scholarly journals 553: Large for gestational age - prevalence and risk factors for intrapartum cesarean delivery

2018 ◽  
Vol 218 (1) ◽  
pp. S330-S331
Author(s):  
Liran Hiersch ◽  
Eran Ashwal ◽  
Sharon Maslovitz ◽  
Michael J. Kupferminc ◽  
Yariv Yogev
Keyword(s):  
Risk Factors ◽  
Cesarean Delivery ◽  
Gestational Age ◽  
Large For Gestational Age

scholarly journals Incidence, Risk Factors, and Outcomes of Preterm and Early Term Births: A Population-Based Register Study

2021 ◽  
Vol 18 (11) ◽  
pp. 5865
Author(s):  
Salma Younes ◽  
Muthanna Samara ◽  
Rana Al-Jurf ◽  
Gheyath Nasrallah ◽  
Sawsan Al-Obaidly ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hospital Mortality ◽  
Gestational Age ◽  
Neonatal Intensive Care ◽  
Population Based ◽  
Incidence Rates ◽  
Large For Gestational Age ◽  
Mortality And Morbidity ◽  
Early Term ◽  
Incidence Risk

Preterm birth (PTB) and early term birth (ETB) are associated with high risks of perinatal mortality and morbidity. While extreme to very PTBs have been extensively studied, studies on infants born at later stages of pregnancy, particularly late PTBs and ETBs, are lacking. In this study, we aimed to assess the incidence, risk factors, and feto-maternal outcomes of PTB and ETB births in Qatar. We examined 15,865 singleton live births using 12-month retrospective registry data from the PEARL-Peristat Study. PTB and ETB incidence rates were 8.8% and 33.7%, respectively. PTB and ETB in-hospital mortality rates were 16.9% and 0.2%, respectively. Advanced maternal age, pre-gestational diabetes mellitus (PGDM), assisted pregnancies, and preterm history independently predicted both PTB and ETB, whereas chromosomal and congenital abnormalities were found to be independent predictors of PTB but not ETB. All groups of PTB and ETB were significantly associated with low birth weight (LBW), large for gestational age (LGA) births, caesarean delivery, and neonatal intensive care unit (NICU)/or death of neonate in labor room (LR)/operation theatre (OT). On the other hand, all or some groups of PTB were significantly associated with small for gestational age (SGA) births, Apgar <7 at 1 and 5 minutes and in-hospital mortality. The findings of this study may serve as a basis for taking better clinical decisions with accurate assessment of risk factors, complications, and predictions of PTB and ETB.

scholarly journals Maternal Prenatal Anthropometry, High Education and Cesarean Delivery as Risk Factors for Low Gestational Age in Iran

2019 ◽  
Vol 6 (1) ◽  
pp. 77-82
Author(s):  
Sorayya Kheirouri ◽  
Mohammad Alizadeh ◽  
Parvin Sarbakhsh
Keyword(s):  
Risk Factors ◽  
High Education ◽  
Preterm Birth ◽  
Cesarean Delivery ◽  
Gestational Age ◽  
Economic Status ◽  
Cross Sectional ◽  
Data Set ◽  
Pregnancy Weight ◽  
High Bmi

