Does the ACS NSQIP Surgical Risk Calculator Accurately Predict Complications Rates After Anterior Lumbar Interbody Fusion Procedures?

STUDY DESIGN: Clinical case series. OBJECTIVE: The aim of this study was to determine the effectiveness of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) surgical risk calculator in the prediction of complications after anterior lumbar interbody fusion (ALIF). SUMMARY OF BACKGROUND DATA: Identifying at-risk patients may aid in the prevention of complications after spine procedures. The ACS NSQIP surgical risk calculator was developed to predict 30-day postoperative complications for a variety of operative procedures. METHODS: Medical records of patients undergoing ALIF at our institution from 2009 to 2019 were retrospectively reviewed. Demographic and comorbidity variables were entered into the ACS NSQIP surgical risk calculator to generate percentage predictions for complication incidence within 30 days postoperatively. The observed incidences of these complications were also abstracted from the medical record. The predictive ability of the ACS NSQIP surgical risk calculator was assessed in comparison to the observed incidence of complications using area under the curve (AUC) analyses. RESULTS: Two hundred fifty-three (253) patients were analyzed. The ACS NSQIP surgical risk calculator was a fair predictor of discharge to non-home facility (AUC 0.71) and surgical site infection (AUC 0.70). The ACS NSQIP surgical risk calculator was a good predictor of acute kidney injury/progressive renal insufficiency (AUC 0.81). The ACS NSQIP surgical risk calculator was not an adequate predictive tool for any other category, including: pneumonia, urinary tract infections, venous thromboembolism, readmission, reoperations, and aggregate complications (AUC < 0.70). CONCLUSION: The ACS NSQIP surgical risk calculator is an adequate predictive tool for a subset of complications after ALIF including acute kidney injury/progressive renal insufficiency, surgical site infections, and discharge to non-home facilities. However, it is a poor predictor for all other complication groups. The reliability of the ACS NSQIP surgical risk calculator is limited, and further identification of models for risk stratification is necessary for patients undergoing ALIF.Level of Evidence: 3.

Increasing hospital admissions for patellar instability: a national database study from 2004 to 2017.

Objectives: Epidemiology of patellar instability is not fully characterized, as some studies have produced conflicting information or been drawn from limited populations. In this study, we used the Pediatric Health Information System (PHIS) database to examine trends in admissions for patellar instability throughout the United States. We hypothesized that there would be an increasing rate of patellar instability admissions in recent years. Secondarily, we examined how demographic factors and insurance status relate to admissions for patellar instability.Methods: This study queried the Pediatric Health Information System (PHIS). Patients with ICD 9 & 10 codes 8363, 8364, 71,785, M221.0, S83.001, S83.002, S83.003, S83.004, S83.005, and S83.006, were abstracted from PHIS. We included all patients admitted with patellofemoral dislocations that were reported in the PHIS database between 1 January 2004 and 30 April 2017. The rate of patellar instability admissions was examined as well as demographic factors and insurance status.Results: An estimated total of 25,413 admissions for patellar instability were identified by the search of the PHIS database; 15,444 (60.8%) were female patients and 9,966 (39.2%) were male. The adjusted number of admissions per reporting hospital significantly increased over the years studied (r = 0.775, p < 0.001), from 14.5 admissions per reporting hospital in 2004 to 86.0 admissions per reporting hospital in 2016. Of all patellar instability admissions, 55.0% were white, 20.4% were black, 1.7% were Asian, and 22.9% were unknown race. A larger number of admissions occurred in patients with insurance status other than Medicaid in every year data were collected.Conclusions: Based on a PHIS database search, pediatric hospital admissions for patellar instability are steadily increasing. The majority of patients admitted for patellar instability are female, white, and have insurance other than Medicaid. Males admitted for patellar instability tended to be older than females admitted for the same.Level of evidence: II.