Identifying Hemodialysis Patients With the Highest Risk of Staphylococcus aureus Endogenous Infection Through a Simple Nasal Sampling Algorithm Article Swipe
Paul O. Verhoeven
,
Julie Gagnaire
,
Cyrille H. Haddar
,
Florence Grattard
,
Damien Thibaudin
,
Aïda Afiani
,
Céline Cazorla
,
Anne Carricajo
,
Christophe Mariat
,
É. Alamartine
,
F. Lucht
,
Olivier Garraud
,
Bruno Pozzetto
,
Élisabeth Botelho-Nevers
,
P. Berthelot
·
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.1097/md.0000000000003231
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.1097/md.0000000000003231
In contrast to Staphylococcus aureus intermittent nasal carriers, persistent ones have the highest risk of infection. This study reports the usefulness of a simple nasal sampling algorithm to identify the S. aureus nasal carriage state of hemodialysis patients (HPs) and their subsequent risk of infection.From a cohort of 85 HPs, 76 were screened for S. aureus nasal carriage once a week during a 10-week period. The S. aureus nasal load was quantified by using either culture on chromogenic medium or fully automated real-time polymerase chain reaction assay. Molecular typing was used to compare strains from carriage and infection.The algorithm based on quantitative cultures was able to determine the status of S. aureus nasal carriage with a sensitivity of 95.8%, a specificity of 94.2%, a positive predictive value of 88.5%, and a negative predictive value of 98.0%. Of note, the determination of the S. aureus carriage state was obtained on the first nasal sample for all the 76 HPs, but 1 (98.7%). The algorithm based on quantitative polymerase chain reaction assay directly from the specimen yielded similar performances. During the 1-year follow-up after the last sampling episode, HPs classified as persistent nasal carriers with the algorithm were found to have a higher risk of S. aureus infection than those classified as nonpersistent carriers (P < 0.05), especially for infections of endogenous origin (P < 0.001).This simple algorithm is reliable for determining the S. aureus nasal carriage status in clinical practice and could contribute to characterize at an early stage of take-up patients with the highest risk of S. aureus infection.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1097/md.0000000000003231
- OA Status
- gold
- Cited By
- 15
- References
- 20
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2341213006
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2341213006Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1097/md.0000000000003231Digital Object Identifier
- Title
-
Identifying Hemodialysis Patients With the Highest Risk of Staphylococcus aureus Endogenous Infection Through a Simple Nasal Sampling AlgorithmWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2016Year of publication
- Publication date
-
2016-04-01Full publication date if available
- Authors
-
Paul O. Verhoeven, Julie Gagnaire, Cyrille H. Haddar, Florence Grattard, Damien Thibaudin, Aïda Afiani, Céline Cazorla, Anne Carricajo, Christophe Mariat, É. Alamartine, F. Lucht, Olivier Garraud, Bruno Pozzetto, Élisabeth Botelho-Nevers, P. BerthelotList of authors in order
- Landing page
-
https://doi.org/10.1097/md.0000000000003231Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1097/md.0000000000003231Direct OA link when available
- Concepts
-
Medicine, Staphylococcus aureus, Carriage, Internal medicine, Staphylococcal infections, Nose, Polymerase chain reaction, Hemodialysis, Algorithm, Microbiology, Surgery, Pathology, Bacteria, Biology, Genetics, Biochemistry, Gene, Computer scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
15Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1, 2023: 2, 2022: 3, 2020: 2, 2019: 2Per-year citation counts (last 5 years)
- References (count)
-
20Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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