Danielle S Gruen1, Francis X Guyette, Joshua B Brown, Brian J Daley, Richard S Miller, Brian G Harbrecht, Jeffrey A Claridge, Herb A Phelan, Mark H Yazer, Matthew D Neal, Brian S Zuckerbraun, Jason L Sperry. 1. From the Department of Surgery (D.S.G., J.B.B., M.D.N., B.S.Z., J.L.S.), University of Pittsburgh; Division of Trauma and Acute Care Surgery (D.S.G., J.B.B., M.D.N., B.S.Z., J.L.S.), Pittsburgh Trauma Research Center; Department of Emergency Medicine (F.X.G.), University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Surgery (B.J.D.), University of Tennessee Health Science Center, Knoxville; Department of Surgery (R.S.M.), Vanderbilt University Medical Center, Nashville, Tennessee; University of Louisville (B.G.H.), Louisville, Kentucky; MetroHealth Medical Center (J.A.C.), Case Western Reserve University, Cleveland, Ohio; Department of Surgery (H.A.P.), University of Texas Southwestern, Parkland Memorial Hospital, Dallas, Texas; and Department of Pathology (M.H.Y.), University of Pittsburgh, Pittsburgh, Pennsylvania.
Abstract
BACKGROUND: Prehospital plasma improves survival for severely injured trauma patients transported by air ambulance. We sought to characterize the unexpected survivors, patients who survived despite having high predicted mortality after traumatic injury. METHODS: The Prehospital Air Medical Plasma trial randomized severely injured patients (n = 501) to receive either standard care (crystalloid) or two units of prehospital plasma followed by standard care fluid resuscitation. We built a generalized linear model to estimate patient mortality. Area under the receiver operating characteristic curve was used to evaluate model performance. We defined unexpected survivors as patients who had a predicted mortality greater than 50% and survived to 30 days. We characterized patient demographics, clinical features, and outcomes of the unexpected survivors. Observed to expected (O/E) ratios and Z-statistics were calculated using model-estimated mortality for each cohort. RESULTS: Our model predicted mortality better than Injury Severity Score or Revised Trauma Score parameters and identified 36 unexpected survivors. Compared with expected survivors, unexpected survivors were younger (33 years [24, 52 years] vs. 47 years [32, 59 years], p = 0.013), were more severely injured (Injury Severity Score 34 [22, 50] vs. 18 [10, 27], p < 0.001), had worse organ dysfunction and hospital resource outcomes (multiple organ failure, intensive care unit, hospital length of stay, and ventilator days), and were more likely to receive prehospital plasma (67 vs. 46%, p = 0.031). Nonsurvivors with high predicted mortality were more likely to receive standard care resuscitation (p < 0.001). Unexpected survivors who received prehospital plasma had a lower observed to expected mortality than those that received standard care resuscitation (O/E 0.56 [0.33-0.84] vs. 1.0 [0.73-1.32]). The number of prehospital plasma survivors (24) exceeded the number of predicted survivors (n = 10) estimated by our model (p < 0.001). CONCLUSION: Prehospital plasma is associated with an increase in the number of unexpected survivors following severe traumatic injury. Prehospital interventions may improve the probability of survival for injured patients with high predicted mortality based on early injury characteristics, vital signs, and resuscitation measures. LEVEL OF EVIDENCE: Therapeutic Level III.
