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CompletedNCT07538531Updated Oct 8, 2026

The Utility and Feasibility of Accessible Diarrhea Etiology Prediction Tool (ADEPT) in an Informal Healthcare Setting

An interventional study of Diagnostic test: Accessible Diarrhea Etiology Prediction Tool (ADEPT) in Diarrhea Infectious, Algorithms and Decision Support Systems, Clinical, sponsored by Daniel Leung. Completed at 1 site in Bangladesh. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-10-08.

Sponsored by Daniel Leung · Not applicable, Interventional, and Diagnostic

Updated Oct 8, 2026Now CompletedPrimary completion moved+2 moreGo to Updates ↓
Phase
Not applicable
Study type
Interventional
Enrollment
30
Allocation
Not applicable
Ages
18 Years and older
Sex
All
01

Study summary

Diarrheal disease remains a leading cause of morbidity and mortality for children under 5 globally. Accepted best practice for managing diarrhea in the absence of blood or suspicion of cholera is rehydration, however in resource poor areas antibiotics are still prescribed at high rates due to pressures such as financial incentives, caregiver expectations, and diagnostic uncertainty. Informal healthcare providers often serve as first point of care for pediatric diarrhea patients in low- and middle- income countries (LMICs) and commonly prescribe antibiotics for pediatric diarrhea at high frequencies.

In this pilot before-after feasibility trial informally trained healthcare providers will use a mobile phone-based application (Accessible Diarrhea Etiology Prediction Tool, ADEPT) which will allow for the exploration of the acceptability, feasibility, and utility of the tool, as well as ADEPTs ability to decrease inappropriate antibiotic prescribing practices.

Read the detailed description

Diarrheal diseases remain a leading cause of morbidity and mortality in children worldwide, accounting for around 500,000 deaths in children under 5 annually. Generally, the management of diarrheal disease relies on rehydration, although other management decisions such as laboratory testing and medication may alter outcome. However, in many low- and middle-income countries (LMICs) where the burden of diarrheal disease is highest, treatment is largely empiric due to high caseloads and lack of accessible and affordable diagnostics. Despite World Health Organization (WHO) guidelines, antibiotics are often overused in management of diarrheal disease leading to adverse side effects and antimicrobial resistance. Meanwhile underuse of antibiotics may result in prolonged illness and increased transmission rates. In resource poor areas with limited access to diagnostics antibiotic overuse is common, especially when prescribed by untrained allopathic providers. Accurate and timely determination of etiology is essential to reduce unnecessary diagnostic and antibiotic use. Clinical prediction rules (CPRs), often in the form of electronic clinical decision-making support tools (eCDSTs), are used to help clinicians make evidence-based decisions with improved patient outcomes. Informally trained allopathic providers, known as Village Doctors (VDs) in Bangladesh, often function as the first point of care for pediatric diarrhea patients. VDs are immensely popular due to enhanced accessibility and familiarity; a recent study in rural Bangladesh found that VDs act as first point of care for up to 65% of patients. VDs and other informally trained practitioners prescribe antibiotics for pediatric diarrhea at rates far exceeding formally trained providers and far beyond what is clinically indicated.

The reliance on VDs, especially in resource poor settings, and their prescribing practices suggests that antimicrobial stewardship efforts should include VDs. A previous study by the investigators has shown that an eCDST based on etiologic prediction rules and WHO guidelines was successful in reducing antibiotics prescribed by formally trained providers by over 50%. Our investigation will seek to understand if an eCDST (the Accessible Diarrhea Etiology Prediction Tool (ADEPT)) could be used to guide antibiotic prescriptions by informally trained healthcare providers like VDs.

02

Conditions studied

  • Diarrhea Infectious
  • Algorithms
  • Decision Support Systems, Clinical
  • Clinical Decision-making

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Keywords

  • Diarrhea
  • Treatment Algorithm
  • mHealth
  • Antimicrobial stewardship
03

In context

Dysentery

44 studies on the registry are indexed under Dysentery; 6 are open to participants now.

This study's enrollment of 30 is below the median of 163 across 38 interventional studies indexed under Dysentery.

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Lead sponsor

This is the only study on the registry with Daniel Leung as lead sponsor.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • Village Doctor with antibiotic prescribing authority for children presenting with diarrheal illness
  • Practice in trial location subdistrict
  • Self-report treating a minimum of 5 pediatric diarrhea cases per week
  • Willing to participate in ADEPT training, use ADEPT in clinical practice with pediatric diarrhea patients, and to collect, via an electronic tool, data on patient characteristics and clinical management

Exclusion criteria

Exclusion Criteria:

- Planning to leave study site prior to completion of study

05

Study design

Phase
Not applicable
Primary purpose
Diagnostic
Allocation
Not applicable
Intervention model
Single group
Masking
None (open label)
Enrollment
30 participants (actual)

Study arms

  • Experimental
    Experimental: Diarrheal assessment with ADEPT, mobile phone tool

    Diagnostic Test: Diagnostic test: Accessible Diarrhea Etiology Prediction Tool (ADEPT)

Interventions

  • Diagnostic testDiagnostic test: Accessible Diarrhea Etiology Prediction Tool (ADEPT)

    The ADEPT tool allows providers to input information about pediatric diarrhea patients and provides outputs related to dehydration management and potential treatment.

06

What researchers measure

Primary outcomes

  1. Proportion of pediatric diarrhea encounters resulting in antibiotic prescription

    By self-report, before vs after ADEPT implementation

    Time frame: 6 weeks

07

Study locations

1 site
  • Icddrb
    Dhaka, Bangladesh
08

References and documents

Individual participant data

Plan to share: No

No publications or documents are linked to this record.

09

Timeline

1 registry update since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reached

Ran from Apr 2026 to primary completion in Jul 2026, 3 months.

How these figures are worked out, and which studies are left out of them.

Registered
Apr 13, 2026
First posted
Apr 20, 2026
StartActual
Apr 12, 2026
Primary completionActual
Jul 15, 2026
CompletionActual
Jul 15, 2026
Last update
Oct 8, 2026
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
Status
Active, not recruiting→Completed
changed Oct 8, 2026
Primary completion
Jul 31, 2026→Jul 15, 2026 (actual)
Oct 8, 2026
Study completion
Jul 31, 2026→Jul 15, 2026 (actual)
Oct 8, 2026
Show all 1 update
  1. Oct 8, 2026
    Active, not recruiting→Completed
    Primary completion Jul 31, 2026→Jul 15, 2026 (now actual)
    Study completion Jul 31, 2026→Jul 15, 2026 (now actual)
    + 1 other change: verification date

From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗

10

Registry details

Key details

Study ID
NCT07538531
Lead sponsor
Daniel Leung
Responsible party
Daniel Leung (Professor of Internal Medicine, University of Utah) — Sponsor-investigator
First posted
Apr 20, 2026
Start date
Apr 12, 2026
Primary completion
Jul 15, 2026
Completion
Jul 15, 2026
Last update
Oct 8, 2026

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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