预测产后出血的风险评估工具

IF 4.7 3区 医学 Q1 ANESTHESIOLOGY Best Practice & Research-Clinical Anaesthesiology Pub Date : 2022-12-01 DOI:10.1016/j.bpa.2022.08.003
Holly B. Ende MD (Assistant Professor of Anesthesiology)
{"title":"预测产后出血的风险评估工具","authors":"Holly B. Ende MD (Assistant Professor of Anesthesiology)","doi":"10.1016/j.bpa.2022.08.003","DOIUrl":null,"url":null,"abstract":"<div><p>Postpartum hemorrhage<span> (PPH) is a leading cause of maternal morbidity and mortality, and accurate risk assessments may allow providers to anticipate and prevent serious hemorrhage-related adverse events. Multiple category-based tools have been developed by national societies through expert consensus, and these tools assign low, medium, or high risk of hemorrhage based on a review of each patient's risk factors. Validation studies of these tools show varying performance, with a wide range of positive and negative predictive values. Risk prediction models for PPH have been developed and studied, and these models offer the advantage of more nuanced and individualized prediction. However, there are no published studies demonstrating external validation or successful clinical use of such models. Future work should include refinement of these models, study of best practices for implementation, and ultimately linkage of prediction to improved patient outcomes.</span></p></div>","PeriodicalId":48541,"journal":{"name":"Best Practice & Research-Clinical Anaesthesiology","volume":"36 3","pages":"Pages 341-348"},"PeriodicalIF":4.7000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Risk assessment tools to predict postpartum hemorrhage\",\"authors\":\"Holly B. Ende MD (Assistant Professor of Anesthesiology)\",\"doi\":\"10.1016/j.bpa.2022.08.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Postpartum hemorrhage<span> (PPH) is a leading cause of maternal morbidity and mortality, and accurate risk assessments may allow providers to anticipate and prevent serious hemorrhage-related adverse events. Multiple category-based tools have been developed by national societies through expert consensus, and these tools assign low, medium, or high risk of hemorrhage based on a review of each patient's risk factors. Validation studies of these tools show varying performance, with a wide range of positive and negative predictive values. Risk prediction models for PPH have been developed and studied, and these models offer the advantage of more nuanced and individualized prediction. However, there are no published studies demonstrating external validation or successful clinical use of such models. Future work should include refinement of these models, study of best practices for implementation, and ultimately linkage of prediction to improved patient outcomes.</span></p></div>\",\"PeriodicalId\":48541,\"journal\":{\"name\":\"Best Practice & Research-Clinical Anaesthesiology\",\"volume\":\"36 3\",\"pages\":\"Pages 341-348\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Best Practice & Research-Clinical Anaesthesiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1521689622000453\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ANESTHESIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Best Practice & Research-Clinical Anaesthesiology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1521689622000453","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ANESTHESIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

产后出血(PPH)是产妇发病和死亡的主要原因,准确的风险评估可以让提供者预测和预防严重的出血相关不良事件。通过专家共识,国家学会开发了多种基于分类的工具,这些工具根据对每位患者风险因素的审查来分配低、中或高风险的出血。这些工具的验证研究显示出不同的性能,具有广泛的正面和负面预测值。PPH的风险预测模型已经被开发和研究,这些模型提供了更细致和个性化的预测的优势。然而,没有发表的研究证明外部验证或成功的临床使用这些模型。未来的工作应包括改进这些模型,研究实施的最佳实践,并最终将预测与改善患者预后联系起来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Risk assessment tools to predict postpartum hemorrhage

Postpartum hemorrhage (PPH) is a leading cause of maternal morbidity and mortality, and accurate risk assessments may allow providers to anticipate and prevent serious hemorrhage-related adverse events. Multiple category-based tools have been developed by national societies through expert consensus, and these tools assign low, medium, or high risk of hemorrhage based on a review of each patient's risk factors. Validation studies of these tools show varying performance, with a wide range of positive and negative predictive values. Risk prediction models for PPH have been developed and studied, and these models offer the advantage of more nuanced and individualized prediction. However, there are no published studies demonstrating external validation or successful clinical use of such models. Future work should include refinement of these models, study of best practices for implementation, and ultimately linkage of prediction to improved patient outcomes.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
37
审稿时长
36 days
期刊最新文献
Editorial Board Non-neuraxial labour analgesia Preeclampsia and eclampsia: Enhanced detection and treatment for morbidity reduction Initiation and maintenance of neuraxial labour analgesia: A narrative review Epidemiology, trends, and disparities in maternal mortality: A framework for obstetric anesthesiologists
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1