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Machine Learning to Reduce Hypertension Treatment Clinical Inertia

StatusNot Yet Recruiting
PhaseNot applicable
Started
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Record status
This record was last updated April 10, 2025 (before its estimated May 31, 2025 completion). Its status may not reflect the trial's current state.

Record History

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  1. Enrollment target: 100 to 50
    • Start date: Oct 1, 2024 to Apr 25, 2025
    • Eligibility criteria shortened, about 4 words
    v4
  2. Re-verified, no change to tracked fieldsv3
  3. Primary completion date: Jun 30, 2024 to May 31, 2025
    • Start date: Jul 1, 2023 to Oct 1, 2024
    • Study completion date: Jun 1, 2025 to Jul 31, 2025
    v2
  4. Study First Submitted
  • Stopped: an ongoing trial was terminated, suspended or withdrawn.
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
Temple University
44 trials monitored
See 2 trials at risk
Hypertension
1,925 trials monitored
See 99 trials at risk
Among individuals with an uncontrolled BP at the current visit, the objective of this study is to compare clinical management of hypertension with and without information from a machine learning algorithm on whether a patient will have uncontrolled blood pressure at their next follow up visit through a case-vignette study.
Trial Details
NCT Number NCT05406336
Lead Sponsor Temple University
Conditions
(from sponsor)		 Hypertension
Related terms Hypertension
Enrollment 50 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov