Summary of best evidence on prevention of intracranial infection after endoscopic endonasal transsphenoidal pituitary neoplasm resection
Notice bibliographique
Résumé
Background: Intracranial infection is one of the most serious complications after pituitary neoplasm resection. However, the quality of the evidence for existing preventive measures varies significantly, and the related content is scattered, and the scope is broad. Nurses lack the specificity and targeted guidance for preventing intracranial infections after endoscopic endonasal transsphenoidal surgery (EETS), and nurses find that evidence necessitates screening and identification during its application, and it is challenging to utilize current tool for guiding clinical practice. Thus, the protocols for preventing intracranial infection after EETS required further refinement. The aim of this study is to summarize the relevant evidence for preventing postoperative intracranial infections after endoscopic endonasal transsphenoidal pituitary neoplasm resection, in order to reduce the incidence of postoperative intracranial infection and provide a reference for clinical medical staff. Methods: We systematically searched a variety of platforms, including British Medical Journal Best Practice, UpToDate, DynaMed, Guidelines International Network, Registered Nurses' Association of Ontario, Scottish Intercollegiate Guidelines Network, Australian Joanna Briggs Institute Evidence based Healthcare Center Database, National Institute for Health and Clinical Excellence, Medlive, Wanfang Data, China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), Cochrane Library, Embase, PubMed, Web of Science, and Chinese biomedical literature service system (Sinomed) to collect clinical decisions, relevant guidelines, evidence summaries, systematic reviews, and expert consensus documents on the prevention of intracranial infection in this context according to the 6S evidence model. The search included literature published up to December, 2023. Then conduct literature screening and evaluation, extract and summarize relevant evidence on perioperative prevention of intracranial infection after EETS from the selected literature. Two researchers applied the JBI levels of evidence preappraisal system (2014 version) to categorize the included evidence into five levels (level 1a being the highest and level 5c being the lowest). Results: A total of 16 pieces of literature were reviewed, including 6 clinical decision-makings, 2 guidelines, 2 systematic reviews, and 6 expert consensus documents. Ultimately, 24 pieces of best evidence for preventing intracranial infections after EETS for pituitary adenomas were formed, and they will be divided into four categories: multidisciplinary collaboration, preoperative evaluation and informed consent, intraoperative prevention and control, and postoperative observation and prevention. Conclusions: This summarized the best evidence for preventing intracranial infection after endoscopic endonasal transsphenoidal pituitary neoplasms resection. Summary of the best evidence for preventing intracranial infections following EETS plays a critical role in enhancing surgical success, optimizing patient management, fostering multidisciplinary collaboration, advancing research, and improving patient satisfaction. It is recommended that medical staff select and apply the evidence in clinical practice in order to avoid the occurrence of intracranial infections.
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 | 0,000 | 0,000 |
| 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 ».