- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06249230
The Analysis of Risk Factors for Recurrent Pregnancy Loss and Prediction of Pregnancy Loss Risk
February 8, 2024 updated by: RenJi Hospital
A Retrospective Study on the Analysis of Risk Factors for Recurrent Pregnancy Loss and Prediction of Pregnancy Loss Risk in Patients With Recurrent Pregnancy Loss
Based on the comprehensive etiological screening results of patients with recurrent pregnancy loss, including basic characteristics, coagulation function indicators, autoimmune indicators, endocrine indicators, and gynecological ultrasound examination results, as well as the outcome of subsequent pregnancy after the patient's visit, analyze the independent risk factors affecting recurrent pregnancy loss, construct and validate an abortion risk prediction model to predict the risk of subsequent pregnancy loss in patients with recurrent pregnancy loss, and classify the patient's risk, Screening high-risk populations and guiding clinical early intervention and active treatment to improve pregnancy success rates.
Study Overview
Status
Not yet recruiting
Conditions
Detailed Description
- Study population and follow-up: Patients were routinely taken history information at the initial consultation and underwent at least two etiological screenings at intervals of 4-6 weeks; during this period, sex hormone tests and uterine artery ultrasonography were performed 5-9 days after ovulation. Autoantibody tests are considered abnormal if they are positive on two or more occasions. Combined with the results of the two etiological screenings and the results of sex hormone and uterine artery ultrasound, anticoagulant, antiplatelet or immunosuppressant medication will be given for at least 2 months, and then coagulation and immunological indexes and uterine artery ultrasound will be carried out again to assess whether the indexes are improved or not, and the patients who have reached the standard of preparation for pregnancy will be given the appropriate preparation for pregnancy based on the programme of assisted reproduction or natural conception. If the patient is not pregnant after three months of pregnancy preparation, outpatient consultation is required to reassess and adjust the regimen; if the patient is pregnant, outpatient consultation is required to assess the post-pregnancy situation and adjust the regimen; after that, platelet aggregation rate (AA and ADP), D-dimer and fibrin degradation product (FDP) will be monitored every fortnight, and every four weeks, autoantibodies, coagulation, liver and renal routines, blood counts, thyroid function, and the corresponding gestational week will be monitored. Obstetric ultrasonography was performed to adjust the medication in time. If the patient had a spontaneous abortion confirmed by ultrasonography or histology after curettage before 28 weeks of gestation, including biochemical pregnancy and embryonic arrest, the pregnancy outcome was judged as pregnancy loss, and if the patient was followed up with an intrauterine viable pregnancy beyond 32 weeks, the pregnancy outcome was judged as pregnancy success, and the reproductive immunity clinic follow-up was then ended. In this study, only the first pregnancy outcome after the initial visit was collected, and follow-up ended if the patient had a pregnancy outcome event. Patients who did not have a pregnancy outcome event as of 31 December 2023 were excluded from this study, and those who had a pregnancy outcome event were included in the study by compiling the history information collected at the initial visit of the included patients, and by querying the medical record system and entering the etiological screening laboratory indexes and ultrasound results as well as the outcome of the first pregnancy after the visit.
- Data collection: history collection at the initial consultation , outpatient medical record system query to collect laboratory indicators and ultrasound results, outpatient or telephone follow-up after the consultation of the outcome of the first pregnancy, "EpiData" software data entry;
- Data processing: data cleaning to remove duplicates, interpolation of missing values, categorisation of variables uniquely hot coding, elimination of heterozygous ratio <0.1 variables; characteristic Engineering descriptive statistics, correlation analysis, handling of outliers; data set division, the data were randomly divided into training set and test set according to the ratio of 7:3 according to the pregnancy outcome;
- Predictive factor screening: t-test, analysis of variance (ANOVA), non-parametric test, chi-square test, and other analyses of the risk factors of miscarriage in patients with recurrent miscarriages; or according to the results of the analysis in combination with the results of previous studies and clinical expertise or LASSO regression (the last absolute shrinkage and the last absolute shrinkage and the last absolute shrinkage and the last absolute shrinkage). (least absolute shrinkage and selection operator, LASSO regression). Method 1: A one-way analysis of variance (ANOVA) was performed in the training set to screen for risk factors associated with miscarriage in patients with recurrent miscarriage. Two independent samples t-tests were used for continuous data, and Mann-Whitney tests were used for non-normally distributed data; for categorical data, Chi-square tests or Fisher's exact test (FET) were used. For categorical data, Chi-square tests or Fisher's exact tests were used. A two-sided p-value of less than 0.05 was considered statistically significant. Differential variables were then included in a multifactorial logistic analysis with stepwise regression to screen for independent risk factors predicting pregnancy loss in patients with recurrent miscarriage. Method 2: LASSO regression (least absolute shrinkage and selection operator) was used for feature selection in the training set. The basic principle is to introduce the L1 regularisation term on the basis of ordinary least squares to achieve feature selection and coefficient sparsification of the model by minimising the objective function, screening the important features related to the outcome variable, while setting the coefficients of irrelevant or redundant features to zero. During the fitting process, the sparsity of features is controlled by adjusting the regularisation parameter. Optimal regularisation parameters are found using methods such as cross-validation or grid search. Obtain the coefficients of all features based on the trained Lasso regression model. Sort the coefficients, in descending order of absolute value. Set a threshold to retain features with coefficients greater than the threshold.
