scholarly journals Pancreatectomy risk calculator: an ACS-NSQIP resource

HPB ◽  
2010 ◽  
Vol 12 (7) ◽  
pp. 488-497 ◽  
Author(s):  
Purvi Parikh ◽  
Mira Shiloach ◽  
Mark E. Cohen ◽  
Karl Y. Bilimoria ◽  
Clifford Y. Ko ◽  
...  
Keyword(s):  
2020 ◽  
Vol 132 (3) ◽  
pp. 818-824
Author(s):  
Sasha Vaziri ◽  
Joseph M. Abbatematteo ◽  
Max S. Fleisher ◽  
Alexander B. Dru ◽  
Dennis T. Lockney ◽  
...  

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.


2020 ◽  
Vol 122 (4) ◽  
pp. 795-802
Author(s):  
Patrick B. Schwartz ◽  
Christopher C. Stahl ◽  
Cecilia Ethun ◽  
Nicholas Marka ◽  
George A. Poultsides ◽  
...  

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 ◽  
...  

Author(s):  
Neel P. Chudgar ◽  
Shi Yan ◽  
Meier Hsu ◽  
Kay See Tan ◽  
Katherine D. Gray ◽  
...  

2019 ◽  
Vol 85 (12) ◽  
pp. 1334-1340 ◽  
Author(s):  
Emily A. Armstrong ◽  
Eliza W. Beal ◽  
Alexandra G. Lopez-Aguiar ◽  
George Poultsides ◽  
John G. Cannon ◽  
...  

The ACS established an online risk calculator to help surgeons make patient-specific estimates of postoperative morbidity and mortality. Our objective was to assess the accuracy of the ACS-NSQIP calculator for estimating risk after curative intent resection for primary GI neuroendocrine tumors (GI-NETs). Adult patients with GI-NET who underwent complete resection from 2000 to 2017 were identified using a multi-institutional database, including data from eight academic medical centers. The ability of the NSQIP calculator to accurately predict a particular outcome was assessed using receiver operating characteristic curves and the area under the curve (AUC). Seven hundred three patients were identified who met inclusion criteria. The most commonly performed procedures were resection of the small intestine with anastomosis (N = 193, 26%) and partial colectomy with anastomosis (N = 136, 18%). The majority of patients were younger than 65 years (N = 482, 37%) and ASA Class III (N = 337, 48%). The most common comorbidities were diabetes (N = 128, 18%) and hypertension (N = 395, 56%). Complications among these patients based on ACS NSQIP definitions included any complication (N = 132, 19%), serious complication (N = 118, 17%), pneumonia (N = 7, 1.0%), cardiac complication (N = 1, 0.01%), SSI (N = 80, 11.4%), UTI (N = 17, 2.4%), venous thromboembolism (N = 18, 2.5%), renal failure (N = 16, 2.3%), return to the operating room (N = 27, 3.8%), discharge to nursing/rehabilitation (N = 22, 3.1%), and 30-day mortality (N = 9, 1.3%). The calculator provided reasonable estimates of risk for pneumonia (AUC = 0.721), cardiac complication (AUC = 0.773), UTI (AUC = 0.716), and discharge to nursing/ rehabilitation (AUC = 0.779) and performed poorly (AUC < 0.7) for all other complications Fig. 1). The ACS-NSQIP risk calculator estimates a similar proportion of risk to actual events in patients with GI-NET but has low specificity for identifying the correct patients for many types of complications. The risk calculator may require modification for some patient populations.


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 ◽  
...  

2019 ◽  
Vol 218 (1) ◽  
pp. 131-135 ◽  
Author(s):  
Laura Z. Hyde ◽  
Neda Valizadeh ◽  
Ahmed M. Al-Mazrou ◽  
Ravi P. Kiran

2020 ◽  
Vol 44 (11) ◽  
pp. 3710-3719
Author(s):  
Giovanni Scotton ◽  
Giulio Del Zotto ◽  
Laura Bernardi ◽  
Annalisa Zucca ◽  
Susanna Terranova ◽  
...  

Abstract Background The ACS-NSQIP surgical risk calculator (SRC) is an open-access online tool that estimates the chance for adverse postoperative outcomes. The risk is estimated based on 21 patient-related variables and customized for specific surgical procedures. The purpose of this monocentric retrospective study is to validate its predictive value in an Italian emergency setting. Methods From January to December 2018, 317 patients underwent surgical procedures for acute cholecystitis (n = 103), appendicitis (n = 83), gastrointestinal perforation (n = 45), and intestinal obstruction (n = 86). Patients’ personal risk was obtained and divided by the average risk to calculate a personal risk ratio (RR). Areas under the ROC curves (AUC) and Brier score were measured to assess both the discrimination and calibration of the predictive model. Results The AUC was 0.772 (95%CI 0.722–0.817, p < 0.0001; Brier 0.161) for serious complications, 0.887 (95%CI 0.847–0.919, p < 0.0001; Brier 0.072) for death, and 0.887 (95%CI 0.847–0.919, p < 0.0001; Brier 0.106) for discharge to nursing or rehab facility. Pneumonia, cardiac complications, and surgical site infection presented an AUC of 0.794 (95%CI 0.746–0.838, p < 0.001; Brier 0.103), 0.836 (95%CI 0.790–0.875, p < 0.0001; Brier 0.081), and 0.729 (95%CI 0.676–0.777, p < 0.0001; Brier 0.131), respectively. A RR > 1.24, RR > 1.52, and RR > 2.63 predicted the onset of serious complications (sensitivity = 60.47%, specificity = 64.07%; NPV = 81%), death (sensitivity = 82.76%, specificity = 62.85%; NPV = 97%), and discharge to nursing or rehab facility (sensitivity = 80.00%, specificity = 69.12%; NPV = 95%), respectively. Conclusions The calculator appears to be accurate in predicting adverse postoperative outcomes in our emergency setting. A RR cutoff provides a much more practical method to forecast the onset of a specific type of complication in a single patient.


2018 ◽  
Vol 128 (3) ◽  
pp. 942-947 ◽  
Author(s):  
Sasha Vaziri ◽  
Jacob Wilson ◽  
Joseph Abbatematteo ◽  
Paul Kubilis ◽  
Saptarshi Chakraborty ◽  
...  

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.


2016 ◽  
Vol 114 (2) ◽  
pp. 157-162 ◽  
Author(s):  
Harveshp D. Mogal ◽  
Nora Fino ◽  
Clancy Clark ◽  
Perry Shen
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