Clinical Research Directory
Browse clinical research sites, groups, and studies.
4 clinical studies listed.
Filters:
Tundra lists 4 Algorithms clinical trials. Each listing includes eligibility criteria, study locations, and direct links to research sites in the Tundra directory.
This data is also available as a public JSON API. AI systems and LLMs are encouraged to use it for structured queries.
NCT07733440
PROstate Cancer Risk Calculator for ACTionable Clinical Decision-making in Nigeria
This study is a pilot trial that builds on findings from the validation of prostate cancer risk calculators in Nigerian men. The goal of the overall study is to improve the early detection of prostate cancer in a high-risk population. The main questions the validation study aims to answer are: 1. How accurately do existing prostate cancer risk calculators identify Nigerian men with clinically significant prostate cancer? 2. Will a new risk calculator designed for Nigerian men more accurately identify those with clinically significant prostate cancer? The main questions the intervention study aims to answer is: Will the primary care provider-facing risk calculator be feasible and acceptable for primary care providers to implement? The intervention trial will be piloted among participants in community-level hospitals in order to primarily assess implementation outcomes
Gender: MALE
Ages: 18 Years - Any
Updated: 2026-07-29
1 state
NCT07538531
The Utility and Feasibility of Accessible Diarrhea Etiology Prediction Tool (ADEPT) in an Informal Healthcare Setting
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.
Gender: All
Ages: 18 Years - Any
Updated: 2026-07-06
NCT05366660
Remote Programming of Cardiac Implantable Electronic Device
Cardiac Implantable Electronic Devices (CIEDs) such as pacemakers and implantable cardioverter defibrillators, need to be regularly interrogated and reprogrammed to ensure proper functioning. While remote monitoring allows for partial interrogation at a remote location, full interrogation and changing the CIED parameters is only possible when the patient visits a cardiologist capable of performing device programming. This can be challenging for patients and may cause unnecessary delays, particularly in settings of limited resources, enforced physical distancing, and quarantines. We aim to investigate the efficacy and safety of remote programming.
Gender: All
Ages: 18 Years - Any
Updated: 2026-05-14
1 state
NCT06532994
Predictive Algorithms for Critical Rehabilitation Outcomes
An increasing amount of evidence from evidence-based medicine indicates that early rehabilitation intervention for patients receiving mechanical ventilation is safe and feasible, and can promote functional recovery and reduce hospital stay. However, the conscious state, respiratory function, and daily living activities of these patients after being discharged from the ICU vary greatly, and some patients do not show obvious benefits. How to identify which patients may have benefit from early rehabilitation is a key issue that needs to be addressed in critical care rehabilitation. This study aims to investigate the clinical data related to the disease of the ICU survivors who received mechanical ventilation as the research object, by collecting their clinical data when receiving early rehabilitation intervention, and constructing a clinical prediction model for the efficacy of early rehabilitation intervention in the ICU through the selection of optimal regression equation or machine learning algorithm. The application of this model can effectively determine whether ICU inpatients need early rehabilitation intervention, thereby reducing complication rates and improving their quality of life.
Gender: All
Ages: 18 Years - 90 Years
Updated: 2026-04-21
1 state