Clinical Outcome Modelling of Rapid Dynamics in Acute Stroke

NCT04641286 | Recruiting

• 2 other identifiers: KCH20-069MR/T005351/1
• Study Type: observational
• Target: 8,000
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Stroke

Outcome Measures

Primary Outcomes (1)

• Quantify the contribution of joint-level motor dynamics to high-dimensional, predictive models of major clinical outcomes in acute stroke through comparisons of predictive fidelity.

  The predictive fidelity will be quantified by out-of-sample receiver operating characteristic curves for binary variables and mean squared error for real number variables.

  Up to 24 weeks

Study Arms (1)

Stroke

Individuals admitted to the Hyper Acute Stroke Unit.

Other: Body motion categorisation

Interventions

Body motion categorisation OTHER

All patients will receive passive motion categorisation monitoring

Stroke

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients admitted to the stroke unit with a putative diagnosis of an acute stroke.

You may qualify if:

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

You may not qualify if:

• Under 18 years of age

Sponsors & Collaborators

• King's College Hospital NHS Trust: lead
• King's College London: collaborator
• University College, London: collaborator

Study Sites (1)

King's College Hospital NHS Foundation Trust

London, United Kingdom

RECRUITING

MeSH Terms

Conditions

Stroke

Condition Hierarchy (Ancestors)

Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Vascular Diseases; Cardiovascular Diseases

Study Officials

• Yee Mah

  King's College Hospital NHS Trust

  STUDY CHAIR

Central Study Contacts

Lead Stroke Research Co-ordionator

CONTACT

02032999000; kch-tr.kingsresearch@nhs.net

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 22, 2020
• First Posted: November 23, 2020
• Study Start: July 7, 2021
• Primary Completion (Estimated): February 1, 2028
• Study Completion (Estimated): February 1, 2028
• Last Updated: October 24, 2024

Record last verified: 2024-10

Locations

GB (1)