Personalized Neurorehabilitative Precision Medicine - From Data to Therapies
MWKNeuroReha
1 other identifier
observational
500
1 country
1
Brief Summary
Stroke is the most common neurological disease leaving one third dead and one third with permanent impairment despite best medical treatment. The aim of the present study is to investigate why patients differ in how they benefit from neurorehabilitation by collecting clinical, electrophysiological, imaging and laboratory data in the acute phase of stroke as well as later on during rehabilitation and after 90 days. Following a closed-loop approach the data is analyzed by a machine learning algorithm to create a personalized neurorehabilitation strategy.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Dec 2020
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
December 1, 2020
CompletedFirst Submitted
Initial submission to the registry
December 21, 2020
CompletedFirst Posted
Study publicly available on registry
December 30, 2020
CompletedPrimary Completion
Last participant's last visit for primary outcome
March 31, 2022
CompletedStudy Completion
Last participant's last visit for all outcomes
June 30, 2022
CompletedDecember 30, 2020
December 1, 2020
1.3 years
December 21, 2020
December 29, 2020
Conditions
Outcome Measures
Primary Outcomes (1)
Motor outcome of the upper extremity (UE) after acute stroke
Fugl-Meyer Assessment for the upper extremity (FMA-UE) in the acute phase compared to the result after 90 days.
90 days
Secondary Outcomes (4)
Functional outcome of the UE after acute stroke
90 days
Independency in daily life after acute stroke
90 days
Independency in daily life after acute stroke
90 days
Qualitiy of life after acute stroke
90 days
Study Arms (1)
Acute stroke with affection of the upper extremity
* Subject is 18 years or above. * Subject has an acute stroke affecting one UE (FMA less than 50). * Subject or caregiver understands the study and its procedures and gives informed consent. * If the subject is not able to give informed consent: * The assumed will of the patient is to be determined by the patient's provision (if existing), the health care proxy (if existing) and/or the moral concepts expressed by the patient to close relatives. * The legal representative gives informed consent because participation is the assumed will of the patient as assessed by the aforementioned points.
Interventions
Eligibility Criteria
We aim to include all patients with acute stroke affecting the UE (FMA less than 50) on our SU. Other symptoms like aphasia or neglect are no reason for exclusion since we intend to include as many patients as possible to capture the whole spectrum of stroke from mild to severe. Especially the last case, the inclusion of severely affected patients, is of utmost importance in our view. Due to their grave impairments they have the greatest need for neurorehabilitation; at the same time, this group of patients is the most vulnerable because of their preexisting comorbidities and conditions coming with immobility e. g. pneumonia. A personalized treatment would meet their need for intense rehabilitation while providing enough recreation time since unnecessary, ineffective rehabilitation could be omitted.
You may qualify if:
- Subject is 18 years or above.
- Subject has an acute stroke affecting one UE (FMA less than 50).
- Subject or understands the study and its procedures and gives informed consent.
- If the subject is not able to give informed consent:
- The assumed will of the patient is to be determined by the patient's provision (if existing), the health care proxy (if existing) and/or the moral concepts expressed by the patient to close relatives.
- The legal representative gives informed consent because participation is the assumed will of the patient as assessed by the aforementioned points.
You may not qualify if:
- Subject is less than 18 years old.
- The subject does not have an acute stroke, or stroke does not affect the UE, or FMA \> 50.
- Subject or legal representative cannot give informed consent.
- Patient has an intracranial implant (e.g., aneurysm clips, shunts, stimulators, cochlear implants, or electrodes) or any other metal object within or near the head (excluding the mouth) that cannot be safely removed.
- Subject has a history of any illness that, in the opinion of the study investigator, might confound the results of the study or poses an additional risk to the subject by their participation in the study.
- There is any concern by the investigator regarding the safe participation of the subject in the study, or for any other reason the investigator considers the subject inappropriate for participation in the study.
- Subject is pregnant.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- University Hospital Tuebingenlead
- Interfaculty Institute for Biomedical Informatics (IBMI)collaborator
- Cluster of Excellence - Machine Learning for Sciencecollaborator
- Department for diagnostic and interventional neuroradiology, University hospital of Tuebingencollaborator
- Deparmet of biomedical magnetic resonance, University hospital of Tuebingencollaborator
- Kliniken Schmiedercollaborator
- SRH-Klinikencollaborator
Study Sites (1)
University hospital of Tuebingen
TĂ¼bingen, Baden-Wurttemberg, 72076, Germany
Related Publications (35)
Brott T, Adams HP Jr, Olinger CP, Marler JR, Barsan WG, Biller J, Spilker J, Holleran R, Eberle R, Hertzberg V, et al. Measurements of acute cerebral infarction: a clinical examination scale. Stroke. 1989 Jul;20(7):864-70. doi: 10.1161/01.str.20.7.864.
