Evidence map›Paper›PMID 41361729›Full record

ArticleInfectious diseases and therapy2026

Chest Computed Tomography Patterns Associated with Severity in Adults with Respiratory Syncytial Virus Infection: A Retrospective Cohort Study.

Marie Le Goff, Youssef Zaarour, Giovanna Melica, Pierre Bay, Slim Fourati, Nicolas de Prost

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In one paragraph

Article in Infectious diseases and therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Marie Le GoffService de Médecine Intensive Réanimation, Hôpitaux Universitaires Henri Mondor, Assistance Publique-Hôpitaux de Paris, Créteil Cedex, France. marie.legoff@aphp.fr.ORCID http://orcid.org/0009-0001-9991-8369
Youssef ZaarourDépartement d'imagerie médicale, Hôpitaux Universitaires Henri Mondor, Assistance Publique-Hôpitaux de Paris, Créteil Cedex, France.
Giovanna MelicaService d'immunologie clinique et Maladies infectieuses, Hôpitaux Universitaires Henri Mondor, Créteil, France.
Pierre BayService de Médecine Intensive Réanimation, Hôpitaux Universitaires Henri Mondor, Assistance Publique-Hôpitaux de Paris, Créteil Cedex, France.
Slim FouratiDepartment of Virology, Hôpitaux Universitaires Henri Mondor, Assistance Publique-Hôpitaux de Paris, Créteil, France.
Nicolas de ProstService de Médecine Intensive Réanimation, Hôpitaux Universitaires Henri Mondor, Assistance Publique-Hôpitaux de Paris, Créteil Cedex, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThere are limited data available on the relationship between chest computed tomography (CT) patterns and clinical severity in adult patients infected with respiratory syncytial virus (RSV). It was hypothesized that specific CT patterns would be associated with distinct clinical outcomes and would correlate with both immune status and viral load.

methodsWe conducted a retrospective, single-center study of adults aged ≥ 18 years with laboratory-confirmed RSV infection and chest CT performed within 7 days of diagnosis. A blinded radiologist reviewed the CT patterns and scored them using the Chest CT Score (CCTS). Clinical severity was defined as World Health Organization (WHO) clinical progression scale ≥ 5 (hospitalized patients requiring oxygen). Multivariable logistic regression was used to identify independent associations between CT features and disease severity.

resultsA total of 113 patients (median age 72 years; 41.6% male) were included from January 2019 to March 2025, of whom 31.9% were immunocompromised. The median CCTS was 6 [25th-75th quartiles, 3-10], with consolidations (55.8%), micronodules (46.0%), mucoid impaction (73.5%), and bronchial wall thickening (65.5%) being the most common chest CT findings. Patients with severe infection (n = 66) had a higher CCTS (7 versus 4; p < 0.001) and were more likely to exhibit consolidations and emphysema. On multivariable analysis, CCTS > 6 (adjusted odds ratio (aOR) 3.66, 95% CI 1.63-8.62), consolidations (aOR 2.87, 95% CI 1.23-6.83), and emphysema (aOR 5.66, 95% CI 1.36-39.15) were independently associated with clinical severity. No significant differences in CT patterns were observed according to immune status, the presence of bacterial co-infection, or elevated versus reduced viral loads.

conclusionHigher CCTS, consolidations, and emphysema were found to be independently associated with clinical severity in adults with RSV infection. Standardized CT scoring could help with risk stratification, but this would need to be validated in a prospective study.

Indexed as

Adult patientsClinical severityRespiratory syncytial virusThoracic imagingTomodensitometry

Identifiers

PMID41361729
PMCPMC12783463

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.