A simple score can identify kidney transplant recipients at high risk of severe infection over the following 2 years. Issue 3 (22nd April 2019)

• Record Type: Journal Article
• Authors: Dendle, Claire; Polkinghorne, Kevan R.; Mulley, William R.; Gan, Poh‐Yi; Kanellis, John; Stuart, Rhonda L.; Thursky, Karin; Holdsworth, Stephen R.
• Is Part Of: Transplant infectious disease. Volume 21:Issue 3(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-04-22
• Subjects: infection risk -- kidney transplant risk -- lymphocytes -- natural killer cells -- score; Transplantation of organs, tissues, etc -- Complications -- Periodicals; Communicable diseases -- Periodicals; Infection -- Periodicals; 617.01
• DOI: 10.1111/tid.13076
• Languages: English
• ISSNs: 1398-2273

Abstract

Abstract: Background: The aim of this study was to determine whether a composite score of simple immune biomarkers and clinical characteristics could predict severe infections in kidney transplant recipients. Methods: We conducted a prospective study of 168 stable kidney transplant recipients who underwent measurement of lymphocyte subsets, immunoglobulins, and renal function at baseline and were followed up for 2 years for the development of any severe infections, defined as infection requiring hospitalization. A point score was developed to predict severe infection based on logistic regression analysis of factors in baseline testing. Results: Fifty‐nine (35%) patients developed severe infection, 36 (21%) had two or more severe infections, and 3 (2%) died of infection. A group of 19 (11%) patients had the highest predicted infectious risk (>60%), as predicted by the score. Predictive variables were mycophenolate use, graft function, CD4+, and natural killer cell number. The level of immunosuppression score had an area under the receiver operating curve of 0.75 (95% CI: 0.67‐0.83). Conclusion: Our level of immunosuppression score for predicting the development of severe infection over 2 years has sufficient prognostic accuracy for identification of high‐risk patients. This data can inform research that examines strategies to reduce the risks of infection.