Ignite Creation Date:
2024-05-06 @ 6:32 PM
Last Modification Date:
2024-10-26 @ 2:49 PM
Study NCT ID:
NCT05691322
Status:
RECRUITING
Last Update Posted:
2023-01-20
First Post:
2023-01-06
Brief Title:
Prospective Validation of the DEVA Algorithm for the Prediction of Severe Endometriosis
Sponsor:
One Clinic
Organization:
One Clinic
Study Overview
Official Title:
Prospective Validation of the DEVA Algorithm for the Prediction of Severe Endometriosis
Status:
RECRUITING
Status Verified Date:
2023-01
Last Known Status:
None
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:
ValDEVA
Brief Summary:
Endometriosis is a chronic disease affecting 1 in 10 women Its diagnosis is difficult and the time between the first symptoms and diagnosis is of about 7 years diagnosis requires specialized imaging performed by referral practitioners for this pathology According to current recommendations non-specialized pelvic ultrasound is the recommended first-line examination However only reference ultrasound performed by a doctor specialized in the disease and carried out according to a specific protocol such as UBESS is sufficiently reliable for diagnosis The number of practitioners performing this type of examination is very low in France which in practice results in a very low reliability of this strategy in real life Pelvic MRI is also a much more reliable examination available for review However its access is limited In addition the false positive rate can be as high as 20 particularly for minor forms of the disease
The DEVA algorithm has been developed for the identification of women with endometriosis based on a self-administered pelvic pain symptom questionnaire ENDOPAIN In a preliminary study this algorithm seems reliable for identify patients at high risk of this disease and would thus allow to triage patients requiring patients requiring an immediate MRI in order to shorten diagnostic delays External validation of the algorithm is therefore necessary before clinical use The main objective od this study is the prospective external validation of the diagnostic reliability of the DEVA algorithm used for the detection of women with endometriosis visible on MRI or transvaginal ultrasound
The DEVA algorithm has been developed for the identification of women with endometriosis based on a self-administered pelvic pain symptom questionnaire ENDOPAIN In a preliminary study this algorithm seems reliable for identify patients at high risk of this disease and would thus allow to triage patients requiring patients requiring an immediate MRI in order to shorten diagnostic delays External validation of the algorithm is therefore necessary before clinical use The main objective od this study is the prospective external validation of the diagnostic reliability of the DEVA algorithm used for the detection of women with endometriosis visible on MRI or transvaginal ultrasound
Detailed Description:
None
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