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Wiley, Clinical Transplantation, 10(37), 2023

DOI: 10.1111/ctr.15052

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Hypoalbuminemia is a risk factor for invasive fungal infections and poor outcomes in infected kidney transplant recipients

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

AbstractIntroductionInvasive fungal infections (IFI), are estimated to occur in 2%–14% of kidney transplant recipients (KTRs) in the current era of immune suppression and are associated with high mortality rates. We hypothesized that hypoalbuminemia in KTRs is a risk factor for IFI and would be associated with poor outcomes.MethodsIn this study, using data from a prospective cohort registry, we describe the frequency of IFI due to Blastomycosis, Coccidioidomycosis, Histoplasmosis, Aspergillosis, and Cryptococcus in KTRs with serum albumin levels measured 3–6 months before diagnosis. Controls were selected based on incidence density sampling. KTRs were divided into three groups based on the pre‐IFI serum albumin level: normal (≥4 g/dL), mild (3–4 g/dL), or severe (<3 g/dL) hypoalbuminemia. Outcomes of interest were uncensored graft failure after IFI and overall mortality.ResultsA total of 113 KTRs with IFI were compared with 348 controls. The incidence rate of IFI among individuals with normal, mild, and severe hypoalbuminemia was 3.6, 8.7, and 29.3 per 100 person‐years, respectively. After adjustment for multiple variables, the trend for risk of uncensored graft failure following IFI was greater in KTRS with mild (HR = 2.1; 95% CI, .75–6.1) and severe (HR = 4.47; 95% CI, 1.56–12.8) hypoalbuminemia (P‐trend < .001) compared to those with normal serum albumin. Similarly, mortality was higher in severe hypoalbuminemia (HR = 1.9; 95% CI, .67–5.6) compared to normal serum albumin (P‐trend < .001).ConclusionHypoalbuminemia precedes the diagnosis of IFI in KTRs, and is associated with poor outcomes following IFI. Hypoalbuminemia may be a useful predictor of IFI in KTRs and could be incorporated into screening algorithms.