A Study to Validate and Improve an Automated Image Analysis Algorithm to Detect Tuberculosis in Sputum Smear Slides

Completed

• Conditions: Tuberculosis, Pulmonary

• Registration Number: NCT05899400
• Lead Sponsor: Diascopic, LLC

Brief Summary

A Study to Validate and Improve an Automated Image Analysis Algorithm to Detect Tuberculosis in Sputum Smear Slides

Detailed Description

Not available

Study Timeline

• Study Start: 2019-09-15
• Primary Completion: 2022-10-31
• Study Completion: 2022-12-31
• Study First Submitted: 2023-05-31
• Status Verified: 2023-06
• Study First Submitted QC: 2023-06-08
• Last Update Submitted: 2023-06-08
• Study First Posted: 2023-06-12
• Last Update Posted: 2023-06-12

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 400

Inclusion Criteria

• Samples sourced from Makerere University's Joint Clinical Research Clinic (JCRC) and Laboratory

Exclusion Criteria

• No samples from outside Makerere's Domain

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Determined sensitivity and specificity of the iON device by comparing MTB slide results to their associated bacterial culture results from the same specimen(s).	Study completed over the grant period 2019 - 2022	Sensitivity, specificity, and average analysis time were determined. An image database of \>40,000 images was also created for internal use.

Trial Locations

Locations (1)

Makerere University; 🇺🇬 Kampala, Uganda