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S10.2 Fungal Infections in Transplant Patients, September 24, 2022, 10:30 AM - 12:00 PM Objectives Diagnosis of histoplasmosis in people living with HIV (PLWHIV) remains challenging despite developments in Histoplasma antigen and molecular detection tools. Fungal markers such as Beta-(1,3)-D-glucan (BDG) and galactomannan Aspergillus antigen (GM) are widely available, but the experience is limited during PLWHIV workup for suspicion of histoplasmosis. Our objective was to evaluate and compare BDG and GM performances for the diagnosis of HIV-associated histoplasmosis. Methods We performed a diagnostic accuracy study using primary serum samples stored frozen in a certified biorepository (CRB Amazonie-DC-2021-4649). Samples consisted of consecutive hospitalized PLWHIV unexposed to oral antifungals during the previous month (EDIRAPHIS study-NCT01884779). All patients gave consent for biobanking and ancillary studies on fungal markers. Histoplasmosis cases, proven (EORTC/MSG criteria) and probable (polyclonal or monoclonal Histoplasma antigen detections in urines or serum), as well as negative controls, were randomly selected. Patients with a proven or suspected Pneumocystis jirovecii infection were excluded. Following manufacturers’ instructions, samples were blindly tested for BDG and GM using Fungitell® and PlateliaTM Aspergillus Ag assays, respectively. Gold standard definition used three scenarios: EORTC scenario (cases and controls defined according to the EORTC/MSG 2020 criteria for endemic mycoses); strict scenario with proven cases restricted to those positives to all three previous Histoplasma antigen detections, and controls conversely negatives for all methods; and a large scenario with proven or probable cases and controls negatives for all methods. Results We included 121 samples, 92 HIV-associated histoplasmosis cases (34 proven and 58 probable), and 29 negative controls. Compared with controls, histoplasmosis cases were significantly younger and advanced in the course of HIV disease [median CD4 count level 33/mm3 (15-87) vs 116 (62-245)]. BDG and GM median detection levels were significantly higher among histoplasmosis cases compared with controls across all scenarios [368 (176-441) pg/ml vs 142 (89-211) for BDG and 2.5 (1.3-4.8) vs 0.19 (0.14-0.36) for GM, in cases vs controls of the strict scenario, respectively]. In the strict scenario, at 150 pg/ml and 0.5 for BDG and GM respectively, sensitivity, specificity, positive and negative likelihood ratios were respectively: 95% [95%confidence interval (CI), 85-100] vs 90% [77-100], 52% [34-70] vs 83% [69-97], 2 [1.4-3.0] vs 5.3 [2.4-12.0], and 0.1 [0.01-0.7] vs 0.12 [0.03-0.45]. ROC curves found AUCs of 0.82 [0.68-0.91] vs 0.92 [0.80-0.98], and optimal thresholds at 288 pg/ml and 1.29, for BDG and GM, respectively (Fig. 1). Post-test probabilities showed best performances at the lowest thresholds for negative testing of both BDG and GM, and at the 0.7 thresholds for a positive GM test (Fig. 2). Conclusion BDG and GM may not be used for the same objective when searching for HIV-associated histoplasmosis. Although a negative BDG test at the lowest thresholds should rule out histoplasmosis in a screening context, limitations of a positive BDG test, even at the highest thresholds, call for a consecutive positive GM test before starting patients on antifungal therapy targeting histoplasmosis. Still, when considering the highest costs of BDG testing, higher balanced diagnostic performances, and lower costs of GM testing alone, one may favor the use of GM, notably in resources-limited settings.

S2.2 Histoplasmosis and talaromycosis, September 21, 2022, 3:00 PM - 4:30 PM In sub-Saharan Africa (SSA) and West African countries, histoplasmosis is rarely diagnosed probably due to lack of epidemiological information, insufficient training and awareness of frontline healthcare workers, and clinical features very similar to those of tuberculosis that can be misleading. This fungal infection mainly affects immunocompromised patients and particularly advanced HIV patients, with a high case-fatality rate in the absence of treatment (from 40%). The classical diagnostic methods are microscopic observation of yeasts with suggestive morphology and a positive culture from a biological sample. However, direct examination requires regular practice, and the yeasts can be confused with other pathogens and culture takes prolonged incubation (often 2-6 weeks) and involves, when positive, handling in a level 3 security laboratory. Implementing non-invasive diagnostic tools will allow us to improve histoplasmosis diagnosis for the most exposed patients and also to evaluate the prevalence of this fungal infection in countries where data are still lacking. Rapid diagnostic tests (RDTs) such as the TB Lam for the diagnosis of tuberculosis or the Cryptococcal antigen (CrAg) lateral flow assay (LFA) for cryptococcosis have demonstrated their usefulness for the management of advanced HIV patients in similar contexts. Recently, two RDTs have been made commercially available for the diagnosis of histoplasmosis, based on urinary monoclonal antigen detection: (1) Histoplasma Capsulatum Urinary Antigen Rapid Test from Optimium Imaging Diagnostics (OIDx) and (2) Histoplasma Urine Antigen Lateral Flow Assay from MiraVista Diagnostics (MV). Objectives and Methods Our objective was to evaluate these new tools, by experimenting with their feasibility in low-and middle-income countries (LMICs) and by studying their diagnostic performances using different sample collections recovered from patients with disseminated histoplasmosis (culture proven), other HIV-related infections, and proven negative urines (culture and other Histoplasma antigen detections). Results Preliminary results were obtained using the EDIRAPHIS study frozen samples from hospitalized patients diagnosed with proven positive and negative histoplasmosis from French Guiana and Suriname (n = 43) tested with OIDx and MV tests. We calculated a Se = 74.2% and a Sp = 83.3% for OIDx and a Se = 77.4% and a Sp = 91,7% for MV. A low number of false positives for both tests, Conclusion These first results are very promising and will be completed with two other specimen collections to increase the total numbers of our sampling and get a whole picture of the performances of these two RDTs. The next step will be to implement these new tools at the bedside or in laboratories together with other tests in different settings across SSA. Diffusion of RDTs together with appropriate training of clinical and laboratory teams and accessibility to treatment may help reduce the burden of histoplasmosis in endemic areas of SSA where the prevalence of the advanced-HIV disease is high.

