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Kechagias KS, Triantafyllidis KK, Zouridaki G, Savvidou M. Obstetric and neonatal outcomes in pregnant women with idiopathic polyhydramnios: a systematic review and meta-analysis. Sci Rep 2024; 14:5296. [PMID: 38438422 PMCID: PMC10912321 DOI: 10.1038/s41598-024-54840-0] [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: 10/07/2023] [Accepted: 02/17/2024] [Indexed: 03/06/2024] Open
Abstract
Although the assessment of the amniotic fluid volume in pregnancy is part of the fetal wellbeing surveillance, the impact of idiopathic polyhydramnios (IP) on maternal and perinatal outcomes in unknown. The aim of this meta-analysis was to investigate the association of IP with different maternal and perinatal outcomes. We screened five electronic databases until December 2023 and performed data extraction and quality assessment using ROBINS-E in duplicates. Pooled risk ratios and 95% confidence intervals (95% CI) were calculated with a random effects model. 38 studies were included. Patients with IP were at increased risk of perinatal complications including preterm delivery (RR 1.96, 95% CI 1.35-2.86; I2 = 92%), placental abruption (RR 3.20, 95% CI 2.20-4.65; I2 = 2%), delivery via caesarean section (RR 1.60, 95% CI 1.39-1.84; I2 = 95%) and postpartum haemorrhage (RR 1.98, 95% CI 1.22-3.22; I2 = 84%). Similarly, IP was associated with increased risk of adverse perinatal outcomes including low APGAR score (RR 3.0, 95% CI 1.23-7.35; I2 = 95%), stillbirth (RR 4.75, 95% CI 2.54-8.86; I2 = 9%) and perinatal mortality (RR 4.75, 95% CI 2.67-8.48; I2 = 37%). This meta-analysis suggests that pregnant women with IP may be at increased risk of perinatal complications and adverse neonatal outcomes. However, data remains inconclusive considering the low quality and high heterogeneity of included studies.PROSPERO registration number: CRD42022359944.
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Affiliation(s)
- Konstantinos S Kechagias
- Department of Metabolism, Digestion and Reproduction & Department of Surgery and Cancer, Faculty of Medicine, IRDB, Imperial College London, Hammersmith Campus, Du Cane Road, 3rd Floor, London, W12 0NN, UK.
| | | | - Georgia Zouridaki
- Department of Metabolism, Digestion and Reproduction & Department of Surgery and Cancer, Faculty of Medicine, IRDB, Imperial College London, Hammersmith Campus, Du Cane Road, 3rd Floor, London, W12 0NN, UK
| | - Makrina Savvidou
- Department of Metabolism, Digestion and Reproduction & Department of Surgery and Cancer, Faculty of Medicine, IRDB, Imperial College London, Hammersmith Campus, Du Cane Road, 3rd Floor, London, W12 0NN, UK
- Fetal Medicine Unit, Department of Obstetrics and Gynaecology, Chelsea and Westminster Hospital, London, UK
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Costanzo A, Ertl-Wagner B, Sussman D. AFNet Algorithm for Automatic Amniotic Fluid Segmentation from Fetal MRI. Bioengineering (Basel) 2023; 10:783. [PMID: 37508809 PMCID: PMC10376488 DOI: 10.3390/bioengineering10070783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 06/25/2023] [Accepted: 06/27/2023] [Indexed: 07/30/2023] Open
Abstract
Amniotic Fluid Volume (AFV) is a crucial fetal biomarker when diagnosing specific fetal abnormalities. This study proposes a novel Convolutional Neural Network (CNN) model, AFNet, for segmenting amniotic fluid (AF) to facilitate clinical AFV evaluation. AFNet was trained and tested on a manually segmented and radiologist-validated AF dataset. AFNet outperforms ResUNet++ by using efficient feature mapping in the attention block and transposing convolutions in the decoder. Our experimental results show that AFNet achieved a mean Intersection over Union (mIoU) of 93.38% on our dataset, thereby outperforming other state-of-the-art models. While AFNet achieves performance scores similar to those of the UNet++ model, it does so while utilizing merely less than half the number of parameters. By creating a detailed AF dataset with an improved CNN architecture, we enable the quantification of AFV in clinical practice, which can aid in diagnosing AF disorders during gestation.
