential to be proposed as a screening tool for the identification of late IUGR fetuses.
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Affiliation(s)
- Nicolò Pini
- Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, Italy.,Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
| | - Maristella Lucchini
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
| | - Giuseppina Esposito
- Department of Obstetrical Gynaecological and Urological Science, Federico II University, Napoli, Italy
| | - Salvatore Tagliaferri
- Department of Obstetrical Gynaecological and Urological Science, Federico II University, Napoli, Italy
| | - Marta Campanile
- Department of Obstetrical Gynaecological and Urological Science, Federico II University, Napoli, Italy
| | - Giovanni Magenes
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Maria G Signorini
- Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, Italy
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