Revision sistemática y metaanálisis de técnicas que previenen el dolor lumbar

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Abstract

Resumen Este trabajo es un comentario del artículo: Steffens D, Maher CG, Pereira LSM, et al. Prevention of Low Back Pain: A Systematic Review and Meta-analysis. JAMA Intern Med. 2016;176(2):199-208. doi:10.1001/jamainternmed.2015.7431.

Translated abstract

Abstract This text is a commentary on the article: Steffens D, Maher CG, Pereira LSM, et al. Prevention of Low Back Pain: A Systematic Review and Meta-analysis. JAMA Intern Med. 2016;176(2):199-208. doi:10.1001/jamainternmed.2015.7431.

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Systems for grading the quality of evidence and the strength of recommendations I: Critical appraisal of existing approaches The GRADE Working Group

David Atkins, Martin Eccles, Signe Flottorp … (2004)

Background A number of approaches have been used to grade levels of evidence and the strength of recommendations. The use of many different approaches detracts from one of the main reasons for having explicit approaches: to concisely characterise and communicate this information so that it can easily be understood and thereby help people make well-informed decisions. Our objective was to critically appraise six prominent systems for grading levels of evidence and the strength of recommendations as a basis for agreeing on characteristics of a common, sensible approach to grading levels of evidence and the strength of recommendations. Methods Six prominent systems for grading levels of evidence and strength of recommendations were selected and someone familiar with each system prepared a description of each of these. Twelve assessors independently evaluated each system based on twelve criteria to assess the sensibility of the different approaches. Systems used by 51 organisations were compared with these six approaches. Results There was poor agreement about the sensibility of the six systems. Only one of the systems was suitable for all four types of questions we considered (effectiveness, harm, diagnosis and prognosis). None of the systems was considered usable for all of the target groups we considered (professionals, patients and policy makers). The raters found low reproducibility of judgements made using all six systems. Systems used by 51 organisations that sponsor clinical practice guidelines included a number of minor variations of the six systems that we critically appraised. Conclusions All of the currently used approaches to grading levels of evidence and the strength of recommendations have important shortcomings.

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The effects of clinical and statistical heterogeneity on the predictive values of results from meta-analyses.

W Melsen, M Bonten, M Rovers … (2014)

Variance between studies in a meta-analysis will exist. This heterogeneity may be of clinical, methodological or statistical origin. The last of these is quantified by the I(2) -statistic. We investigated, using simulated studies, the accuracy of I(2) in the assessment of heterogeneity and the effects of heterogeneity on the predictive value of meta-analyses. The relevance of quantifying I(2) was determined according to the likely presence of heterogeneity between studies (low, high, or unknown) and the calculated I(2) (low or high). The findings were illustrated by published meta-analyses of selective digestive decontamination and weaning protocols. As expected, I(2) increases and the likelihood of drawing correct inferences from a meta-analysis decreases with increasing heterogeneity. With low levels of heterogeneity, I(2) does not appear to be predictive of the accuracy of the meta-analysis result. With high levels of heterogeneity, even meta-analyses with low I(2) -values have low predictive values. Most commonly, the level of heterogeneity in a meta-analysis will be unknown. In these scenarios, I(2) determination may help to identify estimates with low predictive values (high I(2) ). In this situation, the results of a meta-analysis will be unreliable. With low I(2) -values and unknown levels of heterogeneity, predictive values of pooled estimates may range extensively, and findings should be interpreted with caution. In conclusion, quantifying statistical heterogeneity through I(2) -statistics is only helpful when the amount of clinical heterogeneity is unknown and I(2) is high. Objective methods to quantify the levels of clinical and methodological heterogeneity are urgently needed to allow reliable determination of the accuracy of meta-analyses.