Ignite Creation Date:
2024-05-06 @ 3:45 PM
Last Modification Date:
2024-10-26 @ 1:56 PM
Study NCT ID:
NCT04745052
Status:
UNKNOWN
Last Update Posted:
2021-02-09
First Post:
2021-02-04
Brief Title:
Establishment and Validation of a Predictive Model for Hemorrhage
Sponsor:
Shenzhen Second Peoples Hospital
Organization:
Shenzhen Second Peoples Hospital
Study Overview
Official Title:
Establishment and Validation of a Predictive Model for Hemorrhage After Intravenous Thrombolysis in Acute Ischemic Stroke
Status:
UNKNOWN
Status Verified Date:
2021-02
Last Known Status:
NOT_YET_RECRUITING
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Background Patients with acute ischemic stroke AIS are at risk of hemorrhagic transformation HT after intravenous thrombolysis Although there is a risk assessment model for hemorrhagic transformation after thrombolysis there is no evidence of clinical application in the population of Guangdong Province
Purpose To verify the clinical application effect of the existing risk assessment model for hemorrhage transformation after thrombolysis in the local population to improve the existing prediction model and verify the predictive value of HT after intravenous thrombolysis
Methods 1 Continuously collect AIS patients who received intravenous thrombolysis in our hospital from January 2014 to December 2020 to verify the clinical application effects of three existing models HAT SIT-sICH THRIVE on bleeding transformation Collect baseline and bleeding transformation information within 7 days after thrombolysis and use ROC curve calibration curve sensitivity and specificity to evaluate the prediction effect A logistic regression model was used to construct an improved HT prediction model based on the AIC principle 2 Continuous collection of AIS patients who received intravenous thrombolysis in two local hospitals from January 2021 to December 2022 for internal and external verification
Expected results 1 Evaluate the clinical application value of the existing prediction model in local AIS patients with intravenous thrombolysis 2 Develop a modified risk assessment model suitable for hemorrhage transformation after intravenous thrombolysis in AIS patients in Guangdong area and evaluate the risk early Provide guarantee for clinical diagnosis and treatment
Purpose To verify the clinical application effect of the existing risk assessment model for hemorrhage transformation after thrombolysis in the local population to improve the existing prediction model and verify the predictive value of HT after intravenous thrombolysis
Methods 1 Continuously collect AIS patients who received intravenous thrombolysis in our hospital from January 2014 to December 2020 to verify the clinical application effects of three existing models HAT SIT-sICH THRIVE on bleeding transformation Collect baseline and bleeding transformation information within 7 days after thrombolysis and use ROC curve calibration curve sensitivity and specificity to evaluate the prediction effect A logistic regression model was used to construct an improved HT prediction model based on the AIC principle 2 Continuous collection of AIS patients who received intravenous thrombolysis in two local hospitals from January 2021 to December 2022 for internal and external verification
Expected results 1 Evaluate the clinical application value of the existing prediction model in local AIS patients with intravenous thrombolysis 2 Develop a modified risk assessment model suitable for hemorrhage transformation after intravenous thrombolysis in AIS patients in Guangdong area and evaluate the risk early Provide guarantee for clinical diagnosis and treatment
Detailed Description:
This study has two main parts The first part is to verify and optimize the clinical application effect of the existing prediction model The clinical data of the acute ischemic stroke intravenous thrombolytic population is collected retrospectively mainly including baseline indicators and 7 days after thrombolysis Internal bleeding based on the existing prediction models HAT SIT-sICH THRIVE calculate the prediction probability and compare it with the actual bleeding situation evaluate the clinical application effect of the prediction model use ROC curve calibration curve sensitivity and Evaluation of indicators such as specificity Using retrospective data using multivariate logistic regression to analyze the predictive value of baseline clinical indicators screening risk factors and optimizing the HAT SIT-sICH and THRIVE prediction models The logistic regression model is used to construct an improved HT prediction model based on the AIC principle the method of model comparison is used to combine the clinical significance of the indicators to complete the construction of the prediction model The second part is to evaluate the clinical application effect of the improved prediction model and prospectively collect clinical data of AIS patients undergoing intravenous thrombolysis in Shenzhen Second Peoples Hospital Shenzhen Longhua District Peoples Hospital including general demographic data and laboratory tests Baseline indicators such as imaging examinations bleeding within 7 days after thrombolysis etc were used to verify the improved HT prediction model using ROC curve calibration curve sensitivity and specificity and external verification was performed to evaluate the prediction effect of the model
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None