Dynamics of neurological and behavioural recovery after stroke
| Autor: | Saes, Mique |
|---|---|
| Přispěvatelé: | Kwakkel, Gerrit, Meskers, Carolus Gerardus Maria, van Wegen, Erwin, VUmc - School of Medical Sciences, Meskers, Carel, VU University medical center, Rehabilitation medicine |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Saes, M 2022, ' Dynamics of neurological and behavioural recovery after stroke ', PhD, Vrije Universiteit Amsterdam, s.n. . Saes, M 2022, ' Dynamics of neurological and behavioural recovery after stroke ', Doctor of Philosophy, Vrije Universiteit Amsterdam, s.n. . < https://hdl.handle.net/1871.1/19d9f0d1-68ff-4981-901a-a3f98167eaaa > |
| Popis: | Stroke is one of the main causes of serious adult disability in Europe. Around 80% of stroke survivors suffer from motor impairment, typically affecting unilateral motor control of the face, arm, and leg. Especially upper limb impairments limit patient’s activities of daily living. While the majority of patients shows some level of spontaneous neurological recovery, about 20-30% do not recover at all. Most of the observed improvements in upper limb function occur in the first 10 weeks after stroke. However, the mechanisms underlying motor recovery are poorly understood. While primary and secondary prevention measures aim to reduce the number of stroke patients and to detect and treat the stroke as soon as possible, investing in tertiary prevention is important to predict, accelerate, and enhance post-stroke recovery. Chapter 1 discusses two issues. First, the inability to monitor neurological recovery after stroke due to the absence of adequate quantification of neurological state. Secondly, the demand for additional prognostic biomarkers of motor recovery in more severely affected stroke patients. Adequate quantification of neurological recovery is required to investigate whether neurorehabilitation interventions can induce neurological motor recovery after stroke. Unfortunately, neurological motor recovery cannot be measured directly. Therefore, derivatives of neurological state associated with behavioural recovery should be identified, referred to as biomarkers. In this thesis, we investigate biomarkers derived from observed behaviour and biomarkers derived from brain activity. A clinical assessment which is often used in scientific research to monitor behavioural recovery after stroke is the Fugl-Meyer motor assessment of the upper extremity (FM-UE). The FM-UE reflects the ability to perform movements dissociated from abnormal muscle synergies and originates from the different stages of motor recovery after stroke. With this, the FM-UE is assumed to be closely related to behavioural restitution, and thereby neural restitution. However, the FM-UE suffers from a ceiling effect and is amongst others influenced by impairment of muscle strength. Quality of movement (QoM), derived from kinematic data, has been proposed as a more adequate quantification of behavioural recovery as it reflects the degree of motor control. Besides observed behaviour, also neural oscillations have been affected by stroke, which have been proposed to be measured to monitor neurological recovery. Upper limb motor impairment in the chronic phase can be predicted quite well for mildly affected stroke patients, based on their initial upper limb motor impairment. However, especially in moderate to severely affected patients, prediction models are unreliable and require improvement. There is a demand for additional prognostic biomarkers which can be obtained from patients who are not able to perform active motor tasks. Neurophysiological parameters, for example obtained from neural oscillations recorded using EEG in awake resting-state, may serve as additional prognostic biomarkers of behavioural recovery after stroke. In Part I of this thesis, it is determined which quantitative EEG parameters can serve as monitoring or prognostic biomarkers of neurological recovery underlying behavioural recovery of the upper extremity after stroke. In Part II of this thesis, it is described how QoM is measured using kinematics to quantify behavioural restitution, and whether it may serve as monitoring biomarker of neurological recovery. When motor recovery is better understood and the accuracy of early prediction of behavioural recovery is improved, clinicians will be able to: 1) Better inform patients and their families properly early after stroke, 2) Improve the triage by preventing an over- or underestimation of patients’ expected capacity, and 3) Select the most adequate rehabilitation therapy. |
| Databáze: | OpenAIRE |
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