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Surgical Site Infection After Primary Hip and Knee Arthroplasty: A Cohort Study Using a Hospital Database

Published online by Cambridge University Press:  08 July 2015

Leslie Grammatico-Guillon*
Affiliation:
Service d’Information Médicale, d’Epidémiologie et d’Economie de la Santé, Centre Hospitalier Régional Universitaire de Tours, Laboratoire de santé publique, Université François Rabelais, Tours, France
Sabine Baron
Affiliation:
Unité régionale d’épidémiologie hospitalière, Centre Hospitalier Régional Universitaire de Tours, France
Philippe Rosset
Affiliation:
Service de chirurgie orthopédique, Centre Hospitalier Régional Universitaire Tours, Université François Rabelais, Tours, France
Christophe Gaborit
Affiliation:
Unité régionale d’épidémiologie hospitalière, Centre Hospitalier Régional Universitaire de Tours, France
Louis Bernard
Affiliation:
Service de Médecine Interne et Maladies Infectieuses, Centre Hospitalier Régional Universitaire Tours, Université François Rabelais, Tours, France
Emmanuel Rusch
Affiliation:
Service d’Information Médicale, d’Epidémiologie et d’Economie de la Santé, Centre Hospitalier Régional Universitaire de Tours, Laboratoire de santé publique, Université François Rabelais, Tours, France
Pascal Astagneau
Affiliation:
Ecole des Hautes Etudes en Santé Publique & Centre de coordination pour la lutte contre les infections associées aux soins, Paris, France
*
Address correspondence to Leslie Grammatico-Guillon, MD, PhD, SIMEES, CHRU de Tours, Hôpital Bretonneau, 2 BD Tonnellé, 37000 Tours France (Leslie.guillon@univ-tours.fr).

Abstract

BACKGROUND

Hip or knee arthroplasty infection (HKAI) leads to heavy medical consequences even if rare.

OBJECTIVE

To assess the routine use of a hospital discharge detection algorithm of prosthetic joint infection as a novel additional tool for surveillance.

METHODS

A historic 5-year cohort study was built using a hospital database of people undergoing a first hip or knee arthroplasty in 1 French region (2.5 million inhabitants, 39 private and public hospitals): 32,678 patients with arthroplasty code plus corresponding prosthetic material code were tagged. HKAI occurrence was then tracked in the follow-up on the basis of a previously validated algorithm using International Statistical Classification of Disease, Tenth Revision, codes as well as the surgical procedures coded. HKAI density incidence was estimated during the follow-up (up to 4 years after surgery); risk factors were analyzed using Cox regression.

RESULTS

A total of 604 HKAI patients were identified: 1-year HKAI incidence was1.31%, and density incidence was 2.2/100 person-years in hip and 2.5/100 person-years in knee. HKAI occurred within the first 30 days after surgery for 30% but more than 1 year after replacement for 29%. Patients aged 75 years or older, male, or having liver diseases, alcohol abuse, or ulcer sore had higher risk of infection. The inpatient case fatality in HKAI patients was 11.4%.

CONCLUSIONS

The hospital database method used to measure occurrence and risk factors of prosthetic joint infection helped to survey HKAI and could optimize healthcare delivery.

Infect Control Hosp Epidemiol 2015;36(10):1198–1207

Type
Original Articles
Copyright
© 2015 by The Society for Healthcare Epidemiology of America. All rights reserved 

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Supplementary material: File

Grammatico-Guillon supplementary material S1

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