We report an almost 1.7-fold proportional increase in C. glabrata candidaemia (26.7% versus 16% in 2004) in Australia. Antifungal resistance was generally uncommon, but azole resistance (16.7% of isolates) amongst C. tropicalis may be emerging.

Mucormycosis is the second most common cause of invasive mould infection and causes disease in diverse hosts, including those who are immuno-competent. We conducted a multicentre retrospective study of proven and probable cases of mucormycosis diagnosed between 2004-2012 to determine the epidemiology and outcome determinants in Australia. Seventy-four cases were identified (63 proven, 11 probable). The majority (54.1%) were caused by Rhizopus spp. Patients who sustained trauma were more likely to have non-Rhizopus infections relative to patients without trauma (OR 9.0, p 0.001, 95% CI 2.1-42.8). Haematological malignancy (48.6%), chemotherapy (42.9%), corticosteroids (52.7%), diabetes mellitus (27%) and trauma (22.9%) were the most common co-morbidities or risk factors. Rheumatological/autoimmune disorders occurred in nine (12.1%) instances. Eight (10.8%) cases had no underlying co-morbidity and were more likely to have associated trauma (7/8; 87.5% versus 10/66; 15.2%; p <0.001). Disseminated infection was common (39.2%). Apophysomyces spp. and Saksenaea spp. caused infection in immuno-competent hosts, most frequently associated with trauma and affected sites other than lung and sinuses. The 180-day mortality was 56.7%. The strongest predictors of mortality were rheumatological/autoimmune disorder (OR = 24.0, p 0.038 95% CI 1.2-481.4), haematological malignancy (OR = 7.7, p 0.001, 95% CI 2.3-25.2) and admission to intensive care unit (OR = 4.2, p 0.02, 95% CI 1.3-13.8). Most deaths occurred within one month. Thereafter we observed divergence in survival between the haematological and non-haematological populations (p 0.006). The mortality of mucormycosis remains particularly high in the immuno-compromised host. Underlying rheumatological/autoimmune disorders are a previously under-appreciated risk for infection and poor outcome.

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Background Candidaemia is associated with high mortality. Variables associated with mortality have been published previously, but not developed into a risk predictive model for mortality. We sought to describe the current epidemiology of candidaemia in Australia, analyse predictors of 30-day all-cause mortality, and develop and validate a mortality risk predictive model. Methods Adults with candidaemia were studied prospectively over 12 months at eight institutions. Clinical and laboratory variables at time of blood culture-positivity were subject to multivariate analysis for association with 30-day all-cause mortality. A predictive score for mortality was examined by area under receiver operator characteristic curves and a historical data set was used for validation. Results The median age of 133 patients with candidaemia was 62 years; 76 (57%) were male and 57 (43%) were female. Co-morbidities included underlying haematologic malignancy ( n = 20; 15%), and solid organ malignancy in ( n = 25; 19%); 55 (41%) were in an intensive care unit (ICU). Non- albicans Candida spp . accounted for 61% of cases (81/133). All-cause 30-day mortality was 31%. A gastrointestinal or unknown source was associated with higher overall mortality than an intravascular or urologic source ( p < 0.01). A risk predictive score based on age > 65 years, ICU admission, chronic organ dysfunction, preceding surgery within 30 days, haematological malignancy, source of candidaemia and antibiotic therapy for ≥10 days stratified patients into < 20% or ≥ 20% predicted mortality. The model retained accuracy when validated against a historical dataset ( n = 741). Conclusions Mortality in patients with candidaemia remains high. A simple mortality risk predictive score stratifying patients with candidaemia into < 20% and ≥ 20% 30-day mortality is presented. This model uses information available at time of candidaemia diagnosis is easy to incorporate into decision support systems. Further validation of this model is warranted. Electronic supplementary material The online version of this article (10.1186/s12879-019-4065-5) contains supplementary material, which is available to authorized users.

