Chronic Pulmonary Aspergillosis: Burden, Clinical Characteristics and Treatment Outcomes at a Large Australian Tertiary Hospital.
Olivier DespoisSharon C-A ChenNicole GilroyMichael JonesPeter WuTra-My N DuongPublished in: Journal of fungi (Basel, Switzerland) (2022)
Chronic pulmonary aspergillosis (CPA) is a fungal lung infection associated with high morbidity and mortality. Yet, it remains under-recognized worldwide, with few Australian clinical data available. This retrospective study aimed to investigate CPA at a major tertiary referral hospital in Sydney. We identified patients having International Classification of Diseases (ICD-10) codes for "aspergillosis" and/or positive respiratory microbiology samples for Aspergillus species from January 2012-December 2018 at Westmead Hospital. Eligible cases were classified using European Respiratory Society 2016 CPA guidelines. We diagnosed 28 CPA patients: median age 60 years (IQR: 57-66), with 17 (60.7%) being males. Most had chronic cavitary pulmonary aspergillosis phenotype (n = 17, 60.7%). Twenty-three patients had outcomes data returned. Nineteen (82.6%) received antifungal therapy (median duration: 10.5 months (IQR: 6.5-20.7)). Eight (34.7%) patients received <6 months of antifungals, including three (38%) deaths. Two (13%) patients receiving ≥6 months of antifungals died. Chronic obstructive pulmonary disease (COPD) (n = 9, 32.1%) was the leading predisposing factor for CPA in our cohort. This contrasts with the global picture, where prior tuberculosis generally predominates, but is similar to findings from other high-income countries. Nevertheless, further larger-scale studies are required to determine whether these results are generalizable to the wider Australian population.
Keyphrases
- end stage renal disease
- chronic obstructive pulmonary disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- prognostic factors
- pulmonary hypertension
- emergency department
- peritoneal dialysis
- type diabetes
- mental health
- patient reported outcomes
- deep learning
- machine learning
- mycobacterium tuberculosis
- human immunodeficiency virus
- cystic fibrosis
- lung function
- case control