Evaluation of an AI-DP for STH Deworming Programs: a Study Protocol
NCT ID: NCT06055530
Last Updated: 2023-10-02
Study Results
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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UNKNOWN
1100 participants
OBSERVATIONAL
2023-10-31
2024-07-31
Brief Summary
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* 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).
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Detailed Description
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The study protocol describes a comprehensive evaluation of the AI-DP based on its (i) diagnostic performance, (ii) repeatability/reproducibility, (iii) time-to-result, (iv) cost-efficiency to inform large-scale deworming programs and (v) usability in both laboratory and field settings. For each of these five attributes, the investigators designed separate experiments with sufficient power to verify the non-inferiority of the AI-DP (KK2.0) over the manual screening of the KK smears (KK1.0). These experiments will be conducted in two STH endemic countries with national deworming programs (Ethiopia and Uganda), focusing on school-age children (SAC) only. 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).
This comprehensive and well-designed study and accompanying protocols will provide the necessary data to make an evidence-based decision on whether the AI-DP is indeed performant and a cost-efficient end-to-end diagnostic to inform large-scale deworming programs against STHs. Following the protocolized collection of high-quality data the investigators will seek approval by WHO. Through the dissemination of the methodology and statistics, the investigators hope to support additional developments in AI-DP technologies for other neglected tropical diseases in resource-limited settings.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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School aged children in Ethiopia
A number of school aged children in Ethiopia from 5-7 different schools in the Jimma region.
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.
School aged children in Uganda
A number of school aged children from Uganda. Children from 5-7 different schools will be in the group.
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.
Interventions
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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.
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
* Parent(s)/guardian(s) of subject signed an informed consent document indicating that they understand the purpose and procedures required for the study and that they are willing to have their child participate in the study
* Subject of ≥6 (Ethiopia) /8 (Uganda) years old has assented to participate in the study\*
* Subject of ≥12 years old has signed an informed consent document indicating that they understand the purpose of the study and procedures required for the study, and are willing to participate in the study (Ethiopia only)\*
* Subject has provided a stool sample of minimum 5 grams
Exclusion Criteria
* Subject is experiencing a severe concurrent medical condition or has an acute medical condition
* Subject has received anthelmintic treatment within 90 days prior to the start of the study
5 Years
14 Years
ALL
Yes
Sponsors
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Jimma University
OTHER
Ministry of Health, Uganda
OTHER_GOV
University Ghent
OTHER
Enaiblers AB
INDUSTRY
Responsible Party
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Principal Investigators
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Bruno Levecke, PhD
Role: STUDY_DIRECTOR
University Ghent
Zeleke Mekonnen, PhD
Role: PRINCIPAL_INVESTIGATOR
Jimma University
Narcis Kabatereine, PhD
Role: PRINCIPAL_INVESTIGATOR
Ministry of Health, Uganda
Central Contacts
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References
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Ward PK, Roose S, Ayana M, Broadfield LA, Dahlberg P, Kabatereine N, Kazienga A, Mekonnen Z, Nabatte B, Stuyver L, Velde FV, Hoecke SV, Levecke B. A comprehensive evaluation of an artificial intelligence based digital pathology to monitor large-scale deworming programs against soil-transmitted helminths: A study protocol. PLoS One. 2024 Oct 28;19(10):e0309816. doi: 10.1371/journal.pone.0309816. eCollection 2024.
Related Links
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Full protocol - Submitted for publication
Other Identifiers
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76906491
Identifier Type: OTHER_GRANT
Identifier Source: secondary_id
EN-2023-CT001
Identifier Type: -
Identifier Source: org_study_id
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