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Background: Despite tremendous efforts, the incidence of surgical site infection (SSI) following the surgical treatment of pediatric spinal deformity remains a concern. Although previous studies have reported some risk factors for SSI, these studies have been limited by not being able to investigate multiple risk factors at the same time. The aim of the present study was to evaluate a wide range of preoperative and intraoperative factors in predicting SSI and to develop and validate a prediction model that quantifies the risk of SSI for individual pediatric spinal deformity patients.Methods: Pediatric patients with spinal deformity who underwent primary, revision, or definitive spinal fusion at 1 of 7 institutions were included. Candidate predictors were known preoperatively and were not modifiable in most cases; these included 31 patient, 12 surgical, and 4 hospital factors. The Centers for Disease Control and Prevention definition of SSI within 90 days of surgery was utilized. Following multiple imputation and multicollinearity testing, predictor selection was conducted with use of logistic regression to develop multiple models. The data set was randomly split into training and testing sets, and fivefold cross-validation was performed to compare discrimination, calibration, and overfitting of each model and to determine the final model. A risk probability calculator and a mobile device application were developed from the model in order to calculate the probability of SSI in individual patients.Results: A total of 3,092 spinal deformity surgeries were included, in which there were 132 cases of SSI (4.3%). The final model achieved adequate discrimination (area under the receiver operating characteristic curve: 0.76), as well as calibration and no overfitting. Predictors included in the model were nonambulatory status, neuromuscular etiology, pelvic instrumentation, procedure time ≥7 hours, American Society of Anesthesiologists grade >2, revision procedure, hospital spine surgical cases <100/year, abnormal hemoglobin level, and overweight or obese body mass index.Conclusions: The risk probability calculator encompassing patient, surgical, and hospital factors developed in the present study predicts the probability of 90-day SSI in pediatric spinal deformity surgery. This validated calculator can be utilized to improve informed consent and shared decision-making and may allow the deployment of additional resources and strategies selectively in high-risk patients.Level Of Evidence: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

Background: ScoliScore is a DNA-based prognostic test, designed and used to help to predict the risk of curve progression in patients with adolescent idiopathic scoliosis. The role of this test in clinical practice remains unclear as the published results of the ScoliScore have not been validated independently. The purpose of this study was to determine if the ScoliScore effectively predicted the risk of curve progression in patients with mild and moderate adolescent idiopathic scoliosis in two urban academic medical centers.Methods: One hundred and twenty-six patients with adolescent idiopathic scoliosis who met inclusion criteria at two centers were administered the ScoliScore test. Two groups were created: a progression group (those who had a Cobb angle of >40° or those who had undergone surgical fusion) and a non-progression group (those who had skeletal maturity without curve progression to 40°). ScoliScore values and risk levels were compared between the two groups. The negative predictive value was calculated for low-risk scores and the positive predictive value was calculated for high-risk scores.Results: There was no significant difference (p = 0.706) in the mean ScoliScore (and standard deviation) between patients with curve progression (107 ± 55 points) and those without curve progression (102 ± 62 points). There was also no significant difference (p = 0.399) in curve progression between patients with high-risk scores (26.7%) and those with low-risk scores (12.9%). The positive predictive value of the test was 0.27 (95% confidence interval, 0.09 to 0.55), and the negative predictive value was 0.87 (95% confidence interval, 0.69 to 0.96). ScoliScores and rates of progression were not affected by brace-wear.Conclusions: ScoliScores did not differ between patients with and without curve progression, and the negative and positive predictive values were lower in our study than in the previously published validation study by the developers of the test. This may be due to differences in our test population, genetic variability, or failure of patients in the non-progression group to follow up. [ABSTRACT FROM AUTHOR]