- Predictive model building: the training set data are taken to construct the model by machine learning methods such as logistic regression, K-nearest neighbour, decision tree, linear discriminant, neural network, random forest, support vector machine, gradient boosting, extreme gradient boosting, light gradient boosting or deep learning.
- Internal validation method: k-fold cross-validation is used within the training set to compare the model performance, select the optimal model to adjust the hyper-parameters, and then test the generalisation ability of the model in the test set.
- Comparison of model performance: calculate C-statistic (area under the curve AUC), accuracy, precision, recall, F1 score, and draw calibration curves, clinical decision curves and clinical impact curves to compare the prediction performance of different models.
- Risk stratification: patients are classified into low-risk and high-risk according to the model, which is applied to clinical assessment of patients and pregnancy supervision and management. Risk stratification is proposed to construct a column-line diagram based on logistic regression and calculate the column-line diagram score for each patient, and determine the optimal score threshold based on the Youden index; patients lower than or equal to the optimal score threshold are classified as low-risk subgroups, and patients higher than the optimal score threshold are classified as high-risk subgroups. The Pearson chi-square test was used to determine the validity of risk stratification by comparing the differences in pregnancy outcomes between the low-risk and high-risk subgroups.
- Model visualisation: column-line diagrams, risk score scales and "SHAP" were used to explain the model.
Study Type
Observational
Enrollment (Estimated)
1000
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: Mingyang Li
- Phone Number: 86+15026849150
- Email: 1042217951@qq.com
Study Locations
-
-
Shanghai
-
Shanghai, Shanghai, China, 200127
- Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine
-
Contact:
- Mingyang Li
- Phone Number: 86+15026849150
- Email: 1042217951@qq.com
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Adult
Accepts Healthy Volunteers
No
Sampling Method
Probability Sample
Study Population
Patients who had two or more spontaneous miscarriages (including biochemical pregnancies, excluding spontaneous miscarriages due to chromosomal abnormalities in the embryo) before 28 weeks of gestation with the same partner prior to the consultation were included in this study
Description
Inclusion Criteria:
- Diagnosis of recurrent miscarriage: patients who had two or more spontaneous miscarriages (including biochemical pregnancies, excluding spontaneous miscarriages due to chromosomal abnormalities in the embryo) before 28 weeks of gestation with the same partner prior to the consultation were included in this study;
- ≥20 years old;
- Completion of initial history taking and complete results of the etiological screening programme;
- Knowledge of the purpose and significance of the study, consent and sign the informed consent form;
Exclusion Criteria:
- Pregnant at the first visit;
- Presence of severe contraindications to pregnancy, making it inadvisable to conceive;
- Voluntary withdrawal from the pregnancy or from the study;
- No pregnancy outcome as of the follow-up endpoint (December 31, 2023), indicating no pregnancy;
- Loss to follow-up, unable to obtain pregnancy outcome;
- Subsequent pregnancy outcomes after the clinic visit included ectopic pregnancy, molar pregnancy, fetal malformations, and pregnancy at the scar site of previous cesarean section.
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
Pregnancy success
Patients followed up with a live intrauterine pregnancy beyond 32 weeks were judged as pregnancy success.
|
Hematologic features include coagulation indicators, autoimmune indicators, and endocrine indicators.
Ultrasound indices of uterine artery blood flow include endometrial thickness, endometrial artery blood flow parameters , and bilateral uterine artery blood flow parameters.
Demographic characteristics include age, the number of previous spontaneous abortions (including biochemical pregnancies), BMI, fertility history, past disease history, chromosomal status, family and genetic history, etc.
|
Pregnancy loss
Patients with histologically confirmed spontaneous abortion by ultrasound or curettage before 28 weeks of gestation, including biochemical pregnancies and embryonic arrests, were judged as pregnancy loss
|
Hematologic features include coagulation indicators, autoimmune indicators, and endocrine indicators.
Ultrasound indices of uterine artery blood flow include endometrial thickness, endometrial artery blood flow parameters , and bilateral uterine artery blood flow parameters.
Demographic characteristics include age, the number of previous spontaneous abortions (including biochemical pregnancies), BMI, fertility history, past disease history, chromosomal status, family and genetic history, etc.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Number of participants with pregnancy success
Time Frame: Follow-up to 32 weeks of gestation for live intrauterine pregnancies or follow-up cut-off
|
If patients were followed up with a live intrauterine pregnancy beyond 32 weeks, the pregnancy outcome was determined to be a successful pregnancy and the reproductive immunology clinic follow-up ended .
|
Follow-up to 32 weeks of gestation for live intrauterine pregnancies or follow-up cut-off
|
Number of participants with pregnancy loss
Time Frame: The time of spontaneous abortion occurring before 28 weeks of gestation after consultation
|
Patients with histologically confirmed spontaneous abortion by ultrasound or curettage before 28 weeks of gestation, including biochemical pregnancies and embryonic arrests, were judged as pregnancy loss.
|
The time of spontaneous abortion occurring before 28 weeks of gestation after consultation
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Investigators
- Principal Investigator: Aimin Zhao, MD, Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Estimated)
January 31, 2024
Primary Completion (Estimated)
December 31, 2024
Study Completion (Estimated)
December 31, 2024
Study Registration Dates
First Submitted
January 31, 2024
First Submitted That Met QC Criteria
February 7, 2024
First Posted (Actual)
February 8, 2024
Study Record Updates
Last Update Posted (Actual)
February 12, 2024
Last Update Submitted That Met QC Criteria
February 8, 2024
Last Verified
February 1, 2024
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- IIT-2023-0311
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
NO
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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