Objective: To summarize the current evidence and to make recommendations for antenatal fetal health surveillance (FHS) to detect perinatal risk factors and potential fetal decompensation in the antenatal period and to allow for timely intervention to prevent perinatal morbidity and/or mortality.
Target Population: Pregnant individuals with or without maternal, fetal, or pregnancy-associated perinatal risk factors for antenatal fetal decompensation.
Options: To use basic and/or advanced antenatal testing modalities, based on risk factors for potential fetal decompensation.
Outcomes: Early identification of potential fetal decompensation allows for interventions that may support fetal adaptation to maintain well-being or expedite delivery.
Benefits, Harms, And Costs: Antenatal FHS in pregnant individuals with identified perinatal risk factors may reduce the chance of adverse outcomes. Given the high false-positive rate, FHS may increase unnecessary interventions, which may result in harm, including parental anxiety, premature or operative birth, and increased use of health care resources. Optimization of surveillance protocols based on evidence-informed practice may improve perinatal outcomes and reduce harm.
Evidence: Medline, PubMed, Embase, and the Cochrane Library were searched from inception to January 2022, using medical subject headings (MeSH) and key words related to pregnancy, fetal monitoring, fetal movement, stillbirth, pregnancy complications, and fetal sonography. This document represents an abstraction of the evidence rather than a methodological review.
Validation Methods: The authors rated the quality of evidence and strength of recommendations using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. See online Appendix A (Tables A1 for definitions and A2 for interpretations of strong and weak recommendations).
Intended Audience: All health care team members who provide care for or education to obstetrical patients, including maternal fetal medicine specialists, obstetricians, family physicians, midwives, nurses, nurse practitioners, and radiologists.
Summary Statements: RECOMMENDATIONS.
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http://dx.doi.org/10.1016/j.jogc.2023.05.020 | DOI Listing |
Front Biosci (Landmark Ed)
January 2025
School of Cardiovascular and Metabolic Medicine & Sciences, British Heart Foundation Centre of Research Excellence, King's College London, SE5 9NU London, UK.
Cardiovascular disease (CVD) is the most prevalent cause of mortality and morbidity in the Western world. A common underlying hallmark of CVD is the plaque-associated arterial thickening, termed atherosclerosis. Although the molecular mechanisms underlying the aetiology of atherosclerosis remain unknown, it is clear that both its development and progression are associated with significant changes in the pattern of DNA methylation within the vascular cell wall.
View Article and Find Full Text PDFEur Stroke J
January 2025
Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Background: We aimed to assess impairments on health-related quality of life, and mental health resulting from Retinal artery occlusion (RAO) with monocular visual field loss and posterior circulation ischemic stroke (PCIS) with full or partial hemianopia using patient-reported outcome measures (PROMs).
Methods: In a prospective study, consecutive patients with acute RAO on fundoscopy and PCIS on imaging were recruited during their surveillance on a stroke unit over a period of 15 months. Baseline characteristics were determined from medical records and interviews.
Br J Hosp Med (Lond)
January 2025
Department of Nephrology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
The Geriatric Nutritional Risk Index (GNRI) is an effective tool for identifying malnutrition, and helps monitor the prognosis of patients undergoing maintenance hemodialysis. However, the association between the GNRI and cardiovascular or all-cause mortality in hemodialysis patients remains unclear. Therefore, this study investigated the correlation of the GNRI with all-cause and cardiovascular mortality in patients undergoing maintenance hemodialysis.
View Article and Find Full Text PDFBr J Hosp Med (Lond)
January 2025
Department of Surgery & Cancer, Imperial College London, London, UK.
Predictive algorithms have myriad potential clinical decision-making implications from prognostic counselling to improving clinical trial efficiency. Large observational (or "real world") cohorts are a common data source for the development and evaluation of such tools. There is significant optimism regarding the benefits and use cases for risk-based care, but there is a notable disparity between the volume of clinical prediction models published and implementation into healthcare systems that drive and realise patient benefit.
View Article and Find Full Text PDFBr J Hosp Med (Lond)
January 2025
Speech and Language Rehabilitation Department, Beijing Rehabilitation Hospital Affiliated with Capital Medical University, Beijing, China.
The background for establishing and verifying a dehydration prediction model for elderly patients with post-stroke dysphagia (PSD) based on General Utility for Latent Process (GULP) is as follows: For elderly patients with PSD, GULP technology is utilized to build a dehydration prediction model. This aims to improve the accuracy of dehydration risk assessment and provide clinical intervention, thereby offering a scientific basis and enhancing patient prognosis. This research highlights the innovative application of GULP technology in constructing complex medical prediction models and addresses the special health needs of elderly stroke patients.
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