Background: Preterm birth is an important contributor to the global burden of disease. Evidence indicating that maternal health, nutritional and socioeconomic status may contribute to preterm birth. Objective: This cross-sectional study was conducted to describe the contribution of prenatal maternal factors on low gestational age, and to assess newborns anthropometric measurements regarding gestational age. Methods: Data of mothers delivering a singleton live infant (n= 759) and their newborns (n= 755) during the two years up to August 2014 were collected. Data were collected from the data set of eight public health centers which were chosen from different administrative regions of Tabriz city and were analyzed. Differences between the groups were assessed by Student’s t-test or one- way analysis of variance (ANOVA). Multiple linear regression was used to estimate the association between gestational age and variables studied. Results: Incidence of preterm birth was 2.1%. Percentage of infants with low birth weight and Head Circumference (HC) under 34 cm was significantly higher in the preterm group. Mean gestational age was lower in mothers with cesarean delivery, high education, high economic status, high BMI, pre-pregnancy weight ≥ 65 kg and medical problem. Gestational age was inversely associated with maternal pre-pregnancy weight ≥ 65 kg (B= -0.20, p= 0.02), high BMI (B= -0.33, p= 0.01), high education (B= -0.47, p= 0.002) and cesarean delivery (B= -0.74, p< 0.001). Conclusion: The results indicate that maternal anthropometric characteristics, education and type of delivery are associated with gestational age. Explorating potentially modifiable risk factors for unfavorable gestational age and integrating them into intervention efforts may ameliorate adverse birth outcomes.

scholarly journals Do nuclear magnetic resonance (NMR)-based metabolomics improve the prediction of pregnancy-related disorders?

2020 ◽  
Author(s):  
Nancy McBride ◽  
Sara L. White ◽  
Lucilla Poston ◽  
Diane Farrar ◽  
Jane West ◽  
...  
Keyword(s):  
Risk Factors ◽  
Pregnant Women ◽  
Gestational Age ◽  
Prediction Models ◽  
External Validation ◽  
Area Under The Curve ◽  
Large For Gestational Age ◽  
List Type ◽  
Independent Validation ◽  
Pregnancy Smoking

AbstractBackgroundPrediction of pregnancy-related disorders is mostly done based on established and easily measured risk factors. However, these measures are at best moderate at discriminating between high and low risk women. Recent advances in metabolomics may provide earlier and more accurate prediction of women at risk of pregnancy-related disorders.Methods and FindingsWe used data collected from women in the Born in Bradford (BiB; n=8,212) and UK Pregnancies Better Eating and Activity Trial (UPBEAT; n=859) studies to create and validate prediction models for pregnancy-related disorders. These were gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy (HDP), small for gestational age (SGA), large for gestational age (LGA) and preterm birth (PTB). We used ten-fold cross-validation and penalised regression to create prediction models. We compared the predictive performance of 1) risk factors (maternal age, pregnancy smoking status, body mass index, ethnicity and parity) to 2) nuclear magnetic resonance-derived metabolites (N = 156 quantified metabolites, collected at 24-28 weeks gestation) and 3) risk factors and metabolites combined. The multi-ethnic BiB cohort was used for training and testing the models, with independent validation conducted in UPBEAT, a study of obese pregnant women of multiple ethnicities.In BiB, discrimination for GDM, HDP, LGA and SGA was improved with the addition of metabolites to the risk factors only model. Risk factors area under the curve (AUC 95% confidence interval (CI)): GDM (0.69 (0.64, 0.73)), HDP (0.74 (0.70, 0.78)) and LGA (0.71 (0.66, 0.75)), and SGA (0.59 (0.56,0.63)). Combined AUC 95% (CI)): GDM (0.78 (0.74, 0.81)), HDP (0.76 (0.73, 0.79)) and LGA (0.75 (0.70, 0.79)), and SGA (0.66 (0.63,0.70)). For GDM, HDP, LGA, but not SGA, calibration was good for a combined risk factor and metabolite model. Prediction of PTB was poor for all models. Independent validation in UPBEAT at 24-28 weeks and 15-18 weeks gestation confirmed similar patterns of results, but AUC were attenuated. A key limitation was our inability to identify a large general pregnancy population for independent validation.ConclusionsOur results suggest metabolomics combined with established risk factors improves prediction GDM, HDP and LGA, when compared to risk factors alone. They also highlight the difficulty of predicting PTB, with all models performing poorly.Author SummaryBackgroundCurrent methods used to predict pregnancy-related disorders exhibit modest discrimination and calibration.Metabolomics may enable improved prediction of pregnancy-related disorders.Why Was This Study Done?We require tools to identify women with high-risk pregnancies earlier on, so that antenatal care can be more appropriately targeted at women who need it most and tailored to women’s needs and to facilitate early intervention.It has been suggested that metabolomic markers might improve prediction of future pregnancy-related disorders. Previous studies tend to be small and rarely undertake external validation.What Did the Researchers Do and Find?Using BiB (8,212 pregnant women of multiple ethnicities), we created prediction models, using established risk factors and 156 NMR-derived metabolites, for five pregnancy-related disorders. These were gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy (HDP), small for gestational age (SGA), large for gestational age (LGA) and preterm birth (PTB). We sought external validation in UPBEAT (859 obese pregnant women).We compared the predictive discrimination (area under the curve - AUC) and calibration (calibration slopes) of the models. The prediction models we compared were 1) established risk factors (pregnancy smoking, maternal age, body mass index (BMI), maternal ethnicity and parity) 2) NMR-derived metabolites measured in the second trimester and 3) a combined model of risk factors and metabolites.Inclusion of metabolites with risk factors improved prediction of GDM, HDP, LGA and SGA in BiB. Prediction of PTB was poor with all models. Result patterns were similar in validation using UPBEAT, particularly for GDM and HDP, but AUC were attenuated.What Do These Findings Mean?These findings indicate that combining current risk factor and metabolomic data could improve the prediction of GDM, HDP, LGA and SGA. These findings need to be validated in larger, general populations of pregnant women.

