BACKGROUND: The objective of this study was to re-evaluate and simplify the Greenfield risk assessment profile (RAP) for venous thromboembolism (VTE) in trauma using information readily available at the bedside. METHODS: Retrospective review of 1233 consecutive admissions to the trauma intensive care unit from August 2011-January 2015. Univariate analyses were performed to determine which RAP risk factors were significant contributors to VTE. Multivariable logistic regression was used to develop models for risk stratification. All results were considered statistically significant at P ≤ 0.05. RESULTS: The study population was as follows: age 44 ± 19, 75% male, 72% blunt, injury severity score 21 ± 13, RAP score 9 ± 5, and 8% mortality. Groups were separated into +VTE (n = 104) and -VTE (n = 1129). They were similar in age, gender, mechanism, and mortality, but injury severity and RAP scores were higher in the +VTE group (all P < 0.0001). The +VTE group had more transfusions and longer time to prophylaxis (all P < 0.05). Receiving four or more transfusions in the first 24 h (odds ratio [OR], 2.60; 95% confidence interval [CI], 1.64-4.13), Glasgow coma score <8 for >4 h (OR, 2.13; 95% CI, 1.28-3.54), pelvic fracture (OR, 2.26; 95% CI, 1.44-3.57), age 40-59 y (OR, 1.70; 95% CI, 1.10-2.63), and >2-h operation (OR, 1.80; 95% CI, 1.14-2.85) predicted VTE with an area under the receiver operator curve of 0.729, which was comparable with 0.740 for the RAP score alone. CONCLUSIONS: VTE risk in trauma can be easily assessed using only five risk factors, which are all readily available at the bedside (transfusion, Glasgow coma scale, pelvic fracture, prolonged operation, and age). This simplified model provides similar predictive ability to the more complicated RAP score. Prospective validation of a simplified risk assessment score is warranted.
BACKGROUND: The objective of this study was to re-evaluate and simplify the Greenfield risk assessment profile (RAP) for venous thromboembolism (VTE) in trauma using information readily available at the bedside. METHODS: Retrospective review of 1233 consecutive admissions to the trauma intensive care unit from August 2011-January 2015. Univariate analyses were performed to determine which RAP risk factors were significant contributors to VTE. Multivariable logistic regression was used to develop models for risk stratification. All results were considered statistically significant at P ≤ 0.05. RESULTS: The study population was as follows: age 44 ± 19, 75% male, 72% blunt, injury severity score 21 ± 13, RAP score 9 ± 5, and 8% mortality. Groups were separated into +VTE (n = 104) and -VTE (n = 1129). They were similar in age, gender, mechanism, and mortality, but injury severity and RAP scores were higher in the +VTE group (all P < 0.0001). The +VTE group had more transfusions and longer time to prophylaxis (all P < 0.05). Receiving four or more transfusions in the first 24 h (odds ratio [OR], 2.60; 95% confidence interval [CI], 1.64-4.13), Glasgow coma score <8 for >4 h (OR, 2.13; 95% CI, 1.28-3.54), pelvic fracture (OR, 2.26; 95% CI, 1.44-3.57), age 40-59 y (OR, 1.70; 95% CI, 1.10-2.63), and >2-h operation (OR, 1.80; 95% CI, 1.14-2.85) predicted VTE with an area under the receiver operator curve of 0.729, which was comparable with 0.740 for the RAP score alone. CONCLUSIONS: VTE risk in trauma can be easily assessed using only five risk factors, which are all readily available at the bedside (transfusion, Glasgow coma scale, pelvic fracture, prolonged operation, and age). This simplified model provides similar predictive ability to the more complicated RAP score. Prospective validation of a simplified risk assessment score is warranted.
Authors: Denis F Noubouossie; Michael W Henderson; Micah Mooberry; Anton Ilich; Patrick Ellsworth; Mark Piegore; Sarah C Skinner; Rafal Pawlinski; Ian Welsby; Thomas Renné; Maureane Hoffman; Dougald M Monroe; Nigel S Key Journal: Blood Date: 2020-03-05 Impact factor: 22.113
Authors: Hannah V Hayes; Molly E Droege; Craig J Furnish; Michael D Goodman; Neil E Ernst; Christopher A Droege Journal: Surg Open Sci Date: 2020-04-14
Authors: Eric J Ley; Carlos V R Brown; Ernest E Moore; Jack A Sava; Kimberly Peck; David J Ciesla; Jason L Sperry; Anne G Rizzo; Nelson G Rosen; Karen J Brasel; Rosemary Kozar; Kenji Inaba; Matthew J Martin Journal: J Trauma Acute Care Surg Date: 2020-11 Impact factor: 3.313
Authors: Benjamin W Hoyt; Michael D Baird; Seth Schobel; Henry Robertson; Ravi Sanka; Benjamin K Potter; Matthew Bradley; John Oh; Eric A Elster Journal: OTA Int Date: 2021-10-19