Notice bibliographique
Résumé
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]
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,007 | 0,006 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,004 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,087 | 0,092 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».