Identification of high-risk patients for adverse pregnancy outcome based on multivariate logistic regression analysis at 20–23 gestational weeks

Aims: To establish and test a multivariate approach for identification of patients with high risk for adverse pregnancy outcome (APO) by a combination of sonographic (20+0–23+6 weeks) and biometrical data in a test group and to prove its effectiveness in a validation group. Methods: In order to deve...

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Veröffentlicht in:Journal of perinatal medicine 2011-11, Vol.39 (6), p.667-672
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description Aims: To establish and test a multivariate approach for identification of patients with high risk for adverse pregnancy outcome (APO) by a combination of sonographic (20+0–23+6 weeks) and biometrical data in a test group and to prove its effectiveness in a validation group. Methods: In order to develop a multivariate approach for identifying patients at high risk for APO, data from 15,855 non-treated singleton pregnancies (test group A), with well-known outcomes, were analysed retrospectively. Registered parameters were parity, body mass index (BMI), mean of pulsatility index of both uterine arteries (meanPI), presence of notch, and depth of notch described as the mean of the notch index of both uterine arteries (meanNI). In a second step, the model was validated in 3678 subsequent non-treated singleton pregnancies (validation group B). Results: In test group A, the calculated probabilities of APO were found between 1.3% and 82.8%, with the 95th centile at 11.2% and the 99th centile at 28.3%. In validation group B, in patients with a low calculated risk for APO 28%, complications were found in 39.1%. Conclusion: A multivariate approach toward risk-assessment of APO seems to be a promising method for identifying patients who are at high risk for APO. Besides the individual consequence of intensive surveillance, the identification of groups of patients at high risk for APO might serve as a basis for interventional studies.
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Methods: In order to develop a multivariate approach for identifying patients at high risk for APO, data from 15,855 non-treated singleton pregnancies (test group A), with well-known outcomes, were analysed retrospectively. Registered parameters were parity, body mass index (BMI), mean of pulsatility index of both uterine arteries (meanPI), presence of notch, and depth of notch described as the mean of the notch index of both uterine arteries (meanNI). In a second step, the model was validated in 3678 subsequent non-treated singleton pregnancies (validation group B). Results: In test group A, the calculated probabilities of APO were found between 1.3% and 82.8%, with the 95th centile at 11.2% and the 99th centile at 28.3%. In validation group B, in patients with a low calculated risk for APO &lt;10%, complications were found in 4.4%. In patients with an intermediate risk of APO between 10% and 28%, complications were found in 10.7%. In patients from group B who were identified to be at high risk with a calculated probability of APO &gt;28%, complications were found in 39.1%. Conclusion: A multivariate approach toward risk-assessment of APO seems to be a promising method for identifying patients who are at high risk for APO. Besides the individual consequence of intensive surveillance, the identification of groups of patients at high risk for APO might serve as a basis for interventional studies.</description><identifier>ISSN: 0300-5577</identifier><identifier>EISSN: 1619-3997</identifier><identifier>DOI: 10.1515/JPM.2011.079</identifier><identifier>PMID: 21919546</identifier><identifier>CODEN: JPEMAO</identifier><language>eng</language><publisher>Berlin: Walter de Gruyter</publisher><subject>Adolescent ; Adult ; Adverse pregnancy outcome ; Algorithms ; Biological and medical sciences ; Body Mass Index ; Delivery. Postpartum. Lactation ; Epidemiology ; Female ; General aspects ; Gestational Age ; Gynecology. Andrology. Obstetrics ; Humans ; Logistic Models ; Maternal Age ; Medical sciences ; Middle Aged ; Multivariate Analysis ; notch index ; Parity ; prediction ; Pregnancy ; Pregnancy Complications - diagnosis ; Pregnancy Complications - diagnostic imaging ; Pregnancy Complications - etiology ; Pregnancy Outcome ; Pregnancy Trimester, Second ; Public health. Hygiene ; Public health. 