Evaluation of an AI-DP for STH Deworming Programs: a Study Protocol
NCT06055530 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 1100
Last updated 2023-10-02
Summary
The goal of this observational study is to test a new AI diagnostic tool for detection, specification and quantification of parasitic infections (Ascaris, Trichuris, hookworm and S. Mansoni) in School aged children in Ethiopia and Uganda. The main questions it aims to answer are:
* Diagnostic Performance of the AI tool and compare to traditional manual microscopy
* Repeatability and reproducibility of the AI tool and compare to traditional manual microscopy
* Time-to-result for the AI tool
* Cost efficiency for the AI tool and traditional manual microscopy to inform programmatic decisions.
* Usability of the AI tool
Participants will be asked to provide a stool sample for examination by the AI tool and traditional manual microscopy. Participants with a positive test result will receive the proper treatment (Deworming drug).
Conditions
- Soil Transmitted Helminths
- Schistosomiasis Mansoni
Interventions
- DIAGNOSTIC_TEST
-
Artificial Intelligence Digital Pathology
School aged children will be asked to leave a stool sample. The samples will be prepared with the Kato-Katz method and scanned and processed by an artificial intelligence digital pathology system to determine the infection level of soil transmitted helminths and schistosomiasis. The samples will also be analyzed by a human microscopist for comparison.
Sponsors & Collaborators
-
Jimma University
collaborator OTHER -
Ministry of Health, Uganda
collaborator OTHER_GOV -
University Ghent
collaborator OTHER -
Enaiblers AB
lead INDUSTRY
Principal Investigators
-
Bruno Levecke, PhD · University Ghent
-
Zeleke Mekonnen, PhD · Jimma University
-
Narcis Kabatereine, PhD · Ministry of Health, Uganda
Eligibility
- Min Age
- 5 Years
- Max Age
- 14 Years
- Sex
- ALL
- Healthy Volunteers
- Yes
Timeline & Regulatory
- Start
- 2023-10-31
- Primary Completion
- 2023-12-31
- Completion
- 2024-07-31
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