Surgical epidemiology: a call for action
Notice bibliographique
Résumé
Background Surgical approaches are receiving increasing attention as way to solve many global public health problems. The publication of Disease Control Priorities monograph initiated discussions of cost-effectiveness of surgical interventions in developing countries, (1) and many more recent publications have built upon its concepts. (2) Surgery can play vital role in helping countries meet their Millennium Development Goals 4, 5 and 6. (3) To build stronger case for surgery as part of armamentarium of cost-effective interventions in developing countries, epidemiologists need to work alongside their surgical colleagues to develop nascent field of surgical epidemiology. What is surgical epidemiology? Unfortunately, there is not yet an agreed definition for this field. This may reflect emerging nature of field, or lack of clarity and consensus about its goals and objectives. A useful starting point is definition of epidemiology as the study of distribution and determinants of health related or in specified populations and application of this study to control of health problems (4) An analysis of this definition in terms of its applicability to surgery suggests that clarity is needed in three components: (i) distribution and determinants of or events, (ii) populations involved, and (iii) its application to efforts to treat health problems. We focus on developing countries because we feel that discussions about role and cost-effectiveness of surgery in therapeutic armamentarium are most active in this setting. In addition, definitional issues and challenges are greater in developing countries, where we wish to encourage debate on surgical epidemiology. Definitions What are health-related or that we wish to study? Are they states such as obstructed labour? Or are they events such as surgical intervention? From surgical perspective an event often occurs after state, so one could argue that we need to study both. In addition, can also include sequelae and complications of surgery, such as nosocomial infections. (5) It is evident that refers to surgical condition. But what exactly is surgical condition? The Disease Control Priorities monograph defined this as any condition that requires suture, incision, excision, manipulation, or other invasive procedure that usually, but not always, requires local, regional, or general anaesthesia. (1) This definition avoids challenge of defining who is performing sutures, incisions, etc. and may thus include surgical procedures done by nurses, paramedical staff and general practitioners in addition to surgeons. Another definition of surgical condition is any condition for which most treatment is an intervention that requires suture, incision, excision, manipulation, or other invasive procedure that usually, but not always, requires anaesthesia (6) This definition raises more questions than answers. What exactly does potentially effective mean? Does this criterion vary depending on clinical or geographic contexts? Yet another definition from recent publication is that surgical condition is a disease state requiring expertise of surgically trained provider. (7) Here, we are left wondering about precise nature of expertise and surgical training required. In addition, we need to consider conditions for which only minority of patients need surgery. For example, only one out of six persons with severe head injury needs neurosurgical operation. However, ability to rapidly diagnose patients who need surgery along with availability of qualified provider and facilities to safely perform procedure are critical to lowering overall mortality from severe head injuries. Similar considerations apply to availability of Caesarean delivery to treat obstetrical complications. …
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».