Mucormycosis (MCR) has been increasingly described in patients with coronavirus disease 2019 (COVID-19) but the epidemiological factors, presentation, diagnostic certainty, and outcome of such patients are not well described. We review the published COVID-19-associated mucormycosis (CAMCR) cases (total 41) to identify risk factors, clinical features, and outcomes. CAMCR was typically seen in patients with diabetes mellitus (DM) (94%) especially the ones with poorly controlled DM (67%) and severe or critical COVID-19 (95%). Its presentation was typical of MCR seen in diabetic patients (mostly rhino-orbital and rhino-orbital-cerebral presentation). In sharp contrast to reported COVID-associated aspergillosis (CAPA) cases, nearly all CAMCR infections were proven (93%). Treating physicians should have a high suspicion for CAMCR in patients with uncontrolled diabetes mellitus and severe COVID-19 presenting with rhino-orbital or rhino-cerebral syndromes. CAMR is the convergence of two storms, one of DM and the other of COVID-19.

A virtual consensus conference proposal on advanced diagnostics for transplant infectious diseases was submitted by the AST Transplant Diagnostics Community of Practice (TxDxCOP) for consideration and subsequently approved for funding. The consensus conference was fully virtual; participants received no funds from private enterprises. AST provided organizational and technical support for pre-conference and conference proceedings. A steering committee comprising members of TxDxCOP and the Infectious Diseases Community of Practice developed conference definitions, aims, scope, and format. Advanced or novel assays were defined as assays with the capacity for one or more of the following: To detect (1) pathogens, (2) genotypic or phenotypic antimicrobial susceptibility, or (3) pathogen-specific host responses, with an enhanced range of target detection, sensitivity, specificity, speed and/or simplicity of use, relative to conventional methods. Assay categories that met the above definition and for which some data on clinical performance/utility was available were included in this consensus conference.

The exact cause of the disproportionate increase in COVID-19-associated mucormycosis (CAM) cases in India remains unknown. Most researchers consider the major cause of India’s CAM epidemic to be the conjunction of the COVID-19 pandemic and associated corticosteroid treatment with the enormous number of Indians with diabetes mellitus (DM). However, excess CAM cases were not seen to the same extent in the Western world, where diabetes is prevalent and corticosteroids are also used extensively for COVID-19 treatment.

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colonizes the gastrointestinal (GI) tract, resulting in either asymptomatic carriage or a spectrum of diarrheal illness. If clinical suspicion for is low, stool samples are often submitted for analysis by multiplex molecular assays capable of detecting multiple GI pathogens, and some institutions do not report this organism due to concerns for high false-positive rates. Since clinical disease correlates with organism burden and molecular assays yield quantitative data, we hypothesized that numerical cutoffs could be utilized to improve the specificity of the Luminex xTAG GI pathogen panel (GPP) for infection. Analysis of cotested liquid stool samples ( = 1,105) identified a GPP median fluorescence intensity (MFI) value cutoff of ≥1,200 to be predictive of two-step algorithm (2-SA; 96.4% concordance) and toxin enzyme immunoassay (EIA) positivity. Application of this cutoff to a second cotested data set ( = 1,428) yielded 96.5% concordance. To determine test performance characteristics, concordant results were deemed positive or negative, and discordant results were adjudicated via chart review. Test performance characteristics for the MFI cutoff of ≥150 (standard), MFI cutoff of ≥1,200, and 2-SA were as follows (respectively): concordance, 95, 96, and 97%; sensitivity, 93, 78, and 90%; specificity, 95, 98, and 98%; positive predictive value, 67, 82, and 81%;, and negative predictive value, 99, 98, and 99%. To capture the high sensitivity for organism detection (MFI of ≥150) and high specificity for active infection (MFI of ≥1,200), we developed and applied a reporting algorithm to interpret GPP data from patients ( = 563) with clinician orders only for syndromic panel testing, thus enabling accurate reporting of for 95% of samples (514 negative and 5 true positives) irrespective of initial clinical suspicion and without the need for additional testing.

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