Case Control Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Aug 6, 2024; 12(22): 4865-4872
Published online Aug 6, 2024. doi: 10.12998/wjcc.v12.i22.4865
Predictive model for postpartum hemorrhage requiring hysterectomy in a minority ethnic region
Ling Wang, Jun-Yu Pan
Ling Wang, Jun-Yu Pan, Intensive Care Unit, People's Hospital of Qiandongnan Miao and Dong Autonomous Prefecture, Kaili 556000, Guizhou Province, China
Co-first authors: Ling Wang and Jun Yu Pan.
Author contributions: Wang L contributed to the research design, research implementation, data management, statistical analysis, manuscript writing-review and editing; Pan JY contributed to the research conduct, data organization, research execution, review. Wang L and Pan JY equally contributed to the research implementation and manuscript writing.
Supported by Qiandongnan Prefecture Science and Technology Support Plan, No. [2021]11; and Training of High Level Innovative Talents in Guizhou Province, No. [2022]201701.
Institutional review board statement: The Medical Ethics Committee of People's Hospital of Qiandongnan Miao and Dong Autonomous Prefecture provided approval for the study (No. 2017008).
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: No benefits in any form have been received or will be received from a commercial party related directly or indirectly to the subject of this article.
Data sharing statement: Dataset available from the corresponding author at 463082910@qq.com.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (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 and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Ling Wang, MBBS, Chief Physician, Intensive Care Unit, People's Hospital of Qiandongnan Miao and Dong Autonomous Prefecture, No. 31 Shaoshan South Road, Kaili 556000, Guizhou Province, China. 463082910@qq.com
Received: April 19, 2024
Revised: May 23, 2024
Accepted: June 11, 2024
Published online: August 6, 2024
Processing time: 74 Days and 4.6 Hours
Abstract
BACKGROUND

Postpartum hemorrhage (PPH) is a leading cause of maternal mortality, and hysterectomy is an important intervention for managing intractable PPH. Accurately predicting the need for hysterectomy and taking proactive emergency measures is crucial for reducing mortality rates.

AIM

To develop a risk prediction model for PPH requiring hysterectomy in the ethnic minority regions of Qiandongnan, China, to help guide clinical decision-making.

METHODS

The study included 23490 patients, with 1050 having experienced PPH and 74 who underwent hysterectomies. The independent risk factors closely associated with the necessity for hysterectomy were analyzed to construct a risk prediction model, and its predictive efficacy was subsequently evaluated.

RESULTS

The proportion of hysterectomies among the included patients was 0.32% (74/23490), representing 7.05% (74/1050) of PPH cases. The number of deliveries, history of cesarean section, placenta previa, uterine atony, and placenta accreta were identified in this population as independent risk factors for requiring a hysterectomy. Receiver operating characteristic curve analysis of the prediction model showed an area under the curve of 0.953 (95% confidence interval: 0.928-0.978) with a sensitivity of 90.50% and a specificity of 90.70%.

CONCLUSION

The model demonstrates excellent predictive power and is effective in guiding clinical decisions regarding PPH in the ethnic minority regions of Qiandongnan, China.

Keywords: Region; Ethnicity; Postpartum hemorrhage; Hysterectomy; Risk factors; Prediction

Core Tip: This study developed a risk prediction model for hysterectomy following postpartum hemorrhage (PPH) in ethnic minority regions. A total of 23490 patients were included, with 1050 cases of PPH and 74 cases undergoing hysterectomy, accounting for 7.05% of PPH cases. History of cesarean section, placenta previa, uterine atony, placenta accreta and multiple deliveries were identified as independent risk factors for hysterectomy. The model demonstrated strong predictive capability, with an area under the receiver operating characteristic curve of 0.953, sensitivity of 90.50%, and specificity of 90.70%. This model provides valuable guidance for clinical decision-making regarding PPH.