Articles | Volume 9, issue 1
Original full-length article
06 Feb 2024
Original full-length article |  | 06 Feb 2024

Development of an evidence-based diagnostic algorithm for infection in patients with transcutaneous osseointegration following amputation

Shafaf Hasin Alam, Jason S. Hoellwarth, Kevin Tetsworth, Atiya Oomatia, Tristen N. Taylor, and Munjed Al Muderis

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Unexpected positive intraoperative cultures (UPIC) at index osseointegration do not lead to increased postoperative infectious events
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J. Bone Joint Infect., 7, 155–162,,, 2022
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Cited articles

Al Muderis, M., Khemka, A., Lord, S. J., Van de Meent, H., and Frölke, J. P. M.: Safety of Osseointegrated Implants for Transfemoral Amputees: A Two-Center Prospective Cohort Study, J. Bone Joint Surg. Am., 98, 900–909, 2016. 
Al Muderis, M., Lu, W., Tetsworth, K., Bosley, B., and Li, J. J.: Single-stage osseointegrated reconstruction and rehabilitation of lower limb amputees: the Osseointegration Group of Australia Accelerated Protocol-2 (OGAAP-2) for a prospective cohort study, BMJ Open, 7, e013508,, 2017. 
Atallah, R., Leijendekkers, R. A., Hoogeboom, T. J., and Frölke, J. P.: Complications of bone-anchored prostheses for individuals with an extremity amputation: A systematic review, PLoS One, 13, e0201821,, 2018. 
Baars, E. C., Schrier, E., Dijkstra, P. U., and Geertzen, J. H. B.: Prosthesis satisfaction in lower limb amputees: A systematic review of associated factors and questionnaires, Medicine , 97, e12296,, 2018. 
Beck, J. P., Grogan, M., Bennett, B. T., Jeyapalina, S., Agarwal, J., Bartow-McKenney, C., Bugayev, J., Kubiak, E., Sinclair, S., and Grice, E.: Analysis of the Stomal Microbiota of a Percutaneous Osseointegrated Prosthesis: A Longitudinal Prospective Cohort Study, J. Orthop. Res., 37, 2645–2654, 2019. 
Short summary
Osseointegration is a highly enabling reconstruction for patients with limb loss. However, infection can occur. There are currently poor diagnostic criteria for infection, and patients may be brought for surgery too much or too little. The study proposes an algorithm based on history, clinical, and laboratory data to predict the chance of culture-positive deep infection.