Autor: |
Laure Calvet, Virginie Lemiale, Djamel Mokart, Schellongowski Peter, Pickkers Peter, Alexande Demoule, Sangeeta Mehta, Achille Kouatchet, Jordi Rello, Philippe Bauer, Ignacio Martin-Loeches, Amelie Seguin, Victoria Metaxa, Magali Bisbal, Elie Azoulay, Michael Darmon |
Jazyk: |
angličtina |
Rok vydání: |
2024 |
Předmět: |
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Zdroj: |
Annals of Intensive Care, Vol 14, Iss 1, Pp 1-9 (2024) |
Druh dokumentu: |
article |
ISSN: |
2110-5820 |
DOI: |
10.1186/s13613-024-01337-8 |
Popis: |
Abstract Background The accuracy of a diagnostic test depends on its intrinsic characteristics and the disease incidence. This study aims to depict post-test probability of Pneumocystis pneumonia (PJP), according to results of PCR and Beta-D-Glucan (BDG) tests in patients with acute respiratory failure (ARF). Materials and methods Diagnostic performance of PCR and BDG was extracted from literature. Incidence of Pneumocystis pneumonia was assessed in a dataset of 2243 non-HIV immunocompromised patients with ARF. Incidence of Pneumocystis pneumonia was simulated assuming a normal distribution in 5000 random incidence samples. Post-test probability was assessed using Bayes theorem. Results Incidence of PJP in non-HIV ARF patients was 4.1% (95%CI 3.3-5). Supervised classification identified 4 subgroups of interest with incidence ranging from 2.0% (No ground glass opacities; 95%CI 1.4–2.8) to 20.2% (hematopoietic cell transplantation, ground glass opacities and no PJP prophylaxis; 95%CI 14.1–27.7). In the overall population, positive post-test probability was 32.9% (95%CI 31.1–34.8) and 22.8% (95%CI 21.5–24.3) for PCR and BDG, respectively. Negative post-test probability of being infected was 0.10% (95%CI 0.09–0.11) and 0.23% (95%CI 0.21–0.25) for PCR and BDG, respectively. In the highest risk subgroup, positive predictive value was 74.5% (95%CI 72.0-76.7) and 63.8% (95%CI 60.8–65.8) for PCR and BDG, respectively. Conclusion Although both tests yield a high intrinsic performance, the low incidence of PJP in this cohort resulted in a low positive post-test probability. We propose a method to illustrate pre and post-test probability relationship that may improve clinician perception of diagnostic test performance according to disease incidence in predefined clinical settings. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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