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Quantifying bias between reported last menstrual period and ultrasonography estimates of gestational age in Lusaka, Zambia.

ABSTRACT: OBJECTIVE:To quantify differences in assessing preterm delivery when calculating gestational age from last menstrual period (LMP) versus ultrasonography biometry. METHODS:The Zambian Preterm Birth Prevention Study is an ongoing prospective cohort study that commenced enrolment in August 2015 at Women and Newborn Hospital of University Teaching Hospital in Lusaka, Zambia. Women at less than 20 weeks of pregnancy who were enrolled between August 17, 2015, and August 31, 2017, and underwent ultrasonography examination were included in the present analysis. The primary outcome was the difference between ultrasonography- and LMP-based estimated gestational age. Associations between baseline predictors and outcomes were assessed using simple regression. The proportion of preterm deliveries using LMP- and ultrasonography-derived gestational dating was calculated using Kaplan-Meier analysis. RESULTS:The analysis included 942 women. The discrepancy between estimating gestational age using ultrasonography and LMP increased with greater gestational age at presentation and among patients with no history of preterm delivery. In a Kaplan-Meier analysis of 692 deliveries, 140 (20.2%, 95% confidence interval [CI] 17.7-23.0) and 79 (11.4%, 95% CI 9.6-13.6) deliveries were classified as preterm by LMP and ultrasonography estimates, respectively. CONCLUSION:Taking ultrasonography as a standard, a bias was observed in LMP-based gestational age estimates, which increased with advancing gestation at presentation. This resulted in misclassification of term deliveries as preterm.

SUBMITTER: Price JT

PROVIDER: S-EPMC6283668 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Quantifying bias between reported last menstrual period and ultrasonography estimates of gestational age in Lusaka, Zambia.

Price Joan T JT Winston Jennifer J Vwalika Bellington B Cole Stephen R SR Stoner Marie C D MCD Lubeya Mwansa K MK Kumwenda Andrew A Stringer Jeffrey S A JSA

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics 20181019 1

<h4>Objective</h4>To quantify differences in assessing preterm delivery when calculating gestational age from last menstrual period (LMP) versus ultrasonography biometry.<h4>Methods</h4>The Zambian Preterm Birth Prevention Study is an ongoing prospective cohort study that commenced enrolment in August 2015 at Women and Newborn Hospital of University Teaching Hospital in Lusaka, Zambia. Women at less than 20 weeks of pregnancy who were enrolled between August 17, 2015, and August 31, 2017, and un ...[more]

PMID: 30267538

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Project description:Accurate estimation of gestational age is important for both clinical and public health purposes. Estimates of gestational age using fetal ultrasound measurements are considered most accurate but are frequently unavailable in low- and middle-income countries. The objective of this study was to assess the validity of last menstrual period and Farr neonatal examination estimates of gestational age, compared to ultrasound estimates, in a large cohort of women in Vietnam.Data for this analysis come from a randomized, placebo-controlled micronutrient supplementation trial in Vietnam. We analyzed 912 women with ultrasound and prospectively-collected last menstrual period estimates of gestational age and 685 women with ultrasound and Farr estimates of gestational age. We used the Wilcoxon signed rank sum test to assess differences in gestational age estimated by last menstrual period or Farr examination compared to ultrasound and computed the intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC) to quantify agreement between methods. We computed the Kappa coefficient (?) to quantify agreement in preterm, term and post-term classification.The median gestational age estimated by ultrasound was 273.9 days. Gestational age was slightly overestimated by last menstrual period (median 276.0 days, P?<?0.001) and more greatly overestimated by Farr examination (median 286.7 days, P?<?0.001). Gestational age estimates by last menstrual period and ultrasound were moderately correlated (ICC?=?0.78) and concordant (CCC?=?0.63), whereas gestational age estimates by Farr examination and ultrasound were weakly correlated (ICC?=?0.26) and concordant (CCC?=?0.05). Last menstrual period and ultrasound estimates of gestational age were within?±?14 days for 88.4% of women; Farr and ultrasound estimates were within?±?14 days for 55.8% of women. Last menstrual period and ultrasound estimates of gestational age had higher agreement in term classification (??=?0.41) than Farr and ultrasound (??=?0.05).In this study of women in Vietnam, we found last menstrual period provided a more accurate estimate of gestational age than the Farr examination when compared to ultrasound. These findings provide useful information about the utility and accuracy of different methods to estimate gestational age and suggest last menstrual period may be preferred over Farr examination in settings where ultrasound is unavailable.The trial was registered at ClinicalTrials.Gov as NCT01665378 on August 13, 2012.