Centre Hospitalier de Cayenne. Centre d Investigation Clinique Epid?miologie Clinique Antilles Guyane. Cayenne, French Guiana, France. / Universite? Antilles Guyane. Epidemiologie Parasitoses et Mycoses Tropicales. Cayenne, French Guiana. Centre Hospitalier de Cayenne. Centre d Investigation Clinique Epid?miologie Clinique Antilles Guyane. Cayenne, French Guiana, France. / Universite? Antilles Guyane. Epidemiologie Parasitoses et Mycoses Tropicales. Cayenne, French Guiana. Academisch Ziekenhuis Paramaribo Hospital. Paramaribo, Suriname. Laborat?rio Central de Sa?de P?blica do Amap?. Macap?, AP, Brazil. National AIDS Program. Georgetown, Guyana. Laborat?rio Central de Sa?de P?blica do Amap?. Macap?, AP, Brazil. Laborat?rio Central de Sa?de P?blica do Amap?. Macap?, AP, Brazil. Academisch Ziekenhuis Paramaribo Hospital. Paramaribo, Suriname. Public Health Central Laboratory of Suriname. Paramaribo, Suriname. Diakonessenhuis Hospital. Paramaribo, Suriname. Minist?rio da Sa?de. Secretaria de Vigil?ncia em Sa?de. Instituto Evandro Chagas. Ananindeua, PA, Brasil. Minist?rio da Sa?de. Secretaria de Vigil?ncia em Sa?de. Instituto Evandro Chagas. Ananindeua, PA, Brasil. Hospital de Clinicas Dr. Alberto Lima. Macap?, AP, Brazil. Hospital de Clinicas Dr. Alberto Lima. Macap?, AP, Brazil. Universidade Federal do Cear? - Faculdade de Medicina - Departamento de Sa?de Comunitaria. Fortaleza, CE, Brazil. Corporaci?n para Investigaciones Biol?gicas. Medell?n, Colombia. Corporaci?n para Investigaciones Biol?gicas. Medell?n, Colombia Corporaci?n para Investigaciones Biol?gicas. Medell?n, Colombia INEI-ANLIS "Dr. Carlos G. Malbr?n". Buenos Aires, Argentina Universit? Antilles Guyane. Epidemiologie Parasitoses et Mycoses Tropicales. Cayenne, French Guiana Universit? Antilles Guyane. Epidemiologie Parasitoses et Mycoses Tropicales. Cayenne, French Guiana Centre Hospitalier de l'Ouest Guyanais. Saint Laurent du Maroni, French Guiana, France Centre Hospitalier de l'Ouest Guyanais. Saint Laurent du Maroni, French Guiana, France Centre Hospitalier de l'Ouest Guyanais. Saint Laurent du Maroni, French Guiana, France Centers for Disease Control and Prevention. Mycotic Diseases Branch. Atlanta, Georgia, United States of America Centers for Disease Control and Prevention. Mycotic Diseases Branch. Atlanta, Georgia, United States of America Centers for Disease Control and Prevention. Mycotic Diseases Branch. Atlanta, Georgia, United States of America Centers for Disease Control and Prevention. Mycotic Diseases Branch. Atlanta, Georgia, United States of America Institut Pasteur. National Reference Center for Mycoses and Antifungals. Molecular Mycology Unit. Paris, France Centre Hospitalier de Cayenne. Centre d Investigation Clinique Epid?miologie Clinique Antilles Guyane. Cayenne, French Guiana, France. / Universite? Antilles Guyane. Epidemiologie Parasitoses et Mycoses Tropicales. Cayenne, French Guiana Universit? Antilles Guyane. Epidemiologie Parasitoses et Mycoses Tropicales. Cayenne, French Guiana Academisch Ziekenhuis Paramaribo Hospital. Paramaribo, Suriname