Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Detection of risk of pre-eclampsia in obese pregnant women

A pre-eclampsia and obesity technology, applied in the field of assessing the risk of pre-eclampsia in early pregnancy in obese pregnant women, can solve problems such as reducing the incidence rate

Pending Publication Date: 2021-12-03
代谢组学诊断有限公司
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] While progress has been made in identifying these pregnant women who may benefit from aspirin therapy to prevent partial preterm preeclampsia (reported 62% reduction in incidence), applicants recognize that there are no available risk stratification tests to determine- Pregnant women in the population of obese pregnant women who would benefit from preventive treatment such as metformin

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Detection of risk of pre-eclampsia in obese pregnant women
  • Detection of risk of pre-eclampsia in obese pregnant women
  • Detection of risk of pre-eclampsia in obese pregnant women

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0253] Example 1 - Method

[0254] Participants and Samples

[0255] Prospective clinical samples were collected from women with singleton pregnancies at first visit (15+0 weeks to 18+6 weeks' gestation) who were diagnosed with preeclampsia (cases) or not (controls) in late pregnancy Group). All samples were from participants in the UPBEAT (UK Better Diet and Exercise Trial) nulliparous maternal prospective screening study 50 .

[0256] Written consent was obtained from each participant. The inclusion criteria for this study were BMI ≥ 30kg / m 2 And women with singleton pregnancy from 15+0 weeks to 18+6 weeks. Applicable exclusion criteria are: inability or unwillingness to sign informed consent; pregnancy 18+6 weeks; essential hypertension requiring treatment before or during pregnancy; pre-existing renal disease; systemic Lupus erythematosus; antiphospholipid syndrome; sickle cell anemia; thalassemia; celiac disease; thyroid disease; psychosis; multiple pregnancy; cur...

Embodiment 2

[0420] Example 2 - Univariate Analysis of Results

[0421] single predictor selection

[0422] This was taken into account in the univariate analyses, given that the applicants believe that prediction of preeclampsia in obese pregnant women may require different predictors and combinations thereof depending on specific patient populations and / or disease subtypes. First, the applicants investigated variables, more specifically metabolite variables, that were advantageous in predicting preeclampsia in all obese pregnant women. Applicants then worked to identify predictors specific to any of the strata previously defined. To identify predictors that are truly subgroup-specific, as well as predictors that may have been missed by treating the obese pregnant population as a homogenous group, their predictive performance was compared with that of their predictive performance for PE in the total obese population (stratification: total) Compare. They were considered subgroup speci...

Embodiment 3

[0448] Example 3 - Results Multivariate Analysis

[0449] The notion of creating a model space of predictive models containing all possible 2 to 4 predictors, and then exploring that model space using the rigorous statistical criteria explained earlier, enables the discovery of a strong potential for synergistic predictors, i.e., combinations of these predictors that are significantly Improved predictive performance of any constituting parent model. For example, based on the criteria explained earlier, a predictive model ABC consisting of predictors A, B, and C is considered an improved model only if the predictive performance of the ABC model is significantly better than any of the models AB, BC, and AC.

[0450] Again, applicants applied multiple viewpoints in addition to predicting PE in all obese women. Applicants have done this to ensure that the subsequently selected predictors, and the combination of predictors within that selection, will predict PE in patients with ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

A computer implemented method of early prediction of risk of pre-eclampsia in a pregnant obese woman is described. The method comprises the steps of inputting abundance values for a panel of obese pregnancy specific metabolite biomarkers obtained from an assayed biological sample into a computational model, in which the biological sample is obtained from an obese pregnant woman at 8 to 24 weeks of pregnancy, and inputting a patient parameter for the pregnant obese woman into the computational model selected from at least one of ethnicity, risk of gestational diabetes, fetal sex, number of pregnancies and level of obesity. The computational model is configured to select a subset comprising at least two of the obese pregnancy specific metabolite biomarkers based on the patient parameter input, correlate abundance values for the subset of obese pregnancy specific metabolite biomarkers with risk of pre-eclampsia, and output a predicted risk of pre-eclampsia for the pregnant obese woman.

Description

technical field [0001] The present invention relates to methods for assessing the risk of preeclampsia in early pregnancy in obese pregnant women. Background technique [0002] Preeclampsia (PE) is a pregnancy-specific disorder that occurs in 2-8% of all pregnancies. PE originates in the placenta and manifests as new-onset hypertension and proteinuria after 20 weeks of gestation. PE remains a leading cause of maternal and perinatal morbidity and mortality: 70,000 mothers and 500,000 infants die each year as a direct consequence of PE. Maternal complications of PE include cerebrovascular accident, hepatic rupture, pulmonary edema, or acute renal failure. For the fetus, placental insufficiency leads to fetal growth restriction, which is associated with increased neonatal morbidity and mortality. To date, the only treatment for PE is delivery of the placenta and thus the delivery of the baby. Thus, iatrogenic preterm births increase the burden of neonatal morbidity and mort...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G01N33/68
CPCG01N33/6893G01N2560/00G01N2800/044G01N2800/368G01N2800/50G16H50/30
Inventor R·蒂滕G·托马斯
Owner 代谢组学诊断有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com