PREP2: A biomarker-based algorithm for predicting upper limb function after stroke
- PMID: 29159193
- PMCID: PMC5682112
- DOI: 10.1002/acn3.488
PREP2: A biomarker-based algorithm for predicting upper limb function after stroke
Abstract
Objective: Recovery of motor function is important for regaining independence after stroke, but difficult to predict for individual patients. Our aim was to develop an efficient, accurate, and accessible algorithm for use in clinical settings. Clinical, neurophysiological, and neuroimaging biomarkers of corticospinal integrity obtained within days of stroke were combined to predict likely upper limb motor outcomes 3 months after stroke.
Methods: Data from 207 patients recruited within 3 days of stroke [103 females (50%), median age 72 (range 18-98) years] were included in a Classification and Regression Tree analysis to predict upper limb function 3 months poststroke.
Results: The analysis produced an algorithm that sequentially combined a measure of upper limb impairment; age; the presence or absence of upper limb motor evoked potentials elicited with transcranial magnetic stimulation; and stroke lesion load obtained from MRI or stroke severity assessed with the NIHSS score. The algorithm makes correct predictions for 75% of patients. A key biomarker obtained with transcranial magnetic stimulation is required for one third of patients. This biomarker combined with NIHSS score can be used in place of more costly magnetic resonance imaging, with no loss of prediction accuracy.
Interpretation: The new algorithm is more accurate, efficient, and accessible than its predecessors, which may support its use in clinical practice. While further work is needed to potentially incorporate sensory and cognitive factors, the algorithm can be used within days of stroke to provide accurate predictions of upper limb functional outcomes at 3 months after stroke. www.presto.auckland.ac.nz.
Figures
Similar articles
-
Prediction of Upper Limb Motor Recovery by the PREP2 Algorithm in a Nonselected Population: External Validation and Influence of Cognitive Syndromes.Neurorehabil Neural Repair. 2024 Oct;38(10):764-774. doi: 10.1177/15459683241270056. Epub 2024 Aug 20. Neurorehabil Neural Repair. 2024. PMID: 39162251
-
PREP2 Algorithm Predictions Are Correct at 2 Years Poststroke for Most Patients.Neurorehabil Neural Repair. 2019 Aug;33(8):635-642. doi: 10.1177/1545968319860481. Epub 2019 Jul 3. Neurorehabil Neural Repair. 2019. PMID: 31268414
-
Determining the Functional Status of the Corticospinal Tract Within One Week of Stroke.J Vis Exp. 2020 Feb 22;(156). doi: 10.3791/60665. J Vis Exp. 2020. PMID: 32150156
-
Implementing biomarkers to predict motor recovery after stroke.NeuroRehabilitation. 2018;43(1):41-50. doi: 10.3233/NRE-172395. NeuroRehabilitation. 2018. PMID: 30056436 Review.
-
Prediction of recovery of motor function after stroke.Lancet Neurol. 2010 Dec;9(12):1228-1232. doi: 10.1016/S1474-4422(10)70247-7. Epub 2010 Oct 27. Lancet Neurol. 2010. PMID: 21035399 Review.
Cited by
-
Arguments for the biological and predictive relevance of the proportional recovery rule.Elife. 2022 Oct 18;11:e80458. doi: 10.7554/eLife.80458. Elife. 2022. PMID: 36255057 Free PMC article.
-
Baseline robot-measured kinematic metrics predict discharge rehabilitation outcomes in individuals with subacute stroke.Front Bioeng Biotechnol. 2022 Dec 6;10:1012544. doi: 10.3389/fbioe.2022.1012544. eCollection 2022. Front Bioeng Biotechnol. 2022. PMID: 36561043 Free PMC article.
-
Segmental motor recovery after cervical spinal cord injury relates to density and integrity of corticospinal tract projections.Nat Commun. 2023 Feb 9;14(1):723. doi: 10.1038/s41467-023-36390-7. Nat Commun. 2023. PMID: 36759606 Free PMC article.
-
Current therapy for the upper limb after stroke: a cross-sectional survey of UK therapists.BMJ Open. 2019 Sep 30;9(9):e030262. doi: 10.1136/bmjopen-2019-030262. BMJ Open. 2019. PMID: 31575573 Free PMC article.
-
Performance Comparison of Different Neuroimaging Methods for Predicting Upper Limb Motor Outcomes in Patients after Stroke.Neural Plast. 2022 Jun 6;2022:4203698. doi: 10.1155/2022/4203698. eCollection 2022. Neural Plast. 2022. PMID: 35707519 Free PMC article.
References
-
- Langhorne P, Coupar F, Pollock A. Motor recovery after stroke: a systematic review. Lancet Neurol 2009;8:741–754. - PubMed
-
- Veerbeek JM, Kwakkel G, van Wegen EE, et al. Early prediction of outcome of activities of daily living after stroke: a systematic review. Stroke 2011;42:1482–1488. - PubMed
-
- Coupar F, Pollock A, Rowe P, et al. Predictors of upper limb recovery after stroke: a systematic review and meta‐analysis. Clin Rehabil 2012;26:291–313. - PubMed
-
- Nijland RH, van Wegen EE, Harmeling‐van der Wel BC, et al. Accuracy of physical therapists’ early predictions of upper‐limb function in hospital stroke units: the EPOS study. Phys Ther 2013;93:460–469. - PubMed
-
- Stinear CM, Byblow WD, Ackerley SJ, et al. Predicting recovery potential for individual stroke patients increases rehabilitation efficiency. Stroke 2017;48:1011–1019. - PubMed
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
