Platelet lipidome alterations in septic shock: a matched case-control study
Bibliographic record
Abstract
Background: Platelets play a central role in hemostatic and inflammatory responses during septic shock, with lipids being essential for their function. However, the specific lipidomic alterations occurring in platelets during septic shock remain poorly understood. Objectives: This study aimed to characterize platelet lipidomic changes in septic shock and investigate their associations with disease severity. Methods: In this matched case-control study, platelets were isolated from 49 septic shock patients and 47 nonseptic controls (matched for age, gender, and comorbidities). Lipidomic profiling was performed using untargeted lipidomics to identify significant alterations in the platelet lipidome. Associations among lipid changes, clinical data, and plasma biomarkers of coagulopathy and inflammation were explored. Results: More than 60% of the annotated platelet lipids were significantly altered in septic shock. Cholesteryl esters, sphingomyelins, lysophosphatidylcholines, and ether-lipids were significantly reduced, while ceramide levels increased. Fatty acyl chain remodeling displayed distinct patterns, with polyunsaturated fatty acids increasing in triacylglycerols and decreasing in phospholipids. Lipid alterations were strongly associated with thrombocytopenia, and lysophosphatidylcholine levels inversely correlated with disease severity, as indicated by the Sequential Organ Failure Assessment score. Conclusions: Septic shock induces significant disruptions in the platelet lipidome, with the extent of these alterations correlating with sepsis-associated thrombocytopenia severity. The observed changes affect multiple lipid classes, surpassing those reported under physiological conditions or in other diseases. These findings highlight the impact of sepsis-driven dysregulated inflammation and coagulopathy on platelet lipid composition, providing new insights into sepsis pathophysiology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".