Ultrasound‐based gestational‐age estimation in late pregnancy

ABSTRACT Objective Accurate gestational‐age (GA) estimation, preferably by ultrasound measurement of fetal crown–rump length before 14 weeks' gestation, is an important component of high‐quality antenatal care. The objective of this study was to determine how GA can best be estimated by fetal u...

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Veröffentlicht in:Ultrasound in obstetrics & gynecology 2016-12, Vol.48 (6), p.719-726
Hauptverfasser: Papageorghiou, A. T., Kemp, B., Stones, W., Ohuma, E. O., Kennedy, S. H., Purwar, M., Salomon, L. J., Altman, D. G., Noble, J. A., Bertino, E., Gravett, M. G., Pang, R., Cheikh Ismail, L., Barros, F. C., Lambert, A., Jaffer, Y. A., Victora, C. G., Bhutta, Z. A., Villar, J.
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container_end_page 726
container_issue 6
container_start_page 719
container_title Ultrasound in obstetrics & gynecology
container_volume 48
creator Papageorghiou, A. T.
Kemp, B.
Stones, W.
Ohuma, E. O.
Kennedy, S. H.
Purwar, M.
Salomon, L. J.
Altman, D. G.
Noble, J. A.
Bertino, E.
Gravett, M. G.
Pang, R.
Cheikh Ismail, L.
Barros, F. C.
Lambert, A.
Jaffer, Y. A.
Victora, C. G.
Bhutta, Z. A.
Villar, J.
description ABSTRACT Objective Accurate gestational‐age (GA) estimation, preferably by ultrasound measurement of fetal crown–rump length before 14 weeks' gestation, is an important component of high‐quality antenatal care. The objective of this study was to determine how GA can best be estimated by fetal ultrasound for women who present for the first time late in pregnancy with uncertain or unknown menstrual dates. Methods INTERGROWTH‐21st was a large, prospective, multicenter, population‐based project performed in eight geographically defined urban populations. One of its principal components, the Fetal Growth Longitudinal Study, aimed to develop international fetal growth standards. Each participant had their certain menstrual dates confirmed by first‐trimester ultrasound examination. Fetal head circumference (HC), biparietal diameter (BPD), occipitofrontal diameter (OFD), abdominal circumference (AC) and femur length (FL) were measured every 5 weeks from 14 weeks' gestation until delivery. For each participant, a single, randomly selected ultrasound examination was used to explore all candidate biometric variables and permutations to build models to predict GA. Regression equations were ranked based upon minimization of the mean prediction error, goodness of fit and model complexity. An automated machine learning algorithm, the Genetic Algorithm, was adapted to evaluate > 64 000 potential polynomial equations as predictors. Results Of the 4607 eligible women, 4321 (94%) had a pregnancy without major complications and delivered a live singleton without congenital malformations. After other exclusions (missing measurements in GA window and outliers), the final sample comprised 4229 women. Two skeletal measures, HC and FL, produced the best GA prediction, given by the equation loge(GA) = 0.03243 × (loge(HC))2 + 0.001644 × FL × loge(HC) + 3.813. When FL was not available, the best equation based on HC alone was loge(GA) = 0.05970 × (loge(HC))2 + 0.000000006409 × (HC)3 + 3.3258. The estimated uncertainty of GA prediction (half width 95% interval) was 6–7 days at 14 weeks' gestation, 12–14 days at 26 weeks' gestation and > 14 days in the third trimester. The addition of FL to the HC model led to improved prediction intervals compared with using HC alone, but no further improvement in prediction was afforded by adding AC, BPD or OFD. Equations that included other measurements (BPD, OFD and AC) did not perform better. Conclusions Among women initiating antenatal care late
doi_str_mv 10.1002/uog.15894