PMID: 2749846BACKGROUNDCasali AG, Gosseries O, Rosanova M, Boly M, Sarasso S, Casali KR, Casarotto S, Bruno MA, Laureys S, Tononi G, Massimini M. A theoretically based index of consciousness independent of sensory processing and behavior. Sci Transl Med. 2013 Aug 14;5(198):198ra105. doi: 10.1126/scitranslmed.3006294.
PMID: 23946194BACKGROUNDChen HF, Lin KC, Wu CY, Chen CL. Rasch validation and predictive validity of the action research arm test in patients receiving stroke rehabilitation. Arch Phys Med Rehabil. 2012 Jun;93(6):1039-45. doi: 10.1016/j.apmr.2011.11.033. Epub 2012 Mar 14.
PMID: 22420887BACKGROUNDCompston A. Aids to the investigation of peripheral nerve injuries. Medical Research Council: Nerve Injuries Research Committee. His Majesty's Stationery Office: 1942; pp. 48 (iii) and 74 figures and 7 diagrams; with aids to the examination of the peripheral nervous system. By Michael O'Brien for the Guarantors of Brain. Saunders Elsevier: 2010; pp. [8] 64 and 94 Figures. Brain. 2010 Oct;133(10):2838-44. doi: 10.1093/brain/awq270. No abstract available.
PMID: 20928945BACKGROUNDDrozdowska BA, Singh S, Quinn TJ. Thinking About the Future: A Review of Prognostic Scales Used in Acute Stroke. Front Neurol. 2019 Mar 21;10:274. doi: 10.3389/fneur.2019.00274. eCollection 2019.
PMID: 30949127BACKGROUNDFanciullacci C, Bertolucci F, Lamola G, Panarese A, Artoni F, Micera S, Rossi B, Chisari C. Delta Power Is Higher and More Symmetrical in Ischemic Stroke Patients with Cortical Involvement. Front Hum Neurosci. 2017 Jul 28;11:385. doi: 10.3389/fnhum.2017.00385. eCollection 2017.
PMID: 28804453BACKGROUNDFinnigan S, van Putten MJ. EEG in ischaemic stroke: quantitative EEG can uniquely inform (sub-)acute prognoses and clinical management. Clin Neurophysiol. 2013 Jan;124(1):10-9. doi: 10.1016/j.clinph.2012.07.003. Epub 2012 Aug 2.
PMID: 22858178BACKGROUNDGladstone DJ, Danells CJ, Black SE. The fugl-meyer assessment of motor recovery after stroke: a critical review of its measurement properties. Neurorehabil Neural Repair. 2002 Sep;16(3):232-40. doi: 10.1177/154596802401105171.
PMID: 12234086BACKGROUNDGrefkes C, Nowak DA, Eickhoff SB, Dafotakis M, Kust J, Karbe H, Fink GR. Cortical connectivity after subcortical stroke assessed with functional magnetic resonance imaging. Ann Neurol. 2008 Feb;63(2):236-46. doi: 10.1002/ana.21228.
PMID: 17896791BACKGROUNDHutanu A, Iancu M, Balasa R, Maier S, Dobreanu M. Predicting functional outcome of ischemic stroke patients in Romania based on plasma CRP, sTNFR-1, D-Dimers, NGAL and NSE measured using a biochip array. Acta Pharmacol Sin. 2018 Jul;39(7):1228-1236. doi: 10.1038/aps.2018.26. Epub 2018 Jun 21.
PMID: 29926842BACKGROUNDHe L, Wang J, Dong W. The clinical prognostic significance of hs-cTnT elevation in patients with acute ischemic stroke. BMC Neurol. 2018 Aug 20;18(1):118. doi: 10.1186/s12883-018-1121-5.
PMID: 30124165BACKGROUNDHeo J, Yoon JG, Park H, Kim YD, Nam HS, Heo JH. Machine Learning-Based Model for Prediction of Outcomes in Acute Stroke. Stroke. 2019 May;50(5):1263-1265. doi: 10.1161/STROKEAHA.118.024293.
PMID: 30890116BACKGROUNDKasner SE. Clinical interpretation and use of stroke scales. Lancet Neurol. 2006 Jul;5(7):603-12. doi: 10.1016/S1474-4422(06)70495-1.
