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Maternal near-miss prediction model development among pregnant women in Bahir Dar City administration, northwest Ethiopia: a study protocol

INTRODUCTION: Maternal near-miss is a condition when a woman nearly died but survived from complications that happened during pregnancy, childbirth or within 42 days after delivery. Maternal near-miss is more prevalent among women in developing nations. Previous studies have identified the impact of...

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Autores principales: Workineh, Yinager, Alene, Getu Degu, Fekadu, Gedefaw Abeje
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10649620/
https://www.ncbi.nlm.nih.gov/pubmed/37963695
http://dx.doi.org/10.1136/bmjopen-2023-074215
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author Workineh, Yinager
Alene, Getu Degu
Fekadu, Gedefaw Abeje
author_facet Workineh, Yinager
Alene, Getu Degu
Fekadu, Gedefaw Abeje
author_sort Workineh, Yinager
collection PubMed
description INTRODUCTION: Maternal near-miss is a condition when a woman nearly died but survived from complications that happened during pregnancy, childbirth or within 42 days after delivery. Maternal near-miss is more prevalent among women in developing nations. Previous studies have identified the impact of different predictor variables on maternal near-miss but shared prognostic predictors are not adequately explored in Ethiopia. It is therefore necessary to build a clinical prediction model for maternal near-misses in Ethiopia. Hence, the aim of this study is to develop and validate a prognostic prediction model, and generate a risk score for maternal near-miss among pregnant women in Bahir Dar City Administration. METHODS AND ANALYSIS: A prospective follow-up study design will be employed among 2110 selected pregnant women in the Bahir Dar City administration from 1 May 2023 to 1 April 2024. At the initial antenatal visit, pregnant women will be systematically selected. Then, they will be followed until 42 days following birth. Data will be collected using structured questionnaires and data extraction sheet. The model will be created using Cox proportional hazard regression analysis. The performance of the model will be assessed based on its capacity for discrimination using c-index and calibration using calibration plot, intercept and slope. The model’s internal validity will be evaluated through the bootstrapping method. Ultimately, the model will be illustrated through a nomogram and decision tree, which will be made available to prospective users. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Institutional Review Board of the College of Medicine and Health Sciences, Bahir Dar University (protocol number 704/2023). Findings will be published in peer-reviewed journals and local and international seminars, conferences, symposiums and workshops. Manuscripts will be prepared and published in scientifically reputable journals. In addition, policy briefs will be prepared.
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spelling pubmed-106496202023-11-14 Maternal near-miss prediction model development among pregnant women in Bahir Dar City administration, northwest Ethiopia: a study protocol Workineh, Yinager Alene, Getu Degu Fekadu, Gedefaw Abeje BMJ Open Health Services Research INTRODUCTION: Maternal near-miss is a condition when a woman nearly died but survived from complications that happened during pregnancy, childbirth or within 42 days after delivery. Maternal near-miss is more prevalent among women in developing nations. Previous studies have identified the impact of different predictor variables on maternal near-miss but shared prognostic predictors are not adequately explored in Ethiopia. It is therefore necessary to build a clinical prediction model for maternal near-misses in Ethiopia. Hence, the aim of this study is to develop and validate a prognostic prediction model, and generate a risk score for maternal near-miss among pregnant women in Bahir Dar City Administration. METHODS AND ANALYSIS: A prospective follow-up study design will be employed among 2110 selected pregnant women in the Bahir Dar City administration from 1 May 2023 to 1 April 2024. At the initial antenatal visit, pregnant women will be systematically selected. Then, they will be followed until 42 days following birth. Data will be collected using structured questionnaires and data extraction sheet. The model will be created using Cox proportional hazard regression analysis. The performance of the model will be assessed based on its capacity for discrimination using c-index and calibration using calibration plot, intercept and slope. The model’s internal validity will be evaluated through the bootstrapping method. Ultimately, the model will be illustrated through a nomogram and decision tree, which will be made available to prospective users. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Institutional Review Board of the College of Medicine and Health Sciences, Bahir Dar University (protocol number 704/2023). Findings will be published in peer-reviewed journals and local and international seminars, conferences, symposiums and workshops. Manuscripts will be prepared and published in scientifically reputable journals. In addition, policy briefs will be prepared. BMJ Publishing Group 2023-11-14 /pmc/articles/PMC10649620/ /pubmed/37963695 http://dx.doi.org/10.1136/bmjopen-2023-074215 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Health Services Research
Workineh, Yinager
Alene, Getu Degu
Fekadu, Gedefaw Abeje
Maternal near-miss prediction model development among pregnant women in Bahir Dar City administration, northwest Ethiopia: a study protocol
title Maternal near-miss prediction model development among pregnant women in Bahir Dar City administration, northwest Ethiopia: a study protocol
title_full Maternal near-miss prediction model development among pregnant women in Bahir Dar City administration, northwest Ethiopia: a study protocol
title_fullStr Maternal near-miss prediction model development among pregnant women in Bahir Dar City administration, northwest Ethiopia: a study protocol
title_full_unstemmed Maternal near-miss prediction model development among pregnant women in Bahir Dar City administration, northwest Ethiopia: a study protocol
title_short Maternal near-miss prediction model development among pregnant women in Bahir Dar City administration, northwest Ethiopia: a study protocol
title_sort maternal near-miss prediction model development among pregnant women in bahir dar city administration, northwest ethiopia: a study protocol
topic Health Services Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10649620/
https://www.ncbi.nlm.nih.gov/pubmed/37963695
http://dx.doi.org/10.1136/bmjopen-2023-074215
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