StrokeNCT04641286
Clinical Outcome Modelling of Rapid Dynamics in Acute Stroke
An observational study of Stroke, run by King's College Hospital NHS Trust at 1 site in United Kingdom.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Stroke
- What is being tested?
- Body motion categorisation
- How many people
- 8,000 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 7 Jul 2021to Feb 2028
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients admitted to the stroke unit with a putative diagnosis of an acute stroke.
Who may be able to join
- Putative diagnosis of an acute stroke
- Admission on the stroke unit
Who cannot join
- Under 18 years of age
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United Kingdom1 site, 1 recruiting
- Recruiting
King's College Hospital NHS Foundation Trust
London
Lead Stroke Reserach Co-ordinator
About this study
Official title: 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.
Read more
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
- Being tested
- Body motion categorisation
- Medical subject headings
- Stroke
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Body motion categorisationOther
All patients will receive passive motion categorisation monitoring
| Study group | Role | What they receive |
|---|---|---|
| Stroke | Individuals admitted to the Hyper Acute Stroke Unit. Receives: Other: Body motion categorisation |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: Up to 24 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Nov 2020
- Study start7 Jul 2021
- Primary completionFeb 2028 (estimated)
- Study completionFeb 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for StrokeStudies of the same condition, open and under way.
- More trials run by King's College Hospital NHS TrustThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 8,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- King's College Hospital NHS Trust
- Sponsor type
- University, hospital or other
- Collaborators
- King's College London, University College, London
- Responsible party
- Sponsor
- Investigators
- Yee Mah, Study chair, King's College Hospital NHS Trust
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04641286
- Sponsor's protocol ID
- KCH20-069
- Other IDs
- MR/T005351/1
- Status last verified
- Oct 2024
- First submitted
- 22 Sep 2020
- Last updated
- 24 Oct 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 24 Oct 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Clinical Outcome Modelling of Rapid Dynamics in Acute Stroke With Joint-detail, Remote, Body Motion Analysis
- ClinicalTrials.gov ID
- NCT04641286
- Acronym / sponsor ID
- KCH20-069
- Conditions
- Stroke
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 8,000 participants (estimated)
- Lead sponsor
- King's College Hospital NHS TrustUniversity, hospital or other
- Collaborators
- King's College London, University College, London
- Study start
- 7 Jul 2021 (actual)
- Primary completion
- Feb 2028 (estimated)
- Study completion
- Feb 2028 (estimated)
- First posted
- 23 Nov 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Stroke | – | Other: Body motion categorisationIndividuals admitted to the Hyper Acute Stroke Unit. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients admitted to the stroke unit with a putative diagnosis of an acute stroke.
Key inclusion criteria (2 listed)
- Putative diagnosis of an acute stroke
- Admission on the stroke unit
Key exclusion criteria (1 listed)
- Under 18 years of age
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Body motion categorisationAll patients will receive passive motion categorisation monitoring | Other | Stroke |
Primary outcome
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.
Time frame: Up to 24 weeks
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.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Oct 2024.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Yee Mah study chair
King's College Hospital NHS Trust
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Stroke, run by King's College Hospital NHS Trust at 1 site in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 24 Oct 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Lead Stroke Research Co-ordionator (02032999000, kch-tr.kingsresearch@nhs.net), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
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. (time frame: Up to 24 weeks). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Oct 2024; AzTrials last refreshed its copy on 7 Nov 2026.