Early hemostatic responses to trauma identified with hierarchical clustering analysis

Abstract

Background: Trauma-induced coagulopathy is a complex multifactorial hemostatic response that is poorly understood.

Objectives: To identify distinct hemostatic responses to trauma and identify key components of the hemostatic system that vary between responses.

Patients/methods: A cross-sectional observational study of adult trauma patients at an urban level I trauma center emergency department was performed. Hierarchical clustering analysis was used to identify distinct clusters of similar subjects according to vital signs, injury/shock severity, and comprehensive assessment of coagulation, clot formation, platelet function, and thrombin generation.

Results: Among 84 total trauma patients included in the model, three distinct trauma clusters were identified. Cluster 1 (N = 57) showed platelet activation, preserved peak thrombin generation, plasma coagulation dysfunction, a moderately decreased fibrinogen concentration and normal clot formation relative to healthy controls. Cluster 2 (N = 18) showed platelet activation, preserved peak thrombin generation, and a preserved fibrinogen concentration with normal clot formation. Cluster 3 (N = 9) was the most severely injured and shocked, and showed a strong inflammatory and bleeding phenotype. Platelet dysfunction, thrombin inhibition, plasma coagulation dysfunction and a decreased fibrinogen concentration were present in this cluster. Fibrinolytic activation was present in all clusters, but was particularly increased in cluster 3. Trauma clusters were most noticeably different in their relative fibrinogen concentration, peak thrombin generation, and platelet-induced clot contraction.

Conclusions: Hierarchical clustering analysis identified three distinct hemostatic responses to trauma. Further insights into the underlying hemostatic mechanisms responsible for these responses are needed.

Keywords: coagulation; fibrinogen; hemostasis; platelets; thrombin; trauma.

Figure 1

Heat map and dendrogram of hierarchical clustering analysis showing the left to right clustering of individual subjects into separate clusters based upon the similar values for each test variable (A). The results of analysis using a 3-cluster (HC1-3) Ward’s method are shown (A). Selection of best hierarchical clustering model using bayesian information criterion (BIC) plotted against number of clusters (B). The Ward method produced the highest BIC with the least number of clusters and was selected over other models. Discriminant analysis canonical plot of the three-cluster Ward model (C). Good discrimination between clusters was possible with misclassification of only 4 total subjects (open circles). Clusters 1 (Red) and 2 (Blue) were more similar, while cluster 3 (Green) was clearly discriminated. Larger ellipses identify the area in which 50% of the subjects are found for each cluster. Smaller ellipses identify the 95% CI for the center point of each cluster.

Figure 2

(A) Histogram of nominal categories for injury severity, shock severity, and mortality for each cluster. There was a significantly more profound injury and hemorrhagic shock in cluster 3 vs. clusters 1 and 2. 72-hour mortality was also greatest in cluster 3, but statistical analysis comparing to other clusters was not possible due to few nonsurvivors in the other clusters. (B) Histogram of prevalence of standard hemostatic transfusion thresholds present in each cluster.**Criteria from Holcomb et al. Ann Surg 2012;256: 476–486. (C) Histogram of prevalence of subjects receiving blood products within the first 8 hours of hospitalization by cluster (N=68 total). Subjects were counted if they received any amount of specified blood product. Hemostatic transfusion was defined as receiving any amount of fresh frozen plasma, platelet concentrate, or cryoprecipitate. Chi Square LR: *P<0.05 vs. Cluster 1, † P<0.05 vs. Cluster 2.

Figure 3

Box and whisker plots of average percent changes in coagulation and thrombelastography measurements when measured at Emergency Department arrival and again at 8 hours of hospitalization. Whiskers represent 5^th and 95^th percentile. Plots that do not include zero represent statistically significant changes at alpha = 0.05.