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T. ; Kemp, B. ; Stones, W. ; Ohuma, E. O. ; Kennedy, S. H. ; Purwar, M. ; Salomon, L. J. ; Altman, D. G. ; Noble, J. A. ; Bertino, E. ; Gravett, M. G. ; Pang, R. ; Cheikh Ismail, L. ; Barros, F. C. ; Lambert, A. ; Jaffer, Y. A. ; Victora, C. G. ; Bhutta, Z. A. ; Villar, J.</creator><creatorcontrib>Papageorghiou, A. T. ; Kemp, B. ; Stones, W. ; Ohuma, E. O. ; Kennedy, S. H. ; Purwar, M. ; Salomon, L. J. ; Altman, D. G. ; Noble, J. A. ; Bertino, E. ; Gravett, M. G. ; Pang, R. ; Cheikh Ismail, L. ; Barros, F. C. ; Lambert, A. ; Jaffer, Y. A. ; Victora, C. G. ; Bhutta, Z. A. ; Villar, J. ; International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st) ; for the International Fetal and Newborn Growth Consortium for the 21 Century (INTERGROWTH‐21st)</creatorcontrib><description>ABSTRACT Objective Accurate gestational‐age (GA) estimation, preferably by ultrasound measurement of fetal crown–rump length before 14 weeks' gestation, is an important component of high‐quality antenatal care. The objective of this study was to determine how GA can best be estimated by fetal ultrasound for women who present for the first time late in pregnancy with uncertain or unknown menstrual dates. Methods INTERGROWTH‐21st was a large, prospective, multicenter, population‐based project performed in eight geographically defined urban populations. One of its principal components, the Fetal Growth Longitudinal Study, aimed to develop international fetal growth standards. Each participant had their certain menstrual dates confirmed by first‐trimester ultrasound examination. Fetal head circumference (HC), biparietal diameter (BPD), occipitofrontal diameter (OFD), abdominal circumference (AC) and femur length (FL) were measured every 5 weeks from 14 weeks' gestation until delivery. For each participant, a single, randomly selected ultrasound examination was used to explore all candidate biometric variables and permutations to build models to predict GA. Regression equations were ranked based upon minimization of the mean prediction error, goodness of fit and model complexity. An automated machine learning algorithm, the Genetic Algorithm, was adapted to evaluate &gt; 64 000 potential polynomial equations as predictors. Results Of the 4607 eligible women, 4321 (94%) had a pregnancy without major complications and delivered a live singleton without congenital malformations. After other exclusions (missing measurements in GA window and outliers), the final sample comprised 4229 women. Two skeletal measures, HC and FL, produced the best GA prediction, given by the equation loge(GA) = 0.03243 × (loge(HC))2 + 0.001644 × FL × loge(HC) + 3.813. When FL was not available, the best equation based on HC alone was loge(GA) = 0.05970 × (loge(HC))2 + 0.000000006409 × (HC)3 + 3.3258. The estimated uncertainty of GA prediction (half width 95% interval) was 6–7 days at 14 weeks' gestation, 12–14 days at 26 weeks' gestation and &gt; 14 days in the third trimester. The addition of FL to the HC model led to improved prediction intervals compared with using HC alone, but no further improvement in prediction was afforded by adding AC, BPD or OFD. Equations that included other measurements (BPD, OFD and AC) did not perform better. Conclusions Among women initiating antenatal care late in pregnancy, a single set of ultrasound measurements combining HC and FL in the second trimester can be used to estimate GA with reasonable accuracy. We recommend this tool for underserved populations but considerable efforts should be implemented to improve early initiation of antenatal care worldwide. © 2016 Authors. Ultrasound in Obstetrics &amp; Gynecology published by John Wiley &amp; Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology. Linked Comment: Ultrasound Obstet Gynecol 2016; 48: 693–693</description><identifier>ISSN: 0960-7692</identifier><identifier>EISSN: 1469-0705</identifier><identifier>DOI: 10.1002/uog.15894</identifier><identifier>PMID: 26924421</identifier><identifier>CODEN: UOGYFJ</identifier><language>eng</language><publisher>Chichester, UK: John Wiley &amp; Sons, Ltd</publisher><subject>Adult ; Anthropometry ; Crown-Rump Length ; dating ; Female ; Fetal Development ; fetal growth ; Gestational Age ; Head - diagnostic imaging ; Head - embryology ; Humans ; Longitudinal Studies ; Machine Learning ; Maternal Age ; Original Paper ; Original Papers ; Pregnancy ; Pregnancy Trimester, First ; Prospective Studies ; Ultrasonography, Prenatal - methods</subject><ispartof>Ultrasound in obstetrics &amp; gynecology, 2016-12, Vol.48 (6), p.719-726</ispartof><rights>2016 The Authors. published by John Wiley &amp; Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.