Background: The available data regarding morbidity and mortality associated with multiple gestation births is conflicting and contradicting.

Objective: To compare morbidity, mortality, and length of stay (LOS) outcomes between multiple gestation (twin, triplet and higher-order) and singleton births.

Methods: Data from the national multicenter Kids' Inpatient Database of the Healthcare Cost and Utilization Project from the years 2000, 2003, 2006, 2009, 2012, and 2016 were analyzed using a complex survey design using Statistical Analysis System (SAS) 9.4 (SAS Institute, Cary NC). Neonates with ICD9 and ICD10 codes indicating singletons, twins or triplets, and higher-order multiples were included. Mortality was compared between these groups after excluding transfer outs to avoid duplicate inclusion. To analyze LOS, we included inborn neonates and excluded transfers; who died inpatient and any neonates who appear to have been discharged less than 33 weeks PMA. The LOS was compared by gestational age groups.

Results: A total of 22,853,125 neonates were analyzed for mortality after applying inclusion-exclusion criteria; 2.96% were twins, and 0.13% were triplets or more. A total of 22,690,082 neonates were analyzed for LOS. Mean GA, expressed as mean (SD), for singleton, twins and triplets, were 38.30 (2.21), 36.39 (4.21), and 32.72 (4.14), respectively. The adjusted odds for mortality were similar for twin births compared to singleton (aOR: 1.004, 95% CI:0.960-1.051, p = 0.8521). The adjusted odds of mortality for triplet or higher-order gestation births were higher (aOR: 1.33, 95% CI: 1.128-1.575, p = 0.0008) when compared to the singleton births. Median LOS (days) was significantly longer in multiple gestation compared to singleton births overall (singletons: 1.59 [1.13, 2.19] vs. twins 3.29 [2.17, 9.59] vs. triplets or higher-order multiples 19.15 [8.80, 36.38], p < .0001), and this difference remained significant within each GA category.

Conclusion: Multiple gestation births have higher mortality and longer LOS when compared to singleton births. This population data from multiple centers across the country could be useful in counseling parents when caring for multiple gestation pregnancies.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8554969PMC
http://dx.doi.org/10.1186/s40748-021-00135-5DOI Listing

Publication Analysis

Top Keywords

multiple gestation
16
compared singleton
16
gestation births
12
outcomes multiple
8
births compared
8
morbidity mortality
8
triplet higher-order
8
twins triplets
8
triplets higher-order
8
higher-order multiples
8

Similar Publications

Mechanisms of Homoarginine: Looking Beyond Clinical Outcomes.

Acta Physiol (Oxf)

February 2025

Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.

Purpose: Homoarginine (hArg) is an arginine metabolite that has been known for years, but its physiological role in the body remains poorly understood. For instance, it is well known that high hArg concentrations in the blood are protective against several disease states, yet the mechanisms behind these health benefits are unclear. This review compiles what is known about hArg, namely its synthetic pathways, its role in different diseases and conditions, and its proposed mechanisms of action in humans and experimental animals.

View Article and Find Full Text PDF

Deep cascaded registration and weakly-supervised segmentation of fetal brain MRI.

Heliyon

January 2025

BCN MedTech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.

Deformable image registration is a cornerstone of many medical image analysis applications, particularly in the context of fetal brain magnetic resonance imaging (MRI), where precise registration is essential for studying the rapidly evolving fetal brain during pregnancy and potentially identifying neurodevelopmental abnormalities. While deep learning has become the leading approach for medical image registration, traditional convolutional neural networks (CNNs) often fall short in capturing fine image details due to their bias toward low spatial frequencies. To address this challenge, we introduce a deep learning registration framework comprising multiple cascaded convolutional networks.

View Article and Find Full Text PDF

Background: Undernutrition remains a global crisis and is a focus of Sustainable Development Goals. While there are multiple known, effective interventions, complex interactions between prevention and treatment and resource constraints can lead to difficulties in allocating funding. Simulation studies that use in silico simulation can help illuminate the interactions between interventions and provide insight into the cost-effectiveness of alternative packages of options.

View Article and Find Full Text PDF

Prediction and unsupervised clustering of fertility intention among migrant workers based on machine learning: a cross-sectional survey from Henan, China.

BMC Public Health

January 2025

Department of Health Management of Public Health, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin district, Zhengzhou, Henan, 450001, China.

Background: Although China has implemented multiple policies to encourage childbirth, the results have been underwhelming. Migrant workers account for a considerable proportion of China's population, most of whom are of childbearing age. However, few articles focus on their fertility intentions.

View Article and Find Full Text PDF

Preeclampsia (PE) is a major pregnancy-specific cardiovascular complication posing latent life-threatening risks to mothers and neonates. The contribution of immune dysregulation to PE is not fully understood, highlighting the need to explore molecular markers and their relationship with immune infiltration to potentially inform therapeutic strategies. We used bioinformatics tools to analyze gene expression data from the Gene Expression Omnibus (GEO) database using the GEOquery package in R.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!