Interest of a Commercialized Pneumocystis jirovecii Quantitative PCR to Discriminate Colonization from Pneumocystis Pneumonia according to the Revised EORTC/MSGERC Criteria.

Quantitative PCR (qPCR) is highly sensitive to diagnose Pneumocystis jirovecii (Pj) pneumonia (PCP). However, differentiating PCP and colonization remains difficult. This study aimed to establish the performances of the commercialized qPCR MycoGENIE® Pj kit (Ademtech) to distinguish PCP and Pj colonization. Patients with a positive Pj qPCR on bronchoalveolar lavage (BAL) or upper respiratory tract (URT) samples were prospectively included between May 2019 and December 2020 at Bordeaux University Hospital. They were classified in "PCP" or "Pj colonization" groups based on the revised EORTC/MSGERC criteria. The two groups' results were compared; ROC curves were produced to determine the best thresholds. Excluding the low number of HIV-positive subjects, there were 100 PCP (32 BAL, 68 URT) and 70 Pj colonization (34 BAL, 36 URT). Pj loads were significantly higher in PCP compared to Pj colonization group (p ≤ 0.01). The best cut-offs for PCP diagnosis were 31.45 Cq/8275 copies/mL for BAL and 32.33 Cq/8130 copies/mL for URT (sensitivity = 59.4%, 63.3%, specificity = 82.4%, 88.9%, respectively). Fungal load quantification using MycoGENIE® Pj qPCR helps discriminating PCP from colonization, high fungal loads being indicative of probable PCP. Low load results should be interpreted with caution, in accordance with clinical and radiological signs.

Covichem: A biochemical severity risk score of COVID-19 upon hospital admission.

Clinical and laboratory predictors of COVID-19 severity are now well described and combined to propose mortality or severity scores. However, they all necessitate saturable equipment such as scanners, or procedures difficult to implement such as blood gas measures. To provide an easy and fast COVID-19 severity risk score upon hospital admission, and keeping in mind the above limits, we sought for a scoring system needing limited invasive data such as a simple blood test and co-morbidity assessment by anamnesis. A retrospective study of 303 patients (203 from Bordeaux University hospital and an external independent cohort of 100 patients from Paris Pitié-Salpêtrière hospital) collected clinical and biochemical parameters at admission. Using stepwise model selection by Akaike Information Criterion (AIC), we built the severity score Covichem. Among 26 tested variables, 7: obesity, cardiovascular conditions, plasma sodium, albumin, ferritin, LDH and CK were the independent predictors of severity used in Covichem (accuracy 0.87, AUROC 0.91). Accuracy was 0.92 in the external validation cohort (89% sensitivity and 95% specificity). Covichem score could be useful as a rapid, costless and easy to implement severity assessment tool during acute COVID-19 pandemic waves.