A latent class model for defining severe hemorrhage

Abstract

Background Several predictive models have been developed to identify trauma patients who have had severe hemorrhage (SH) and may need a massive transfusion protocol (MTP). However, almost all these models define SH as the transfusion of ≥10 units of red blood cells (RBCs) within 24 hours of ED admission (aka massive transfusion, MT). This definition excludes some patients with SH, especially those who die before a 10th unit of RBCs could be transfused, which calls the validity of these prediction models into question. We show how a latent class model could improve the accuracy of identifying the SH patients. Methods Modeling SH classification as a latent variable, we estimate the posterior probability of a patient in SH based on ED admission variables (SBP, HR, pH, Hemoglobin), the 24-hour blood product utilization (plasma:RBCs and platelets: RBCs ratios), and 24-hour survival status. We define the SH subgroup as those having a posterior probability of ≥0.5. We compare our new classification of SH with that of the traditional MT using data from PROMMTT study. Results Of 1245 patients, 913 had complete data which were used in the latent class model. About 25.3% of patients were classified as SH. The overall agreement between the MT and SH classifications was 83.8%. However, among 49 patients who died before receiving the 10th unit of RBCs 41 (84%) were classified as SH. Seven of the remaining 8 (87.5%) who were not classified as SH had head injury. Conclusion Our definition of SH based on the aforementioned latent class model has an advantage of improving on the traditional MT definition by identifying SH patients who die before receiving the 10th unit of RBCs. We recommend further improvements to more accurately classify SH patients that could replace the traditional definition of MT for use in developing prediction algorithms. Level of Evidence II, Prospective

The Role of Plasma Transfusion in Massive Bleeding: Protecting the Endothelial Glycocalyx?

“…High mortality rates during the first 24 h and rapid time course of massive hemorrhage make transfusion rate (e.g., ≥3 PRBC units/60 min) a more appropriate definition ( 4 ). In addition, data analysis from the PROMMT study enabled Rahbar et al to identify those patients most likely to develop massive hemorrhage based on emergency admission variables, such as systolic blood pressure, heart rate, pH, and hemoglobin ( 5 ). This prospective observational study showed that transfusion with higher ratio of plasma to PRBC early in resuscitation is associated with an improved survival at 24 h ( 6 ).…”

Survival bias in pediatric hemorrhagic shock: Are we misrepresenting the data?

“…The potential for survival bias has previously been described and estimated in studies of massive transfusion in adults. In one study, a latent class model classified injured adults as potentially needing or receiving a massive transfusion protocol (severe hemorrhage) based on several features, including the arrival vital signs, hemoglobin, and the ratios of plasma and platelets to red blood cells transfused 44,45 . In this model, most adults (84%) who died before receiving enough blood to meet the definition of massive transfusion were classified as severe hemorrhage, suggesting a survival bias in many patients when using blood volume to define significant hemorrhage.…”

Recurrent event frailty models reduced time-varying and other biases in evaluating transfusion protocols for traumatic hemorrhage

“…Information on in-hospital mortality, complications, and later treatment were recorded daily from the medical record until death or discharge. Additional details regarding the design and main results of PROMMTT have been previously published [2,13,14,22]. …”