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  • Author or Editor: Joseph Abbatematteo x
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Sasha Vaziri, Jacob Wilson, Joseph Abbatematteo, Paul Kubilis, Saptarshi Chakraborty, Khare Kshitij and Daniel J. Hoh

OBJECTIVE

The American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) universal Surgical Risk Calculator is an online decision-support tool that uses patient characteristics to estimate the risk of adverse postoperative events. Further validation of this risk calculator in the neurosurgical population is needed; therefore, the object of this study was to assess the predictive performance of the ACS NSQIP Surgical Risk Calculator in neurosurgical patients treated at a tertiary care center.

METHODS

A single-center retrospective review of 1006 neurosurgical patients treated in the period from September 2011 through December 2014 was performed. Individual patient characteristics were entered into the NSQIP calculator. Predicted complications were compared with actual occurrences identified through chart review and administrative quality coding data. Statistical models were used to assess the predictive performance of risk scores. Traditionally, an ideal risk prediction model demonstrates good calibration and strong discrimination when comparing predicted and observed events.

RESULTS

The ACS NSQIP risk calculator demonstrated good calibration between predicted and observed risks of death (p = 0.102), surgical site infection (SSI; p = 0.099), and venous thromboembolism (VTE; p = 0.164) Alternatively, the risk calculator demonstrated a statistically significant lack of calibration between predicted and observed risk of pneumonia (p = 0.044), urinary tract infection (UTI; p < 0.001), return to the operating room (p < 0.001), and discharge to a rehabilitation or nursing facility (p < 0.001). The discriminative performance of the risk calculator was assessed using the c-statistic. Death (c-statistic 0.93), UTI (0.846), and pneumonia (0.862) demonstrated strong discriminative performance. Discharge to a rehabilitation facility or nursing home (c-statistic 0.794) and VTE (0.767) showed adequate discrimination. Return to the operating room (c-statistic 0.452) and SSI (0.556) demonstrated poor discriminative performance. The risk prediction model was both well calibrated and discriminative only for 30-day mortality.

CONCLUSIONS

This study illustrates the importance of validating universal risk calculators in specialty-specific surgical populations. The ACS NSQIP Surgical Risk Calculator could be used as a decision-support tool for neurosurgical informed consent with respect to predicted mortality but was poorly predictive of other potential adverse events and clinical outcomes.

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Sasha Vaziri, Joseph M. Abbatematteo, Max S. Fleisher, Alexander B. Dru, Dennis T. Lockney, Paul S. Kubilis and Daniel J. Hoh

OBJECTIVE

The American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) online surgical risk calculator uses inherent patient characteristics to provide predictive risk scores for adverse postoperative events. The purpose of this study was to determine if predicted perioperative risk scores correlate with actual hospital costs.

METHODS

A single-center retrospective review of 1005 neurosurgical patients treated between September 1, 2011, and December 31, 2014, was performed. Individual patient characteristics were entered into the NSQIP calculator. Predicted risk scores were compared with actual in-hospital costs obtained from a billing database. Correlational statistics were used to determine if patients with higher risk scores were associated with increased in-hospital costs.

RESULTS

The Pearson correlation coefficient (R) was used to assess the correlation between 11 types of predicted complication risk scores and 5 types of encounter costs from 1005 health encounters involving neurosurgical procedures. Risk scores in categories such as any complication, serious complication, pneumonia, cardiac complication, surgical site infection, urinary tract infection, venous thromboembolism, renal failure, return to operating room, death, and discharge to nursing home or rehabilitation facility were obtained. Patients with higher predicted risk scores in all measures except surgical site infection were found to have a statistically significant association with increased actual in-hospital costs (p < 0.0005).

CONCLUSIONS

Previous work has demonstrated that the ACS NSQIP surgical risk calculator can accurately predict mortality after neurosurgery but is poorly predictive of other potential adverse events and clinical outcomes. However, this study demonstrates that predicted high-risk patients identified by the ACS NSQIP surgical risk calculator have a statistically significant moderate correlation to increased actual in-hospital costs. The NSQIP calculator may not accurately predict the occurrence of surgical complications (as demonstrated previously), but future iterations of the ACS universal risk calculator may be effective in predicting actual in-hospital costs, which could be advantageous in the current value-based healthcare environment.

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Maryam Rahman, Joseph Abbatematteo, Edward K. De Leo, Paul S. Kubilis, Sasha Vaziri, Frank Bova, Elias Sayour, Duane Mitchell and Alfredo Quinones-Hinojosa

OBJECTIVE

An increased extent of resection (EOR) has been shown to improve overall survival of patients with glioblastoma (GBM) but has the potential for causing a new postoperative neurological deficit. To investigate the impact of surgical neurological morbidity on survival, the authors performed a retrospective analysis of the clinical data from patients with GBM to quantify the impact of a new neurological deficit on the survival benefit achieved with an increased EOR.

METHODS

The data from all GBM patients who underwent resection at the University of Florida from 2010 to 2015 with postoperative imaging within 72 hours of surgery were included in the study. Retrospective analysis was performed on clinical outcomes and tumor volumes determined on postoperative and follow-up imaging examinations.

RESULTS

Overall, 115 patients met the inclusion criteria for the study. Tumor volume at the time of presentation was a median of 59 cm3 (enhanced on T1-weighted MRI scans). The mean EOR (± SD) was 94.2% ± 8.7% (range 59.9%–100%). Almost 30% of patients had a new postoperative neurological deficit, including motor weakness, sensory deficits, language difficulty, visual deficits, confusion, and ataxia. The neurological deficits had resolved in 41% of these patients on subsequent follow-up examinations. The median overall survival was 13.1 months (95% CI 10.9–15.2 months). Using a multipredictor Cox model, the authors observed that increased EOR was associated with improved survival except for patients with smaller tumor volumes (≤ 15 cm3). A residual volume of 2.5 cm3 or less predicted a favorable overall survival. Developing a postoperative neurological deficit significantly affected survival (9.2 months compared with 14.7 months, p = 0.02), even if the neurological deficit had resolved by the first follow-up. However, there was a trend of improved survival among patients with resolution of a neurological deficit by the first follow-up compared with patients with a permanent neurological deficit. Any survival benefit from achieving a 95% EOR was abrogated by the development of a new neurological deficit postoperatively.

CONCLUSIONS

Developing a new neurological deficit after resection of GBM is associated with a decrease in overall survival. A careful balance between EOR and neurological compromise needs to be taken into account to reduce the likelihood of neurological morbidity from surgery.