2014
DOI: 10.1007/s11999-013-3382-z
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A Model to Predict Limb Salvage in Severe Combat-related Open Calcaneus Fractures

Abstract: This report demonstrates an artificial neural network was capable of accurately estimating the likelihood of amputation. Furthermore, decision curve analysis suggested the artificial neural network is better suited for clinical use than logistic regression. Once properly validated, this may provide a tool for surgeons and patients faced with combat-related open calcaneus fractures in which decisions between limb salvage and amputation remain difficult.

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Cited by 23 publications
(22 citation statements)
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References 29 publications
(56 reference statements)
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“…Previous reports have emphasized the need for health outcomes data to inform and improve treatment and rehabilitation of patients with serious leg injuries [49,30,31]. Our previous [5] and present study findings further support the need to investigate and refine existing clinical treatment pathways.…”
Section: Discussionsupporting
confidence: 81%
See 1 more Smart Citation
“…Previous reports have emphasized the need for health outcomes data to inform and improve treatment and rehabilitation of patients with serious leg injuries [49,30,31]. Our previous [5] and present study findings further support the need to investigate and refine existing clinical treatment pathways.…”
Section: Discussionsupporting
confidence: 81%
“…For patients with the most severe leg injuries, treatment required either amputation or leg-threatening injuries without amputation (hereafter referred to as limb salvage) through reconstructive surgeries [3]. Patients with combat-related amputation and limb salvage continue to present new treatment and rehabilitation challenges to healthcare providers at both military and Department of Veterans Affairs (VA) facilities [48]. …”
Section: Introductionmentioning
confidence: 99%
“…also used this model in their study entitled “A Model to Predict Limb Salvage in Severe Combat-related Open Calcaneus Fractures” to examine the possibility of amputation of an injured person in the open bone fractures which is a major challenge in making decision for clinician and patient on limb salvage or amputation. [ 13 ] Moreover, this method has been widely used for comparing different statistical models in predicting clinical results. [ 33 34 35 36 ]…”
Section: Discussionmentioning
confidence: 99%
“…Using DCA, the relative impact of false-positive and false-negative results produced by the prediction model is measured to yield the “net benefit” for the model. [ 13 ]…”
Section: Methodsmentioning
confidence: 99%
“…Twenty healthy individuals (age 30.7+6.3 years; 10 men: average BMI 24.2, height 179.2 cm, weight 77.6 kg; 10 women: average BMI 23.9, height 165.2 cm, weight 65.3 kg) with no history of major ankle injury or surgery were imaged using computed tomography (CT) from 10 cm above the ankle joint down through the toes after providing informed consent to participate in this IRB-approved study. From these CT scans, 3-dimensional surface models of each distal tibia, talus, and calcaneus were created based on reformatted scans with cubic voxel sizes ranging from 0.59 to 0.72 mm 3 using Mimics software (Materialise, Leuven, Belgium). A previous validation study, using a high-precision laser scanner to obtain the ground truth bone morphology, determined the accuracy of bone models using these methods is +0.63 mm.…”
Section: Methodsmentioning
confidence: 99%