Effect of Aging and Sex on Clot Formation, Structure, and Lysis in Trauma Patients
Bibliographic record
Abstract
BACKGROUND: The dynamics of blood clotting are influenced by age and sex, potentially impacting treatment outcomes and susceptibility to complications in trauma patients. This study aimed to identify how age and sex impact clot formation and resolution kinetics, and network structure in trauma patients, exploring their potential implications for personalized treatment strategies. STUDY DESIGN: Trauma patients meeting the highest level of trauma designation had plasma isolated after emergency department admission before any resuscitative fluid administration. Thrombin generation kinetics, rheological clot mechanics, fibrin network properties, and optical density were measured in patient plasma. RESULTS: Sixty-three patients were included in this study. The majority (76%) were male, and the age range was 18 to 87 years, with a median age of 38 years. Older patients had increased mortality at a similar Injury Severity Score as compared with younger patients while exhibiting greater clot stiffness and increased time to thrombin generation. Increasing patient age was associated with increased thrombin lag time, time to peak thrombin, and fibrinogen-normalized stiffness. Male and female patients had similar mortality rates and Injury Severity Scores but exhibited significant differences in clot stiffness and lysis with aging. CONCLUSIONS: This study suggests that aging in trauma patients correlates with a prolonged clot formation rate despite the presence of stiffer clots and reduced fibrinolysis in older men. Our findings highlight the importance of age and sex when developing resuscitation protocols and tailoring treatment strategies for acute traumatic coagulopathy in trauma patients. Further research is needed to effectively develop and implement such protocols to optimize clinical outcomes in this patient population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".