Evidence map›Paper›PMID 36536852›Full record

ArticleAJOG global reports2022

Validation of gestational age determination from ultrasound or a metabolic gestational age algorithm using exact date of conception in a cohort of newborns conceived using assisted reproduction technologies.

Steven Hawken, Brieanne Olibris, Robin Ducharme, A Brianne Bota, Jeffrey C Murray, Beth K Potter, Mark Walker, Pranesh Chakraborty, Kumanan Wilson

Open access · goldAbstract read
In one paragraph

Article in AJOG global reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.5field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Gestational age determination in pregnancies conceived via assisted reproductive technology.Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 2 countries.

Steven HawkenClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (Drs Hawken and Olibris, Ms. Ducharme, and Drs Bota, Walker, and Wilson).
Brieanne OlibrisClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (Drs Hawken and Olibris, Ms. Ducharme, and Drs Bota, Walker, and Wilson).
Robin DucharmeClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (Drs Hawken and Olibris, Ms. Ducharme, and Drs Bota, Walker, and Wilson).
A Brianne BotaClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (Drs Hawken and Olibris, Ms. Ducharme, and Drs Bota, Walker, and Wilson).
Jeffrey C MurrayDepartment of Pediatrics, University of Iowa, Iowa City, IA (Dr Murray).
Beth K PotterSchool of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada (Dr Potter).
Mark WalkerClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (Drs Hawken and Olibris, Ms. Ducharme, and Drs Bota, Walker, and Wilson).
Pranesh ChakrabortyClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada Newborn Screening Ontario, Children's Hospital of Eastern Ontario, Ottawa, Canada (Dr Chakraborty).
Kumanan WilsonClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada (Drs Hawken and Olibris, Ms. Ducharme, and Drs Bota, Walker, and Wilson).
Ottawa Hospital · CAChildren's Hospital of Eastern Ontario · CAUniversity of Iowa · USUniversity of Ottawa · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate estimates of gestational age in pregnancy are important for the provision of optimal care. Although current guidelines generally recommend estimating gestational age via first-trimester ultrasound measurement of crown-rump length, error associated with this method can range from 3 to 8 days of gestation. In pregnancies resulting from assisted reproductive technology, estimated due date can be calculated on the basis of the age of the embryo and the date of embryo transfer, arguably providing the most accurate estimates possible. We have developed and extensively validated statistical models to estimate gestational age postnatally using metabolomic markers from blood samples in combination with clinical and demographic data. These models have shown high accuracy compared with first-trimester ultrasound, the recommended method for estimating gestational age in spontaneous pregnancies. We hypothesized that gestational age derived from date and stage of embryo at transfer in newborns conceived using assisted reproduction therapy would provide the most accurate reference standard possible to evaluate and compare the accuracy of both first-trimester ultrasound and metabolomic model-based gestational dating.

objectiveThis study aimed to validate both first-trimester ultrasound dating and postnatal metabolomic gestational age estimation models against gestational age derived from date and stage of embryo at transfer in a cohort of newborns conceived via assisted reproductive technology, both overall and in important subgroups of interest (preterm birth, small for gestational age, and multiple birth). STUDY

designThis was a retrospective cohort study of infants born in Ontario, Canada between 2015 and 2017 and captured in the provincial birth registry. Spontaneous conceptions were randomly partitioned into a model derivation sample (80%) and a test sample (20%) for model validation. A cohort of assisted conceptions resulting from fresh embryo transfers was derived to evaluate the accuracy of both ultrasound and model-based gestational dating. Postnatal gestational age estimation models were developed with multivariable linear regression using elastic-net regularization. Gestational age estimates from dating ultrasound and from postnatal metabolomic models were compared with date of embryo transfer reference gestational age in the independent test cohorts. Accuracy was quantified by calculating mean absolute error and the square root of mean squared error.

resultsOur model derivation cohort included 202,300 spontaneous conceptions, and the testing cohorts included 50,735 spontaneous conceptions and 1924 assisted conceptions. In the assisted conception cohort, first-trimester dating ultrasound was accurate to within approximately ±1.5 days compared with date of embryo transfer reference overall (mean absolute error, 0.21 [95% confidence interval, 0.20-0.23]). When compared with gestational age derived from date of embryo transfer, the metabolomic estimation models were accurate to within approximately ±5 days overall (0.79 [0.76-0.81] weeks). When ultrasound was used as the reference in validating the metabolomic model, the mean absolute error was slightly higher overall (0.81 [0.78-0.84] weeks). In general, the accuracy of gestational age estimates derived from ultrasound or metabolomic models was highest in term infants and lower in preterm and small-for-gestational-age newborns.

conclusionOur findings support the accuracy of ultrasound as a gestational age dating tool. They also support the potential utility of metabolic gestational age dating algorithms in settings where ultrasound or other accurate methods of estimating gestational age are not available because of lack of infrastructure or specialized training (eg, low-income countries). However, the accuracy of metabolomic model-based dating was generally lower than that of ultrasound.

Indexed as

assisted reproductionepidemiologygestational agein vitro fertilizationprediction modelingultrasonography

Identifiers

PMID36536852
PMCPMC9758343
OpenAlexW4293217032

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.