Observational study, no intervention
OtherObservational study, no intervention
NCT Number: NCT05245695
The goal of this observational study is to determine the clinical validity of a deep neural network algorithm that utilizes protein biomarker detection of Endometriosis - "EndoCheck" - as an "aid in diagnosis" for endometriosis and to show validity as a diagnostic test
Interested in participating?
Request Info14 year–50 year
Female
Observational
New Horizons Clinical Trials, Chandler, Arizona, United States
The objective is to confirm the clinical performance (sensitivity and specificity) of EndoCheck when compared to laparoscopic surgical assessment as an "aid in diagnosis" for endometriosis in subjects who present with chronic pelvic pain.
The primary endpoint of the study is to optimize the test to achieve the success criteria of at least 94% and 79% sensitivity and specificity, respectively. Secondary endpoints include examining the performance of the test in patients stratified by pain severity and other clinical factors.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Observational study, no intervention
Time frame: 24 months
The primary endpoint of the study is to optimize the test to achieve the success criteria of at least 94% and 79% sensitivity and specificity, respectively
Time frame: 24 months
Examining the performance of the test in patients stratified by pain severity and other clinical factors.
Contact information is provided by the study sponsor or research team.
Aspira Women's Health
Industry
Deep Neural Network Stratification for the Use in Detecting Endometriosis in Women Affected by Chronic Pelvic Pain (EndoCheck)
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