Endometriosis and ATR-FTIR Spectroscopy

NCT ID: NCT06426420

Last Updated: 2024-05-29

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

600 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-09-15

Study Completion Date

2026-04-29

Brief Summary

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The goal of this study is to explore the use of mid-infrared spectroscopy (ATR-FTIR) as a detection tool for endometriosis in urine.

Detailed Description

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Endometriosis is a chronic gynecological disease that is considered debilitating and multifactorial. Its diagnosis is invasive and can be prolonged due to non-specific symptoms and erroneous or late investigations, which can lead to delays and impair the provision of adequate treatment.

ATR-FTIR Spectroscopy is a non-invasive technique with the capability to identify the chemical composition and molecular changes of samples through its interaction with mid-infrared radiation. The aim of this work is to develop a rapid test for the detection of endometriosis in urine samples using spectroscopy and machine learning algorithms.

Conditions

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Endometriosis Endometriomas

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

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Pelvic Pain

Patients referred to the gynecology outpatient clinic, with complain of pelvic pain. Positives and negatives for endometriosis will be outlined by an expert gynecologist according to the following criteria:

* Pelvic MRI (Magnetic Resonance Imaging) report;
* Gynecologic exam;
* Clinical symptoms and history;

The intervention is the use of the ATR-FTIR Spectrometer in patient's urine samples to develop and validate a tool for detecting endometriosis.

Group Type EXPERIMENTAL

FTIR spectroscopy analysis

Intervention Type DIAGNOSTIC_TEST

ATR-FTIR Spectroscopy analysis combined with machine learning algorithms.

Interventions

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FTIR spectroscopy analysis

ATR-FTIR Spectroscopy analysis combined with machine learning algorithms.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* Female
* Pelvic pain complain

Exclusion Criteria

* Age under 18 or above 55
* Lack of informed consent
Minimum Eligible Age

18 Years

Maximum Eligible Age

55 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

No

Sponsors

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Conselho Nacional de Desenvolvimento Científico e Tecnológico

OTHER_GOV

Sponsor Role collaborator

Federal University of Espirito Santo

OTHER

Sponsor Role lead

Responsible Party

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VALERIO GARRONE BARAUNA

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Valerio G Barauna, PhD

Role: PRINCIPAL_INVESTIGATOR

Universidade Federal do Espírito Santo

Locations

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University Hospital Cassiano Antonio Moraes at Federal Univeristy Of Espírito Santo

Vitória, Espírito Santo, Brazil

Site Status RECRUITING

Countries

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Brazil

Central Contacts

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Valerio G Barauna, PhD

Role: CONTACT

+5527996892407

Facility Contacts

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Neide A Boldrini, phD

Role: primary

+552733357100

Mara RB Barcelos, phD

Role: backup

+5527999829511

Other Identifiers

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FTIR-ENDOMETRIOSIS

Identifier Type: -

Identifier Source: org_study_id

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