Utility of the ACS‐NSQIP surgical risk calculator in predicting postoperative complications in patients undergoing oncologic proximal femoral replacement

2021 ◽  
Author(s):  
Joshua R. Labott ◽  
Elyse J. Brinkmann ◽  
Mario Hevesi ◽  
Cody C. Wyles ◽  
Cory G. Couch ◽  
...  
Keyword(s):  
Postoperative Complications ◽  
Risk Calculator ◽  
Surgical Risk ◽  
Acs Nsqip

The ACS-NSQIP surgical risk calculator is a poor predictor of postoperative complications in patients undergoing oncologic distal femoral replacement

The Knee ◽  
2021 ◽  
Vol 33 ◽  
pp. 17-23
Author(s):  
Joshua R. Labott ◽  
Elyse J. Brinkmann ◽  
Mario Hevesi ◽  
Cory G. Couch ◽  
Peter S. Rose ◽  
...  
Keyword(s):  
Postoperative Complications ◽  
Risk Calculator ◽  
Surgical Risk ◽  
Acs Nsqip ◽  
Poor Predictor ◽  
Distal Femoral Replacement

Can the ACS‐NSQIP surgical risk calculator predict postoperative complications in patients undergoing sacral tumor resection for chordoma?

2020 ◽  
Vol 121 (6) ◽  
pp. 1036-1041 ◽  
Author(s):  
Matthew T. Houdek ◽  
Mario Hevesi ◽  
Anthony M. Griffin ◽  
Michael J. Yaszemski ◽  
Franklin H. Sim ◽  
...  
Keyword(s):  
Postoperative Complications ◽  
Tumor Resection ◽  
Risk Calculator ◽  
Surgical Risk ◽  
Acs Nsqip ◽  
Sacral Tumor

Correlation of perioperative risk scores with hospital costs in neurosurgical patients

2020 ◽  
Vol 132 (3) ◽  
pp. 818-824
Author(s):  
Sasha Vaziri ◽  
Joseph M. Abbatematteo ◽  
Max S. Fleisher ◽  
Alexander B. Dru ◽  
Dennis T. Lockney ◽  
...  
Keyword(s):  
Surgical Site Infection ◽  
Hospital Costs ◽  
Patient Characteristics ◽  
Risk Scores ◽  
Site Infection ◽  
Risk Calculator ◽  
Surgical Risk ◽  
Acs Nsqip ◽  
Neurosurgical Patients ◽  
Predicted Risk

OBJECTIVEThe 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.METHODSA 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.RESULTSThe 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).CONCLUSIONSPrevious 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.

Inadequate prediction of postoperative complications in breast cancer surgery: An evaluation of the ACS Surgical Risk Calculator

2021 ◽  
Author(s):  
Miguel A. Gonzalez‐Woge ◽  
Karla S. Martin‐Tellez ◽  
Ricardo Gonzalez‐Woge ◽  
Kevin Teran‐De‐la‐Sancha ◽  
Marco Rosa‐Abaroa ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Postoperative Complications ◽  
Cancer Surgery ◽  
Breast Cancer Surgery ◽  
Risk Calculator ◽  
Surgical Risk

Validation of the ACS NSQIP Surgical Risk Calculator in older patients with colorectal cancer undergoing elective surgery

2021 ◽  
Vol 12 (8) ◽  
pp. S67
Author(s):  
H. Van der Hulst ◽  
J.W.T. Dekker ◽  
E. Bastiaannet ◽  
J. van der Bol ◽  
F. van den Bos ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Older Patients ◽  
Elective Surgery ◽  
Risk Calculator ◽  
Surgical Risk ◽  
Acs Nsqip

scholarly journals Performance Comparison between SURPAS and ACS NSQIP Surgical Risk Calculator in Pulmonary Resection

2020 ◽  
Author(s):  
Neel P. Chudgar ◽  
Shi Yan ◽  
Meier Hsu ◽  
Kay See Tan ◽  
Katherine D. Gray ◽  
...  
Keyword(s):  
Pulmonary Resection ◽  
Performance Comparison ◽  
Risk Calculator ◽  
Surgical Risk ◽  
Acs Nsqip

scholarly journals Whipple-specific complications result in prolonged length of stay not accounted for in ACS-NSQIP Surgical Risk Calculator

HPB ◽  
2017 ◽  
Vol 19 (2) ◽  
pp. 147-153 ◽  
Author(s):  
Brian M. Cusworth ◽  
Bradley A. Krasnick ◽  
Timothy M. Nywening ◽  
Cheryl A. Woolsey ◽  
Ryan C. Fields ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Risk Calculator ◽  
Surgical Risk ◽  
Prolonged Length ◽  
Acs Nsqip

Predictive performance of the American College of Surgeons universal risk calculator in neurosurgical patients

2018 ◽  
Vol 128 (3) ◽  
pp. 942-947 ◽  
Author(s):  
Sasha Vaziri ◽  
Jacob Wilson ◽  
Joseph Abbatematteo ◽  
Paul Kubilis ◽  
Saptarshi Chakraborty ◽  
...  
Keyword(s):  
Predictive Performance ◽  
Decision Support Tool ◽  
Patient Characteristics ◽  
Risk Calculator ◽  
Discriminative Performance ◽  
Surgical Risk ◽  
Support Tool ◽  
Acs Nsqip ◽  
C Statistic ◽  
Neurosurgical Patients

OBJECTIVEThe 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.METHODSA 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.RESULTSThe 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.CONCLUSIONSThis 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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