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In patients from group B who were identified to be at high risk with a calculated probability of APO &gt;28%, complications were found in 39.1%. Conclusion: A multivariate approach toward risk-assessment of APO seems to be a promising method for identifying patients who are at high risk for APO. Besides the individual consequence of intensive surveillance, the identification of groups of patients at high risk for APO might serve as a basis for interventional studies.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Adverse pregnancy outcome</subject><subject>Algorithms</subject><subject>Biological and medical sciences</subject><subject>Body Mass Index</subject><subject>Delivery. Postpartum. Lactation</subject><subject>Epidemiology</subject><subject>Female</subject><subject>General aspects</subject><subject>Gestational Age</subject><subject>Gynecology. Andrology. Obstetrics</subject><subject>Humans</subject><subject>Logistic Models</subject><subject>Maternal Age</subject><subject>Medical sciences</subject><subject>Middle Aged</subject><subject>Multivariate Analysis</subject><subject>notch index</subject><subject>Parity</subject><subject>prediction</subject><subject>Pregnancy</subject><subject>Pregnancy Complications - diagnosis</subject><subject>Pregnancy Complications - diagnostic imaging</subject><subject>Pregnancy Complications - etiology</subject><subject>Pregnancy Outcome</subject><subject>Pregnancy Trimester, Second</subject><subject>Public health. Hygiene</subject><subject>Public health. Hygiene-occupational medicine</subject><subject>Retrospective Studies</subject><subject>Risk Assessment</subject><subject>Risk Factors</subject><subject>Ultrasonography, Doppler</subject><subject>Ultrasonography, Prenatal</subject><subject>Uterine Artery - diagnostic imaging</subject><subject>Young Adult</subject><issn>0300-5577</issn><issn>1619-3997</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNptkc9uEzEQxlcIREPhxhn5griwwV7b65hbqSgtFAFSEdysiXc2dbJ_gme3JTeeAd6QJ8FpQrlwsuX5zTfj78uyx4JPhRb6xduP76cFF2LKjb2TTUQpbC6tNXezCZec51obc5A9IFpyLrTWxf3soBBWWK3KSfbzrMJuCHXwMIS-Y33NLsPiMo-BVmyd3lKVWN1HBtUVRkK2jrjooPMb1o-D71tkcyCsWGpux2YIVxADDMiafhFoCJ4lPiLRVh06aDYUiMHACv77x69CsgXScDMbGnaNuKKH2b0aGsJH-_Mw-3zy-uL4ND__8Obs-Og898roIVfaopelFUJamGOpZspKY2UtfCUUYFEhVlwaYUpeCYuKiwI0mPlMKoEzLw-zZzvddey_jWkL1wby2DTQYT-Ss1wKNZuZIpHPd6SPPVHE2q1jaCFunOBuG4Jbrlu3DcGlEBL-ZC88zlusbuG_rifg6R4A8tDUMdkZ6B-nzM2vEvdyx11DM2CskpHjJl3csh9j8ov-P9-WZWlSc75rTing91txiCuXqka7TxfKnXx9Zbj98s6dyj-ZQbTM</recordid><startdate>20111101</startdate><enddate>20111101</enddate><creator>Becker, Rolf</creator><general>Walter de Gruyter</general><general>De Gruyter</general><scope>BSCLL</scope><scope>IQODW</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>7X8</scope></search><sort><creationdate>20111101</creationdate><title>Identification of high-risk patients for adverse pregnancy outcome based on multivariate logistic regression analysis at 20–23 gestational weeks</title><author>Becker, Rolf</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c475t-459ec3691139abe648493793f1cd14ae2deed0371760d19e4012a5a7b8341e8c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Adverse pregnancy outcome</topic><topic>Algorithms</topic><topic>Biological and medical sciences</topic><topic>Body Mass Index</topic><topic>Delivery. Postpartum. Lactation</topic><topic>Epidemiology</topic><topic>Female</topic><topic>General aspects</topic><topic>Gestational Age</topic><topic>Gynecology. Andrology. Obstetrics</topic><topic>Humans</topic><topic>Logistic Models</topic><topic>Maternal Age</topic><topic>Medical sciences</topic><topic>Middle Aged</topic><topic>Multivariate Analysis</topic><topic>notch index</topic><topic>Parity</topic><topic>prediction</topic><topic>Pregnancy</topic><topic>Pregnancy