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Clinical Trial Summary

Establish an international registry of over 400 patients with deep infections involving the bone and/or joint from≥20 centers representing all regions of the world with varied hospital and surgeon practice settings to ensure that registry analyses and research reflect typical clinical practice thereby providing optimal guidance for patients, clinicians, and healthcare researchers. Using a data collection platform that minimizes entry burden, collects most information at the time of surgery, and uses Internet technology to minimize data entry. The registry will include:

1. baseline patient attributes;

2. surgical approach, implants and technology;

3. hospital course;

4. surgeon and institutional characteristics;

5. longitudinal patient outcome,

6. post-procedure complications and revisions,

7. serum/tissue/drainage samples.


Clinical Trial Description

Establish an international registry with AOCID of over 400 patients with deep infections involving the bone and/or joint from ≥ 20 centers representing all regions of the world with varied hospital and surgeon practice settings to ensure that registry analyses and research reflect typical clinical practice thereby providing optimal guidance for patients, clinicians, and healthcare researchers. Creation of an AOCID Registry for musculoskeletal infection cases will permit better analysis of the causes, contributing factors including patient immune responses, treatments and clinical outcomes of musculoskeletal infections.

- Establish a practice network that includes ≥ 20 geographically distributed centers. These busy practices will be treating patients with varied geographic status to assure balanced representation of diverse patients and practices.

- Establish a Data Coordinating Core team with AOCID using a data collection platform that minimizes entry burden, collects most information at the time of surgery, and uses Internet technology to minimize data entry.

The registry will include:

- baseline patient attributes

- surgical approach, implants and technology

- hospital course

- surgeon and institutional characteristics

- longitudinal patient outcome

- post-procedure complications and revisions

- serum/tissue/drainage samples

- Establish a Statistical Support team with AOCID to implement cutting-edge statistical techniques including the use of hierarchical generalized linear latent and mixed effects models to address the complex structure and longitudinal nature of registry data. Multivariable predictive models for outcome(s) of infection will be developed.

- Establish an Outcomes Measurement Team with AOCID and Investigators from the CPP team to advance the science of infection-specific and global patient-reported outcomes to support efficient data collection of web-based, longitudinal data in this registry and future comparative effectiveness research.

- Develop new assessment tools and conduct research useful to clinical practice. Establish consensus on the definition of treatment failure- characterized as lack of clinically meaningful improvement in infection, pain or physical function following treatment, validate, and refine prediction algorithms for patients at risk for failure. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT01677000
Study type Observational
Source AO Innovation Translation Center
Contact
Status Completed
Phase
Start date June 2012
Completion date June 30, 2019

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