• Stephen L Kates, Severine Hurni, and Maio S Chen.
• Department of Orthopaedic Surgery, Virginia Commonwealth University, 1200 East Broad St, PO Box 980153, Richmond, VA, 23298, USA. Stephen.Kates@vcuhealth.org.
• Arch Orthop Trauma Surg. 2020 Jun 1; 140 (6): 741-749.

IntroductionOsteomyelitis is an increasing burden on the society especially due to the emergence of multiple drug-resistant organisms. The lack of a central registry that prospectively collects data on patient risk factors, laboratory test results, treatment modalities, serological analysis results, and outcomes has hampered the research effort that could have improved and provided guidelines for treatments of bone infections. The current manuscript describes the lessons learned in setting up a multi-continent registry.Materials And MethodsThis multicenter, international registry was conducted to prospectively collect essential patient, clinical, and surgical data with a 1-year follow-up period. Patients 18 years or older with confirmed S. aureus long bone infection through fracture fixation or arthroplasty who consented to participate in the study were included. The outcomes using the Short Form 36 Health Survey Questionnaire (version 2), Parker Mobility Score, and Katz Index of Independence in Activities of Daily Living were assessed at baseline and at 1 month, 6 months, and 12 months. Serological samples were collected at follow-ups.ResultsContract negotiation with a large number of study sites was difficult; obtaining ethics approvals were time-consuming but straightforward. The initial patient recruitment was slow, leading to a reduction of target patient number from 400 to 300 and extension of enrollment period. Finally, 292 eligible patients were recruited by 18 study sites (in 10 countries of 4 continents, Asia, North and South America, and Central Europe). Logistical and language barriers were overcome by employing courier service and local monitoring personnel.ConclusionsMulticenter registry is useful for collecting a large number of cases for analysis. A well-defined data collection practice is important for data quality but challenging to coordinate with the large number of study sites.

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