Clinical and biological clusters of sepsis patients using hierarchical clustering.
<h4>Background</h4>Heterogeneity in sepsis expression is multidimensional, including highly disparate data such as the underlying disorders, infection source, causative micro-organismsand organ failures. The aim of the study is to identify clusters of patients based on clinical and biolo...
Guardado en:
| Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Public Library of Science (PLoS)
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/c8ddec62c3b44ff7a9a8d0e7e6c459c9 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| id |
oai:doaj.org-article:c8ddec62c3b44ff7a9a8d0e7e6c459c9 |
|---|---|
| record_format |
dspace |
| spelling |
oai:doaj.org-article:c8ddec62c3b44ff7a9a8d0e7e6c459c92021-12-02T20:18:48ZClinical and biological clusters of sepsis patients using hierarchical clustering.1932-620310.1371/journal.pone.0252793https://doaj.org/article/c8ddec62c3b44ff7a9a8d0e7e6c459c92021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0252793https://doaj.org/toc/1932-6203<h4>Background</h4>Heterogeneity in sepsis expression is multidimensional, including highly disparate data such as the underlying disorders, infection source, causative micro-organismsand organ failures. The aim of the study is to identify clusters of patients based on clinical and biological characteristic available at patients' admission.<h4>Methods</h4>All patients included in a national prospective multicenter ICU cohort OUTCOMEREA and admitted for sepsis or septic shock (Sepsis 3.0 definition) were retrospectively analyzed. A hierarchical clustering was performed in a training set of patients to build clusters based on a comprehensive set of clinical and biological characteristics available at ICU admission. Clusters were described, and the 28-day, 90-day, and one-year mortality were compared with log-rank rates. Risks of mortality were also compared after adjustment on SOFA score and year of ICU admission.<h4>Results</h4>Of the 6,046 patients with sepsis in the cohort, 4,050 (67%) were randomly allocated to the training set. Six distinct clusters were identified: young patients without any comorbidities, admitted in ICU for community-acquired pneumonia (n = 1,603 (40%)); young patients without any comorbidities, admitted in ICU for meningitis or encephalitis (n = 149 (4%)); elderly patients with COPD, admitted in ICU for bronchial infection with few organ failures (n = 243 (6%)); elderly patients, with several comorbidities and organ failures (n = 1,094 (27%)); patients admitted after surgery, with a nosocomial infection (n = 623 (15%)); young patients with immunosuppressive conditions (e.g., AIDS, chronic steroid therapy or hematological malignancy) (n = 338 (8%)). Clusters differed significantly in early or late mortality (p < .001), even after adjustment on severity of organ dysfunctions (SOFA) and year of ICU admission.<h4>Conclusions</h4>Clinical and biological features commonly available at ICU admission of patients with sepsis or septic shock enabled to set up six clusters of patients, with very distinct outcomes. Considering these clusters may improve the care management and the homogeneity of patients in future studies.Grégory PapinSébastien BaillyClaire DupuisStéphane RucklyMarc GainnierLaurent ArgaudElie AzoulayChristophe AdrieBertrand SouweineDany Goldgran-ToledanoGuillaume MarcotteAntoine GrosJean ReignierBruno MourvillierJean-Marie ForelRomain SonnevilleAnne-Sylvie DumenilMichael DarmonMaité Garrouste-OrgeasCarole SchwebelJean-François TimsitOUTCOMEREA study groupPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0252793 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Medicine R Science Q |
| spellingShingle |
Medicine R Science Q Grégory Papin Sébastien Bailly Claire Dupuis Stéphane Ruckly Marc Gainnier Laurent Argaud Elie Azoulay Christophe Adrie Bertrand Souweine Dany Goldgran-Toledano Guillaume Marcotte Antoine Gros Jean Reignier Bruno Mourvillier Jean-Marie Forel Romain Sonneville Anne-Sylvie Dumenil Michael Darmon Maité Garrouste-Orgeas Carole Schwebel Jean-François Timsit OUTCOMEREA study group Clinical and biological clusters of sepsis patients using hierarchical clustering. |
| description |
