Ignite Creation Date:
2024-05-06 @ 7:27 PM
Last Modification Date:
2024-10-26 @ 3:07 PM
Study NCT ID:
NCT06017843
Status:
RECRUITING
Last Update Posted:
2023-09-06
First Post:
2023-08-21
Brief Title:
Impact Evaluation of Use of MATCH AI Predictive Modelling for Identification of Hotspots for TB Active Case Finding
Sponsor:
Centre for Global Public Health Pakistan
Organization:
Centre for Global Public Health Pakistan
Study Overview
Official Title:
Impact Evaluation of Use of MATCH AI Predictive Modelling for Identification of Hotspots for TB Active Case Finding in Pakistan a Pragmatic Stepped Wedge Cluster Randomized Trial
Status:
RECRUITING
Status Verified Date:
2024-07
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
SPOT-TB
Brief Summary:
The aim of this pragmatic stepped wedge cluster-randomized trial is to measure the comparative yield number of incident TB cases diagnosed during active case-finding camps using a site selection approach based on predictions generated via an artificial intelligence software called MATCH-AI intervention group versus the conventional approach of camp site selection using field-staff knowledge and experience control group The trial will help inform whether a targeted approach towards screening for TB using artificial-intelligence can improve yields of TB cases detected through community-based active case-finding
Detailed Description:
Despite significant progress over the past decades an estimated 106 million individuals fell ill with tuberculosis TB in 2021 and the disease caused 16 million deaths globally Pakistan is ranked as the 5th highest TB burden country in the world and TB causes 42000 deaths annually in the country A key challenge in the Pakistans response to TB is ensuring diagnosis and treatment of all individuals with TB In 2020 out of the 573000 cases a total of 276736 48 were notified Bridging this case-detection gap is a critical objective for the National TB Program NTP Active case-finding ACF is a potential strategy to increase case-detection by systematic screening of communities for TB Recent evidence indicates that ACF can also reduce population-level TB incidence and prevalence through early detection While ACF interventions have demonstrated effectiveness in community-trials and are now being conducted at scale in Pakistan concerns remain regarding their yields and cost-effectiveness in programmatic settings
The primary aim of this study is to investigate whether a targeted approach towards community-based screening using MATCH-AI an artificial intelligence software that models sub-district TB prevalence can improve the yield of ACF interventions in Pakistan In the intervention arm field-team will conduct community-based ACF activities called chest camps primarily in locations predicted by MATCH-AI to have a higher prevalence of TB In the control arm field-teams will continue to utilize existing approaches towards camp site-selection The trial will be conducted in 65 districts of Pakistan in collaboration with implementation partners of the NTP
The primary aim of this study is to investigate whether a targeted approach towards community-based screening using MATCH-AI an artificial intelligence software that models sub-district TB prevalence can improve the yield of ACF interventions in Pakistan In the intervention arm field-team will conduct community-based ACF activities called chest camps primarily in locations predicted by MATCH-AI to have a higher prevalence of TB In the control arm field-teams will continue to utilize existing approaches towards camp site-selection The trial will be conducted in 65 districts of Pakistan in collaboration with implementation partners of the NTP
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None