PMID: 16781990BACKGROUNDKim B, Winstein C. Can Neurological Biomarkers of Brain Impairment Be Used to Predict Poststroke Motor Recovery? A Systematic Review. Neurorehabil Neural Repair. 2017 Jan;31(1):3-24. doi: 10.1177/1545968316662708. Epub 2016 Aug 8.
PMID: 27503908BACKGROUNDLeao MT, Naros G, Gharabaghi A. Detecting poststroke cortical motor maps with biphasic single- and monophasic paired-pulse TMS. Brain Stimul. 2020 Jul-Aug;13(4):1102-1104. doi: 10.1016/j.brs.2020.05.005. Epub 2020 May 8.
PMID: 32418913BACKGROUNDLerner AJ, Wassermann EM, Tamir DI. Seizures from transcranial magnetic stimulation 2012-2016: Results of a survey of active laboratories and clinics. Clin Neurophysiol. 2019 Aug;130(8):1409-1416. doi: 10.1016/j.clinph.2019.03.016. Epub 2019 Apr 6.
PMID: 31104898BACKGROUNDMakris K, Haliassos A, Chondrogianni M, Tsivgoulis G. Blood biomarkers in ischemic stroke: potential role and challenges in clinical practice and research. Crit Rev Clin Lab Sci. 2018 Aug;55(5):294-328. doi: 10.1080/10408363.2018.1461190. Epub 2018 Apr 18.
PMID: 29668333BACKGROUNDMaruyama K, Uchiyama S, Shiga T, Iijima M, Ishizuka K, Hoshino T, Kitagawa K. Brain Natriuretic Peptide Is a Powerful Predictor of Outcome in Stroke Patients with Atrial Fibrillation . Cerebrovasc Dis Extra. 2017;7(1):35-43. doi: 10.1159/000457808. Epub 2017 Mar 2.
PMID: 28253498BACKGROUNDPark CH, Chang WH, Ohn SH, Kim ST, Bang OY, Pascual-Leone A, Kim YH. Longitudinal changes of resting-state functional connectivity during motor recovery after stroke. Stroke. 2011 May;42(5):1357-62. doi: 10.1161/STROKEAHA.110.596155. Epub 2011 Mar 24.
PMID: 21441147BACKGROUNDPuig J, Blasco G, Alberich-Bayarri A, Schlaug G, Deco G, Biarnes C, Navas-Marti M, Rivero M, Gich J, Figueras J, Torres C, Daunis-I-Estadella P, Oramas-Requejo CL, Serena J, Stinear CM, Kuceyeski A, Soriano-Mas C, Thomalla G, Essig M, Figley CR, Menon B, Demchuk A, Nael K, Wintermark M, Liebeskind DS, Pedraza S. Resting-State Functional Connectivity Magnetic Resonance Imaging and Outcome After Acute Stroke. Stroke. 2018 Oct;49(10):2353-2360. doi: 10.1161/STROKEAHA.118.021319.
PMID: 30355087BACKGROUNDRehme AK, Eickhoff SB, Wang LE, Fink GR, Grefkes C. Dynamic causal modeling of cortical activity from the acute to the chronic stage after stroke. Neuroimage. 2011 Apr 1;55(3):1147-58. doi: 10.1016/j.neuroimage.2011.01.014. Epub 2011 Jan 14.
PMID: 21238594BACKGROUNDRichter P, Werner J, Heerlein A, Kraus A, Sauer H. On the validity of the Beck Depression Inventory. A review. Psychopathology. 1998;31(3):160-8. doi: 10.1159/000066239.
PMID: 9636945BACKGROUNDRosanova M, Fecchio M, Casarotto S, Sarasso S, Casali AG, Pigorini A, Comanducci A, Seregni F, Devalle G, Citerio G, Bodart O, Boly M, Gosseries O, Laureys S, Massimini M. Sleep-like cortical OFF-periods disrupt causality and complexity in the brain of unresponsive wakefulness syndrome patients. Nat Commun. 2018 Oct 24;9(1):4427. doi: 10.1038/s41467-018-06871-1.
PMID: 30356042BACKGROUNDRossi S, Hallett M, Rossini PM, Pascual-Leone A; Safety of TMS Consensus Group. Safety, ethical considerations, and application guidelines for the use of transcranial magnetic stimulation in clinical practice and research. Clin Neurophysiol. 2009 Dec;120(12):2008-2039. doi: 10.1016/j.clinph.2009.08.016. Epub 2009 Oct 14.
