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

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.

Study Overview

• Status: Recruiting
• Conditions: Stroke
• Intervention / Treatment: Other: Body motion categorisation

• Study Type: Observational
• Enrollment (Estimated): 5000

Contacts and Locations

• Study Contact: Name: Lead Stroke Research Co-ordionator; Phone Number: 02032999000; Email: j.aeron-thomas@nhs.net

Study Locations

• United Kingdom
  • London, United Kingdom
    • Recruiting
    • King's College Hospital NHS Foundation Trust
    • Contact: Lead Stroke Reserach Co-ordinator

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

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

Description

Inclusion Criteria:

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

Exclusion Criteria:

• Under 18 years of age

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Stroke; Individuals admitted to the Hyper Acute Stroke Unit.	Other: Body motion categorisation; All patients will receive passive motion categorisation monitoring

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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

Collaborators and Investigators

• Sponsor: King's College Hospital NHS Trust
• Collaborators: King's College London; University College, London
• Investigators: Study Chair: Yee Mah, King's College Hospital NHS Trust

Study record dates

Study Major Dates

• Study Start (Actual): July 7, 2021
• Primary Completion (Estimated): January 1, 2025
• Study Completion (Estimated): January 1, 2025

Study Registration Dates

• First Submitted: September 22, 2020
• First Submitted That Met QC Criteria: November 20, 2020
• First Posted (Actual): November 23, 2020

Study Record Updates

• Last Update Posted (Actual): October 5, 2023
• Last Update Submitted That Met QC Criteria: October 4, 2023
• Last Verified: October 1, 2023

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Cardiovascular Diseases; Vascular Diseases; Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Stroke
• Other Study ID Numbers: KCH20-069; MR/T005351/1 (Other Grant/Funding Number: MRC)

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No