Clinical predictive score for shoulder dystocia

© JOURNAL OF THE MEDICAL ASSOCIATION OF THAILAND| 2020 Objective: To develop a new risk score as a predictive tool from clinical risk factors for determining high-risk pregnancy with shoulder dystocia. Materials and Methods: A retrospective study was performed. The demographic data, prenatal care hi...

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Main Authors: N. Vorathiankul, C. Tanprasertkul, C. Ruengorn, T. Nanthakomon, N. Vinayanuvattikhun, C. Somprasit
Format: Journal
Published: 2020
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/70952
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spelling th-cmuir.6653943832-709522020-10-14T08:45:27Z Clinical predictive score for shoulder dystocia N. Vorathiankul C. Tanprasertkul C. Ruengorn T. Nanthakomon N. Vinayanuvattikhun C. Somprasit Medicine © JOURNAL OF THE MEDICAL ASSOCIATION OF THAILAND| 2020 Objective: To develop a new risk score as a predictive tool from clinical risk factors for determining high-risk pregnancy with shoulder dystocia. Materials and Methods: A retrospective study was performed. The demographic data, prenatal care history, and the risk factors, such as total weight gain, estimated fetal weight, and the instrumental assisted vaginal delivery (InVD), were recorded and compared between the shoulder dystocia (SD) and non-shoulder dystocia (non-SD) groups. The risk score for prediction was developed by multivariate logistic regression analysis. Results: Of 872 vaginal deliveries, 42 SD cases were collected and 830 non-SD cases were included. In a multivariate analysis, there were three clinical risk factors, statistically significant; total weight gain >16 kg (TWG16), Estimated fetal weight >3,200 grams (EFW3200) and the InVD. The odd ratios of these risk factors were calculated and converted to the risk score. The final score model to predict shoulder dystocia had receiver operating characteristic curve of 79.73%. Each patient was given a score as the presented risks; TWG16 = 2, EFW3200 = 3, and InVD = 5. Then, the summation of the score was divided into low-, intermediate-, and high-risk groups at cut off value scores of 0 to 4, 5 to 6, and >7, respectively. Positive likelihood ratio in those groups were 0.12, 5.94 and 10.97, in orderly, with statistically significance (p-value <0.001). Conclusion: The study has developed an easy and practical new risk score for predicting pregnant women who at risk of shoulder dystocia. 2020-10-14T08:45:27Z 2020-10-14T08:45:27Z 2020-01-01 Journal 01252208 2-s2.0-85082496159 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85082496159&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/70952
institution Chiang Mai University
building Chiang Mai University Library
continent Asia
country Thailand
Thailand
content_provider Chiang Mai University Library
collection CMU Intellectual Repository
topic Medicine
spellingShingle Medicine
N. Vorathiankul
C. Tanprasertkul
C. Ruengorn
T. Nanthakomon
N. Vinayanuvattikhun
C. Somprasit
Clinical predictive score for shoulder dystocia
description © JOURNAL OF THE MEDICAL ASSOCIATION OF THAILAND| 2020 Objective: To develop a new risk score as a predictive tool from clinical risk factors for determining high-risk pregnancy with shoulder dystocia. Materials and Methods: A retrospective study was performed. The demographic data, prenatal care history, and the risk factors, such as total weight gain, estimated fetal weight, and the instrumental assisted vaginal delivery (InVD), were recorded and compared between the shoulder dystocia (SD) and non-shoulder dystocia (non-SD) groups. The risk score for prediction was developed by multivariate logistic regression analysis. Results: Of 872 vaginal deliveries, 42 SD cases were collected and 830 non-SD cases were included. In a multivariate analysis, there were three clinical risk factors, statistically significant; total weight gain >16 kg (TWG16), Estimated fetal weight >3,200 grams (EFW3200) and the InVD. The odd ratios of these risk factors were calculated and converted to the risk score. The final score model to predict shoulder dystocia had receiver operating characteristic curve of 79.73%. Each patient was given a score as the presented risks; TWG16 = 2, EFW3200 = 3, and InVD = 5. Then, the summation of the score was divided into low-, intermediate-, and high-risk groups at cut off value scores of 0 to 4, 5 to 6, and >7, respectively. Positive likelihood ratio in those groups were 0.12, 5.94 and 10.97, in orderly, with statistically significance (p-value <0.001). Conclusion: The study has developed an easy and practical new risk score for predicting pregnant women who at risk of shoulder dystocia.
format Journal
author N. Vorathiankul
C. Tanprasertkul
C. Ruengorn
T. Nanthakomon
N. Vinayanuvattikhun
C. Somprasit
author_facet N. Vorathiankul
C. Tanprasertkul
C. Ruengorn
T. Nanthakomon
N. Vinayanuvattikhun
C. Somprasit
author_sort N. Vorathiankul
title Clinical predictive score for shoulder dystocia
title_short Clinical predictive score for shoulder dystocia
title_full Clinical predictive score for shoulder dystocia
title_fullStr Clinical predictive score for shoulder dystocia
title_full_unstemmed Clinical predictive score for shoulder dystocia
title_sort clinical predictive score for shoulder dystocia
publishDate 2020
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85082496159&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/70952
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