BACKGROUND: Prehospital plasma improves survival for severely injured trauma patients transported by air ambulance. We sought to characterize the unexpected survivors, patients who survived despite having high predicted mortality after traumatic injury. METHODS: The Prehospital Air Medical Plasma trial randomized severely injured patients (n = 501) to receive either standard care (crystalloid) or two units of prehospital plasma followed by standard care fluid resuscitation. We built a generalized linear model to estimate patient mortality. Area under the receiver operating characteristic curve was used to evaluate model performance. We defined unexpected survivors as patients who had a predicted mortality greater than 50% and survived to 30 days. We characterized patient demographics, clinical features, and outcomes of the unexpected survivors. Observed to expected (O/E) ratios and Z-statistics were calculated using model-estimated mortality for each cohort. RESULTS: Our model predicted mortality better than Injury Severity Score or Revised Trauma Score parameters and identified 36 unexpected survivors. Compared with expected survivors, unexpected survivors were younger (33 years [24, 52 years] vs. 47 years [32, 59 years], p = 0.013), were more severely injured (Injury Severity Score 34 [22, 50] vs. 18 [10, 27], p < 0.001), had worse organ dysfunction and hospital resource outcomes (multiple organ failure, intensive care unit, hospital length of stay, and ventilator days), and were more likely to receive prehospital plasma (67 vs. 46%, p = 0.031). Nonsurvivors with high predicted mortality were more likely to receive standard care resuscitation (p < 0.001). Unexpected survivors who received prehospital plasma had a lower observed to expected mortality than those that received standard care resuscitation (O/E 0.56 [0.33-0.84] vs. 1.0 [0.73-1.32]). The number of prehospital plasma survivors (24) exceeded the number of predicted survivors (n = 10) estimated by our model (p < 0.001). CONCLUSION: Prehospital plasma is associated with an increase in the number of unexpected survivors following severe traumatic injury. Prehospital interventions may improve the probability of survival for injured patients with high predicted mortality based on early injury characteristics, vital signs, and resuscitation measures. LEVEL OF EVIDENCE: Therapeutic Level III.
Authors: R J Russell; T J Hodgetts; J McLeod; K Starkey; P Mahoney; K Harrison; E Bell Journal: Philos Trans R Soc Lond B Biol Sci Date: 2011-01-27 Impact factor: 6.237
Authors: Rob Norris; Randy Woods; Brian Harbrecht; Timothy Fabian; Michael Rhodes; John Morris; Timothy R Billiar; Anita P Courcoulas; Anthony O Udekwu; Christine Stinson; Andrew B Peitzman Journal: J Trauma Date: 2002-02
Authors: Danielle S Gruen; Joshua B Brown; Francis X Guyette; Yoram Vodovotz; Pär I Johansson; Jakob Stensballe; Derek A Barclay; Jinling Yin; Brian J Daley; Richard S Miller; Brian G Harbrecht; Jeffrey A Claridge; Herb A Phelan; Matthew D Neal; Brian S Zuckerbraun; Timothy R Billiar; Jason L Sperry Journal: JCI Insight Date: 2020-04-23
Authors: Jason L Sperry; Francis X Guyette; Joshua B Brown; Mark H Yazer; Darrell J Triulzi; Barbara J Early-Young; Peter W Adams; Brian J Daley; Richard S Miller; Brian G Harbrecht; Jeffrey A Claridge; Herb A Phelan; William R Witham; A Tyler Putnam; Therese M Duane; Louis H Alarcon; Clifton W Callaway; Brian S Zuckerbraun; Matthew D Neal; Matthew R Rosengart; Raquel M Forsythe; Timothy R Billiar; Donald M Yealy; Andrew B Peitzman; Mazen S Zenati Journal: N Engl J Med Date: 2018-07-26 Impact factor: 91.245
Authors: Stacy A Shackelford; Deborah J Del Junco; Nicole Powell-Dunford; Edward L Mazuchowski; Jeffrey T Howard; Russ S Kotwal; Jennifer Gurney; Frank K Butler; Kirby Gross; Zsolt T Stockinger Journal: JAMA Date: 2017-10-24 Impact factor: 56.272
Authors: Danielle S Gruen; Francis X Guyette; Joshua B Brown; David O Okonkwo; Ava M Puccio; Insiyah K Campwala; Matthew T Tessmer; Brian J Daley; Richard S Miller; Brian G Harbrecht; Jeffrey A Claridge; Herb A Phelan; Matthew D Neal; Brian S Zuckerbraun; Mark H Yazer; Timothy R Billiar; Jason L Sperry Journal: JAMA Netw Open Date: 2020-10-01