ArticleThe Clinical biochemist. Reviews2005
The Evidence Based Medicine approach to diagnostic testing: practicalities and limitations.
Article in The Clinical biochemist. Reviews, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Rational development and application of biomarkers in the field of autoimmunity: A conceptual framework guiding clinicians and researchers.Journal of translational autoimmunity · 2022Review
- How to create PICO questions about diagnostic tests.BMJ evidence-based medicine · 2021Article
- Veterinary Diagnostic Practice and the Use of Rapid Tests in Antimicrobial Stewardship on UK Livestock Farms.Frontiers in veterinary science · 2020Article
- The Toronto Cognitive Assessment (TorCA): normative data and validation to detect amnestic mild cognitive impairment.Alzheimer's research & therapy · 2018Article
- Observational
- On-the-Job Evidence-Based Medicine Training for Clinician-Scientists of the Next Generation.The Clinical biochemist. Reviews · 2013Review
- The validation of screening tests: meet the new screen same as the old screen?Journal of gambling studies · 2012Review
- Clinical care improvement with use of health information technology focusing on evidence based medicine.Healthcare informatics research · 2012Article
- Assessing strength of evidence in diagnostic tests.Plastic and reconstructive surgery · 2012Review
- Immunohistochemistry in diagnostic surgical pathology: contributions of protein life-cycle, use of evidence-based methods and data normalization on interpretation of immunohistochemical stains.International journal of clinical and experimental pathology · 2009Review
- Evidence-based veterinary medicine at 20 - a commentary on historical, philosophical, practical, and ethical aspects.Veterinary evidenceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Evidence-Based Medicine (EBM) has become a popular approach to medical decision making and is increasingly part of undergraduate and postgraduate medical education. EBM follows four steps: 1. formulate a clear clinical question from a patient's problem; 2. search the literature for relevant clinical articles; 3. evaluate (critically appraise) the evidence for its validity and usefulness; 4. implement useful findings into clinical practice. This review describes the concepts, terminology and skills taught to attendees at EBM courses, focusing specifically on the approach taken to diagnostic questions. It covers how to ask an answerable clinical question, search for evidence, construct diagnostic critically appraised topics (CATs), and use sensitivity, specificity, likelihood ratios, kappa and phi statistics. It familiarises readers with the lexicon and techniques of EBM and allows better understanding of the needs of EBM practitioners.
Identifiers
16278748PMC1252824What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.