BACKGROUND: Necrotizing soft-tissue infections (NSTIs) are associated with significant morbidity and mortality, but a definitive nonsurgical diagnostic test remains elusive. Despite the widespread use of computed tomography (CT) as a diagnostic adjunct, there is little data that definitively correlate CT findings with the presence of NSTI. Our goal was the development of a CT-based scoring system to discriminate non-NSTI from NSTI. METHODS: Patients older than 17 years undergoing CT for evaluation of soft-tissue infection at a tertiary care medical center over a 10-year period (2000-2009) were included. Abstracted data included comorbidities and social history, physical examination, laboratory findings, and operative and pathologic findings. NSTI was defined as soft-tissue necrosis in the dictated operative note or the accompanying pathology report. CT scans were reviewed by a radiologist blinded to clinical and laboratory data. A scoring system was developed and the area under the receiver operating characteristic curve was calculated. RESULTS: During the study period, 305 patients underwent CT scanning (57% men; mean age, 47.4 years). Forty-four patients (14.4%) evaluated had an NSTI. A scoring system was retrospectively developed (table). A score >6 points was 86.3% sensitive and 91.5% specific for the diagnosis of NSTI (positive predictive value, 63.3%; negative predictive value, 85.5%). The area under the receiver operating characteristic curve was 0.928 (95% confidence interval, 0.893-0.964). The mean score of the non-NSTI group was 2.74. CONCLUSIONS: We have developed a CT scoring system that is both sensitive and specific for the diagnosis of NSTIs. This system may allow clinicians to more accurately diagnose NSTIs. Prospective validation of this scoring system is planned.
BACKGROUND:Necrotizing soft-tissue infections (NSTIs) are associated with significant morbidity and mortality, but a definitive nonsurgical diagnostic test remains elusive. Despite the widespread use of computed tomography (CT) as a diagnostic adjunct, there is little data that definitively correlate CT findings with the presence of NSTI. Our goal was the development of a CT-based scoring system to discriminate non-NSTI from NSTI. METHODS:Patients older than 17 years undergoing CT for evaluation of soft-tissue infection at a tertiary care medical center over a 10-year period (2000-2009) were included. Abstracted data included comorbidities and social history, physical examination, laboratory findings, and operative and pathologic findings. NSTI was defined as soft-tissue necrosis in the dictated operative note or the accompanying pathology report. CT scans were reviewed by a radiologist blinded to clinical and laboratory data. A scoring system was developed and the area under the receiver operating characteristic curve was calculated. RESULTS: During the study period, 305 patients underwent CT scanning (57% men; mean age, 47.4 years). Forty-four patients (14.4%) evaluated had an NSTI. A scoring system was retrospectively developed (table). A score >6 points was 86.3% sensitive and 91.5% specific for the diagnosis of NSTI (positive predictive value, 63.3%; negative predictive value, 85.5%). The area under the receiver operating characteristic curve was 0.928 (95% confidence interval, 0.893-0.964). The mean score of the non-NSTI group was 2.74. CONCLUSIONS: We have developed a CT scoring system that is both sensitive and specific for the diagnosis of NSTIs. This system may allow clinicians to more accurately diagnose NSTIs. Prospective validation of this scoring system is planned.
Authors: David H Ballard; Parisa Mazaheri; Constantine A Raptis; Meghan G Lubner; Christine O Menias; Perry J Pickhardt; Vincent M Mellnick Journal: Can Assoc Radiol J Date: 2020-01-28 Impact factor: 2.248
Authors: David H Ballard; George Patton Pennington; George P Pennington; Joe Johnson; Sanjeev Bhalla; Constantine Raptis Journal: Clin Imaging Date: 2018-02-06 Impact factor: 1.605
Authors: David H Ballard; Constantine A Raptis; Jarot Guerra; Laurie Punch; Obeid Ilahi; John P Kirby; Vincent M Mellnick Journal: AJR Am J Roentgenol Date: 2018-08-07 Impact factor: 3.959
Authors: Myriam Martinez; Thomas Peponis; Aglaia Hage; Daniel D Yeh; Haytham M A Kaafarani; Peter J Fagenholz; David R King; Marc A de Moya; George C Velmahos Journal: World J Surg Date: 2018-01 Impact factor: 3.352