Thirty-day readmission and reoperation after surgery for spinal tumors: a National Surgical Quality Improvement Program analysis.

OBJECTIVE The goal of this study was to use a large national registry to evaluate the 30-day cumulative incidence and predictors of adverse events, readmissions, and reoperations after surgery for primary and secondary spinal tumors. METHODS Data from adult patients who underwent surgery for spinal tumors (2011-2014) were extracted from the prospective National Surgical Quality Improvement Program (NSQIP) registry. Multivariable logistic regression was used to evaluate predictors of reoperation, readmission, and major complications (death, neurological, cardiopulmonary, venous thromboembolism [VTE], surgical site infection [SSI], and sepsis). Variables screened included patient age, sex, tumor location, American Society of Anesthesiologists (ASA) physical classification, preoperative functional status, comorbidities, preoperative laboratory values, case urgency, and operative time. Additional variables that were evaluated when analyzing readmission included complications during the surgical hospitalization, hospital length of stay (LOS), and discharge disposition. RESULTS Among the 2207 patients evaluated, 51.4% had extradural tumors, 36.4% had intradural extramedullary tumors, and 12.3% had intramedullary tumors. By spinal level, 20.7% were cervical lesions, 47.4% were thoracic lesions, 29.1% were lumbar lesions, and 2.8% were sacral lesions. Readmission occurred in 10.2% of patients at a median of 18 days (interquartile range [IQR] 12-23 days); the most common reasons for readmission were SSIs (23.7%), systemic infections (17.8%), VTE (12.7%), and CNS complications (11.9%). Predictors of readmission were comorbidities (dyspnea, hypertension, and anemia), disseminated cancer, preoperative steroid use, and an extended hospitalization. Reoperation occurred in 5.3% of patients at a median of 13 days (IQR 8-20 days) postoperatively and was associated with preoperative steroid use and ASA Class 4-5 designation. Major complications occurred in 14.4% of patients: the most common complications and their median time to occurrence were VTE (4.5%) at 9 days (IQR 4-19 days) postoperatively, SSIs (3.6%) at 18 days (IQR 14-25 days), and sepsis (2.9%) at 13 days (IQR 7-21 days). Predictors of major complications included dependent functional status, emergency case status, male sex, comorbidities (dyspnea, bleeding disorders, preoperative systemic inflammatory response syndrome, preoperative leukocytosis), and ASA Class 3-5 designation (p < 0.05). The median hospital LOS was 5 days (IQR 3-9 days), the 30-day mortality rate was 3.3%, and the median time to death was 20 days (IQR 12.5-26 days). CONCLUSIONS In this NSQIP analysis, 10.2% of patients undergoing surgery for spinal tumors were readmitted within 30 days, 5.3% underwent a reoperation, and 14.4% experienced a major complication. The most common complications were SSIs, systemic infections, and VTE, which often occurred late (after discharge from the surgical hospitalization). Patients were primarily readmitted for new complications that developed following discharge rather than exacerbation of complications from the surgical hospital stay. The strongest predictors of adverse events were comorbidities, preoperative steroid use, and higher ASA classification. These models can be used by surgeons to risk-stratify patients preoperatively and identify those who may benefit from increased surveillance following hospital discharge.

A novel score to predict shunt dependency after aneurysmal subarachnoid hemorrhage.

OBJECTIVE Feasible clinical scores for predicting shunt-dependent hydrocephalus (SDHC) after aneurysmal subarachnoid hemorrhage (aSAH) are scarce. The chronic hydrocephalus ensuing from SAH score (CHESS) was introduced in 2015 and has a high predictive value for SDHC. Although this score is easy to calculate, several early clinical and radiological factors are required. The authors designed the retrospective analysis described here for external CHESS validation and determination of predictive values for the radiographic Barrow Neurological Institute (BNI) scoring system and a new simplified combined scoring system. METHODS Consecutive data of 314 patients with aSAH were retrospectively analyzed with respect to CHESS parameters and BNI score. A new score, the shunt dependency in aSAH (SDASH) score, was calculated from independent risk factors identified with multivariate analysis. RESULTS Two hundred twenty-five patients survived the initial phase after the hemorrhage, and 27.1% of these patients developed SDHC. The SDASH score was developed from results of multivariate analysis, which revealed acute hydrocephalus (aHP), a BNI score of ≥ 3, and a Hunt and Hess (HH) grade of ≥ 4 to be independent risk factors for SDHC (ORs 5.709 [aHP], 6.804 [BNI], and 4.122 [HH]; p < 0.001). All 3 SDHC scores tested (CHESS, BNI, and SDASH) reliably predicted chronic hydrocephalus (ORs 1.533 [CHESS], 2.021 [BNI], and 2.496 [SDASH]; p ≤ 0.001). Areas under the receiver operating curve (AUROC) for CHESS and SDASH were comparable (0.769 vs 0.785, respectively; p = 0.447), but the CHESS and SDASH scores were superior to the BNI grading system for predicting SDHC (BNI AUROC 0.649; p = 0.014 and 0.001, respectively). In contrast to CHESS and BNI scores, an increase in the SDASH score coincided with a monotonous increase in the risk of developing SDHC. CONCLUSIONS The newly developed SDASH score is a reliable tool for predicting SDHC. It contains fewer factors and is more intuitive than existing scores that were shown to predict SDHC. A prospective score evaluation is needed.

The application of adult traumatic brain injury models in a pediatric cohort.

OBJECTIVE There is increasing interest in the use of predictive models of outcome in adult head injury. Two international models have been identified to be reliable modalities for predicting outcome: the Corticosteroid Randomisation After Significant Head Injury (CRASH) model, and the International Mission on Prognosis and Analysis of randomized Controlled Trials in TBI (IMPACT) model. However, these models are designed only to identify outcomes in adult populations. METHODS A retrospective analysis was performed on pediatric patients with severe traumatic brain injury (TBI) admitted to the pediatric intensive care unit (PICU) of Addenbrooke's Hospital between January 2009 and December 2013. The individual risk of 14-day mortality was calculated using the CRASH-Basic and -CT models, and the risk of 6-month mortality calculated using the IMPACT-Core and -Extended (including CT findings) models. Model accuracy was determined by standardized mortality ratio (SMtR; observed/expected deaths), discrimination was evaluated as the area under the receiver operating curve (AUROC), and calibration assessed using the Hosmer-Lemeshow χ2 test. RESULTS Ninety-four patients with an average age of 7.3 years were admitted to the PICU with a TBI. The mortality rate was 12.7% at 14 days and at 6 months. For the CRASH-Basic model, the SMtR was 1.42 and both calibration (χ2 = 6.1, p = 0.64) and discrimination (AUROC = 0.92) were good. For the IMPACT-Core model, the SMtR was 1.03 and the model was also well calibrated (χ2 = 8.99, p = 0.34) and had good discrimination (AUROC = 0.85). Poor outcome was observed in 17% of the cohort and identified with the CRASH-Basic and IMPACT-Core models to varying degrees: standardized morbidity ratio = 0.89 vs 0.67, respectively; calibration = 6.5 (χ2) and 0.59 (p value) versus 8.52 (χ2) and 0.38 (p value), respectively; and discrimination (AUROC) = 0.92 versus 0.83, respectively. CONCLUSIONS Adult head injury models may be applied with sufficient accuracy to identify predictors of morbidity and mortality in pediatric TBI.