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Multimorbid Pregnancy: Determinants, Clusters, Consequences and Trajectories (MuM-PreDiCCT)

Multimorbid Pregnancy: Determinants, Clusters, Consequences and Trajectories (MuM-PreDiCCT)
多病态妊娠:决定因素、聚类、后果和轨迹 (MuM-PreDiCCT)
批准号:
MR/V005243/1
负责人:
Krishnarajah Nirantharakumar
金额:
$12.79万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --

项目摘要

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中文摘要
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英文摘要
The ProblemMultimorbidity is when people suffer from more than one long-term illness. It can be difficult for people with several long-term illnesses to manage their conditions and sometimes they don't receive the best quality care. Patients with multimorbidity may have to coordinate appointments with different specialists and their medications need to be managed carefully. During pregnancy, these challenges may increase for women with multimorbidity. We know that multimorbidity in pregnancy is becoming more common, but we don't understand why this is and what the consequences are for mothers and babies. Without this deeper understanding of the problem, women with several long-term illnesses won't have the best experience of care before, during and after pregnancy because services are not tailored to their specific needs. Our aims and approachOur collaboration will bring together experts in data analysis, diseases and public health from 7 academic institutions in the UK. We will work in close partnership with women with experience of multimorbidity in pregnancy. Firstly, our data specialists will look at electronic health records to find out how many women have multimorbidity in pregnancy and what illnesses they have. We will try and identify if factors such as age, weight, cultural or social background, level of education and number of previous pregnancies influences whether a woman has multimorbidity in pregnancy. We will also find out which illnesses group together(cluster) during pregnancy, which clusters are most common and whether some clusters affect some women more than others. In the second part of the study, we will compare what happens to mothers with and without multimorbidity during pregnancy. We will find out whether women with multimorbidity are more likely to develop illnesses during the pregnancy (e.g. gestational diabetes), after the pregnancy (e.g postnatal depression) and also in the longer-term (e.g. heart-disease). We will also look at the health and wellbeing of children of women with multimorbidity in pregnancy.The third part of our research will focus on medications in pregnancy. We will find out what medicines women with multimorbidity take during pregnancy and how the medications affect the health of the mother and the baby during pregnancy. This knowledge will help doctors prescribe safely during pregnancy. We know that complications in pregnancy are a warning sign of future illnesses in women. As part of this project, we will be able to find out more about how different pregnancy complications affect the longer-term health of women. We can use this knowledge to put preventative measures in place where possible. Finally, we will meet with women and healthcare professionals to discuss the services available for women with multimorbidity in pregnancy. We will find out how appropriate and accessible these services are and how services can be improved. Going forward, this will help us to jointly design health services with women and their partners. Involving the publicWe will work in partnership with women with experience of multimorbidity in pregnancy. Their insights will help ensure that our project is grounded in the experiences of women and that all stages of the project drive towards improving care for women. Sharing our findingsOur team has large networks and we will share our findings with healthcare professionals, through professional organisations (e.g. Royal Colleges of Obstetricians and Gynaecologists); through NHS networks (e.g. Local Maternity Services) and through charities and women's networks (e.g. Maternity Voice Partnerships). Our ImpactThis study will give healthcare professionals and women a much better understanding of multimorbidity in pregnancy. Through this enhanced understanding, we will be able to plan and design services that meet the needs of women and their families before, during and after the birth of their babies.
期刊论文(10)
专著(0)
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会议论文
DOI: 10.1136/bmjopen-2022-067585
发表时间: 2023-03-06
期刊: BMJ open
影响因子: 2.9
作者: []
通讯作者:
DOI: 10.1186/s12916-023-03058-4
发表时间: 2023-09-12
期刊: BMC MEDICINE
影响因子: 9.3
作者: [Azcoaga-Lorenzo, Amaya, Fagbamigbe, Adeniyi Francis, Agrawal, Utkarsh, Black, Mairead, Usman, Muhammad, Lee, Siang Ing, Eastwood, Kelly-Ann, Moss, Ngawai, Plachcinski, Rachel, Nelson-Piercy, Catherine, Brophy, Sinead, O'Reilly, Dermot, Nirantharakumar, Krishnarajah, Mccowan, Colin]
通讯作者: Mccowan, Colin
mmVAE: multimorbidity clustering using Relaxed Bernoulli ß-Variational Autoencoders
mmVAE:使用松弛伯努利变分自动编码器进行多病态聚类
DOI: --
发表时间: 2022
期刊: Machine Learning for Health
影响因子: --
作者: [Charles Gadd]
通讯作者: Charles Gadd
England's preconception health report: convenient and valuable data.
英国的孕前健康报告:方便且有价值的数据。
DOI: 10.1111/1471-0528.17483
发表时间: 2023
期刊: an international journal of obstetrics and gynaecology
影响因子: --
作者: [Black M]
通讯作者: Black M
7
    Multimorbidity and Pregnancy: Determinants, Clusters, Consequences and Trajectories (MuM-PreDiCT)
    • 批准号:
      MR/W014432/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $375.72万
    • 财政年份:
      2021
    • 负责人:
      Krishnarajah Nirantharakumar
    • 依托单位:
    Automated Clinical Epidemiology Studies (ACES) platform for complex epidemiology study designs and diverse databases
    • 批准号:
      MR/S003878/1
    • 项目类别:
      Fellowship
    • 资助金额:
      $38.16万
    • 财政年份:
      2018
    • 负责人:
      Krishnarajah Nirantharakumar
    • 依托单位:
    海外基金