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Affiliation(s)
- Alejo Costanzo
- Department of Electrical, Computer and Biomedical Engineering, Faculty of Engineering and Architectural Sciences, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada
- Institute for Biomedical Engineering, Science and Technology (iBEST), Toronto Metropolitan University and St. Michael's Hospital, Toronto, ON M5B 1T8, Canada
| | - Birgit Ertl-Wagner
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
- Department of Medical Imaging, Faculty of Medicine, University of Toronto, Toronto, ON M5T 1W7, Canada
| | - Dafna Sussman
- Department of Electrical, Computer and Biomedical Engineering, Faculty of Engineering and Architectural Sciences, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada
- Institute for Biomedical Engineering, Science and Technology (iBEST), Toronto Metropolitan University and St. Michael's Hospital, Toronto, ON M5B 1T8, Canada
- Department of Obstetrics and Gynecology, Faculty of Medicine, University of Toronto, Toronto, ON M5G 1E2, Canada
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Long-term digestive hospitalizations of premature infants (besides necrotizing enterocolitis): is there a critical threshold? Arch Gynecol Obstet 2021; 304:455-463. [PMID: 33885970 DOI: 10.1007/s00404-021-06068-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 04/09/2021] [Indexed: 12/26/2022]
Abstract
BACKGROUND In this study we sought to ascertain a critical threshold of the degree of prematurity and long-term digestive morbidity of the offspring. METHODS A population-based cohort analysis was conducted, comparing long-term incidence of digestive morbidity in infants born preterm. Cases were divided into four groups according to the extremity of prematurity. Digestive morbidity included hospitalizations involving a predefined set of ICD9 codes. A Kaplan-Meier survival curve was constructed to compare cumulative incidence of digestive morbidity. A Cox proportional hazards model was used to control for confounders. RESULTS During the study period 220,563 patients met the inclusion criteria. Offspring born preterm had significantly more hospitalizations due to digestive morbidity compared to term offspring. The Kaplan-Meier survival curve demonstrated significant higher cumulative incidence of long-term digestive morbidity of the offspring with decreasing gestational age (Log rank p < 0.001). The risk was highest at 28 weeks gestation. Using a Cox proportional hazards model, being born at very and moderate to late preterm birth was independently associated with long-term digestive morbidity. CONCLUSION Preterm delivery is an independent risk factor for long-term digestive morbidity of the offspring. In our population, 28 weeks gestation is the critical cut-off for pronounced digestive morbidity.
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Adam MJ, Enderle I, Le Bouar G, Cabaret-Dufour AS, Tardif C, Contin L, Arnaud A, Proisy M, Jaillard S, Pasquier L, Le Lous M. Performance of diagnostic ultrasound to identify causes of hydramnios. Prenat Diagn 2020; 41:111-122. [PMID: 32920845 DOI: 10.1002/pd.5825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 09/01/2020] [Accepted: 09/01/2020] [Indexed: 11/06/2022]
Abstract
INTRODUCTION We aimed to assess the diagnostic yield of ultrasonography in the identification of the etiology of hydramnios, and the added value of MRI or amniocentesis. METHODS We conducted a single-center retrospective study including pregnancies with confirmed hydramnios (defined as deepest pocket ≥8 cm) between January 2013 and May 2017. Twin pregnancies, secondary hydramnios discovered after the diagnosis of a causal pathology, and pregnancies of unknown outcome were excluded. All pregnancies underwent a targeted scan, and selected cases underwent MRI or amniocentesis. RESULTS A total of 158 patients with confirmed hydramnios were included. Hydramnios was associated with a fetal pathology in 37 cases (23.4%), with diabetes in 39 (24.6%), isolated macrosomia in 16 (10.1%), and considered idiopathic in 66 (41.7%). Ultrasonography established a diagnosis of the underlying pathology in 73% of cases. Amniocentesis was done in 31 cases (20%) and it allowed diagnosis of chromosome anomalies, esophageal atresia, myotonic dystrophy congenital type, Prader-Willi syndrome, and Bartter syndrome. MRI was done in 15 cases (10%) and it allowed one additional diagnosis of esophageal atresia. The diagnostic yields of MRI and amniocentesis were 91.7% and 95.2%, respectively. There were five false positive diagnoses at ultrasonography, and one false positive diagnosis at MRI. CONCLUSION Hydramnios can be associated with a wide variety of underlying pathologies. Diagnostic ultrasound can attain a diagnosis in the majority of cases. Amniocentesis offers a valuable complementary assessment.
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Affiliation(s)
- Marie-José Adam
- Department of Obstetrics and Gynecology, University Hospital of Rennes, Rennes, France
| | - Isabelle Enderle
- Department of Obstetrics and Gynecology, University Hospital of Rennes, Rennes, France.,CIC Inserm 1414, University Hospital of Rennes, University of Rennes, Rennes, France
| | - Gwenaëlle Le Bouar
- Department of Obstetrics and Gynecology, University Hospital of Rennes, Rennes, France
| | | | - Cécile Tardif
- Department of Obstetrics and Gynecology, University Hospital of Rennes, Rennes, France
| | - Laurence Contin
- Department of Obstetrics and Gynecology, University Hospital of Rennes, Rennes, France
| | - Alexis Arnaud
- Department of Pediatric Surgery, University Hospital of Rennes, Rennes, France
| | - Maïa Proisy
- Department of Radiology, University Hospital of Rennes, Rennes, France
| | - Sylvie Jaillard
- Department of Cytogenetics, University Hospital of Rennes, Rennes, France
| | - Laurent Pasquier
- Department of Genetics, University Hospital of Rennes, Rennes, France
| | - Maela Le Lous
- Department of Obstetrics and Gynecology, University Hospital of Rennes, Rennes, France.,CIC Inserm 1414, University Hospital of Rennes, University of Rennes, Rennes, France
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