Matthew J Pommerening1, Michael D Goodman2, John B Holcomb3, Charles E Wade4, Erin E Fox5, Deborah J Del Junco6, Karen J Brasel7, Eileen M Bulger8, Mitch J Cohen9, Louis H Alarcon10, Martin A Schreiber11, John G Myers12, Herb A Phelan13, Peter Muskat14, Mohammad Rahbar15, Bryan A Cotton16. 1. Center for Translational Injury Research, University of Texas Health Science Center at Houston, United States; Division of Acute Care Surgery, Department of Surgery, University of Texas Health Science Center at Houston, United States. Electronic address: matthew.j.pommerening@uth.tmc.edu. 2. Division of Trauma/Critical Care, Department of Surgery, College of Medicine, University of Cincinnati, United States. Electronic address: md-goodman@hotmail.com. 3. Center for Translational Injury Research, University of Texas Health Science Center at Houston, United States; Division of Acute Care Surgery, Department of Surgery, University of Texas Health Science Center at Houston, United States. Electronic address: john.holcomb@uth.tmc.edu. 4. Center for Translational Injury Research, University of Texas Health Science Center at Houston, United States; Division of Acute Care Surgery, Department of Surgery, University of Texas Health Science Center at Houston, United States. Electronic address: charles.e.wade@uth.tmc.edu. 5. Division of Acute Care Surgery, Department of Surgery, University of Texas Health Science Center at Houston, United States; Biostatistics/Epidemiology/Research Design Core, Center for Clinical and Translational Sciences, University of Texas Health Science Center at Houston, United States. Electronic address: erin.e.fox@uth.tmc.edu. 6. Division of Acute Care Surgery, Department of Surgery, University of Texas Health Science Center at Houston, United States; Biostatistics/Epidemiology/Research Design Core, Center for Clinical and Translational Sciences, University of Texas Health Science Center at Houston, United States. Electronic address: Deborah.J.DelJunco@uth.tmc.edu. 7. Division of Trauma and Critical Care, Department of Surgery, Medical College of Wisconsin, United States. Electronic address: kbrasel@mcw.edu. 8. Division of Trauma and Critical Care, Department of Surgery, School of Medicine, University of Washington, United States. Electronic address: ebulger@u.washington.edu. 9. Division of General Surgery, Department of Surgery, School of Medicine, University of California San Francisco, United States. Electronic address: mcohen@sfghsurg.ucsf.edu. 10. Division of Trauma and General Surgery, Department of Surgery, School of Medicine, University of Pittsburgh, United States. Electronic address: alarconl@upmc.edu. 11. Division of Trauma, Critical Care and Acute Care Surgery, School of Medicine, Oregon Health & Science University, United States. Electronic address: schreibm@ohsu.edu. 12. Division of Trauma, Department of Surgery, School of Medicine, University of Texas Health Science Center at San Antonio, United States. Electronic address: myersjg@uthscsa.edu. 13. Division of Burn/Trauma/Critical Care, Department of Surgery, Medical School, University of Texas Southwestern Medical Center at Dallas, United States. Electronic address: Herb.Phelan@UTSouthwestern.edu. 14. Division of Trauma/Critical Care, Department of Surgery, College of Medicine, University of Cincinnati, United States. 15. Division of Acute Care Surgery, Department of Surgery, University of Texas Health Science Center at Houston, United States; Division of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, United States. 16. Center for Translational Injury Research, University of Texas Health Science Center at Houston, United States; Division of Acute Care Surgery, Department of Surgery, University of Texas Health Science Center at Houston, United States. Electronic address: Bryan.A.Cotton@uth.tmc.edu.
Abstract
INTRODUCTION: Early recognition and treatment of trauma patients requiring massive transfusion (MT) has been shown to reduce mortality. While many risk factors predicting MT have been demonstrated, there is no universally accepted method or algorithm to identify these patients. We hypothesised that even among experienced trauma surgeons, the clinical gestalt of identifying patients who will require MT is unreliable. METHODS: Transfusion and mortality outcomes after trauma were observed at 10 U.S. Level-1 trauma centres in patients who survived ≥ 30 min after admission and received ≥ 1 unit of RBC within 6h of arrival. Subjects who received ≥ 10 units within 24h of admission were classified as MT patients. Trauma surgeons were asked the clinical gestalt question "Is the patient likely to be massively transfused?" 10 min after the patients arrival. The performance of clinical gestalt to predict MT was assessed using chi-square tests and ROC analysis to compare gestalt to previously described scoring systems. RESULTS: Of the 1245 patients enrolled, 966 met inclusion criteria and 221 (23%) patients received MT. 415 (43%) were predicted to have a MT and 551(57%) were predicted to not have MT. Patients predicted to have MT were younger, more often sustained penetrating trauma, had higher ISS scores, higher heart rates, and lower systolic blood pressures (all p<0.05). Gestalt sensitivity was 65.6% and specificity was 63.8%. PPV and NPV were 34.9% and 86.2% respectively. CONCLUSION: Data from this large multicenter trial demonstrates that predicting the need for MT continues to be a challenge. Because of the increased mortality associated with delayed therapy, a more reliable algorithm is needed to identify and treat these severely injured patients earlier.
