Radiographic features in investigated for Pneumocystis jirovecii pneumonia: a nested case-control study.


Journal

BMC infectious diseases
ISSN: 1471-2334
Titre abrégé: BMC Infect Dis
Pays: England
ID NLM: 100968551

Informations de publication

Date de publication:
10 Jul 2020
Historique:
received: 12 09 2019
accepted: 02 07 2020
entrez: 12 7 2020
pubmed: 12 7 2020
medline: 9 9 2020
Statut: epublish

Résumé

Pneumocystis jirovecii pneumonia (PJP) can be challenging to diagnose, often requiring bronchoscopy. Since most patients suspected of PJP undergo imaging, we hypothesized that the findings of these studies could help estimate the probability of disease prior to invasive testing. We created a cohort of patients who underwent bronchoscopy specifically to diagnose PJP and conducted a nested case-control study to compare the radiographic features between patients with (n = 72) and without (n = 288) pathologically proven PJP. We used multivariable logistic regression to identify radiographic features independently associated with PJP. Chest x-ray findings poorly predicted the diagnosis of PJP. However, multivariable analysis of CT scan findings found that "increased interstitial markings" (OR 4.3; 95%CI 2.2-8.2), "ground glass opacities" (OR 3.3; 95%CI 1.2-9.1) and the radiologist's impression of PJP being "possible" (OR 2.0; 95%CI 1.0-4.1) or "likely" (OR 9.3; 95%CI 3.4-25.3) were independently associated with the final diagnosis (c-statistic 0.75). Where there is clinical suspicion of PJP, the use of CT scan can help determine the probability of PJP. Identifying patients at low risk of PJP may enable better use of non-invasive testing to avoid bronchoscopy while higher probability patients could be prioritized.

Sections du résumé

BACKGROUND BACKGROUND
Pneumocystis jirovecii pneumonia (PJP) can be challenging to diagnose, often requiring bronchoscopy. Since most patients suspected of PJP undergo imaging, we hypothesized that the findings of these studies could help estimate the probability of disease prior to invasive testing.
METHODS METHODS
We created a cohort of patients who underwent bronchoscopy specifically to diagnose PJP and conducted a nested case-control study to compare the radiographic features between patients with (n = 72) and without (n = 288) pathologically proven PJP. We used multivariable logistic regression to identify radiographic features independently associated with PJP.
RESULTS RESULTS
Chest x-ray findings poorly predicted the diagnosis of PJP. However, multivariable analysis of CT scan findings found that "increased interstitial markings" (OR 4.3; 95%CI 2.2-8.2), "ground glass opacities" (OR 3.3; 95%CI 1.2-9.1) and the radiologist's impression of PJP being "possible" (OR 2.0; 95%CI 1.0-4.1) or "likely" (OR 9.3; 95%CI 3.4-25.3) were independently associated with the final diagnosis (c-statistic 0.75).
CONCLUSIONS CONCLUSIONS
Where there is clinical suspicion of PJP, the use of CT scan can help determine the probability of PJP. Identifying patients at low risk of PJP may enable better use of non-invasive testing to avoid bronchoscopy while higher probability patients could be prioritized.

Identifiants

pubmed: 32650730
doi: 10.1186/s12879-020-05217-x
pii: 10.1186/s12879-020-05217-x
pmc: PMC7350625
doi:

Types de publication

Controlled Clinical Trial Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

492

Subventions

Organisme : Faculty of Medicine, McGill University
ID : Student Bursary
Organisme : Faculty of Medicine, McGill University
ID : Student Bursary

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Auteurs

Jimmy M Hsu (JM)

Faculty of Medicine, McGill University, Montreal, Canada.

Aaron Hass (A)

Faculty of Medicine, McGill University, Montreal, Canada.

Marc-Alexandre Gingras (MA)

Department of Medicine, McGill University, Montreal, Canada.

Jaron Chong (J)

Department of Radiology, McGill University, Montreal, Canada.

Cecilia Costiniuk (C)

Department of Medicine, McGill University, Montreal, Canada.
Clinical Practice Assessment Unit, McGill University Health Centre, Montreal, Canada.
McGill Interdisciplinary Initiative in Infection and Immunity, Montreal, Canada.

Nicole Ezer (N)

Department of Medicine, McGill University, Montreal, Canada.

Richard S Fraser (RS)

Department of Pathology, McGill University, Montreal, Canada.

Emily G McDonald (EG)

Department of Medicine, McGill University, Montreal, Canada.
Clinical Practice Assessment Unit, McGill University Health Centre, Montreal, Canada.
McGill Interdisciplinary Initiative in Infection and Immunity, Montreal, Canada.

Todd C Lee (TC)

Department of Medicine, McGill University, Montreal, Canada. todd.lee@mcgill.ca.
Clinical Practice Assessment Unit, McGill University Health Centre, Montreal, Canada. todd.lee@mcgill.ca.
McGill Interdisciplinary Initiative in Infection and Immunity, Montreal, Canada. todd.lee@mcgill.ca.
McGill University Health Centre / Royal Victoria Hospital, McGill University, 1001 Décarie Blvd, E5.1820, Montreal, QC, H4A 3J1, Canada. todd.lee@mcgill.ca.

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Classifications MeSH