Potential use of artificial intelligence for vaginal swab analysis in the assessment of common genital disorders: a pilot study.

Genital disorders, such as vulvo-vaginal candidiasis (VVC), bacterial vaginosis (BV), and aerobic vaginitis (AV), are very common among fertile women and negatively impact their reproductive and relational life. Vaginal culture can help in the diagnostic workflow of these conditions. Recently, culture-based techniques have taken advantages of up-front specimen processing units, which also include a digital imaging system to record images of plates at programmable time points. In this proof-of-concept study, we assessed the characteristics of digital plate images of vaginal swabs plated by WASPLab system into different media, in order to detect microbial growth morphotypes specific for each genital disorder. A total of 104 vaginal specimens were included: 62 cases of normal lactobacilli-dominated flora, 12 of BV, 16 of VVC, and 14 of AV were analysed. Vaginal specimens were plated by WASPLab system into different chromogenic media and blood agar plates. Plate images were taken automatically by the digital imager at 38 h post-inoculation. We found that each genital condition was characterized by specific morphotypes in terms of microbial growth and colony colour, thus allowing the potential use of artificial intelligence not only to assess the presence of specific microbial genera/species but also to 'categorize' peculiar clinical conditions.

Respiratory bacterial co-infections in intensive care unit-hospitalized COVID-19 patients: Conventional culture vs BioFire FilmArray pneumonia Plus panel.

The prevalence and microbiology of concomitant respiratory bacterial infections in patients with SARS-CoV-2 infection are not yet fully understood. In this retrospective study, we assessed respiratory bacterial co-infections in lower respiratory tract samples taken from intensive care unit-hospitalized COVID-19 patients, by comparing the conventional culture approach to an innovative molecular diagnostic technology. A total of 230 lower respiratory tract samples (i.e., bronchial aspirates or bronchoalveolar lavages) were taken from 178 critically ill COVID-19 patients. Each sample was processed by a semi-quantitative culture and by a multiplex PCR panel (FilmArray Pneumonia Plus panel), allowing rapid detection of a wide range of clinically relevant pathogens and a limited number of antimicrobial resistance markers. More than 30% of samples showed a positive bacterial culture, with Pseudomonas aeruginosa, Klebsiella pneumoniae and Staphylococcus aureus the most detected pathogens. FilmArray showed an overall sensitivity and specificity of 89.6% and 98.3%, respectively, with a negative predictive value of 99.7%. The molecular test significantly reduced the turn-around-time (TAT) and increased the rates of microbial detection. Most cases missed by culture were characterized by low bacterial loads (104-105 copies/mL). FilmArray missed a list of pathogens not included in the molecular panel, especially Stenotrophomonas maltophilia (8 cases). FilmArray can be useful to detect bacterial pathogens in lower respiratory tract specimens of COVID-19 patients, with a significant decrease of TAT. The test is particularly useful to rule out bacterial co-infections and avoid the inappropriate prescription of antibiotics.

Recent Advances in the Evaluation of Serological Assays for the Diagnosis of SARS-CoV-2 Infection and COVID-19.

Introduction: Few data on the diagnostic performance of serological tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are currently available. We evaluated sensitivity and specificity of five different widely used commercial serological assays for the detection of SARS-CoV-2-specific IgG, IgM, and IgA antibodies using reverse transcriptase-PCR assay in nasopharyngeal swab as reference standard test. Methods: A total of 337 plasma samples collected in the period April-June 2020 from SARS-CoV-2 RT-PCR positive (n = 207) and negative (n = 130) subjects were investigated by one point-of-care lateral flow immunochromatographic assay (LFIA IgG and IgM, Technogenetics) and four fully automated assays: two chemiluminescence immunoassays (CLIA-iFlash IgG and IgM, Shenzhen YHLO Biotech and CLIA-LIAISON® XL IgG, DiaSorin), one electrochemiluminescence immunoassay (ECLIA-Elecsys® total predominant IgG, Roche), and one enzyme-linked immunosorbent assay (ELISA IgA, Euroimmune). Results: The overall sensitivity of all IgG serological assays was >80% and the specificity was >97%. The sensitivity of IgG assays was lower within 2 weeks from the onset of symptoms ranging from 70.8 to 80%. The LFIA and CLIA-iFlash IgM showed an overall low sensitivity of 47.6 and 54.6%, while the specificity was 98.5 and 96.2%, respectively. The ELISA IgA yielded a sensitivity of 84.3% and specificity of 81.7%. However, the ELISA IgA result was indeterminate in 11.7% of cases. Conclusions: IgG serological assays seem to be a reliable tool for the retrospective diagnosis of SARS-CoV-2 infection. IgM assays seem to have a low sensitivity and IgA assay is limited by a substantial rate of indeterminate results.