scholarly journals 502: Small for gestational age - prevalence and risk factors for intrapartum cesarean delivery

2018 ◽  
Vol 218 (1) ◽  
pp. S301
Author(s):  
Eran Ashwal ◽  
Liran Hiersch ◽  
Sharon Maslovitz ◽  
Michael J. Kupferminc ◽  
Yariv Yogev
Keyword(s):  
Risk Factors ◽  
Cesarean Delivery ◽  
Gestational Age ◽  
Small For Gestational Age

scholarly journals How boys and testicles wander to surgery: a nationwide cohort study of surgical delay in Sweden

2020 ◽  
Vol 4 (1) ◽  
pp. e000741
Author(s):  
Erik Omling ◽  
Sanna Bergbrant ◽  
Andreas Persson ◽  
Jonas Björk ◽  
Lars Hagander
Keyword(s):  
Risk Factors ◽  
Travel Time ◽  
Gestational Age ◽  
Financial Support ◽  
Large For Gestational Age ◽  
Income Quintile ◽  
Paediatric Surgery ◽  
Delayed Treatment ◽  
Incidence Risk ◽  
Timely Treatment

BackgroundEarly orchidopexy is recommended for cryptorchidism and the surgery is increasingly centralised. The objectives were to determine the incidence, risk factors and if distance to treating hospital impacted on timely treatment of cryptorchidism.MethodsIn this observational study, all boys born in Sweden from 2001 to 2014 were followed in national registers to determine the incidence of cryptorchidism by levels of birth-related risk factors and social determinants. Travel time to hospital was used as the primary exposure in multivariable survival analysis, with age at surgery as main outcome.ResultsOf 748 678 boys at risk for cryptorchidism, 7351 were treated and evaluated for timing of surgery (cumulative childhood incidence 1.4%, 95% CI 1.3% to 1.5%). The incidence was clearly associated with prematurity and overdue pregnancy (HR for <32 weeks 2.77 (95% CI 2.39 to 3.21); 32–36 weeks HR 1.36 (95% CI 1.24 to 1.49); >41 weeks HR 1.19 (95% CI 1.10 to 1.29)), low birth weight (<1000 g HR 3.94 (95% CI 3.15 to 4.92); 1000–1499 g HR 3.70 (95% CI 3.07 to 4.46); 1500–2500 g HR 1.69 (95% CI 1.52 to 1.88)) and intrauterine growth restriction (small for gestational age HR 2.38 (95% CI 2.14 to 2.65); large for gestational age HR 1.26 (95% CI 1.13 to 1.42)), but not with smoking or maternal age. Each 30 min increase in travel time was associated with a reduced probability of timely treatment (HR for being treated by age 3 adjusted for risk factors and socioeconomic determinants: 0.91 (95% CI 0.88 to 0.95)). Lower income and financial support were also associated with treatment delays (adjusted HR for lowest income quintile 0.82 (95% CI 0.72 to 0.93) and for families with financial support 0.85 (95% CI 0.73 to 0.97)).ConclusionsTravel distance to treating hospital was associated with delayed treatment. ‘Not all those who wander are lost’, but these findings suggest a trade-off between centralisation benefits and barriers of geography also in elective paediatric surgery.

