Notice bibliographique
Résumé
Evidence Based Resource in Anaesthesia and Analgesia M.Tramer, ed. London: BMJ Books, 2000. ISBN 0-7279-1437-5. 225 pp. $30.00. Has it come to this? A review of reviews? All physicians understand the need for original study of important clinical questions, and appreciate the perspective offered by review articles about a subject. But do we really need a review of review articles? Unfortunately, randomized clinical trials ask “does intervention “X” work compared to placebo?” rather than “how well does intervention “X” work?” Narrative reviews add little but the personal perspective of the author, and are often biased in their sampling of the literature. And so we have progressed to systematic reviews that sample the literature objectively, assess the quality of studies (randomization, blinding, and measured attrition), and provide both qualitative and quantitative answers to medical questions. This book devotes itself to the application of “evidence-based medicine” to the specialty, explains what is involved in the systematic review process, and catalogues the currently published work of interest to anesthesiologists. The authors are well versed in epidemiology and are, fortunately, less than evangelical in their approach to the subject than some have been. They carefully point out that there is no evidence (nor likely to be) that “evidence-based medicine” provides better medical care than what we like to call that which went before. They also caution that large research projects or systematic reviews fail to hold direct relevance to clinical practice, and to medical decisions about individual patients. Finally, they point out that lack of evidence from high-quality studies does not constitute evidence of lack of effect, but only that we have a measured uncertainty in our data base. This book will be enjoyed by those who wish to reliably interpret the literature of anesthesia. It also provides a comprehensive list (to the end of 1999) of systematic reviews of interest to the specialty. Notably, only 51% were published in our specialty journals! It provides a lucid explanation of the terminology of “evidence based medicine”, and presents an approach to modern medical decision-making. For example, the three systematic reviews of the role of epidural analgesia in the genesis of Caesarean sections all came to different conclusions. Can they all be correct? Finally, as examples, the authors provide comprehensive discussions of the evidence on which anesthesiologists manage acute pain, treat nausea and vomiting, and reduce the need for allogeneic blood transfusion. That we find we don’t know as much as we thought should not reflect adversely upon anesthesia research, but only stimulate an open mind to new ideas as we elevate the “standard of proof.” If there is a deficiency in this book it is in the lack of justification of the principles of “evidence-based medicine” in a specialty such as anesthesia. Our “facilitating” medical specialty works within a complex medical system and may have different requirements for “evidence” than does a traditional specialty, charged as the latter is with responsibility to treat a specific disease entity. Can the principles of evidence be applicable if there is not a direct cause-and-effect relationship of the anesthesiologist’s action to the patient’s outcome? That reservation aside, the value of this monograph lies not in the cited evidence (which will soon become dated), but in the way it encourages one to think critically. It has come to this, and fortunately so!
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 | 0,006 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,004 | 0,002 |
| Bibliométrie | 0,008 | 0,011 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,006 | 0,007 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,005 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,061 | 0,050 |
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 ».