<h4>Background</h4>Heterogeneity in sepsis expression is multidimensional, including highly disparate data such as the underlying disorders, infection source, causative micro-organismsand organ failures. The aim of the study is to identify clusters of patients based on clinical and biological characteristic available at patients' admission.<h4>Methods</h4>All patients included in a national prospective multicenter ICU cohort OUTCOMEREA and admitted for sepsis or septic shock (Sepsis 3.0 definition) were retrospectively analyzed. A hierarchical clustering was performed in a training set of patients to build clusters based on a comprehensive set of clinical and biological characteristics available at ICU admission. Clusters were described, and the 28-day, 90-day, and one-year mortality were compared with log-rank rates. Risks of mortality were also compared after adjustment on SOFA score and year of ICU admission.<h4>Results</h4>Of the 6,046 patients with sepsis in the cohort, 4,050 (67%) were randomly allocated to the training set. Six distinct clusters were identified: young patients without any comorbidities, admitted in ICU for community-acquired pneumonia (n = 1,603 (40%)); young patients without any comorbidities, admitted in ICU for meningitis or encephalitis (n = 149 (4%)); elderly patients with COPD, admitted in ICU for bronchial infection with few organ failures (n = 243 (6%)); elderly patients, with several comorbidities and organ failures (n = 1,094 (27%)); patients admitted after surgery, with a nosocomial infection (n = 623 (15%)); young patients with immunosuppressive conditions (e.g., AIDS, chronic steroid therapy or hematological malignancy) (n = 338 (8%)). Clusters differed significantly in early or late mortality (p < .001), even after adjustment on severity of organ dysfunctions (SOFA) and year of ICU admission.<h4>Conclusions</h4>Clinical and biological features commonly available at ICU admission of patients with sepsis or septic shock enabled to set up six clusters of patients, with very distinct outcomes. Considering these clusters may improve the care management and the homogeneity of patients in future studies. |
| format |
article |
| author |
Grégory Papin Sébastien Bailly Claire Dupuis Stéphane Ruckly Marc Gainnier Laurent Argaud Elie Azoulay Christophe Adrie Bertrand Souweine Dany Goldgran-Toledano Guillaume Marcotte Antoine Gros Jean Reignier Bruno Mourvillier Jean-Marie Forel Romain Sonneville Anne-Sylvie Dumenil Michael Darmon Maité Garrouste-Orgeas Carole Schwebel Jean-François Timsit OUTCOMEREA study group |
| author_facet |
Grégory Papin Sébastien Bailly Claire Dupuis Stéphane Ruckly Marc Gainnier Laurent Argaud Elie Azoulay Christophe Adrie Bertrand Souweine Dany Goldgran-Toledano Guillaume Marcotte Antoine Gros Jean Reignier Bruno Mourvillier Jean-Marie Forel Romain Sonneville Anne-Sylvie Dumenil Michael Darmon Maité Garrouste-Orgeas Carole Schwebel Jean-François Timsit OUTCOMEREA study group |
| author_sort |
Grégory Papin |
| title |
Clinical and biological clusters of sepsis patients using hierarchical clustering. |
| title_short |
Clinical and biological clusters of sepsis patients using hierarchical clustering. |
| title_full |
Clinical and biological clusters of sepsis patients using hierarchical clustering. |
| title_fullStr |
Clinical and biological clusters of sepsis patients using hierarchical clustering. |
| title_full_unstemmed |
Clinical and biological clusters of sepsis patients using hierarchical clustering. |
| title_sort |
clinical and biological clusters of sepsis patients using hierarchical clustering. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2021 |
| url |
https://doaj.org/article/c8ddec62c3b44ff7a9a8d0e7e6c459c9 |
| work_keys_str_mv |
AT gregorypapin clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT sebastienbailly clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT clairedupuis clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT stephaneruckly clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT marcgainnier clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT laurentargaud clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT elieazoulay clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT christopheadrie clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT bertrandsouweine clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT danygoldgrantoledano clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT guillaumemarcotte clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT antoinegros clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT jeanreignier clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT brunomourvillier clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT jeanmarieforel clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT romainsonneville clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT annesylviedumenil clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT michaeldarmon clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT maitegarrousteorgeas clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT caroleschwebel clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT jeanfrancoistimsit clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering AT outcomereastudygroup clinicalandbiologicalclustersofsepsispatientsusinghierarchicalclustering |
| _version_ |
1718374251203919872 |