Abstract

ObjectiveTraumatic popliteal vascular injuries are associated with the highest risk of limb loss of all peripheral vascular injuries. A method to evaluate the predictors of amputation is needed because previous scores could not be validated. In the present study, we aimed to provide a simplified scoring system (POPSAVEIT [popliteal scoring assessment for vascular extremity injuries in trauma]) that could be used preoperatively to risk stratify patients with traumatic popliteal vascular injuries for amputation. MethodsA review of patients sustaining traumatic popliteal artery injuries was performed. Patients requiring amputation were compared with those with limb salvage at the last follow-up. Of these patients, 80% were randomly assigned to a training group for score generation and 20% to a testing group for validation. Significant predictors of amputation (P < .1) on univariate analysis were included in a multivariable analysis. Those with P < .05 on multivariable analysis were assigned points according to the relative value of their odds ratios (ORs). Receiver operating characteristic curves were generated to determine low- vs high-risk scores. An area under the curve of >0.65 was considered adequate for validation. ResultsA total of 355 patients were included, with an overall amputation rate of 16%. On multivariate regression analysis, the risk factors independently associated with amputation in the final model were as follows: systolic blood pressure <90 mm Hg (OR, 3.2; P = .027; 1 point), associated orthopedic injury (OR, 4.9; P = .014; 2 points), and a lack of preoperative pedal Doppler signals (OR, 5.5; P = .002; 2 points [or 1 point for a lack of palpable pedal pulses if Doppler signal data were unavailable]). A score of ≥3 was found to maximize the sensitivity (85%) and specificity (49%) for a high risk of amputation. The receiver operating characteristic curve for the validation group had an area under the curve of 0.750, meeting the threshold for score validation. ConclusionsThe POPSAVEIT score provides a simple and practical method to effectively stratify patients preoperatively into low- and high-risk major amputation categories.

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