Identification and validation of robust hospital-acquired pneumonia subphenotypes associated with all-cause mortality: a multi-cohort derivation and validation
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| Title: | Identification and validation of robust hospital-acquired pneumonia subphenotypes associated with all-cause mortality: a multi-cohort derivation and validation |
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| Authors: | Martin, Florian Pierre, Poulain, Cécile, Mulier, Jelle Haitsma, Motos, Ana, Gourain, Victor, Ogan, Ismaël, Montassier, Emmanuel, Launey, Yoann, Lasocki, Sigismond, Cinotti, Raphaël, Dahyot-Fizelier, Claire, Ranzani, Otavio, Reyes, Luis Felipe, Martin-Loeches, Ignacio, Derde, Lennie, Torres, Antoni, Cremer, Olaf, Roquilly, Antoine |
| Contributors: | Centre de Recherche en Transplantation et Immunologie - Center for Research in Transplantation and Translational Immunology (U1064 Inserm - CR2TI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Nantes Université - UFR de Médecine et des Techniques Médicales (Nantes Univ - UFR MEDECINE), Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), Service d'anesthésie et réanimation chirurgicale Nantes, Hôtel-Dieu-Centre Hospitalier Universitaire de Nantes = Nantes University Hospital (CHU Nantes), Julius Center for Health Sciences and Primary Care Utrecht, University Medical Center Utrecht (UMCU), Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Universitat de Barcelona (UB), Service des Urgences CHU Nantes, Hôtel-Dieu de Nantes, Service d'Anesthésie Réanimation Rennes, Centre Hospitalier Universitaire de Rennes CHU Rennes = Rennes University Hospital Pontchaillou, Centre Hospitalier Universitaire d'Angers (CHU Angers), methodS in Patients-centered outcomes and HEalth ResEarch (SPHERE), Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Nantes Université - UFR des Sciences Pharmaceutiques et Biologiques (Nantes Univ - UFR Pharmacie), Pharmacologie des anti-infectieux et antibiorésistance U 1070 (PHAR2 Poitiers ), Université de Poitiers = University of Poitiers (UP)-Institut National de la Santé et de la Recherche Médicale (INSERM), Instituto de Salud Global - Institute For Global Health Barcelona (ISGlobal), Institut de Recerca Sant Pau Barcelona = Institut de Recerca de L’hospital de La Santa Creu i de Sant Pau Barcelona = Sant Pau Institute for Biomedical Research Barcelona (IR Sant Pau / IIBSP / IIBSP-CERCA), Universidad de La Sabana Chía, Cundinamarca, Colombia = La Sabana University Chía, Cundinamarca, Colombia (Unisabana), University of Oxford, St. James's Hospital Dublin = Ospidéal San Séamas (Ospidéal Naomh Séamas) Baile Átha Cliath (SJH), European Project: 847782,H2020-SC1-BHC-2018-2020,H2020-SC1-2019-Two-Stage-RTD,HAP2(2020) |
| Source: | ISSN: 0342-4642. |
| Publisher Information: | CCSD Springer Verlag |
| Publication Year: | 2025 |
| Collection: | Université de Poitiers: Publications de nos chercheurs.ses (HAL) |
| Subject Terms: | Antimicrobial therapy, Hospital-acquired pneumonia, Lung microbiome, Machine learning, Mortality, Subphenotype, MESH: Aged, MESH: Anti-Bacterial Agents / therapeutic use, MESH: Machine Learning, MESH: Male, MESH: Middle Aged, MESH: Netherlands / epidemiology, MESH: Phenotype, MESH: Prognosis, MESH: Cohort Studies, MESH: Critical Illness / mortality, MESH: Female, MESH: France / epidemiology, MESH: Healthcare-Associated Pneumonia* / classification, MESH: Healthcare-Associated Pneumonia* / drug therapy, MESH: Healthcare-Associated Pneumonia* / mortality, MESH: Humans, [SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML] |
