2014
DOI: 10.1016/j.jspd.2014.05.004
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Surgical Risk Stratification Based on Preoperative Risk Factors in Severe Pediatric Spinal Deformity Surgery

Abstract: Corrective spine surgery for complex pediatric deformity is challenging and carries a substantial risk. No single parameter appears to independently predict postoperative complications. However, when all risk factors are considered, there is a trend toward increased intraoperative electromonitoring change and postoperative neurologic risk with the higher level score in our classification. The newly established surgical risk stratification based on patient-specific clinical and radiographic factors can guide su… Show more

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Cited by 24 publications
(34 citation statements)
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“…In a review of 145 pediatric spinal deformities, the authors introduced a scoring system Foundation of Orthopedics and Complex Spine (FOCOS level) that included these two factors and found that the FOCOS level correlated with blood loss, operation duration, and complication rate. 30 Suk et al in his study on single-staged VCR in 16 patients, reported 3 major complications; 1 had acute complete paralysis, 1 had hematoma, and 1 had hemopneumothorax. 7 Riley et al reviewed 109 patients who underwent posterior VCR for severe spinal deformity.…”
Section: Discussionmentioning
confidence: 98%
“…In a review of 145 pediatric spinal deformities, the authors introduced a scoring system Foundation of Orthopedics and Complex Spine (FOCOS level) that included these two factors and found that the FOCOS level correlated with blood loss, operation duration, and complication rate. 30 Suk et al in his study on single-staged VCR in 16 patients, reported 3 major complications; 1 had acute complete paralysis, 1 had hematoma, and 1 had hemopneumothorax. 7 Riley et al reviewed 109 patients who underwent posterior VCR for severe spinal deformity.…”
Section: Discussionmentioning
confidence: 98%
“…Supervised learning (i.e., classification and regression) uses input features (X) to predict a defined outcome (Y), while unsupervised learning (i.e., clustering) involves analyzing input variables (X) to elucidate patterns and structure in the data. Supervised learning algorithms can predict rare events such as surgical complications 20 and have the potential to improve patient risk stratification, clinical decision making, informed consent and health service planning 18,[21][22][23][24][25] . Supervised learning has been used in DBS surgery to predict clinical outcomes 26,27 , surgical targets 28,29 , side effects 30 , discharge status 31 and neurophysiological detection of DBS structures [32][33][34] .…”
Section: Introductionmentioning
confidence: 99%
“…Транспедикулярная спинальная система позволяет достичь полноценной коррекции врожденной деформации после удаления тела аномального позвонка с опорой только на соседние интактные тела позвонков относительно порочного [3, 14,16]. Однако при установке транспедикулярной металлоконструкции существует ряд технических сложностей и проблем, а также риск возникновения различного рода осложнений, прежде всего неврологического характера [17,18].…”
Section: Discussionunclassified