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Comparison of gestational dating methods and implications for exposure-outcome associations: an example with PM2.5 and preterm birth.

ABSTRACT: Estimating gestational age is usually based on date of last menstrual period (LMP) or clinical estimation (CE); both approaches introduce potential bias. Differences in methods of estimation may lead to misclassification and inconsistencies in risk estimates, particularly if exposure assignment is also gestation-dependent. This paper examines a 'what-if' scenario in which alternative methods are used and attempts to elucidate how method choice affects observed results.We constructed two 20-week gestational age cohorts of pregnancies between 2000 and 2005 (New Jersey, Pennsylvania, Ohio, USA) using live birth certificates: one defined preterm birth (PTB) status using CE and one using LMP. Within these, we estimated risk for 4 categories of preterm birth (PTBs per 106 pregnancies) and risk differences (RD (95% CIs)) associated with exposure to particulate matter (PM2.5).More births were classified preterm using LMP (16%) compared with CE (8%). RD divergences increased between cohorts as exposure period approached delivery. Among births between 28 and 31?weeks, week 7 PM2.5 exposure conveyed RDs of 44 (21 to 67) for CE and 50 (18 to 82) for LMP populations, while week 24 exposure conveyed RDs of 33 (11 to 56) and -20 (-50 to 10), respectively.Different results from analyses restricted to births with both CE and LMP are most likely due to differences in dating methods rather than selection issues. Results are sensitive to choice of gestational age estimation, though degree of sensitivity can vary by exposure timing. When both outcome and exposure depend on estimate of gestational age, awareness of nuances in the method used for estimation is critical.

SUBMITTER: Rappazzo KM

PROVIDER: S-EPMC6128148 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Comparison of gestational dating methods and implications for exposure-outcome associations: an example with PM2.5 and preterm birth.

Rappazzo Kristen M KM Lobdell Danelle T DT Messer Lynne C LC Poole Charles C Daniels Julie L JL

Occupational and environmental medicine 20161025 2

<h4>Objectives</h4>Estimating gestational age is usually based on date of last menstrual period (LMP) or clinical estimation (CE); both approaches introduce potential bias. Differences in methods of estimation may lead to misclassification and inconsistencies in risk estimates, particularly if exposure assignment is also gestation-dependent. This paper examines a 'what-if' scenario in which alternative methods are used and attempts to elucidate how method choice affects observed results.<h4>Meth ...[more]

PMID: 27919061

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Project description:BackgroundDifferent formulae have been developed globally to estimate gestational age (GA) by ultrasonography in the first trimester of pregnancy. In this study, we develop an Indian population-specific dating formula and compare its performance with published formulae. Finally, we evaluate the implications of the choice of dating method on preterm birth (PTB) rate. This study's data was from GARBH-Ini, an ongoing pregnancy cohort of North Indian women to study PTB.MethodsComparisons between ultrasonography-Hadlock and last menstrual period (LMP) based dating methods were made by studying the distribution of their differences by Bland-Altman analysis. Using data-driven approaches, we removed data outliers more efficiently than by applying clinical parameters. We applied advanced machine learning algorithms to identify relevant features for GA estimation and developed an Indian population-specific formula (Garbhini-GA1) for the first trimester. PTB rates of Garbhini-GA1 and other formulae were compared by estimating sensitivity and accuracy.ResultsPerformance of Garbhini-GA1 formula, a non-linear function of crown-rump length (CRL), was equivalent to published formulae for estimation of first trimester GA (LoA, - 0.46,0.96 weeks). We found that CRL was the most crucial parameter in estimating GA and no other clinical or socioeconomic covariates contributed to GA estimation. The estimated PTB rate across all the formulae including LMP ranged 11.27-16.50% with Garbhini-GA1 estimating the least rate with highest sensitivity and accuracy. While the LMP-based method overestimated GA by 3 days compared to USG-Hadlock formula; at an individual level, these methods had less than 50% agreement in the classification of PTB.ConclusionsAn accurate estimation of GA is crucial for the management of PTB. Garbhini-GA1, the first such formula developed in an Indian setting, estimates PTB rates with higher accuracy, especially when compared to commonly used Hadlock formula. Our results reinforce the need to develop population-specific gestational age formulae.

Project description:BackgroundPreterm birth is the leading cause of death among children <5 years of age. Accurate determination of prematurity is necessary to provide appropriate neonatal care and guide preventive measures. To estimate the most accurate method to identify infants at risk for adverse outcomes, we assessed the validity of two widely available methods-last menstrual period (LMP) and the New Ballard (NB) neonatal assessment-against ultrasound in determining gestational age and preterm birth in highland Guatemala.MethodsPregnant women (n = 188) were recruited with a gestational age <20 weeks and followed until delivery. Ultrasound was performed by trained physicians and LMP was collected during recruitment. NB was performed on infants within 96 hours of birth by trained study nurses. LMP and NB accuracy at determining gestational age and identifying prematurity was assessed by comparing them to ultrasound.ResultsBy ultrasound, infant mean gestational age at birth was 38.3 weeks (SD = 1.6) with 16% born at less than 37 gestation. LMP was more accurate than NB (mean difference of +0.13 weeks for LMP and +0.61 weeks for NB). However, LMP and NB estimates had low agreement with ultrasound-determined gestational age (Lin's concordance<0.48 for both methods) and preterm birth (?<0.29 for both methods). By LMP, 18% were judged premature compared with 6% by NB. LMP underestimated gestational age among women presenting later to prenatal care (0.18 weeks for each additional week). Gestational age for preterm infants was overestimated by nearly one week using LMP and nearly two weeks using NB. New Ballard neuromuscular measurements were more predictive of preterm birth than those measuring physical criteria.ConclusionIn an indigenous population in highland Guatemala, LMP overestimated prematurity by 2% and NB underestimated prematurity by 10% compared with ultrasound estimates. New, simple and accurate methods are needed to identify preterm birth in resource-limited settings worldwide.

