BACKGROUND AND OBJECTIVES: Although associated with increased morbidity and mortality, AKI has not been systematically examined in military personnel injured from combat operations in Iraq and Afghanistan. DESIGN, SETTINGS, PARTICIPANTS, & MEASUREMENTS: Patients evacuated from Iraq and Afghanistan to a burn unit were examined. AKI was classified by the Acute Kidney Injury Network (AKIN) and Risk-Injury-Failure-Loss-End Stage (RIFLE) schemas. Age, sex, percentage of total body surface area burned (TBSA), percentage of full-thickness burn, inhalation injury, and injury severity score were recorded. Additional data that could be associated with poor outcomes were recorded for patients with TBSA ≥20%. Multivariate logistic regression analyses were performed to determine factors associated with morbidity and mortality. RESULTS: AKI prevalence rates by the RIFLE and AKIN criteria were 23.8% and 29.9%, respectively. After logistic regression, RIFLE categories of risk (odds ratio [OR], 15.34; 95% confidence interval [CI], 1.75-134; P=0.01), injury (OR, 46.28; 95% CI, 5.02-427; P<0.001), and failure (OR, 126; 95% CI, 13.39->999; P<0.001); AKIN-2 (OR, 23.70; 95% CI, 2.32-242; P=0.008); and AKIN-3 (OR, 130; 95% CI, 13.38->999; P<0.001) were significantly associated with death. AKIN-3, injury, and failure remained significant in the subset of patients with ≥20% TBSA. There was also a strong interaction between TBSA and the stage of AKI with respect to ventilator and intensive care unit days. CONCLUSIONS: AKI is prevalent in military casualties with burn injury and is independently associated with morbidity and mortality after adjustment for factors associated with injury severity.
BACKGROUND AND OBJECTIVES: Although associated with increased morbidity and mortality, AKI has not been systematically examined in military personnel injured from combat operations in Iraq and Afghanistan. DESIGN, SETTINGS, PARTICIPANTS, & MEASUREMENTS: Patients evacuated from Iraq and Afghanistan to a burn unit were examined. AKI was classified by the Acute Kidney Injury Network (AKIN) and Risk-Injury-Failure-Loss-End Stage (RIFLE) schemas. Age, sex, percentage of total body surface area burned (TBSA), percentage of full-thickness burn, inhalation injury, and injury severity score were recorded. Additional data that could be associated with poor outcomes were recorded for patients with TBSA ≥20%. Multivariate logistic regression analyses were performed to determine factors associated with morbidity and mortality. RESULTS: AKI prevalence rates by the RIFLE and AKIN criteria were 23.8% and 29.9%, respectively. After logistic regression, RIFLE categories of risk (odds ratio [OR], 15.34; 95% confidence interval [CI], 1.75-134; P=0.01), injury (OR, 46.28; 95% CI, 5.02-427; P<0.001), and failure (OR, 126; 95% CI, 13.39->999; P<0.001); AKIN-2 (OR, 23.70; 95% CI, 2.32-242; P=0.008); and AKIN-3 (OR, 130; 95% CI, 13.38->999; P<0.001) were significantly associated with death. AKIN-3, injury, and failure remained significant in the subset of patients with ≥20% TBSA. There was also a strong interaction between TBSA and the stage of AKI with respect to ventilator and intensive care unit days. CONCLUSIONS: AKI is prevalent in military casualties with burn injury and is independently associated with morbidity and mortality after adjustment for factors associated with injury severity.
Authors: Joseph C Watso; Steven A Romero; Gilbert Moralez; Mu Huang; Matthew N Cramer; Elias Johnson; Craig G Crandall Journal: J Appl Physiol (1985) Date: 2022-08-11
Authors: Stephanie A Mason; Avery B Nathens; Celeste C Finnerty; Richard L Gamelli; Nicole S Gibran; Brett D Arnoldo; Ronald G Tompkins; David N Herndon; Marc G Jeschke Journal: Ann Surg Date: 2016-12 Impact factor: 12.969
Authors: Jonathan A Bolanos; Christina M Yuan; Dustin J Little; David K Oliver; Steven R Howard; Kevin C Abbott; Stephen W Olson Journal: Clin J Am Soc Nephrol Date: 2015-09-03 Impact factor: 8.237
Authors: Mohamed Diwan M AbdulHameed; Danielle L Ippolito; Jonathan D Stallings; Anders Wallqvist Journal: BMC Genomics Date: 2016-10-10 Impact factor: 3.969
Authors: Kevin K Chung; Elsa C Coates; David J Smith; Rachel A Karlnoski; William L Hickerson; Angela L Arnold-Ross; Michael J Mosier; Marcia Halerz; Amy M Sprague; Robert F Mullins; Daniel M Caruso; Marlene Albrecht; Brett D Arnoldo; Agnes M Burris; Sandra L Taylor; Steven E Wolf Journal: Crit Care Date: 2017-11-25 Impact factor: 9.097
Authors: Joseph L Alge; Nithin Karakala; Benjamin A Neely; Michael G Janech; Juan Carlos Q Velez; John M Arthur Journal: Crit Care Date: 2013-04-15 Impact factor: 9.097