scholarly journals Prothrombotic State, Cardiovascular, and Metabolic Syndrome Risk Factors in Prepubertal Children Born Large for Gestational Age

Diabetes Care ◽  
2010 ◽  
Vol 33 (11) ◽  
pp. 2468-2470 ◽  
Author(s):  
E. N. Evagelidou ◽  
V. I. Giapros ◽  
A. S. Challa ◽  
V. K. Cholevas ◽  
G. A. Vartholomatos ◽  
...  
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Gestational Age ◽  
Large For Gestational Age ◽  
Prothrombotic State ◽  
Prepubertal Children

scholarly journals 449: Trends in cesarean delivery among twins in different gestational age groups and risk factors, in the United States; 2006 -2013

2016 ◽  
Vol 214 (1) ◽  
pp. S247-S248
Author(s):  
Bahram Salmanian ◽  
Zhoobin H. Bateni ◽  
Steven L. Clark ◽  
Alex C. Vidaeff ◽  
Amirhossein Moaddab ◽  
...  
Keyword(s):  
United States ◽  
Risk Factors ◽  
Cesarean Delivery ◽  
Gestational Age ◽  
Age Groups ◽  
The United States

scholarly journals Risk factors for congenital hypothyroidism: results of a population case-control study (1997–2003)

2005 ◽  
Vol 153 (6) ◽  
pp. 765-773 ◽  
Author(s):  
Emanuela Medda ◽  
Antonella Olivieri ◽  
Maria Antonietta Stazi ◽  
Michele E Grandolfo ◽  
Cristina Fazzini ◽  
...  
Keyword(s):  
Risk Factors ◽  
Congenital Hypothyroidism ◽  
Gestational Age ◽  
Case Control Study ◽  
Female Gender ◽  
Maternal Diabetes ◽  
Case Control ◽  
Large For Gestational Age ◽  
Increased Risk ◽  
Control Study

Objective: To identify risk factors for permanent and transient congenital hypothyroidism (CH). Design: A population-based case-control study was carried out by using the network created in Italy for the National Register of Infants with CH. Methods: Four controls were enrolled for each new CH infant; 173 cases and 690 controls were enrolled in 4 years. In order to distinguish among risk factors for permanent and transient CH, diagnosis was re-evaluated 3 years after enrolment when there was a suspicion of transient CH being present. Familial, maternal, neonatal and environmental influences were investigated. Results: An increased risk for permanent CH was detected in twins by a multivariate analysis (odds ratio (OR) = 12.2, 95% confidence interval (CI): 2.4–62.3). A statistically significant association with additional birth defects, female gender and gestational age >40 weeks was also confirmed. Although not significant, an increased risk of CH was observed among infants with a family history of thyroid diseases among parents (OR = 1.9, 95% CI: 0.7–5.2). Maternal diabetes was also found to be slightly associated with permanent CH (OR = 15.7, 95% CI: 0.9–523) in infants who were large for gestational age. With regard to transient CH, intrauterine growth retardation and preterm delivery were independent risk factors for this form of CH. Conclusion: This study showed that many risk factors contribute to the aetiology of CH. In particular, our results suggested a multifactorial origin of CH in which genetic and environmental factors play a role in the development of the disease.

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