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Construction of a comprehensive fetal monitoring database for the study of perinatal hypoxic ischemic encephalopathy.
Kearney, Robert E; Wu, Yvonne W; Vargas-Calixto, Johann; Kuzniewicz, Michael W; Cornet, Marie-Coralie; Forquer, Heather; Gerstley, Lawrence; Hamilton, Emily; Warrick, Philip A.
Afiliação
  • Kearney RE; Department of Biomedical Engineering, Faculty of Medicine, McGill University, 3775 University Street, Montreal, Quebec, H3A 2B4, Canada.
  • Wu YW; Departments of Neurology and Pediatrics, University of California, San Francisco, 675 Nelson Rising Lane, Ste 411, San Francisco, CA 94158, USA.
  • Vargas-Calixto J; Department of Biomedical Engineering, Faculty of Medicine, McGill University, 3775 University Street, Montreal, Quebec, H3A 2B4, Canada.
  • Kuzniewicz MW; Department of Pediatrics and Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612, USA.
  • Cornet MC; Department of Pediatrics, Benioff Children's Hospital, University of California San Francisco, 550 16th St, Floor 5, San Francisco, CA 94143, USA.
  • Forquer H; Department of Pediatrics and Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612, USA.
  • Gerstley L; Kaiser Permanente, Division of Research, 2000 Broadway, Oakland, CA 94612, USA.
  • Hamilton E; PeriGen Inc.100 Regency Forest Drive, Suite 200 Cary, North Carolina 27518, USA.
  • Warrick PA; PeriGen Inc.100 Regency Forest Drive, Suite 200 Cary, North Carolina 27518, USA.
MethodsX ; 12: 102664, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38524309
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: MethodsX Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Canadá

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: MethodsX Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Canadá