INTRODUCTION: Early recognition and treatment of traumapatients requiring massive transfusion (MT) has been shown to reduce mortality. While many risk factors predicting MT have been demonstrated, there is no universally accepted method or algorithm to identify these patients. We hypothesised that even among experienced trauma surgeons, the clinical gestalt of identifying patients who will require MT is unreliable. METHODS: Transfusion and mortality outcomes after trauma were observed at 10 U.S. Level-1 trauma centres in patients who survived ≥ 30 min after admission and received ≥ 1 unit of RBC within 6h of arrival. Subjects who received ≥ 10 units within 24h of admission were classified as MT patients. Trauma surgeons were asked the clinical gestalt question "Is the patient likely to be massively transfused?" 10 min after the patients arrival. The performance of clinical gestalt to predict MT was assessed using chi-square tests and ROC analysis to compare gestalt to previously described scoring systems. RESULTS: Of the 1245 patients enrolled, 966 met inclusion criteria and 221 (23%) patients received MT. 415 (43%) were predicted to have a MT and 551(57%) were predicted to not have MT. Patients predicted to have MT were younger, more often sustained penetrating trauma, had higher ISS scores, higher heart rates, and lower systolic blood pressures (all p<0.05). Gestalt sensitivity was 65.6% and specificity was 63.8%. PPV and NPV were 34.9% and 86.2% respectively. CONCLUSION: Data from this large multicenter trial demonstrates that predicting the need for MT continues to be a challenge. Because of the increased mortality associated with delayed therapy, a more reliable algorithm is needed to identify and treat these severely injured patients earlier.
Authors: Timothy C Nunez; William D Dutton; Addison K May; John B Holcomb; Pampee P Young; Bryan A Cotton Journal: Transfusion Date: 2010-09 Impact factor: 3.157
Authors: Josenia N M Tan; Peter A Burke; Suresh K Agarwal; Nelson Mantilla-Rey; Karen Quillen Journal: Am J Clin Pathol Date: 2012-04 Impact factor: 2.493
Authors: Andrea Penaloza; Franck Verschuren; Guy Meyer; Sybille Quentin-Georget; Caroline Soulie; Frédéric Thys; Pierre-Marie Roy Journal: Ann Emerg Med Date: 2013-02-21 Impact factor: 5.721
Authors: Joseph J Dubose; Thomas M Scalea; John B Holcomb; Binod Shrestha; Obi Okoye; Kenji Inaba; Tiffany K Bee; Timothy C Fabian; James Whelan; Rao R Ivatury Journal: J Trauma Acute Care Surg Date: 2013-01 Impact factor: 3.313
Authors: Martin A Schreiber; Jeremy Perkins; Laszlo Kiraly; Samantha Underwood; Charles Wade; John B Holcomb Journal: J Am Coll Surg Date: 2007-08-08 Impact factor: 6.113
Authors: Lauren M McDaniel; Matthew D Neal; Jason L Sperry; Louis H Alarcon; Raquel M Forsythe; Darrell Triulzi; Andrew B Peitzman; Jay S Raval Journal: J Am Coll Surg Date: 2013-04-06 Impact factor: 6.113
Authors: George Kasotakis; Nichole Starr; Erek Nelson; Bedabrata Sarkar; Peter Ashley Burke; Daniel George Remick; Ronald Gary Tompkins Journal: Eur J Trauma Emerg Surg Date: 2018-04-07 Impact factor: 3.693
Authors: Rachael A Callcut; Michael W Cripps; Mary F Nelson; Amanda S Conroy; Bryce B R Robinson; Mitchell J Cohen Journal: J Trauma Acute Care Surg Date: 2016-03 Impact factor: 3.313
Authors: E I Hodgman; M W Cripps; M J Mina; E M Bulger; M A Schreiber; K J Brasel; M J Cohen; P Muskat; J G Myers; L H Alarcon; M H Rahbar; J B Holcomb; B A Cotton; E E Fox; D J Del Junco; C E Wade; H A Phelan Journal: J Trauma Acute Care Surg Date: 2018-02 Impact factor: 3.313
Authors: Kamil Hanna; Charles Harris; Marc D Trust; Andrew Bernard; Carlos Brown; Mohammad Hamidi; Bellal Joseph Journal: World J Surg Date: 2020-06 Impact factor: 3.352
Authors: Jacob B Schriner; Mitchell J George; Jessica C Cardenas; Scott D Olson; Kimberly A Mankiewicz; Charles S Cox; Brijesh S Gill; Charles E Wade Journal: Shock Date: 2022-07-19 Impact factor: 3.533
Authors: Jing Ning; Mohammad H Rahbar; Sangbum Choi; Chuan Hong; Jin Piao; Deborah J del Junco; Erin E Fox; Elaheh Rahbar; John B Holcomb Journal: Stat Med Date: 2015-08-09 Impact factor: 2.373
Authors: Taleen A MacArthur; Grant M Spears; Rosemary A Kozar; Jing-Fei Dong; Matthew Auton; Donald H Jenkins; Kent R Bailey; Aneel A Ashrani; Mike J Ferrara; Joseph M Immermann; Timothy M Halling; Myung S Park Journal: Shock Date: 2021-03-01 Impact factor: 3.533
Authors: David Dreizin; Yuyin Zhou; Tina Chen; Guang Li; Alan L Yuille; Ashley McLenithan; Jonathan J Morrison Journal: J Trauma Acute Care Surg Date: 2020-03 Impact factor: 3.697