Improving Prediction of Surgical Site Infection Risk with Multilevel Modeling

BACKGROUND: Surgical site infection (SSI) surveillance is a key factor in the elaboration of strategies to reduce SSI occurrence and in providing surgeons with appropriate data feedback (risk indicators, clinical prediction rule). AIM: To improve the predictive performance of an individual-based SSI...

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Detalles Bibliográficos
Autores principales: Saunders, Lauren, Perennec-Olivier, Marion, Jarno, Pascal, L’Hériteau, François, Venier, Anne-Gaëlle, Simon, Loïc, Giard, Marine, Thiolet, Jean-Michel, Viel, Jean-François
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4023946/
https://www.ncbi.nlm.nih.gov/pubmed/24835189
http://dx.doi.org/10.1371/journal.pone.0095295

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4023946/
https://www.ncbi.nlm.nih.gov/pubmed/24835189
http://dx.doi.org/10.1371/journal.pone.0095295

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