Pneumocystis jirovecii Pneumonia Diagnostic Approach: Real-Life Experience in a Tertiary Centre.
Cristina VeintimillaAna Álvarez-UríaPablo Martín-RabadánMaricela ValerioMarina MachadoBelén PadillaRoberto AlonsoCristina DiezPatricia MuñozMercedes MarínPublished in: Journal of fungi (Basel, Switzerland) (2023)
Pneumocystis jirovecii pneumonia (PJP) in immunocompromised patients entails high mortality and requires adequate laboratory diagnosis. We compared the performance of a real time-PCR assay against the immunofluorescence assay (IFA) in the routine of a large microbiology laboratory. Different respiratory samples from HIV and non-HIV-infected patients were included. The retrospective analysis used data from September 2015 to April 2018, which included all samples for which a P. jirovecii test was requested. A total of 299 respiratory samples were tested (bronchoalveolar lavage fluid ( n = 181), tracheal aspirate ( n = 53) and sputum ( n = 65)). Forty-eight (16.1%) patients fulfilled the criteria for PJP. Five positive samples (10%) had only colonization. The PCR test was found to have a sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 96%, 98%, 90% and 99%, compared to 27%, 100%, 100% and 87%, for the IFA, respectively. PJ-PCR sensitivity and specificity were >80% and >90% for all tested respiratory samples. Median cycle threshold values in definite PJP cases were 30 versus 37 in colonized cases ( p < 0.05). Thus, the PCR assay is a robust and reliable test for the diagnosis PJP in all respiratory sample types. Ct values of ≥36 could help to exclude PJP diagnosis.
Keyphrases
- end stage renal disease
- real time pcr
- hiv infected patients
- newly diagnosed
- ejection fraction
- antiretroviral therapy
- high throughput
- prognostic factors
- peritoneal dialysis
- machine learning
- chronic kidney disease
- computed tomography
- cardiovascular disease
- hepatitis c virus
- cystic fibrosis
- risk factors
- cardiovascular events
- intensive care unit
- hiv positive
- hiv infected
- contrast enhanced
- deep learning
- coronary artery disease
- big data
- pulmonary tuberculosis
- respiratory failure
- magnetic resonance
- artificial intelligence
- image quality