PMID: 19833552BACKGROUNDSaber H, Somai M, Rajah GB, Scalzo F, Liebeskind DS. Predictive analytics and machine learning in stroke and neurovascular medicine. Neurol Res. 2019 Aug;41(8):681-690. doi: 10.1080/01616412.2019.1609159. Epub 2019 Apr 30.
PMID: 31038007BACKGROUNDSheorajpanday RV, Nagels G, Weeren AJ, van Putten MJ, De Deyn PP. Quantitative EEG in ischemic stroke: correlation with functional status after 6 months. Clin Neurophysiol. 2011 May;122(5):874-83. doi: 10.1016/j.clinph.2010.07.028. Epub 2010 Oct 18.
PMID: 20961806BACKGROUNDStinear CM, Byblow WD, Ackerley SJ, Smith MC, Borges VM, Barber PA. PREP2: A biomarker-based algorithm for predicting upper limb function after stroke. Ann Clin Transl Neurol. 2017 Oct 24;4(11):811-820. doi: 10.1002/acn3.488. eCollection 2017 Nov.
PMID: 29159193BACKGROUNDThiel A, Vahdat S. Structural and resting-state brain connectivity of motor networks after stroke. Stroke. 2015 Jan;46(1):296-301. doi: 10.1161/STROKEAHA.114.006307. Epub 2014 Dec 4. No abstract available.
PMID: 25477218BACKGROUNDTscherpel C, Dern S, Hensel L, Ziemann U, Fink GR, Grefkes C. Brain responsivity provides an individual readout for motor recovery after stroke. Brain. 2020 Jun 1;143(6):1873-1888. doi: 10.1093/brain/awaa127.
PMID: 32375172BACKGROUNDvan Kuijk AA, Pasman JW, Hendricks HT, Zwarts MJ, Geurts AC. Predicting hand motor recovery in severe stroke: the role of motor evoked potentials in relation to early clinical assessment. Neurorehabil Neural Repair. 2009 Jan;23(1):45-51. doi: 10.1177/1545968308317578. Epub 2008 Sep 15.
PMID: 18794218BACKGROUNDVanGilder RL, Davidov DM, Stinehart KR, Huber JD, Turner RC, Wilson KS, Haney E, Davis SM, Chantler PD, Theeke L, Rosen CL, Crocco TJ, Gutmann L, Barr TL. C-reactive protein and long-term ischemic stroke prognosis. J Clin Neurosci. 2014 Apr;21(4):547-53. doi: 10.1016/j.jocn.2013.06.015. Epub 2013 Aug 23.
PMID: 24211144BACKGROUNDWezel J, Kooij BJ, Webb AG. Assessing the MR compatibility of dental retainer wires at 7 Tesla. Magn Reson Med. 2014 Oct;72(4):1191-8. doi: 10.1002/mrm.25019. Epub 2013 Nov 11.
PMID: 24408149BACKGROUNDWilliams LS, Weinberger M, Harris LE, Clark DO, Biller J. Development of a stroke-specific quality of life scale. Stroke. 1999 Jul;30(7):1362-9. doi: 10.1161/01.str.30.7.1362.
PMID: 10390308BACKGROUNDZeiler SR. Should We Care About Early Post-Stroke Rehabilitation? Not Yet, but Soon. Curr Neurol Neurosci Rep. 2019 Feb 20;19(3):13. doi: 10.1007/s11910-019-0927-x.
PMID: 30788609BACKGROUNDBlum C, Baur D, Achauer LC, Berens P, Biergans S, Erb M, Homberg V, Huang Z, Kohlbacher O, Liepert J, Lindig T, Lohmann G, Macke JH, Romhild J, Rosinger-Hein C, Zrenner B, Ziemann U. Personalized neurorehabilitative precision medicine: from data to therapies (MWKNeuroReha) - a multi-centre prospective observational clinical trial to predict long-term outcome of patients with acute motor stroke. BMC Neurol. 2022 Jun 30;22(1):238. doi: 10.1186/s12883-022-02759-2.
PMID: 35773640DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Ulf Ziemann, PhD, M. d., Prof.
Head of the department of neurology of the university hospital Tuebingen and Hertie-Institut for clinical brain research
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- CASE ONLY
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
December 21, 2020
First Posted
December 30, 2020
Study Start
December 1, 2020
Primary Completion
March 31, 2022
Study Completion
June 30, 2022
Last Updated
December 30, 2020
Record last verified: 2020-12