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Prospective Validation of the DEVA Algorithm for the Prediction of Severe Endometriosis — ValDEVA  

Endometriosis Clinical Trial

Official title:
Prospective Validation of the DEVA Algorithm for the Prediction of Severe Endometriosis

Clinical Trial 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).

Clinical Trial Description

n/a

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT05691322
Study type Observational
Source One Clinic
Contact Alba Nicolas-Boluda, PhD
Phone 0033782873392
Email alba.nicolas-boluda@one.fr
Status Recruiting
Phase
Start date October 19, 2022
Completion date January 19, 2024
View Details
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