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Evidence-based medicine: Classifying the evidence from clinical trials – the need to consider other dimensions
The current approach to assessing the quality of evidence obtained from clinical trials focuses on three dimensions: the quality of the design (with double-blinded randomised controlled trials representing the highest level of such design); the statistical power (beta) and the level of significance...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2006
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1751050/ https://www.ncbi.nlm.nih.gov/pubmed/17029653 http://dx.doi.org/10.1186/cc5045 |
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author | Bellomo, Rinaldo Bagshaw, Sean M |
author_facet | Bellomo, Rinaldo Bagshaw, Sean M |
author_sort | Bellomo, Rinaldo |
collection | PubMed |
description | The current approach to assessing the quality of evidence obtained from clinical trials focuses on three dimensions: the quality of the design (with double-blinded randomised controlled trials representing the highest level of such design); the statistical power (beta) and the level of significance (alpha). While these aspects are important, we argue that other significant aspects of trial quality impinge upon the truthfulness of the findings: biological plausibility, reproducibility and generalisability. We present several recent studies in critical care medicine where the design, beta and alpha components of the study are seemingly satisfactory but where the aspects of biological plausibility, reproducibility and generalisability show serious limitations. Accordingly, we argue for more reflection, definition and consensus on these aspects of the evaluation of evidence. |
format | Text |
id | pubmed-1751050 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-17510502006-12-27 Evidence-based medicine: Classifying the evidence from clinical trials – the need to consider other dimensions Bellomo, Rinaldo Bagshaw, Sean M Crit Care Review The current approach to assessing the quality of evidence obtained from clinical trials focuses on three dimensions: the quality of the design (with double-blinded randomised controlled trials representing the highest level of such design); the statistical power (beta) and the level of significance (alpha). While these aspects are important, we argue that other significant aspects of trial quality impinge upon the truthfulness of the findings: biological plausibility, reproducibility and generalisability. We present several recent studies in critical care medicine where the design, beta and alpha components of the study are seemingly satisfactory but where the aspects of biological plausibility, reproducibility and generalisability show serious limitations. Accordingly, we argue for more reflection, definition and consensus on these aspects of the evaluation of evidence. BioMed Central 2006 2006-10-04 /pmc/articles/PMC1751050/ /pubmed/17029653 http://dx.doi.org/10.1186/cc5045 Text en Copyright © 2006 BioMed Central Ltd |
spellingShingle | Review Bellomo, Rinaldo Bagshaw, Sean M Evidence-based medicine: Classifying the evidence from clinical trials – the need to consider other dimensions |
title | Evidence-based medicine: Classifying the evidence from clinical trials – the need to consider other dimensions |
title_full | Evidence-based medicine: Classifying the evidence from clinical trials – the need to consider other dimensions |
title_fullStr | Evidence-based medicine: Classifying the evidence from clinical trials – the need to consider other dimensions |
title_full_unstemmed | Evidence-based medicine: Classifying the evidence from clinical trials – the need to consider other dimensions |
title_short | Evidence-based medicine: Classifying the evidence from clinical trials – the need to consider other dimensions |
title_sort | evidence-based medicine: classifying the evidence from clinical trials – the need to consider other dimensions |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1751050/ https://www.ncbi.nlm.nih.gov/pubmed/17029653 http://dx.doi.org/10.1186/cc5045 |
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