Complications - diagnosis</topic><topic>Pregnancy Complications - diagnostic imaging</topic><topic>Pregnancy Complications - etiology</topic><topic>Pregnancy Outcome</topic><topic>Pregnancy Trimester, Second</topic><topic>Public health. Hygiene</topic><topic>Public health. Hygiene-occupational medicine</topic><topic>Retrospective Studies</topic><topic>Risk Assessment</topic><topic>Risk Factors</topic><topic>Ultrasonography, Doppler</topic><topic>Ultrasonography, Prenatal</topic><topic>Uterine Artery - diagnostic imaging</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Becker, Rolf</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of perinatal medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Becker, Rolf</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of high-risk patients for adverse pregnancy outcome based on multivariate logistic regression analysis at 20–23 gestational weeks</atitle><jtitle>Journal of perinatal medicine</jtitle><addtitle>Journal of Perinatal Medicine</addtitle><date>2011-11-01</date><risdate>2011</risdate><volume>39</volume><issue>6</issue><spage>667</spage><epage>672</epage><pages>667-672</pages><issn>0300-5577</issn><eissn>1619-3997</eissn><coden>JPEMAO</coden><abstract>Aims: To establish and test a multivariate approach for identification of patients with high risk for adverse pregnancy outcome (APO) by a combination of sonographic (20+0–23+6 weeks) and biometrical data in a test group and to prove its effectiveness in a validation group. Methods: In order to develop a multivariate approach for identifying patients at high risk for APO, data from 15,855 non-treated singleton pregnancies (test group A), with well-known outcomes, were analysed retrospectively. Registered parameters were parity, body mass index (BMI), mean of pulsatility index of both uterine arteries (meanPI), presence of notch, and depth of notch described as the mean of the notch index of both uterine arteries (meanNI). In a second step, the model was validated in 3678 subsequent non-treated singleton pregnancies (validation group B). Results: In test group A, the calculated probabilities of APO were found between 1.3% and 82.8%, with the 95th centile at 11.2% and the 99th centile at 28.3%. In validation group B, in patients with a low calculated risk for APO &lt;10%, complications were found in 4.4%. In patients with an intermediate risk of APO between 10% and 28%, complications were found in 10.7%. In patients from group B who were identified to be at high risk with a calculated probability of APO &gt;28%, complications were found in 39.1%. Conclusion: A multivariate approach toward risk-assessment of APO seems to be a promising method for identifying patients who are at high risk for APO. Besides the individual consequence of intensive surveillance, the identification of groups of patients at high risk for APO might serve as a basis for interventional studies.</abstract><cop>Berlin</cop><pub>Walter de Gruyter</pub><pmid>21919546</pmid><doi>10.1515/JPM.2011.079</doi><tpages>6</tpages></addata></record>
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source MEDLINE; De Gruyter journals
subjects Adolescent
Adult
Adverse pregnancy outcome
Algorithms
Biological and medical sciences
Body Mass Index
Delivery. Postpartum. Lactation
Epidemiology
Female
General aspects
Gestational Age
Gynecology. Andrology. Obstetrics
Humans
Logistic Models
Maternal Age
Medical sciences
Middle Aged
Multivariate Analysis
notch index
Parity
prediction
Pregnancy
Pregnancy Complications - diagnosis
Pregnancy Complications - diagnostic imaging
Pregnancy Complications - etiology
Pregnancy Outcome
Pregnancy Trimester, Second
Public health. Hygiene
Public health. Hygiene-occupational medicine
Retrospective Studies
Risk Assessment
Risk Factors
Ultrasonography, Doppler
Ultrasonography, Prenatal
Uterine Artery - diagnostic imaging
Young Adult
title Identification of high-risk patients for adverse pregnancy outcome based on multivariate logistic regression analysis at 20–23 gestational weeks
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