Muscle Trajectories in Acute Stroke Patients

NCT ID: NCT04337411

Last Updated: 2021-10-06

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 200 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2019-11-19
• Study Completion Date: 2024-07-31

Brief Summary

The aim of this study is to explore time-related trajectories of muscle alterations and inflammation in acute hospitalized stroke patients. Furthermore, the researchers want to gain insight in the predictive values of these time-related trajectories towards gait recovery in the acute stroke population.

Detailed Description

STUDY DESIGN:

Two longitudinal prospective cohort studies will be conducted in which non-ambulatory (cohort 1) and ambulatory (cohort 2) acute stroke patients will participate.

PATIENT RECRUITMENT:

The investigators aim to recruit 200 subjects (100/cohort). Patients will be recruited at the Neurology ward of the UZ Brussel.

PROCEDURE:

All stroke survivors admitted to the Neurology ward of UZ Brussel will be screened for eligibility. Afterwards, an informed consent will be conducted for all subjects who met the inclusion criteria.

Baseline assessments (T0) of gait recovery outcomes on the one hand and predictors for gait recovery on the other hand will be measured. To predict gait recovery, researchers will observe two novel biomarkers: stroke-induced muscle wasting and inflammation. Furthermore, the investigators will also assess relevant known predictors for gait recovery to compare the relevance of the novel markers. T0 assessments will start preferably within 3 days post-stroke.

To assess time-related trajectories of muscle alterations and inflammation, follow-up assessments of these predictors will be performed 3 days after baseline assessments (T1), at discharge (T2) and 3 months follow-up (T3). T1 follow-up measurements will only be possible for patients with motor impairments post-stroke since they have a longer stay at the hospital compared to patients without motor impairments after stroke (mean hospital stay of 5 to 8 days for patients without or with motor impairments post-stroke respectively).

The assessments of the gait recovery outcome measures will be repeated at discharge (T2) and 3 months follow-up (T3).

MATERIALS:

To measure gait recovery in acute stroke survivors, the researchers will make use of wearable gait sensors (Physiolog®, Gait Up SA, Switzerland) to register gait speed and a lightweight chest carrying gas analysis system (Metamax 3B, Cortex, Germany) to measure cardiorespiratory parameters.

For the predictors, investigators will use handheld dynamometers (MicroFET2 and Martin Vigorimeter) to assess muscle strength, grip strength and muscle fatigue. Furthermore, researchers need a Bioelectrical Impedance analysis (BIA) device (Bodystat® QuadScan 4000, UK) to assess the muscle mass of our subjects and a portable ultrasound system (Viamo SV 7 with linear-array transducer, Canon Medical Systems, Netherlands) to assess muscle architecture.

STATISTICAL ANALYSIS:

Various biomarkers will be observed at each of the planned time points. Because the aim is to make correct predictions based on any information that is available at the early stages, the observations will not only be considered as such, but also summarized in terms of their time- related characteristics, such as steepest drop, frequency of improvement, or any other characteristic that may reveal itself as distinguishing. These predictors will be combined into predictive models such as random forests and boosting to establish the best combinations for making good predictions while accommodating inter-predictor correlations. The quality of the models will be established with cross-validation. The large set of observations and their summarized temporal characteristics will be used to determine whether different types of trajectories emerge. Hierarchical cluster analysis will label patients for each of the cluster solutions and the usefulness of patient labelling will be evaluated by their predicted gait performance. The extracted patient type will be included in random forests or boosting to evaluate its importance. The extracted patient type could also be used jointly with other predictors suggested as important in either a linear/logistic (mixed) model or an extended cox proportional hazard model, which are more traditional statistical approaches. While predictive performance remains the key goal, such models would be more interpretable on the potential underlying mechanism, with parameter estimates and confidence intervals.

Conditions

Stroke

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

Cohort 1

Non-ambulatory acute stroke survivors at admission (Functional Ambulation Categories (FAC) ≤ 2)

Follow-up assessments

Intervention Type: OTHER

Longitudinal evaluation of recovery

Cohort 2

Ambulatory acute stroke survivors at admission (Functional Ambulation Categories (FAC) ≥ 3)

Follow-up assessments

Intervention Type: OTHER

Longitudinal evaluation of recovery

Interventions

Follow-up assessments

Longitudinal evaluation of recovery

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Adults (≥18 years)
• Hospitalized at the Neurology ward of UZ Brussel
• Diagnosed with first-ever stroke (as defined by the World Health Organisation)
• Able to provide written or verbal informed consent

Exclusion Criteria

• Other neurological or orthopaedic problems leading to impaired gait
• Severe deficits of communication, memory or understanding

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Universitair Ziekenhuis Brussel

OTHER

Sponsor Role: collaborator

Vrije Universiteit Brussel

OTHER

Sponsor Role: lead

Responsible Party

Lotte Cuypers

Doctoral Researcher

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

David Beckwée, Prof. Ph.D

Role: STUDY_CHAIR

Vrije Universiteit Brussel

Eva Swinnen, Prof. Ph.D

Role: STUDY_CHAIR

Vrije Universiteit Brussel

Lotte Cuypers, Dra.

Role: PRINCIPAL_INVESTIGATOR

Vrije Universiteit Brussel

Locations

Universitair Ziekenhuis Brussel

Jette, Brussels Capital, Belgium

Site Status: RECRUITING

Countries

Belgium

Central Contacts

Lotte Cuypers, Dra.

Role: CONTACT

lotte.cuypers@vub.be

00324774505

Eva Swinnen, Prof. Ph.D

Role: CONTACT

eva.swinnen@vub.be

003224774529

Facility Contacts

Lotte Cuypers, Dra.

Role: primary

lotte.cuypers@vub.be

00324774505

Other Identifiers

Muscle trajectories

Identifier Type: -

Identifier Source: org_study_id