Meta-analysis, Evidence-Based Medicine, and Clinical Guidelines

2014 ◽  
pp. 203-231 ◽  
Author(s):  
Stephen P. Glasser ◽  
Sue Duval
Keyword(s):  
Evidence Based Medicine ◽  
Clinical Guidelines ◽  
Meta Analysis ◽  
Evidence Based ◽  
Based Medicine

Evidence-based medicine in anaesthesia

2017 ◽  
Author(s):  
Ann Merete Møller
Keyword(s):  
Evidence Based Medicine ◽  
Meta Analysis ◽  
Consort Statement ◽  
Current Evidence ◽  
Evidence Based ◽  
Clinical Question ◽  
Clinical Expertise ◽  
Clinical Databases ◽  
Patient Values ◽  
Based Medicine

Evidence-based medicine (EBM) is defined as ‘The judicious use of the best current evidence in making decisions about the care of individual patients’. Evidence-based medicine (EBM) is meant to integrate clinical expertise with the best available research evidence and patient values. The purpose of EBM is to assist clinicians in making the best decisions. Practising EBM includes asking an answerable, well-defined clinical question, searching for information, critically appraising information retrieved, extracting data, synthesizing data, and making conclusions about the overall effect. The clinical question includes information of the following elements: the population, the intervention, and the clinically relevant outcomes in focus. The clinical question is a tool to make the focus of the question clearer, and an aid to build the following search strategy. A comprehensive and reproducible literature search is essential for conducting a high-quality and up-to-date search. The search should include all relevant clinical databases. Papers retrieved after the search must be critically appraised and evaluated for the risk of bias. Evidence-based methods are used in the production of systematic reviews, and the development of clinical guidelines. Whether a meta-analysis should be performed depends on the quality and nature of the extracted data. Practising EBM may be challenged by a lack of well-performed trials, various types of bias (including publication bias), and heterogeneity between existing trials. Several tools have been constructed to help the process; examples are the CONSORT statement, the PRISMA statement, and the AGREE instrument.

scholarly journals What is a multiple treatments meta-analysis?

2012 ◽  
Vol 21 (2) ◽  
pp. 151-153 ◽  
Author(s):  
A. Cipriani ◽  
C. Barbui ◽  
C. Rizzo ◽  
G. Salanti
Keyword(s):  
Evidence Based Medicine ◽  
Treatment Effects ◽  
Meta Analysis ◽  
Evidence Based ◽  
Relative Efficacy ◽  
Analytical Technique ◽  
Multiple Treatments ◽  
Meta Analyses ◽  
Based Medicine ◽  
Indirect Comparisons

Standard meta-analyses are an effective tool in evidence-based medicine, but one of their main drawbacks is that they can compare only two alternative treatments at a time. Moreover, if no trials exist which directly compare two interventions, it is not possible to estimate their relative efficacy. Multiple treatments meta-analyses use a meta-analytical technique that allows the incorporation of evidence from both direct and indirect comparisons from a network of trials of different interventions to estimate summary treatment effects as comprehensively and precisely as possible.

scholarly journals Atrioventricular Block in Children

2018 ◽  
Vol 15 (5) ◽  
pp. 365-375
Author(s):  
Igor A. Kovalev ◽  
Yuri M. Belozerov ◽  
Dinara I. Sadykova ◽  
Dina R. Sabirova ◽  
Lyudmila V. Yakovleva ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Atrioventricular Block ◽  
Evidence Based Medicine ◽  
Clinical Guidelines ◽  
Diagnosis And Treatment ◽  
Evidence Based ◽  
Cardiovascular Pathology ◽  
Slowing Down ◽  
Conduction Disorders ◽  
Based Medicine

Rhythm and conduction disorders of the heart occupy one of the leading places in the structure of cardiovascular pathology in children. Atrioventricular block is the slowing down or loss of impulses from the atria to the ventricles. The team of authors presents clinical guidelines based on the principles of evidence-based medicine, including all stages of diagnosis and treatment of children with atrioventricular block. The use of guidelines in clinical practice will allow to choose the best strategy for the diagnosis and treatment of atrioventricular block for each individual patient.

