Abstract Background Fungal infections contribute substantially to morbidity and mortality after kidney transplantation, yet pathogen-specific epidemiology and clinical risk profiles remain incompletely defined. We aimed to characterize incidence, timing, and pathogen-specific risk factors in a contemporary multicenter cohort. Methods This prospective study, performed by the German Center for Infection Research, included 1,258 adult kidney transplant recipients across five German centers (2011–2022). Fungal infections were diagnosed using clinical, radiological, and mycological criteria. Cox regression identified pathogen-specific associations. Detailed clinical presentation was additionally analyzed in a predefined Heidelberg subcohort. Results The cumulative incidence of fungal infections was 6.7% (95% CI 5.3–8.5). The most frequent pathogens were Candida albicans (40.6%), non-albicans Candida (26.0%), Aspergillus fumigatus (13.5%), and Pneumocystis jirovecii (13.5%). Fever was absent in 79.2% of episodes, and 67.2% had preceding bacterial infections. Pneumocystis jirovecii pneumonia occurred predominantly between October and April, whereas Aspergillus fumigatus infections were observed year-round. ICU stay (HR 5.7, p < 0.01) and prolonged hospitalization were associated with Candida albicans. Prior linezolid exposure (HR 3.9, p = 0.037), delayed graft function (HR 2.9, p = 0.049), and pancreas–kidney transplantation (HR 5.0, p = 0.005) were linked with non-albicans Candida. Carbapenem exposure was associated with Pneumocystis jirovecii pneumonia (HR 6.8, p = 0.002) and invasive aspergillosis (HR 9.8, p < 0.001). Invasive aspergillosis showed the highest mortality (41.7%). In the Heidelberg subcohort ( n = 495), invasive aspergillosis was diagnosed mainly during inpatient care or shortly thereafter, while Pneumocystis jirovecii pneumonia was primarily identified after outpatient care. Conclusion Fungal infections after kidney transplantation show distinct epidemiological patterns with pathogen-specific risk profiles, supporting risk-adapted monitoring and diagnostics.
Schröter et al. (Mon,) studied this question.