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NCT04641286Recruiting

Clinical Outcome Modelling of Rapid Dynamics in Acute Stroke

Clinical Outcome Modelling of Rapid Dynamics in Acute Stroke With Joint-detail, Remote, Body Motion Analysis

Source: ClinicalTrials.gov · Last updated 24 Oct 2024 · Not updated for over 12 months - ask the site whether it is still open

Brief summary (registry, in English)

Stroke - still the second commonest cause of death and principal cause of adult neurological disability in the Western World - is characterised by rapid changes over time and marked variability in outcomes. A patient may improve or deteriorate over minutes, and the resultant disability may range from an obvious complete paralysis to subtle, task dependent incoordination of a single limb. Unlike many other neurological disorders, stroke can be exquisitely sensitive to prompt and intelligently tailored treatment, rewarding innovation in the delivery of care with real-world, tangible impact on patient outcomes. Optimal treatment therefore requires both detailed characterisation of the patient's clinical picture and its pattern of change over time. Arguably the most important aspect of the patient's clinical picture -- body movement -- remains remarkably poorly documented: quantified only subjectively and at infrequent intervals in the patient's clinical evolution. The combination of artificial intelligence with high-performance computing now enables automatic extraction of a patient's skeletal frame resolved down to major joints, like that of a stick-man, to be delivered simply, safely, and inexpensively, without the use of cumbersome body worn markers. Central to this technology is patient privacy, with the skeletal frame extracted in real time, ensuring no video data, from which patients can be identified, to be stored or transmitted by the device. Our motion categorisation system -- MoCat -- will be used to study the rapid dynamics of acute stroke, seamlessly embedded in the clinical stream. By quantifying the change in motor deficit over time we shall examine the relationship between these trajectories with clinical outcomes and develop predictive models that can support clinical management and optimise service delivery.

Status (registry)
Recruiting
Study type
Observational
Enrollment
8000 (estimated)
First submitted
22 Sept 2020
Start date
7 Jul 2021
Primary completion date
Feb 2028
Lead sponsor
King's College Hospital NHS Trust
Diseases
Stroke
NCT number
NCT04641286

What you commit to

  • Study type: Observational
  • Planned participants: 8000
  • From 7 Jul 2021 to the primary completion date, Feb 2028
  • 1 site in 1 country
  • Visits and tests: ask the trial team, the registry does not list them

Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.

Who cannot take part

Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.

Age

  • Under 18 years of age

Who the study is looking for

  • Putative diagnosis of an acute stroke
  • Admission on the stroke unit

Age in the registry: 18 years to - · Sex: All · Does not accept healthy volunteers

Full criteria on ClinicalTrials.gov

Sites (1)

Sites in registry order. Pick your city on the disease page to sort them by distance.

SiteCityCountrySite status
King's College Hospital NHS Foundation Trust
Coordinator of this site? Confirm its status
LondonUnited KingdomRecruiting

This page is information, not medical advice. Discuss any trial with your doctor.