dWe developed an Australian database for the identification of Aspergillus, Scedosporium, and Fusarium species (n ‫؍‬ 28) by matrix-assisted laser desorption ionization؊time of flight mass spectrometry (MALDI-TOF MS). In a challenge against 117 isolates, species identification significantly improved when the in-house-built database was combined with the Bruker Filamentous Fungi Library compared with that for the Bruker library alone (Aspergillus, 93% versus 69%; Fusarium, 84% versus 42%; and Scedosporium, 94% versus 18%, respectively). Rapid, accurate mold identification is important due to the widening spectrum of pathogens and species-specific differences in antifungal susceptibility (1-3). Matrix-assisted laser desorption ionizationϪtime of flight mass spectrometry (MALDI-TOF MS) has proven useful, but mold identification remains challenged by the limited access to validated purpose-built databases that are necessary because of small species and strain representations in commercial libraries (4-16).Given the prior poor performance of the Bruker Filamentous Fungi Library v1.0 (Bruker Daltonics, Bremen, Germany) for mold identification using the manufacturer-recommended broth-based protein extraction methods (in our laboratory Ͼ50% of isolates were not identified; internal data) and because the geographic generalizability of in-house-built databases is not yet known, we hypothesized that a MS library of molds relevant to our region (17-21) will improve identification. Here, we constructed an in-house database containing 117 strains (see Table S1 in the supplemental material) covering 28 species of Aspergillus, Scedosporium, and Fusarium encountered in Australia. Challenge isolates (also n ϭ 117; 21 species) comprising 55 Aspergillus, 45 Fusarium, and 17 Scedosporium clinical strains (Table 1) were then used to assess the performance of the Bruker library alone versus that of the Bruker library supplemented with the in-house library for species identification.All isolates were identified using phenotypic methods (22) with definitive identification by DNA sequencing of the internal transcribed spacer (ITS) (all isolates), ␤-tubulin (Aspergillus and Scedosporium spp.), and partial elongation factor-1alpha (EF-1␣) (to identify Fusarium to the species complex level) gene regions (23)(24)(25)(26). Sequence data were analyzed against the Centraalbureau voor Schimmelkultures (http://www.cbs.knaw.nl/Collections /BioloMICSSequences.aspx?fileϭall), International Society for Human and Animal Mycology ITS (http://its.mycologylab.org/), and Fusarium-ID (http://www.fusariumdb.org/index.php) databases, and species were assigned using published criteria (27).Protein extraction for MALDI-TOF MS was performed as previously described (11). The Bruker bacterial test standard (Bruker Daltonics) was used for calibration and Aspergillus ustus CBS 261.67T scoring of Ն2.00 was required for quality extraction and spectra acceptability (11). The in-house database was constructed using published protocols (11, 28) with 20 to 25 quality spe...

In vitro bacterial-fungal interaction studies in cystic fibrosis (CF) have mainly focused on interactions between bacteria and Candida. Here we investigated the effect of Pseudomonas aeruginosa on the growth of Scedosporium/Lomentospora spp. Standard suspensions of P. aeruginosa (16 non-mucoid and nine mucoid isolates) were dropped onto paper disks, placed on lawns of Lomentospora prolificans (formerly Scedosporium prolificans) strain WM 14.140 or Scedosporium aurantiacum strain WM 11.78 on solid agar. The median inhibitory activity (mIz) was calculated for each fungal-bacterial combination. As a group, mIz values for non-mucoid phenotype P. aeruginosa strains were significantly lower than those for mucoid strains (P < 0.001); 14/16 (87.5%) non-mucoid strains had mIz <1.0 against both fungi versus just 3/9 mucoid strains (33.4%) (P = 0.01). One non-mucoid (PA14) and one mucoid (CIDMLS-PA-28) P. aeruginosa strain effecting inhibition were selected for further studies. Inhibition of both L. prolificans and S. aurantiacum by these strains was confirmed using the XTT (2,3-bis(2-methoxy-4-nitro-5-sulfophenyl)-5-[(phenylamino)carbonyl]-2H-tetrazolium hydroxide) reduction assay. Following incubation with XTT, inhibition of fungal growth was determined as the ratio of absorbance in liquid culture with Pseudomonas to that in control fungal cultures. An absorbance ratio of <1.0 consistent with bacterial inhibition of fungal growth was observed for all four P. aeruginosa-fungal combinations (P < 0.05). Fluorescence microscopy, subsequent to co-culture of either fungal isolate with P. aeruginosa strain PA14 or CIDMLS-PA-28 revealed poorly formed hyphae, compared with control fungal cultures. P. aeruginosa inhibits growth of L. prolificans and S. aurantiacum in vitro, with non-mucoid strains more commonly having an inhibitory effect. As P. aeruginosa undergoes phenotype transitions from non-mucoid to the mucoid form with progression of CF lung disease, this balance may influence the appearance of Scedosporium fungi in the airways.

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Objectives Candidaemia carries a mortality of up to 40% and may be related to increasing complexity of medical care. Here, we determined risk factors for the development of candidaemia. Methods We conducted a prospective, multi‐centre, case‐control study over 12 months. Cases were aged ≥18 years with at least one blood culture positive for Candida spp. Each case was matched with two controls, by age within 10 years, admission within 6 months, admitting unit, and admission duration at least as long as the time between admission and onset of candidaemia. Results A total of 118 incident cases and 236 matched controls were compared. By multivariate analysis, risk factors for candidaemia included neutropenia, solid organ transplant, significant liver, respiratory or cardiovascular disease, recent gastrointestinal, biliary or urological surgery, central venous access device, intravenous drug use, urinary catheter and carbapenem receipt. Conclusions Risk factors for candidaemia derive from the infection source, carbapenem use, host immune function and organ‐based co‐morbidities. Preventive strategies should target iatrogenic disruption of mucocutaneous barriers and intravenous drug use.