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Treatment based classification systems for patients with non-specific neck pain. A systematic review. | LitMetric

Treatment based classification systems for patients with non-specific neck pain. A systematic review.

Musculoskelet Sci Pract

Department of Health Sciences, VU University, Amsterdam, the Netherlands; Department of Epidemiology and Biostatistics, Amsterdam UMC, Amsterdam, Amsterdam Movement Sciences, the Netherlands.

Published: June 2020

AI Article Synopsis

Article Abstract

Objective: We aimed to identify published classification systems with a targeted treatment approach (treatment-based classification systems (TBCSs)) for patients with non-specific neck pain, and assess their quality and effectiveness.

Design: Systematic review.

Data Sources: MEDLINE, CINAHL, EMBASE, PEDro and the grey literature were systematically searched from inception to December 2019.

Study Appraisal And Synthesis: The main selection criterium was a TBCS for patients with non-specific neck pain with physiotherapeutic interventions. For data extraction of descriptive data and quality assessment we used the framework developed by Buchbinder et al. We considered as score of ≤3 as low quality, a score between 3 and 5 as moderate quality and a score ≥5 as good quality. To assess the risk of bias of studies concerning the effectiveness of TBCSs (only randomized clinical trials (RCTs) were included) we used the PEDro scale. We considered a score of ≥ six points on this scale as low risk of bias.

Results: Out of 7664 initial references we included 13 studies. The overall quality of the TBCSs ranged from low to moderate. We found two RCTs, both with low risk of bias, evaluating the effectiveness of two TBCSs compared to alternative treatments. The results showed that both TBCSs were not superior to alternative treatments.

Conclusion: Existing TBCSs are, at best, of moderate quality. In addition, TBCSs were not shown to be more effective than alternatives. Therefore using these TBCSs in daily practice is not recommended.

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Source
http://dx.doi.org/10.1016/j.msksp.2020.102133DOI Listing

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