Prediction instrument for obstructed labor
<p><strong><em>Background:</em></strong><em> Obstructed labor is a complication during childbirth that can increase maternal and neonatal mortality and morbidity, making early detection crucial for prevention. However, currently, no instrument is available to pred...
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| Format: | Article |
| Language: | Indonesian |
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Alma Ata University Press
2025-06-01
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| Series: | Jurnal Ners dan Kebidanan Indonesia |
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| Online Access: | https://ejournal.almaata.ac.id/index.php/JNKI/article/view/5419 |
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| author | Rafhani Rosyidah Nurul Azizah Evi Rinata |
| author_facet | Rafhani Rosyidah Nurul Azizah Evi Rinata |
| author_sort | Rafhani Rosyidah |
| collection | DOAJ |
| description | <p><strong><em>Background:</em></strong><em> Obstructed labor is a complication during childbirth that can increase maternal and neonatal mortality and morbidity, making early detection crucial for prevention. However, currently, no instrument is available to predict the occurrence of obstructed labor.</em></p><p><strong><em>Objectives:</em></strong><em> This study aims to develop an effective prediction instrument for the early identification of obstructed labor, enabling timely interventions to reduce associated risks. </em></p><p><strong><em>Methods:</em></strong><em> The study employs a case-control design for the development of the instrument and a cohort design for its testing. The research is conducted in three phases: Phase I involves a literature review to identify risk factors, Phase II focuses on the initial testing of the instrument, and Phase III includes the validation of the instrument in a clinical setting. The study population consists of 360 women in labor for instrument development and 40 women for instrument testing. Bivariate analysis is conducted using chi-square tests, while multivariate analysis is performed using logistic regression, followed by ROC curve analysis to determine the optimal cutoff point. </em></p><p><strong><em>Results:</em></strong><em> The results indicate significant associations between obstructed labor and factors such as infant birth weight, maternal height, age, obesity, upper arm circumference, anemia, history of abdominal surgery, and weight gain during pregnancy. The final predictive model demonstrated an AUC of 0.908, indicating excellent predictive performance with a sensitivity of 85.7% and specificity of 80.8%. </em></p><strong><em>Conclusions:</em></strong><em> This study highlights the importance of early risk detection and intervention and contributes to the literature by providing an instrument capable of predicting the risk of obstructed labor.</em> |
| format | Article |
| id | doaj-art-ad516b9e49f84bc399c3079b795b7e92 |
| institution | DOAJ |
| issn | 2354-7642 2503-1856 |
| language | Indonesian |
| publishDate | 2025-06-01 |
| publisher | Alma Ata University Press |
| record_format | Article |
| series | Jurnal Ners dan Kebidanan Indonesia |
| spelling | doaj-art-ad516b9e49f84bc399c3079b795b7e922025-08-20T03:13:33ZindAlma Ata University PressJurnal Ners dan Kebidanan Indonesia2354-76422503-18562025-06-0113222623710.21927/jnki.2025.13(2).226-2371822Prediction instrument for obstructed laborRafhani Rosyidah0Nurul Azizah1Evi Rinata2Universitas Muhamamdiyah SidoarjoUniversitas Muhammadiyah SidoarjoUniversitas Muhammadiyah Sidoarjo<p><strong><em>Background:</em></strong><em> Obstructed labor is a complication during childbirth that can increase maternal and neonatal mortality and morbidity, making early detection crucial for prevention. However, currently, no instrument is available to predict the occurrence of obstructed labor.</em></p><p><strong><em>Objectives:</em></strong><em> This study aims to develop an effective prediction instrument for the early identification of obstructed labor, enabling timely interventions to reduce associated risks. </em></p><p><strong><em>Methods:</em></strong><em> The study employs a case-control design for the development of the instrument and a cohort design for its testing. The research is conducted in three phases: Phase I involves a literature review to identify risk factors, Phase II focuses on the initial testing of the instrument, and Phase III includes the validation of the instrument in a clinical setting. The study population consists of 360 women in labor for instrument development and 40 women for instrument testing. Bivariate analysis is conducted using chi-square tests, while multivariate analysis is performed using logistic regression, followed by ROC curve analysis to determine the optimal cutoff point. </em></p><p><strong><em>Results:</em></strong><em> The results indicate significant associations between obstructed labor and factors such as infant birth weight, maternal height, age, obesity, upper arm circumference, anemia, history of abdominal surgery, and weight gain during pregnancy. The final predictive model demonstrated an AUC of 0.908, indicating excellent predictive performance with a sensitivity of 85.7% and specificity of 80.8%. </em></p><strong><em>Conclusions:</em></strong><em> This study highlights the importance of early risk detection and intervention and contributes to the literature by providing an instrument capable of predicting the risk of obstructed labor.</em>https://ejournal.almaata.ac.id/index.php/JNKI/article/view/5419obstructed laborpredictionscore |
| spellingShingle | Rafhani Rosyidah Nurul Azizah Evi Rinata Prediction instrument for obstructed labor Jurnal Ners dan Kebidanan Indonesia obstructed labor prediction score |
| title | Prediction instrument for obstructed labor |
| title_full | Prediction instrument for obstructed labor |
| title_fullStr | Prediction instrument for obstructed labor |
| title_full_unstemmed | Prediction instrument for obstructed labor |
| title_short | Prediction instrument for obstructed labor |
| title_sort | prediction instrument for obstructed labor |
| topic | obstructed labor prediction score |
| url | https://ejournal.almaata.ac.id/index.php/JNKI/article/view/5419 |
| work_keys_str_mv | AT rafhanirosyidah predictioninstrumentforobstructedlabor AT nurulazizah predictioninstrumentforobstructedlabor AT evirinata predictioninstrumentforobstructedlabor |