Development and validation of the tic score for early detection of traumatic coagulopathy upon hospital admission: a cohort study

Abstract

Background: Critically injured patients need rapid and appropriate hemostatic treatment, which requires prompt identification of trauma-induced coagulopathy (TIC) upon hospital admission. We developed and validated the performance of a clinical score based on prehospital resuscitation parameters and vital signs at hospital admission for early diagnosis of TIC.

Methods: The score was derived from a level-1 trauma center registry (training set). It was then validated on data from two other level-1 trauma centers: first on a trauma registry (retrospective validation set), and then on a prospective cohort (prospective validation set). TIC was defined as a PT_ratio > 1.2 at hospital admission. Prehospital (vital signs and resuscitation care) and admission data (vital signs and laboratory parameters) were collected. We considered parameters independently associated with TIC in the score (binomial logistic regression). We estimated the score's performance for the prediction of TIC.

Results: A total of 3489 patients were included, and among these a TIC was observed in 22% (95% CI 21-24%) of cases. Five criteria were identified and included in the TIC Score: Glasgow coma scale < 9, Shock Index > 0.9, hemoglobin < 11 g.dL^-1, prehospital fluid volume > 1000 ml, and prehospital use of norepinephrine (yes/no). The score, ranging from 0 and 9 points, had good performance for the identification of TIC (AUC: 0.82, 95% CI: 0.81-0.84) without differences between the three sets used. A score value < 2 had a negative predictive value of 93% and was selected to rule-out TIC. Conversely, a score value ≥ 6 had a positive predictive value of 92% and was selected to indicate TIC.

Conclusion: The TIC Score is quick and easy to calculate and can accurately identify patients with TIC upon hospital admission.

Keywords: Blood products; Coagulopathy; Prediction; Prehospital; Score; Trauma.

Fig. 1

Flowchart of the study. Exclusion criteria: Patients < 18 years old, receiving anticoagulant therapy, prehospital administration of fresh frozen plasma/fibrinogen concentrate

Fig. 2

TIC Score receiving operating curve and calibration plot for predicting PT_ratio > 1.2, by dataset and overall. Panel A: ROC curve. Plot of the TIC Score sensitivity by specificity for predicting PT_ratio > 1.2, by dataset; Panel B: Calibration Plot. Plot of observed probabilities by the probabilities predicted by the TIC Score for observing a PT_ratio > 1.2, and dataset. Lines are smoothed using coefficients from linear regression: blue line indicates Training Set, Sky blue line indicates retrospective Set, red line indicates prospective set and purple line indicates All Cohorts

Fig. 3

Outcome according to score values. Bars correspond to frequency of event (percentage) by score value (ranging from 0 to 9). The 95% CI are displayed for each point using error bars in lightgrey

Fig. 4

Suggested triage algorithm using the TIC Score. This algorithm proposes à patient management strategy found on clinical features and TIC Score values. FFP fresh frozen plasma; RBC red blood cell