| Description: | International audience ; Purpose: Despite optimal antimicrobial therapy, the treatment failure rate of hospital-acquired pneumonia (HAP) routinely reaches 40% in critically ill patients. Subphenotypes have been identified within sepsis and acute respiratory distress syndrome with important predictive and possibly therapeutic implications. We derived prognosis subphenotypes for HAP and explored whether they were associated with biological markers and response to treatment. Methods: We separately analysed data from four cohorts of critically ill patients in France (PNEUMOCARE, n=511, ATLANREA, n=401), Netherlands (MARS, n=1351) and Europe-South America (ENIRRI, n=900) to investigate HAP heterogeneity using unsupervised clustering based on clinical and routine biological variables available at HAP diagnosis. Then, we developed a machine learning-based workflow to create a simplified classification model using discovery datasets. This model was validated by applying it to an independent replication dataset from an international randomized clinical trial comparing linezolid and tedizolid for the treatment of HAP (VITAL, n=726 patients). The primary outcome was the association of subphenotypes with 28-day all-cause mortality. Secondary analyses included subphenotype associations with treatment failure at test-of-cure, respiratory microbiome and cytokine profiles in the ATLANREA subgroup, and treatment response in the VITAL trial. Results: We tested twelve metrics and determined that a two-cluster model best fits all cohorts. HAP subphenotype 2 had greater disease severity, lower body temperature, and worse PaO2/FiO2 ratio than subphenotype 1 patients. Although the prevalence of subphenotype 2 ranged from 26.9% to 66.9% across the four derivation cohorts, the rates of 28-day mortality and treatment failure at test-of-cure were consistently higher to subphenotype 1 (p<0.01 for all comparisons). Subphenotype 2 was associated with greater respiratory microbiome dysbiosis and higher levels of proinflammatory cytokines ... |
| Document Type: | article in journal/newspaper |
| Language: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/pmid/40261385; info:eu-repo/grantAgreement//847782/EU/Host-targeted Approaches for the Prevention and the treatment of Hospital-Acquired Pneumonia/HAP2; PUBMED: 40261385 |
| DOI: | 10.1007/s00134-025-07884-3 |
| Availability: | https://hal.science/hal-05248288 https://hal.science/hal-05248288v1/document https://hal.science/hal-05248288v1/file/PHOENYCS_manuscript.pdf https://doi.org/10.1007/s00134-025-07884-3 |
| Rights: | info:eu-repo/semantics/OpenAccess |
| Accession Number: | edsbas.EEE44CD7 |
| Database: | BASE |
Nájsť tento článok vo Web of Science | Abstract: | International audience ; Purpose: Despite optimal antimicrobial therapy, the treatment failure rate of hospital-acquired pneumonia (HAP) routinely reaches 40% in critically ill patients. Subphenotypes have been identified within sepsis and acute respiratory distress syndrome with important predictive and possibly therapeutic implications. We derived prognosis subphenotypes for HAP and explored whether they were associated with biological markers and response to treatment. Methods: We separately analysed data from four cohorts of critically ill patients in France (PNEUMOCARE, n=511, ATLANREA, n=401), Netherlands (MARS, n=1351) and Europe-South America (ENIRRI, n=900) to investigate HAP heterogeneity using unsupervised clustering based on clinical and routine biological variables available at HAP diagnosis. Then, we developed a machine learning-based workflow to create a simplified classification model using discovery datasets. This model was validated by applying it to an independent replication dataset from an international randomized clinical trial comparing linezolid and tedizolid for the treatment of HAP (VITAL, n=726 patients). The primary outcome was the association of subphenotypes with 28-day all-cause mortality. Secondary analyses included subphenotype associations with treatment failure at test-of-cure, respiratory microbiome and cytokine profiles in the ATLANREA subgroup, and treatment response in the VITAL trial. Results: We tested twelve metrics and determined that a two-cluster model best fits all cohorts. HAP subphenotype 2 had greater disease severity, lower body temperature, and worse PaO2/FiO2 ratio than subphenotype 1 patients. Although the prevalence of subphenotype 2 ranged from 26.9% to 66.9% across the four derivation cohorts, the rates of 28-day mortality and treatment failure at test-of-cure were consistently higher to subphenotype 1 (p<0.01 for all comparisons). Subphenotype 2 was associated with greater respiratory microbiome dysbiosis and higher levels of proinflammatory cytokines ... |
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| DOI: | 10.1007/s00134-025-07884-3 |