Spinal infection: state of the art and management algorithm

Detalhes bibliográficos
Autor(a) principal: Duarte, RM
Data de Publicação: 2013
Outros Autores: Vaccaro, AR
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.23/427
Resumo: INTRODUCTION: Spinal infection is a rare pathology although a concerning rising incidence has been observed in recent years. This increase might reflect a progressively more susceptible population but also the availability of increased diagnostic accuracy. Yet, even with improved diagnosis tools and procedures, the delay in diagnosis remains an important issue. This review aims to highlight the importance of a methodological attitude towards accurate and prompt diagnosis using an algorithm to aid on spinal infection management. METHODS: Appropriate literature on spinal infection was selected using databases from the US National Library of Medicine and the National Institutes of Health. RESULTS: Literature reveals that histopathological analysis of infected tissues is a paramount for diagnosis and must be performed routinely. Antibiotic therapy is transversal to both conservative and surgical approaches and must be initiated after etiological diagnosis. Indications for surgical treatment include neurological deficits or sepsis, spine instability and/or deformity, presence of epidural abscess and upon failure of conservative treatment. CONCLUSIONS: A methodological assessment could lead to diagnosis effectiveness of spinal infection. Towards this, we present a management algorithm based on literature findings
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spelling Spinal infection: state of the art and management algorithmInfecções BacterianasDoenças da Coluna VertebralINTRODUCTION: Spinal infection is a rare pathology although a concerning rising incidence has been observed in recent years. This increase might reflect a progressively more susceptible population but also the availability of increased diagnostic accuracy. Yet, even with improved diagnosis tools and procedures, the delay in diagnosis remains an important issue. This review aims to highlight the importance of a methodological attitude towards accurate and prompt diagnosis using an algorithm to aid on spinal infection management. METHODS: Appropriate literature on spinal infection was selected using databases from the US National Library of Medicine and the National Institutes of Health. RESULTS: Literature reveals that histopathological analysis of infected tissues is a paramount for diagnosis and must be performed routinely. Antibiotic therapy is transversal to both conservative and surgical approaches and must be initiated after etiological diagnosis. Indications for surgical treatment include neurological deficits or sepsis, spine instability and/or deformity, presence of epidural abscess and upon failure of conservative treatment. CONCLUSIONS: A methodological assessment could lead to diagnosis effectiveness of spinal infection. Towards this, we present a management algorithm based on literature findingsRepositório Científico do Hospital de BragaDuarte, RMVaccaro, AR2013-06-19T21:32:32Z2013-01-01T00:00:00Z2013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.23/427engEur Spine J. 2013;22(12):2787-99info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-09-21T09:02:03Zoai:repositorio.hospitaldebraga.pt:10400.23/427Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T15:54:56.299590Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Spinal infection: state of the art and management algorithm
title Spinal infection: state of the art and management algorithm
spellingShingle Spinal infection: state of the art and management algorithm
Duarte, RM
Infecções Bacterianas
Doenças da Coluna Vertebral
title_short Spinal infection: state of the art and management algorithm
title_full Spinal infection: state of the art and management algorithm
title_fullStr Spinal infection: state of the art and management algorithm
title_full_unstemmed Spinal infection: state of the art and management algorithm
title_sort Spinal infection: state of the art and management algorithm
author Duarte, RM
author_facet Duarte, RM
Vaccaro, AR
author_role author
author2 Vaccaro, AR
author2_role author
dc.contributor.none.fl_str_mv Repositório Científico do Hospital de Braga
dc.contributor.author.fl_str_mv Duarte, RM
Vaccaro, AR
dc.subject.por.fl_str_mv Infecções Bacterianas
Doenças da Coluna Vertebral
topic Infecções Bacterianas
Doenças da Coluna Vertebral
description INTRODUCTION: Spinal infection is a rare pathology although a concerning rising incidence has been observed in recent years. This increase might reflect a progressively more susceptible population but also the availability of increased diagnostic accuracy. Yet, even with improved diagnosis tools and procedures, the delay in diagnosis remains an important issue. This review aims to highlight the importance of a methodological attitude towards accurate and prompt diagnosis using an algorithm to aid on spinal infection management. METHODS: Appropriate literature on spinal infection was selected using databases from the US National Library of Medicine and the National Institutes of Health. RESULTS: Literature reveals that histopathological analysis of infected tissues is a paramount for diagnosis and must be performed routinely. Antibiotic therapy is transversal to both conservative and surgical approaches and must be initiated after etiological diagnosis. Indications for surgical treatment include neurological deficits or sepsis, spine instability and/or deformity, presence of epidural abscess and upon failure of conservative treatment. CONCLUSIONS: A methodological assessment could lead to diagnosis effectiveness of spinal infection. Towards this, we present a management algorithm based on literature findings
publishDate 2013
dc.date.none.fl_str_mv 2013-06-19T21:32:32Z
2013-01-01T00:00:00Z
2013-01-01T00:00:00Z
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dc.relation.none.fl_str_mv Eur Spine J. 2013;22(12):2787-99
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