Yannik Kalbas (Zurich / CH), Felix Karl-Ludwig Klingebiel (Zurich / CH), Michel Paul Johan Teuben (Zurich / CH), Sascha Halvachizadeh (Zurich / CH), Kai Oliver Jensen (Zurich / CH), Valentin Neuhaus (Zurich / CH), Roman Pfeifer (Zurich / CH), Paolo Cinelli (Zurich / CH), Hans-Christoph Pape (Zurich / CH)
Purpose: Recent advances in analytic technology allow for characterization of lipid profile dynamics on a molecular level. The aim of this study was to characterize lipid profile dynamics in a cohort of polytrauma patients.
Methods: Lipidomic analysis was performed on samples from a polytrauma biobank. Patients were included upon arrival at the trauma bay and venous sampling was performed at 6 timepoints (Arrival, 8h, 24h, 48h, 5d and 10d). Inclusion criteria were an ISS > 25, survival > 24h and an age > 18 years. Plasma samples were analyzed using liquid chromatography mass spectrometry (LC-MS). Lipid profiles were characterized using bioinformatic approaches and dimensionality reduction. Linear mixed models were programmed to analyze lipid class dynamics over time. Lipid profile dynamics were collated with clinical data (demographics, injury characteristics, outcomes and laboratory markers).
Results: 85 subjects with a total of 440 samples were analyzed to account for the optimal batch size for LC-MS. Mean ISS was 31.7 and mean NISS 38.4. Overall, 633 individual lipids were identified. Principle component analysis (PCA) revealed clustering of lipids with similar molecular characteristics, thus lipids were organized into 19 functional subgroups (classes). K-means clustering based on lipid profile revealed 2 specific patient groups, which differed in injury pattern and - severity. In more severely injured patients, we detected a significant decrease of the majority of lipid classes over the early timepoints (0-48h). Restoration of lipid levels at 24h was indicative of clinical outcome: Levels of "AcCa", "LPC" and "HEX" were highly predictive of major complications.
Conclusion: The early lipid profile in polytraumatized patients aligns with injury pattern and severity while the dynamic over time can predict complications. AcCa as a marker of mitochondrial damage seems to be a promising clinical marker for point of care resuscitation.
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