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Interpretation of results of PCR and B-D-glucan for the diagnosis of Pneumocystis Jirovecii Pneumonia in immunocompromised adults with acute respiratory failure

  • 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

摘要

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.