Your browser doesn't support javascript.
loading
Diagnosing Osteomyelitis: A Histology Guide for Pathologists.
Sybenga, Amelia B; Jupiter, Daniel C; Speights, V O; Rao, Arundhati.
Afiliação
  • Sybenga AB; Clinical Fellow, Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN. Electronic address: amelia.b.sybenga@vumc.org.
  • Jupiter DC; Associate Professor, Department of Preventive Medicine and Community Health, Department of Orthopaedic Surgery and Rehabilitation, The University of Texas Medical Branch, Galveston, TX.
  • Speights VO; Professor, Department of Pathology and Laboratory Medicine, Scott & White Medical Center, Baylor Scott and White Health, Texas A&M Health Science Center, Temple, TX.
  • Rao A; Professor, Department of Pathology and Laboratory Medicine, Scott & White Medical Center, Baylor Scott and White Health, Texas A&M Health Science Center, Temple, TX.
J Foot Ankle Surg ; 59(1): 75-85, 2020.
Article em En | MEDLINE | ID: mdl-31753572
ABSTRACT
Histopathologic examination of bone specimens coupled with bone culture is considered the gold standard for the diagnosis of osteomyelitis (OM). Despite this, studies have demonstrated interpathologist agreement in the diagnosis of OM as low as 30%, largely stemming from a lack of specific definitions and diagnostic criteria. Review of the literature has provided insight into the lifecycle of OM, illustrating the histologic progression of OM phases from acute to chronic, and provides support for defining subcategories of OM. Using an algorithmic histopathologic tool consisting of 15 criteria, each with an associated score, we defined 5 categories of OM (1) acute OM, (2) acute and chronic OM, (3) chronic OM, (4) chronic active OM, and (5) chronic inactive OM. We reviewed 462 microscopic slides from 263 patients with suspected OM, and for each slide, we determined an algorithm-derived diagnosis, which was then used to calculate a total histopathologic load score (Jupiter score). Algorithm-derived diagnoses recapitulated original clinical diagnoses and diagnosed cases as OM that had not been originally diagnoses. These novel cases were more likely to have subsequent clinical complications. Finally, pathologic load scores were assessed for association with the category of OM.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Osteomielite / Algoritmos / Tomada de Decisão Clínica Tipo de estudo: Diagnostic_studies / Etiology_studies / Prognostic_studies Limite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: J Foot Ankle Surg Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Osteomielite / Algoritmos / Tomada de Decisão Clínica Tipo de estudo: Diagnostic_studies / Etiology_studies / Prognostic_studies Limite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: J Foot Ankle Surg Ano de publicação: 2020 Tipo de documento: Article