scholarly journals Evidence-Based Medicine, Systematic Reviews, and Guidelines in Interventional Pain Management: Part 6. Systematic Reviews and Meta-Analyses of Observational Studies

2008 ◽  
Vol 5;12 (5;9) ◽  
pp. 819-850
Author(s):  
Laxmaiah Manchikanti
Keyword(s):  
Systematic Review ◽  
Systematic Reviews ◽  
Evidence Based Medicine ◽  
Observational Studies ◽  
Meta Analysis ◽  
Evidence Based ◽  
Confounding Bias ◽  
Meta Analyses ◽  
Based Medicine

Observational studies provide an important source of information when randomized controlled trials (RCTs) cannot or should not be undertaken, provided that the data are analyzed and interpreted with special attention to bias. Evidence-based medicine (EBM) stresses the examination of evidence from clinical research and describes it as a shift in medical paradigm, in contrast to intuition, unsystematic clinical experience, and pathophysiologic rationale. While the importance of randomized trials has been created by the concept of the hierarchy of evidence in guiding therapy, much of the medical research is observational. The reporting of observational research is often not detailed and clear enough with insufficient quality and poor reporting, which hampers the assessment of strengths and weaknesses of the study and the generalizability of the mixed results. Thus, in recent years, progress and innovations in health care are measured by systematic reviews and meta-analyses. A systematic review is defined as, “the application of scientific strategies that limit bias by the systematic assembly, clinical appraisal, and synthesis of all relevant studies on a specific topic.” Meta-analysis usually is the final step in a systematic review. Systematic reviews and meta-analyses are labor intensive, requiring expertise in both the subject matter and review methodology, and also must follow the rules of EBM which suggests that a formal set of rules must complement medical training and common sense for clinicians to integrate the results of clinical research effectively. While expertise in the review methods is important, the expertise in the subject matter and technical components is also crucial. Even though, systematic reviews and meta-analyses, specifically of RCTs, have exploded, the quality of the systematic reviews is highly variable and consequently, the opinions reached of the same studies are quite divergent. Numerous deficiencies have been described in methodologic assessment of the quality of the individual articles. Consequently, observational studies can provide an important complementary source of information, provided that the data are analyzed and interpreted in the context of confounding bias to which they are prone. Appropriate systematic reviews of observational studies, in conjunction with RCTs, may provide the basis for elimination of a dangerous discrepancy between the experts and the evidence. Steps in conducting systematic reviews of observational studies include planning, conducting, reporting, and disseminating the results. MOOSE, or Meta-analysis of Observational Studies in Epidemiology, a proposal for reporting contains specifications including background, search strategy, methods, results, discussion, and conclusion. Use of the MOOSE checklist should improve the usefulness of meta-analysis for authors, reviewers, editors, readers, and decision-makers. This manuscript describes systematic reviews and meta-analyses of observational studies. Authors frequently utilize RCTs and observational studies in one systematic review; thus, they should also follow the reporting standards of the Quality of Reporting of Meta-analysis (QUOROM) statement, which also provides a checklist. A combined approach of QUOROM and MOOSE will improve reporting of systematic reviews and lead to progress and innovations in health care. Key words: Observational studies, evidence-based medicine, systematic reviews, metaanalysis, randomized trials, case-control studies, cross-sectional studies, cohort studies, confounding bias, QUOROM, MOOSE

Epidemiology and evidence-based medicine

2016 ◽  
Keyword(s):  
Survival Analysis ◽  
Relative Risk ◽  
Sample Size ◽  
Evidence Based Medicine ◽  
Diagnostic Tests ◽  
Meta Analysis ◽  
Descriptive Statistics ◽  
Number Needed To Treat ◽  
Evidence Based ◽  
Based Medicine

Chapter 20 focuses on epidemiology and evidence-based medicine. It covers study design, types of data and descriptive statistics, from samples to populations, relationships, relative risk, odds ratios, and 'number needed to treat', survival analysis, sample size, diagnostic tests, meta-analysis, before concluding with advice on how to read a paper.

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