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A Prediction Model for Acute Respiratory Distress Syndrome in Immunocompetent Adults with Adenovirus-associated Pneumonia: a Multicenter Retrospective Analysis

Overview
Journal BMC Pulm Med
Publisher Biomed Central
Specialty Pulmonary Medicine
Date 2023 Nov 6
PMID 37932725
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Abstract

Background: In recent years, the number of human adenovirus (HAdV)-related pneumonia cases has increased in immunocompetent adults. Acute respiratory distress syndrome (ARDS) in these patients is the predominant cause of HADV-associated fatality rates. This study aimed to identify early risk factors to predict early HAdV-related ARDS.

Methods: Data from immunocompetent adults with HAdV pneumonia between June 2018 and May 2022 in ten tertiary general hospitals in central China was analyzed retrospectively. Patients were categorized into the ARDS group based on the Berlin definition. The prediction model of HAdV-related ARDS was developed using multivariate stepwise logistic regression and visualized using a nomogram.

Results: Of 102 patients with adenovirus pneumonia, 41 (40.2%) developed ARDS. Overall, most patients were male (94.1%), the median age was 38.0 years. Multivariate logistic regression showed that dyspnea, SOFA (Sequential Organ Failure Assessment) score, lactate dehydrogenase (LDH) and mechanical ventilation status were independent risk factors for this development, which has a high mortality rate (41.5%). Incorporating these factors, we established a nomogram with good concordance statistics of 0.904 (95% CI 0.844-0.963) which may help to predict early HAdV-related ARDS.

Conclusion: A nomogram with good accuracy in the early prediction of ARDS in patients with HAdV-associated pneumonia may could contribute to the early management and effective treatment of severe HAdV infection.

Citing Articles

Adenoviral Pneumonia Outbreak in Immunocompetent Adults-A Missed Antimicrobial Stewardship Opportunity?.

Gjurasin B, Stemberger Maric L, Jukic T, Radmanic Matotek L, Zidovec Lepej S, Kutlesa M Antibiotics (Basel). 2025; 14(1).

PMID: 39858309 PMC: 11760906. DOI: 10.3390/antibiotics14010023.

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