The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Predictors of upper limb recovery after stroke: a systematic review and meta-analysis
Abstract
Objective: To systematically review and summarize the current available literature on prognostic variables relating to upper limb recovery following stroke. To identify which, if any variables predict upper limb recovery following stroke. Data sources: We completed searches in MEDLINE, EMBASE, AMED, CINAHL and Cochrane CENTRAL databases. Searches were completed in November 2010. Review methods: Studies were included if predictor variables were measured at baseline and linked to an outcome of upper limb recovery at a future time point. Exclusion criteria included predictor variables relating to response to treatment and outcome measurements of very specific upper limb impairments such as spasticity or pain. Two independent reviewers completed data extraction and assessed study quality. Results: Fifty-eight studies met the inclusion criteria. Predictor variables which have been considered within these studies include; age, sex, lesion site, initial motor impairment, motor-evoked potentials andsomatosensory-evoked potentials. Initial measures of upper limb impairment and function were found to be the most significant predictors of upper limb recovery; odds ratio 14.84 (95% confidence intervals (CI) 9.08–24.25) and 38.62 (95% CI 8.40–177.53), respectively. Conclusions: Interpretation of these results is complicated by methodological factors including variations in study populations, upper limb motor outcome scales, timing of baseline and outcome assessments and predictors selected. The most important predictive factors for upper limb recovery following stroke appears to the initial severity of motor impairment or function.
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Cites
Cochrane Handbook for Systematic Reviews of Interventions: Cochrane Book Series
(2008) · doi:10.1002/9780470712184 · Cited by 25,048
Meta-analysis of Observational Studies in Epidemiology<SUBTITLE>A Proposal for Reporting</SUBTITLE>
Stroup, D. F. (2000) · JAMA · doi:10.1001/jama.283.15.2008 · Cited by 20,623
Publication bias in clinical research
Easterbrook, P. J., Gopalan, R., Berlin, J. A., & Matthews, D. R. (1991) · The Lancet · doi:10.1016/0140-6736(91)90201-y · Cited by 3,109
Cited by
Heart Disease and Stroke Statistics—2016 Update: A Report From the American Heart Association
Mozaffarian, D., Benjamin, E. J., Go, A. S., Arnett, D. K., Blaha, M. J., Cushman, M., Das, S. R., de Ferranti, S., Després, J.-P., Fullerton, H. J., et al. (2016) · Circulation · doi:10.1161/cir.0000000000000350 · Cited by 6,596
Heart Disease and Stroke Statistics—2015 Update: A Report From the American Heart Association
Mozaffarian, D., Benjamin, E. J., Go, A. S., Arnett, D. K., Blaha, M. J., Cushman, M., de Ferranti, S., Després, J.-P., Fullerton, H. J., Howard, V. J., et al. (2015) · Circulation · doi:10.1161/cir.0000000000000152 · Cited by 5,797
Hatem, S. M., Saussez, G., della Faille, M., Prist, V., Zhang, X., Dispa, D., & Bleyenheuft, Y. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00442 · Cited by 918
Interventions for improving upper limb function after stroke
Pollock, A., Farmer, S. E., Brady, M. C., Langhorne, P., Mead, G. E., Mehrholz, J., & van Wijck, F. (2014) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd010820.pub2 · Cited by 909
Self-citationPREP2: A biomarker‐based algorithm for predicting upper limb function after stroke
Stinear, C. M., Byblow, W. D., Ackerley, S. J., Smith, M., Borges, V. M., & Barber, P. A. (2017) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.488 · Cited by 359
Metadata
- Authors
- Coupar, F., Pollock, A., Rowe, P., Weir, C., & Langhorne, P.
- Venue
- Clinical Rehabilitation
- Publisher
- SAGE Publications
- Published
- 2011-10-24
- Volume
- 26
- Issue
- 4
- Pages
- 291-313
- ISSN
- 0269-2155 (ISSN-L)
- 1477-0873
- OpenAlex
- W2095845270
- Cited by
- 408
- References
- 3
- FWCI
- 2.31
- Type
- journal article
- Language
- en
- Open access
- closed
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- Coupar, F., Pollock, A., Rowe, P., Weir, C., & Langhorne, P. (2012). Predictors of upper limb recovery after stroke: a systematic review and meta-analysis. Clinical Rehabilitation. https://doi.org/10.1177/0269215511420305
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