Bibliographic record
Abstract
Evidence-based medicine (EBM) is the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients.1 It is one of the approaches required to gather and interpret the increasingly scientific application of knowledge as to how we assess and manage patients under the care of anesthesiologists. Many anesthesiologists lack confidence tackling the task of finding relevant studies and interpreting their quality and results, let alone deciding whether this information can be used to help the patient in front of them. The book Painless Evidence-Based Medicine was written as a primer to help us more easily negotiate the minefield of information and misinformation. This book is available in both paperback and eBook format. The paperback is small and light, with succinctly written chapters punctuated by diagrams, graphs, and cartoons to break up the text. As stated in the title, the authors’ goal was to make this complex topic as painless and easy to read as possible. Consisting of just 166 pages of concisely written text, this book is easily portable, and each chapter can be easily read in 1 sitting. The authors are a professor of internal medicine, a professor of pediatrics, and a neonatologist. Two of the authors completed a master’s degree in clinical epidemiology at McMaster University in Ontario, Canada, followed by producing multiple publications, including the series Users’ Guides to the Medical Literature.2 Their passion for teaching is obvious, as is their fundamental understanding that doctors are time-poor—we want to improve our skills in EBM, but we want to do it in the least amount of time possible. The book is divided into 9 chapters. The introduction explains the concept of EBM and the approach used throughout the book of acquiring, appraising, and finally applying evidence. This section would be an excellent starting point for medical students or those unfamiliar with the topic. For those with more experience, however, it would be advisable to skim this section and move on. Chapters 2–7 are separated according to the type of article being reviewed, namely, therapy, diagnostic tests, harm, prognosis, systematic reviews, and clinical practice guidelines. Each chapter follows the same basic structure, which helps to reinforce the authors’ suggested approach to EBM as you progress through the book. The starting point is to “appraise directness.” Does the article attempt to answer your clinical question? Is it worth reading? If so, you proceed to the second step, assessing validity. This step is more complex, with different techniques required depending on the study type. The authors break this down into 4 or 5 key questions, thereby converting the process into a manageable task. Next, in the sections on interpreting medical statistics, the authors have included “tackle boxes,” boxed case studies with workings laid out for the reader to follow. These boxes are a highlight of this book and serve as a potentially useful resource for future reference (eg, if you want to calculate a number needed to treat or recall why some studies use odds ratios while others use relative risks). The final step in the process is to decide whether the study’s results can be applied to your individual patient or the local population. We are given a mnemonic to help us remember the important biological and socioeconomic factors to consider, along with the prudent advice to include patients and their goals in decision making. The final chapter of this book gives advice on how to search the literature. Understanding the techniques involved in using Boolean language to search electronic databases is essential. If you read just 1 chapter, make it “Literature Searches.” The book has many strengths in addition to those discussed, 1 of which is the frequent use of humor. This text would be of limited value for those with significant experience in EBM because it is pitched at beginners and those with some experience who want to fill knowledge gaps. In future editions, it would be helpful to include a checklist of key points to cover in appraisal of each type of study, potentially as a quick reference PDF or app for use in busy clinical settings. In summary, Painless Evidence-Based Medicine is a succinct, easy-to-read, and useful resource for anesthesiology trainees and specialists wanting an introduction or to upskill in this area of modern medical practice. It would be a useful addition to any anesthesiology library. Stephanie Clark, MBChBDouglas Campbell, MB, FRCA, FANZCADepartment of AnaesthesiaAuckland City HospitalAuckland, New Zealand[email protected]
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.087 | 0.092 |
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".