In celebration of Global Health Trials' fifth birthday (May 11th 2015) Professor Trudie Lang, Principal Investigator of the programme, talks to us about why Global Health Trials was started, why people should share their experience, and what the future holds.

8th May 2015 • comment
21st December 2014 • comment

This paper assess the intra- and interobserver variability of fetal biometry measurements throughout pregnancy. Authors concluded that although intra- and interobserver variability increases with advancing gestation when expressed in milimeters, both are constant as a percentage of the fetal dimensions or when reported as a Z-score. Thus, measurement variability should be considered when interpreting fetal growth rates.  http://www.ncbi.nlm.nih.gov/pubmed/22535628

15th May 2014 • comment

A comprehensive classification system for preterm birth requires expanded gestational boundaries that recognize the early origins of preterm parturition and emphasize fetal maturity over fetal age. This paper explores the issues to consider in creating a classification system for preterm birth syndrome. http://www.ncbi.nlm.nih.gov/pubmed/22177186

15th May 2014 • comment

Preterm birth is a syndrome with many causes and phenotypes. We propose a classification system that is based on clinical phenotypes that are defined by >1 characteristics of the mother, the fetus, the placenta, the signs of parturition, and the pathway to delivery. Risk factors and mode of delivery are not included. There are 5 components in a preterm birth phenotype:

  1. Maternal conditions that are present before presentation for delivery,
  2. Fetal conditions that are present before presentation for delivery,
  3. Placental pathologic conditions,
  4. Signs of the initiation of parturition, and,
  5. The pathway to delivery
This system does not force any preterm birth into a predefined phenotype and allows all relevant conditions to become part of the phenotype. Needed data can be collected from the medical records to classify every preterm birth. The classification system will improve understanding of the cause and improve surveillance across populations. http://www.ncbi.nlm.nih.gov/pubmed/22177191

15th May 2014 • comment

In 2009, the Global Alliance to Prevent Prematurity and Stillbirth Conference charged the authors to propose a new comprehensive, consistent, and uniform classification system for preterm birth. This first article reviews issues related to measurement of gestational age, clinical vs etiologic phenotypes, inclusion vs exclusion of multifetal and stillborn infants, and separation vs combination of pathways to preterm birth. http://www.ncbi.nlm.nih.gov/pubmed/22118964

15th May 2014 • comment

Being able to predict preterm birth is important, as it may allow a high-risk population to be selected for future interventional studies and help in understanding the pathways that lead to preterm birth. This paper investigates the accuracy of novel biomarkers to predict spontaneous preterm birth in women with singleton pregnancies and no symptoms of preterm labour. http://www.ncbi.nlm.nih.gov/pubmed/21401853  

15th May 2014 • comment

Reliable ultrasound charts are necessary for the prenatal assessment of fetal size, yet there is a wide variation of methodologies for the creation of such charts. This paper evaluates the methodological quality of studies of fetal biometry using a set of predefined quality criteria of study design, statistical analysis and reporting methods. Eighty-three studies met the inclusion criteria, and although multiple regression analysis shows that quality of studies has improved over time, there is considerable heterogeneity in study methodology still observed today. Standardisation of methodologies is necessary in order to make correct interpretations and comparisons between different charts. A checklist of recommended methodologies in proposed. http://www.ncbi.nlm.nih.gov/pubmed/22882780

15th May 2014 • comment

The objective of this paper was to assess whether a standardization exercise prior to commencing a fetal growth study involving multiple sonographers can reduce interobserver variation. http://www.ncbi.nlm.nih.gov/pubmed/22411446

14th May 2014 • comment