</rights><rights>2016 The Authors. Ultrasound in Obstetrics &amp; Gynecology published by John Wiley &amp; Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.</rights><rights>Copyright © 2016 ISUOG. Published by John Wiley &amp; Sons Ltd</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4764-79f3b9513f5e57755cab110c0ba27dc2cb4f1bec58297c4d824c4faefa2bda033</citedby><cites>FETCH-LOGICAL-c4764-79f3b9513f5e57755cab110c0ba27dc2cb4f1bec58297c4d824c4faefa2bda033</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fuog.15894$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fuog.15894$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,1411,1427,27901,27902,45550,45551,46384,46808</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26924421$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Papageorghiou, A. T.</creatorcontrib><creatorcontrib>Kemp, B.</creatorcontrib><creatorcontrib>Stones, W.</creatorcontrib><creatorcontrib>Ohuma, E. O.</creatorcontrib><creatorcontrib>Kennedy, S. H.</creatorcontrib><creatorcontrib>Purwar, M.</creatorcontrib><creatorcontrib>Salomon, L. J.</creatorcontrib><creatorcontrib>Altman, D. G.</creatorcontrib><creatorcontrib>Noble, J. A.</creatorcontrib><creatorcontrib>Bertino, E.</creatorcontrib><creatorcontrib>Gravett, M. G.</creatorcontrib><creatorcontrib>Pang, R.</creatorcontrib><creatorcontrib>Cheikh Ismail, L.</creatorcontrib><creatorcontrib>Barros, F. C.</creatorcontrib><creatorcontrib>Lambert, A.</creatorcontrib><creatorcontrib>Jaffer, Y. A.</creatorcontrib><creatorcontrib>Victora, C. G.</creatorcontrib><creatorcontrib>Bhutta, Z. A.</creatorcontrib><creatorcontrib>Villar, J.</creatorcontrib><creatorcontrib>International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st)</creatorcontrib><creatorcontrib>for the International Fetal and Newborn Growth Consortium for the 21 Century (INTERGROWTH‐21st)</creatorcontrib><title>Ultrasound‐based gestational‐age estimation in late pregnancy</title><title>Ultrasound in obstetrics &amp; gynecology</title><addtitle>Ultrasound Obstet Gynecol</addtitle><description>ABSTRACT Objective Accurate gestational‐age (GA) estimation, preferably by ultrasound measurement of fetal crown–rump length before 14 weeks' gestation, is an important component of high‐quality antenatal care. The objective of this study was to determine how GA can best be estimated by fetal ultrasound for women who present for the first time late in pregnancy with uncertain or unknown menstrual dates. Methods INTERGROWTH‐21st was a large, prospective, multicenter, population‐based project performed in eight geographically defined urban populations. One of its principal components, the Fetal Growth Longitudinal Study, aimed to develop international fetal growth standards. Each participant had their certain menstrual dates confirmed by first‐trimester ultrasound examination. Fetal head circumference (HC), biparietal diameter (BPD), occipitofrontal diameter (OFD), abdominal circumference (AC) and femur length (FL) were measured every 5 weeks from 14 weeks' gestation until delivery. For each participant, a single, randomly selected ultrasound examination was used to explore all candidate biometric variables and permutations to build models to predict GA. Regression equations were ranked based upon minimization of the mean prediction error, goodness of fit and model complexity. An automated machine learning algorithm, the Genetic Algorithm, was adapted to evaluate &gt; 64 000 potential polynomial equations as predictors. Results Of the 4607 eligible women, 4321 (94%) had a pregnancy without major complications and delivered a live singleton without congenital malformations. After other exclusions (missing measurements in GA window and outliers), the final sample comprised 4229 women. Two skeletal measures, HC and FL, produced the best GA prediction, given by the equation loge(GA) = 0.03243 × (loge(HC))2 + 0.001644 × FL × loge(HC) + 3.813. When FL was not available, the best equation based on HC alone was loge(GA) = 0.05970 × (loge(HC))2 + 0.000000006409 × (HC)3 + 3.3258. The estimated uncertainty of GA prediction (half width 95% interval) was 6–7 days at 14 weeks' gestation, 12–14 days at 26 weeks' gestation and &gt; 14 days in the third trimester. The addition of FL to the HC model led to improved prediction intervals compared with using HC alone, but no further improvement in prediction was afforded by adding AC, BPD or OFD. Equations that included other measurements (BPD, OFD and AC) did not perform better. Conclusions Among women initiating antenatal care late in pregnancy, a single set of ultrasound measurements combining HC and FL in the second trimester can be used to estimate GA with reasonable accuracy. We recommend this tool for underserved populations but considerable efforts should be implemented to improve early initiation of antenatal care worldwide. © 2016 Authors. Ultrasound in Obstetrics &amp; Gynecology published by John Wiley &amp; Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology. Linked Comment: Ultrasound Obstet Gynecol 2016; 48: 693–693</description><subject>Adult</subject><subject>Anthropometry</subject><subject>Crown-Rump Length</subject><subject>dating</subject><subject>Female</subject><subject>Fetal Development</subject><subject>fetal growth</subject><subject>Gestational Age</subject><subject>Head - diagnostic imaging</subject><subject>Head - embryology</subject><subject>Humans</subject><subject>Longitudinal Studies</subject><subject>Machine Learning</subject><subject>Maternal Age</subject><subject>Original Paper</subject><subject>Original Papers</subject><subject>Pregnancy</subject><subject>Pregnancy Trimester, First</subject><subject>Prospective Studies</subject><subject>Ultrasonography, Prenatal - methods</subject><issn>0960-7692</issn><issn>1469-0705</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>EIF</sourceid><recordid>eNqNkU9LwzAYh4Mobk4PfgEpeNFDtyTNn-YijKFTGOziziFN09rRNbNZld38CH5GP4nZOocKguQQ-OXh4X3zA-AcwT6CEA8am_cRjQU5AF1EmAghh_QQdKFgMORM4A44cW4OIWQkYsegg31GCEZdMJyVq1o521Tpx9t7opxJg9y4lVoVtlKlz1RuAh8Ui20UFFVQqpUJlrXJK1Xp9Sk4ylTpzNnu7oHZ3e3j6D6cTMcPo-Ek1IQzEnKRRYmgKMqooZxTqlWCENQwUZinGuuEZCgxmsZYcE3SGBNNMmUyhZNUwSjqgZvWu2yShUm1qfzgpVzWfrJ6La0q5M-XqniSuX2RjMUwIsILrnaC2j43fiW5KJw2ZakqYxsnUUwp5EQg8g8UM0Z5xDfWy1_o3Da1_7oNRfyJEEGeum4pXVvnapPt50ZQbjqUvkO57dCzF98X3ZNfpXlg0AKvRWnWf5vkbDpulZ-4AajR</recordid><startdate>201612</startdate><enddate>201612</enddate><creator>Papageorghiou, A. T.</creator><creator>Kemp, B.</creator><creator>Stones, W.</creator><creator>Ohuma, E. O.</creator><creator>Kennedy, S. H.</creator><creator>Purwar, M.</creator><creator>Salomon, L. J.</creator><creator>Altman, D. G.</creator><creator>Noble, J. A.</creator><creator>Bertino, E.</creator><creator>Gravett, M. G.</creator><creator>Pang, R.</creator><creator>Cheikh Ismail, L.</creator><creator>Barros, F. C.</creator><creator>Lambert, A.</creator><creator>Jaffer, Y. A.</creator><creator>Victora, C. G.</creator><creator>Bhutta, Z. A.</creator><creator>Villar, J.</creator><general>John Wiley &amp; Sons, Ltd</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>201612</creationdate><title>Ultrasound‐based gestational‐age estimation in late pregnancy</title><author>Papageorghiou, A. T. ; Kemp, B. ; Stones, W. ; Ohuma, E. O. ; Kennedy, S. H. ; Purwar, M. ; Salomon, L. J. ; Altman, D. G. ; Noble, J. A. ; Bertino, E. ; Gravett, M. G. ; Pang, R. ; Cheikh Ismail, L. ; Barros, F. C. ; Lambert, A. ; Jaffer, Y. A. ; Victora, C. G. ; Bhutta, Z. 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A.</creatorcontrib><creatorcontrib>Villar, J.</creatorcontrib><creatorcontrib>International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st)</creatorcontrib><creatorcontrib>for the International Fetal and Newborn Growth Consortium for the 21 Century (INTERGROWTH‐21st)</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Ultrasound in obstetrics &amp; gynecology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Papageorghiou, A. T.</au><au>Kemp, B.</au><au>Stones, W.</au><au>Ohuma, E. O.</au><au>Kennedy, S. H.</au><au>Purwar, M.</au><au>Salomon, L. J.</au><au>Altman, D. G.</au><au>Noble, J. A.</au><au>Bertino, E.</au><au>Gravett, M. G.</au><au>Pang, R.</au><au>Cheikh Ismail, L.</au><au>Barros, F. C.</au><au>Lambert, A.</au><au>Jaffer, Y. A.</au><au>Victora, C. G.</au><au>Bhutta, Z. A.</au><au>Villar, J.