OBJECTIVE: The purpose of this study was to describe variations in blood-based resuscitation in an injured cohort. We hypothesize that distinct transfusion trajectories are present. BACKGROUND: Retrospective studies of hemorrhage utilize the concept of massive transfusion, where a set volume of blood is required. Patterns of hemorrhage vary and massive transfusion does little to describe these differences. METHODS: Patients were prospectively included from June 2012 to 2013. Time of transfusion for each packed red blood cell (PRBC) transfused was recorded, in minutes, for all patients. Additional measures included demographic and injury data, admission laboratory values, and vital signs and outcomes including mortality, tempo of transfusion, and operative requirements. Group-based trajectory modeling was utilized to describe transfusion trajectories throughout the cohort. RESULTS: Three hundred sixteen patients met the inclusion criteria. Among them, 72% were men and median age was 35 years (interquartile range [IQR] 24-50), median injury severity score was 13 (IQR 9-22), median 24-hour transfusion volume was 4 units of PRBCs (IQR 2-8), and mortality was 14%. Six transfusion trajectories were identified. Among the patients, 35% received negligible transfusions (group 1). Groups 2 and 3 received greater than 15 units PRBCs-the former as early resuscitation, whereas the latter intermittently throughout the day. Groups 4 and 5 had similar small resuscitations with distinct demographic differences. Group 6 suffered blunt injuries and required rapid resuscitation. CONCLUSIONS: Traditional definitions of massive transfusion are broad and imprecise. In cohorts of severely injured patients, there are distinct, identifiable transfusion trajectories. Identification of subgroups is important in understanding clinical course and to anticipate resuscitative and therapeutic needs.
OBJECTIVE: The purpose of this study was to describe variations in blood-based resuscitation in an injured cohort. We hypothesize that distinct transfusion trajectories are present. BACKGROUND: Retrospective studies of hemorrhage utilize the concept of massive transfusion, where a set volume of blood is required. Patterns of hemorrhage vary and massive transfusion does little to describe these differences. METHODS:Patients were prospectively included from June 2012 to 2013. Time of transfusion for each packed red blood cell (PRBC) transfused was recorded, in minutes, for all patients. Additional measures included demographic and injury data, admission laboratory values, and vital signs and outcomes including mortality, tempo of transfusion, and operative requirements. Group-based trajectory modeling was utilized to describe transfusion trajectories throughout the cohort. RESULTS: Three hundred sixteen patients met the inclusion criteria. Among them, 72% were men and median age was 35 years (interquartile range [IQR] 24-50), median injury severity score was 13 (IQR 9-22), median 24-hour transfusion volume was 4 units of PRBCs (IQR 2-8), and mortality was 14%. Six transfusion trajectories were identified. Among the patients, 35% received negligible transfusions (group 1). Groups 2 and 3 received greater than 15 units PRBCs-the former as early resuscitation, whereas the latter intermittently throughout the day. Groups 4 and 5 had similar small resuscitations with distinct demographic differences. Group 6 suffered blunt injuries and required rapid resuscitation. CONCLUSIONS: Traditional definitions of massive transfusion are broad and imprecise. In cohorts of severely injured patients, there are distinct, identifiable transfusion trajectories. Identification of subgroups is important in understanding clinical course and to anticipate resuscitative and therapeutic needs.
Authors: Florian Roquet; Arthur Neuschwander; Sophie Hamada; Gersende Favé; Arnaud Follin; David Marrache; Bernard Cholley; Romain Pirracchio Journal: JAMA Netw Open Date: 2019-09-04
Authors: Emily Rimmer; Allan Garland; Anand Kumar; Steve Doucette; Brett L Houston; Chantalle E Menard; Murdoch Leeies; Alexis F Turgeon; Salah Mahmud; Donald S Houston; Ryan Zarychanski Journal: Can J Anaesth Date: 2022-07-29 Impact factor: 6.713
Authors: Makoto Mori; Cornell Brooks; Erica Spatz; Bobak J Mortazavi; Sanket S Dhruva; George C Linderman; Lawrence A Grab; Yawei Zhang; Arnar Geirsson; Sarwat I Chaudhry; Harlan M Krumholz Journal: BMJ Open Date: 2020-09-01 Impact factor: 2.692