Ventilator-associated pneumonia (VAP) is a common and serious infection in patients receiving mechanical ventilation in intensive care units. Current diagnostic methods are imprecise, leading to unnecessary antibiotic use and delayed treatment. The ClusterVAP study aims to identify biologically and clinically distinct subgroups of patients with suspected VAP by analyzing proteins in bronchoalveolar lavage (BAL) fluid using advanced proteomic techniques. This multicentre observational study will enroll approximately 400 adult patients from intensive care units in Sweden, France, Portugal, Denmark, and the United Kingdom. BAL or mini-BAL samples collected for clinical reasons will be analyzed to define "pneumoclusters" and explore their association with patient outcomes. The study will also identify candidate biomarkers that could support future diagnostic tools. No experimental treatments are given; all patients receive standard care. Results may improve diagnostic accuracy and guide personalized treatment strategies for critically ill patients.
ClusterVAP is an exploratory, observational, prospective, multicentre cross-sectional study designed to identify biologically and clinically distinct subgroups ("pneumoclusters") among patients with suspected ventilator-associated pneumonia (VAP). The study will enroll approximately 400 adult patients admitted to intensive care units in Sweden, France, Portugal, Denmark, and the United Kingdom who are receiving mechanical ventilation and undergo bronchoalveolar lavage (BAL) or mini-BAL for clinical reasons. Residual BAL supernatant will be processed for proteomic analysis using liquid chromatography tandem mass spectrometry (LC-MS/MS). Unsupervised consensus clustering will be applied to proteomic data, alone and in combination with clinical and microbiological variables, to define pneumoclusters. These clusters will be characterized by clinical features, microbiology, and radiology, and compared for 30-day outcomes including mortality, ventilator-free days, antibiotic-free days, ICU-free days, and hospital-free days. Differential protein abundance analysis will be used to identify candidate biomarkers for pragmatic cluster assignment. Data will be collected in electronic case report forms hosted in REDCap, with built-in quality checks. All data will be pseudonymized, and biological samples will be stored under controlled conditions for up to ten years for confirmatory analyses. No experimental interventions are administered; all patients receive standard care. The study has been approved by the Swedish Ethical Review Authority (Dnr 2025-04564-01) and equivalent bodies in participating countries. Results will be disseminated through peer-reviewed publications and scientific conferences, with statistical code shared for transparency.
Study Type
OBSERVATIONAL
Enrollment
400
Distribution of patients into biologically distinct clusters ("pneumoclusters") based on BAL proteomic data
Unsupervised consensus clustering of bronchoalveolar lavage (BAL) proteomic profiles, alone and in combination with clinical and microbiological variables, will be performed to classify patients with suspected ventilator-associated pneumonia into biologically distinct clusters ("pneumoclusters"). The number of clusters, the number of patients per cluster, and key distinguishing features will be reported.
Time frame: Day 0 (at enrolment)
30-day all-cause mortality
Mortality status compared across identified clusters.
Time frame: 30 days after enrolment
Ventilator-free days
Number of days alive and free from invasive mechanical ventilation.
Time frame: 30 days after enrolment
Antibiotic-free days
Number of days alive and not receiving systemic antibiotics.
Time frame: 30 days after enrolment
ICU-free days
Number of days alive and not in an intensive care unit.
Time frame: 30 days after enrolment
Hospital-free days
Number of days alive and not hospitalized.
Time frame: 30 days after enrolment
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