</au><aucorp>International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st)</aucorp><aucorp>for the International Fetal and Newborn Growth Consortium for the 21 Century (INTERGROWTH‐21st)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Ultrasound‐based gestational‐age estimation in late pregnancy</atitle><jtitle>Ultrasound in obstetrics &amp; gynecology</jtitle><addtitle>Ultrasound Obstet Gynecol</addtitle><date>2016-12</date><risdate>2016</risdate><volume>48</volume><issue>6</issue><spage>719</spage><epage>726</epage><pages>719-726</pages><issn>0960-7692</issn><eissn>1469-0705</eissn><coden>UOGYFJ</coden><abstract>ABSTRACT Objective Accurate gestational‐age (GA) estimation, preferably by ultrasound measurement of fetal crown–rump length before 14 weeks' gestation, is an important component of high‐quality antenatal care. The objective of this study was to determine how GA can best be estimated by fetal ultrasound for women who present for the first time late in pregnancy with uncertain or unknown menstrual dates. Methods INTERGROWTH‐21st was a large, prospective, multicenter, population‐based project performed in eight geographically defined urban populations. One of its principal components, the Fetal Growth Longitudinal Study, aimed to develop international fetal growth standards. Each participant had their certain menstrual dates confirmed by first‐trimester ultrasound examination. Fetal head circumference (HC), biparietal diameter (BPD), occipitofrontal diameter (OFD), abdominal circumference (AC) and femur length (FL) were measured every 5 weeks from 14 weeks' gestation until delivery. For each participant, a single, randomly selected ultrasound examination was used to explore all candidate biometric variables and permutations to build models to predict GA. Regression equations were ranked based upon minimization of the mean prediction error, goodness of fit and model complexity. An automated machine learning algorithm, the Genetic Algorithm, was adapted to evaluate &gt; 64 000 potential polynomial equations as predictors. Results Of the 4607 eligible women, 4321 (94%) had a pregnancy without major complications and delivered a live singleton without congenital malformations. After other exclusions (missing measurements in GA window and outliers), the final sample comprised 4229 women. Two skeletal measures, HC and FL, produced the best GA prediction, given by the equation loge(GA) = 0.03243 × (loge(HC))2 + 0.001644 × FL × loge(HC) + 3.813. When FL was not available, the best equation based on HC alone was loge(GA) = 0.05970 × (loge(HC))2 + 0.000000006409 × (HC)3 + 3.3258. The estimated uncertainty of GA prediction (half width 95% interval) was 6–7 days at 14 weeks' gestation, 12–14 days at 26 weeks' gestation and &gt; 14 days in the third trimester. The addition of FL to the HC model led to improved prediction intervals compared with using HC alone, but no further improvement in prediction was afforded by adding AC, BPD or OFD. Equations that included other measurements (BPD, OFD and AC) did not perform better. Conclusions Among women initiating antenatal care late in pregnancy, a single set of ultrasound measurements combining HC and FL in the second trimester can be used to estimate GA with reasonable accuracy. We recommend this tool for underserved populations but considerable efforts should be implemented to improve early initiation of antenatal care worldwide. © 2016 Authors. Ultrasound in Obstetrics &amp; Gynecology published by John Wiley &amp; Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology. Linked Comment: Ultrasound Obstet Gynecol 2016; 48: 693–693</abstract><cop>Chichester, UK</cop><pub>John Wiley &amp; Sons, Ltd</pub><pmid>26924421</pmid><doi>10.1002/uog.15894</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record>
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subjects Adult
Anthropometry
Crown-Rump Length
dating
Female
Fetal Development
fetal growth
Gestational Age
Head - diagnostic imaging
Head - embryology
Humans
Longitudinal Studies
Machine Learning
Maternal Age
Original Paper
Original Papers
Pregnancy
Pregnancy Trimester, First
Prospective Studies
Ultrasonography, Prenatal - methods
title Ultrasound‐based gestational‐age estimation in late pregnancy
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