Project description:ObjectiveTo explore the prevalence and determinants of calendar literacy and last menstrual period (LMP) recall among women in Bangladesh.DesignCross-sectional survey.SettingsTwo rural subdistricts and one urban area from three Northern districts of Bangladesh.ParticipantsWe interviewed 2731 women who had a live birth in the last 1 year.Primary and secondary outcome measuresThe primary outcome variable was LMP recall and the secondary outcome was calendar literacy.ResultsThe majority of participants (65%) correctly mentioned the current date according to the English calendar while 12% mentioned according to the Bengali calendar. During the interview sessions, we used three different calendars: Bengali, English and Hijri to assess calendar literacy. We asked women to mark the current date using the calendar on the day of the interview. Almost 61% women marked the English calendar, 16% marked the Bengali calendar and 4% marked the Hijri calendar correctly. Sixty-three per cent women were found as calendar literate who marked any of the calendars. Among the participants, 58% had calendars available at their home and only 10% of women used calendars to track their LMPs. Overall, 53% women were able to recall their recent LMP. Among the calendar literate, 60% could recall their LMPs. Factors found associated with recalling LMP were: completed eight or more years of schooling (adj.OR 1.39), primigravida (adj.OR 1.88), the richest wealth quintile (adj.OR 1.55) and calendar literacy (adj.OR 1.59).ConclusionsDespite having reasonable calendar literacy and availability, the use of calendars for tracking LMP found very low. Calendar literacy and sociodemographic characteristics were found as the key factors associated with LMP recall. Maternal, neonatal and child health programmes in low-resource settings can promote a simple tool like calendar and target the communities where ultrasound is not available to ensure accurate LMP recall for early pregnancy registration and timely antenatal care coverage.

Project description:Introduction and objectiveValidation studies of algorithms for pregnancy outcomes based on International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes are important for conducting drug safety research using administrative claims databases. To facilitate the conduct of pregnancy safety studies, this exploratory study aimed to develop and validate ICD-10-CM-based claims algorithms for date of last menstrual period (LMP) and pregnancy outcomes using medical records.MethodsUsing a mother-infant-linked claims database, the study included women with a pregnancy between 2016-2017 and their infants. Claims-based algorithms for LMP date utilized codes for gestational age (Z3A codes). The primary outcomes were major congenital malformations (MCMs) and spontaneous abortion; additional secondary outcomes were also evaluated. Each pregnancy outcome was identified using a claims-based simple algorithm, defined as presence of ≥ 1 claim for the outcome. Positive predictive values (PPV) and 95% confidence intervals (CI) were calculated.ResultsOverall, 586 medical records were sought and 365 (62.3%) were adjudicated, including 125 records each for MCMs and spontaneous abortion. Last menstrual period date was validated among maternal charts procured for pregnancy outcomes and fewer charts were adjudicated for the secondary outcomes. The median difference in days between LMP date based on Z3A codes and adjudicated LMP date was 4.0 (interquartile range: 2.0-10.0). The PPV of the simple algorithm for spontaneous abortion was 84.7% (95% CI 78.3, 91.2). The PPV for the MCM algorithm was < 70%. The algorithms for the secondary outcomes pre-eclampsia, premature delivery, and low birthweight performed well, with PPVs > 70%.ConclusionsThe ICD-10-CM claims-based algorithm for spontaneous abortion performed well and may be used in pregnancy studies. Further algorithm refinement for MCMs is needed. The algorithms for LMP date and the secondary outcomes would benefit from additional validation in a larger sample.

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Quantifying bias between reported last menstrual period and ultrasonography estimates of gestational age in Lusaka, Zambia.

Publications

Quantifying bias between reported last menstrual period and ultrasonography estimates of gestational age in Lusaka, Zambia.

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