Project description:BACKGROUND:In low resource settings recall of the date of the mother's last menstrual period may be unreliable and due to limited availability of prenatal ultrasound, gestational age of newborns may not be assessed reliably. Preterm babies are at high risk of morbidity and mortality so an alternative strategy is to identify them soon after birth is needed for early referral and management. OBJECTIVE:The objective of this study was to assess the accuracy in assessing prematurity of newborn, over and above birthweight, using a pictorial Simplified Gestational Age Score adapted for use as a Tablet App. METHODS:Two trained nurse midwives, blinded to each other's assessment and the actual gestational age of the baby used the app to assess gestational age at birth in 3 hospitals based on the following 4 parameters-newborn's posture, skin texture, breast and genital development. Inter-observer variation was evaluated and the optimal scoring cut-off to detect preterm birth was determined. Sensitivity and specificity of gestational age score using the tablet was estimated using combinations of last menstrual period and ultrasound as reference standards to assess preterm birth. The predictive accuracy of the score using the area under a receiver operating characteristic curve was also determined. To account for potential reference standard bias, we also evaluated the score using latent class models. RESULTS:A total of 8,591 live singleton births whose gestational age by last menstrual period and ultrasound was within 1 weeks of each other were enrolled. There was strong agreement between assessors (concordance correlation coefficient 0.77 (95% CI 0.76-0.78) and Fleiss' kappa was 0.76 (95% CI 0.76-0.78). The optimal cut-off for the score to predict preterm was 13. Irrespective of the reference standard, the specificity of the score was 90% and sensitivity varied from 40-50% and the predictive accuracy between 74%-79% for the reference standards. The likelihood ratio of a positive score varied between 3.75-4.88 while the same for a negative likelihood ratio consistently varied between 0.57-0.72. Latent class models showed similar results indicating no reference standard bias. CONCLUSION:Gestational age scores had strong inter-observer agreement, robust prediction of preterm births simplicity of use by nurse midwives and can be a useful tool in resource-limited scenarios. TRIAL REGISTRATION:The Tablet App for the Simplified Gestational Age Score (T-SGAS) study was registered at ClinicalTrials.gov NCT02408783.

Project description:BACKGROUND:Although rates of preterm birth continue to increase globally, identification of preterm from low birth weight infants remains a challenge. The burden of low birth weight vs preterm is greatest in resource-limited settings, where gestational age (GA) prior to delivery is frequently not known because ultrasound in early pregnancy is not available and estimates of the date of the mother's last menstrual period (LMP) may not be reliable. An alternative option is to assess GA at birth to optimize referral and care of preterm newborns. We previously developed and pilot-tested a system to measure the simplified gestational age score (SGAS) based on 4 easily observable neonatal characteristics. OBJECTIVE:The objective of this study is to adapt the scoring system as a tablet app (potentially scalable approach) to assess feasibility of use and to validate whether the scoring system accurately predicts prematurity by itself, over and above birth weight in a large sample of newborns. METHODS:The study is based in Nagpur, India, at the Research Unit of the National Institute of Child Health and Human Development's Global Network for Women's and Children's Health Research. The Android tablet app for the SGAS (T-SGAS) displays de-identified photographs of skin, breasts, and genitalia across a range of GAs and line drawings of infant posture. Each item is associated with a score. The user is trained to choose the photograph or line drawing that most closely matches the newborn being evaluated, and the app determines the neonate's GA category (preterm or term) from the cumulative score. The validation study will be conducted in 3 second level care facilities (most deliveries in India occur in hospitals, and women known to be at risk of preterm birth are referred to second level care facilities). Within 24 hours of delivery, women and their babies who are stable will be enrolled in the study. Two auxiliary nurse midwives (ANMs) blinded to prior GA assessments will use the T-SGAS to estimate the GA status of the newborn. An independent data collector will abstract the GA from the ultrasound recorded in the hospital chart and record the date of the mother's LMP. Eligibility for analysis is determined by the ultrasound and LMP data being collected within 1 week of each other to have a rigorous assessment of true GA. RESULTS:Publication of the results of the study is anticipated in 2019. CONCLUSIONS:Until GA dating by ultrasound is universally available and easy to use in resource-limited settings, and where there are restrictions on ultrasound use due to their use for sex determination and abortion of female fetuses, this study will determine whether the T-SGAS app can accurately assess GA in risk categories at birth. TRIAL REGISTRATION:ClinicalTrials.gov NCT02408783; https://clinicaltrials.gov/ct2/show/NCT02408783 (Archived by Webcite at http://www.webcitation.org/75S2kmr3T). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):DERR1-10.2196/11913.

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Comparison of gestational dating methods and implications for exposure-outcome associations: an example with PM2.5 and preterm birth.

Publications

Comparison of gestational dating methods and implications for exposure-outcome associations: an example with PM2.5 and preterm birth.

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