Validation of Early Warning Systems for Severe Maternal Morbidity and Individualised Prediction of Severe Maternal Morbidity within Ethnic Groups

严重孕产妇发病早期预警系统的验证以及族群内严重孕产妇发病的个性化预测

• 批准号: MR/X006115/1
• 负责人: Ian Henderson
• 金额: $ 34.9万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FX006115%2F1
• 关键词: Validation; Early; Warning; Systems; Severe

What is the aim of the research?This research is about understanding the best system to identify women from all ethnic groups who are unwell during or after pregnancy. This will ensure health inequalities do not affect the recognition of medical problems and will enable faster treatment to prevent severe illness and death.What is the research about?The 'early warning score' is a system used in everyday medical care to identify women at risk of severe illness. Severe illness includes pregnancy-related problems like infection, high blood pressure, and bleeding, as well as medical problems unrelated to pregnancy. The 'vital signs' of the pulse, blood pressure, rate of breathing, temperature and oxygen level are measured several times per day for women in hospital. Healthcare workers calculate an 'early warning score' based on these vital signs. The higher the number, the greater the risk of severe illness in the short term, and the more urgent the woman's care becomes. The purpose is to ensure fast diagnosis and treatment of illness.The problem is that the evidence for these 'early warning scores' is poor. Scores are developed, changed, and used without testing how good they are. Consequently, hospitals use over a hundred different scores in obstetrics and this means that how the risk of severe illness is calculated varies unacceptably. Additionally, in the UK the risk of a woman becoming severely unwell and dying is different based on her ethnicity. No early warning scores have been tested to make sure they perform well in different ethnic groups. If we do not measure and understand differences then we risk creating early warning scores that work for most women but not all women.Second, there is a large amount of important and easily-accessible information that is not included in early warning scores. For example, a woman's age, body mass index, and medical problems would help to interpret her vital signs and understand her risk of illness better. This information should be used if it can help to account for differences between ethnic groups and prevent severe illness.How will the research be undertaken?Initially, I need to understand why women from some ethnic groups are at higher risk of severe illness. I will therefore review the existing scientific literature in depth to identify the most important risk factors in different ethnic groups. I also need to understand how early warning scores are used in real life, so I will review the medical records and interviews of women who had abnormal vital signs, and interview healthcare workers. I want to make sure early warning scores help treat illness in all women fairly. I will test whether existing scores work well in each ethnic group using information from the electronic medical records of a large group of women. I will then take some of the most sophisticated early warning systems and test whether adding extra risk factors that are important within individual ethnic minority groups makes them perform more fairly.Who will be involved in the research?Women from different ethnic backgrounds who have experienced severe illness during or after pregnancy have been consulted on the design of the research. They will be involved in conducting the research, and refining the research plan at key points. Involvement will be facilitated through a workshop event. The public and healthcare decision-makers will be involved and updated throughout the research. Findings and recommendations will be shared among the public and community, professional committees from different healthcare groups, and patient advocacy groups.

研究的目的是什么？这项研究是关于了解最好的系统，以确定妇女从所有种族群体谁是怀孕期间或之后不适。这将确保健康不平等不会影响对医疗问题的认识，并将使更快的治疗，以防止严重的疾病和死亡。“早期预警评分”是一种用于日常医疗护理的系统，用于识别有严重疾病风险的妇女。严重的疾病包括与怀孕有关的问题，如感染，高血压和出血，以及与怀孕无关的医疗问题。住院妇女的脉搏、血压、呼吸频率、体温和含氧量等“生命体征”每天都要测量几次。医护人员根据这些生命体征计算“预警分数”。数字越高，短期内患重病的风险就越大，妇女的护理就越紧迫。其目的是确保疾病的快速诊断和治疗，问题是这些“早期预警分数”的证据不足。分数的制定、修改和使用都没有经过测试。因此，医院在产科中使用了一百多种不同的评分，这意味着严重疾病的风险计算方法差异令人无法接受。此外，在英国，妇女因种族不同而严重不适和死亡的风险也不同。没有对预警分数进行测试，以确保它们在不同种族群体中表现良好。如果我们不衡量和理解差异，那么我们就有可能建立适用于大多数妇女而不是所有妇女的预警分数;第二，预警分数中没有包括大量重要和容易获得的信息。例如，女性的年龄、体重指数和医疗问题将有助于解释她的生命体征，并更好地了解她患病的风险。如果这些信息有助于解释种族群体之间的差异并预防严重疾病，则应使用这些信息。首先，我需要了解为什么来自某些民族的妇女患严重疾病的风险更高。因此，我将深入审查现有的科学文献，以确定不同种族群体中最重要的风险因素。我还需要了解预警评分在真实的生活中是如何使用的，因此我将审查生命体征异常的女性的医疗记录和访谈，并采访医护人员。我想确保早期预警分数有助于公平地治疗所有女性的疾病。我将测试现有的分数是否在每个种族群体中使用大量女性电子病历中的信息。然后，我将采用一些最先进的早期预警系统，并测试是否添加额外的风险因素，这是重要的个别少数民族群体，使他们更公平地执行。谁将参与研究？来自不同种族背景的妇女在怀孕期间或之后经历过严重的疾病，在研究设计方面进行了咨询。他们将参与开展研究，并在关键点完善研究计划。将通过讲习班活动促进参与。公众和医疗保健决策者将参与并在整个研究过程中更新。调查结果和建议将在公众和社区、来自不同医疗保健团体的专业委员会以及患者倡导团体之间分享。

项目成果

The diagnosis and management of vulval intraepithelial neoplasia

外阴上皮内瘤变的诊断和治疗

• DOI: 10.1111/tog.12906
• 发表时间: 2023
• 期刊: The Obstetrician & Gynaecologist
• 作者: Henderson I

Diagnosis and management of endometrial hyperplasia: A UK national audit of adherence to national guidance 2012-2020

• DOI: 10.1371/journal.pmed.1004346
• 发表时间: 2024-02-01
• 期刊: PLOS MEDICINE
• 影响因子: 15.8
• 作者: Henderson，Ian;Black，Naomi;Rimmer，Michael P.
• 通讯作者: Rimmer，Michael P.