H12 A history of evidence-based medicine and dermatology as an early adopter
Bibliographic record
Abstract
Abstract In 1992, a search for evidence-based medicine (EBM) would have only yielded two articles. Now, searching this term in PubMed generates over 276 000 results. But how did the ‘era of evidence-based medicine’ begin and what were its foundations? The concept of using evidence to guide medical practice is thought to date back to Ancient Greece. However, it was not until the 20th century that it started to take hold in modern medicine. Social principles calling for effective healthcare for the masses were a driving force, with British clinical epidemiologist Archie Cochrane (1909–1988) being the first advocate of this practice. Predating Archie Cochrane’s work, the early 20th century’s advancement in statistics and development of the meta-analysis would form the building blocks for modern-day EBM. British statistician Karl Pearson was the first to propose the concept of combining results of individual studies to minimize random error. Later in the 1920s fellow Briton, Ronald Fisher laid the foundation for the systematic approach by developing the statistical method of meta-analysis, first called ‘Fisher’s combined probability test’. In 1976 American statistician Gene Glass coined the term ‘meta-analysis’. By 1989 meta-analysis was changing clinical practice. Sir Ian Chalmers demonstrated that a short course of corticosteroids could drastically reduce complications following delivery of preterm infants. His work, and that of others, highlighted that lives could be saved through the evidence-based approach of performing up-to-date systematic reviews of randomized clinical trials. Meanwhile, in Canada the EBM movement was starting. In 1981 a group led by David Sackett published the first of a series of articles on how to appraise medical literature, influencing the practice of a whole generation. The actual term EBM was announced by Sackett’s mentee Gordon Guyatt in 1992. The levels of evidence that we use today can be attributed to Sackett and his book Evidence-Based Medicine: How to Practice and Teach EBM, which gave clinicians the tools to adopt EBM into everyday practice. Dermatology was an early adopter of EBM. The Cochrane Skin Group (CSG) was founded by Hywel Williams in 1997, with the clear aim of disseminating evidence-based guidelines to prevent, diagnose and treat dermatological disease. The first CSG review was published in 1999, and to date there are 130 active systematic review titles. The work of the CSG elicits tangible effects on international health policy, contributing to national and international guidelines. The work of the CSG is bolstered by the UK Dermatology Clinical Trials Network at the Centre of Evidence Based Dermatology, a group that aims to explore research gaps identified by the CSG reviews.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.003 | 0.026 |
| Scholarly communication | 0.011 | 0.018 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.014 | 0.030 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".