ACS NSQIP Surgical Risk Calculator Research Articles

A comparative assessment of ACS NSQIP-predicted and actual surgical risk outcomes of robotic transhiatal esophagectomy for esophageal adenocarcinoma resection at a high volume institution.

Esophageal adenocarcinoma incidence is increasing in Western nations. There has been a shift toward minimally invasive approaches for transhiatal esophagectomy (THE). This study compares the outcomes of robotic THE for esophageal adenocarcinoma resection at our institution with the predicted metrics from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP). With Institutional Review Board (IRB) approval, we prospectively followed 83 patients who underwent robotic THE from 2012 to 2023. Predicted outcomes were determined using the ACS NSQIP Surgical Risk Calculator. Our outcomes were compared with these predicted outcomes and with general outcomes for transhiatal esophagectomy reported in ACS NSQIP, which includes a mix of surgical approaches. The median age of patients was 70years, with a body mass index (BMI) of 26.4kg/m2 and a male prevalence of 82%. The median length of stay was 7days. The rates of any complications and in-hospital mortality were 16% and 5%, respectively. Seven patients (8%) were readmitted within a 30-day postoperative window. The median survival is anticipated to surpass 95months. Our outcomes were generally aligned with or surpassed the predicted ACS NSQIP metrics. The extended median survival of over 95months highlights the potential effectiveness of robotic THE in the resection of esophageal adenocarcinoma. Further exploration into its long-term survival benefits and outcomes is warranted, along with studies that provide a more direct comparison between robotic and other surgical approaches.

Validity of the ACS NSQIP surgical risk calculator as a tool to predict postoperative outcomes in subacute orthopedic trauma diagnoses

PurposeThis retrospective study aimed to validate the ACS NSQIP Surgical Risk Calculator (SCR) to predict 30-day postoperative outcomes in patients with one of the following subacute orthopedic trauma diagnoses; multiple rib fractures, pelvic ring/acetabular fracture, or unilateral femoral fracture. MethodsData of patients with these diagnoses treated between January 1, 2015 and September 19, 2020 were extracted from the patients’ medical files. Diagnostic performance, discrimination, calibration, and accuracy of the ACS NSQIP SRC to predict specific outcomes developing within 30 days after surgery was determined. ResultsThe total cohort of the three diagnoses consisted of 435 patients. ACS NSQIP SRC underestimated the risk for serious complications, especially in patients with multiple rib fractures (8.3% predicted vs 17.2% observed) or pelvic ring/acetabular fracture (6.1% vs 19.8%). Underestimation was more pronounced for the composite outcome ‘any complication’. Sensitivity ranged from 16.7% to 100% and specificity from 41.1% to 97.1%. Specificity exceeded sensitivity for pelvic ring/acetabular and femoral fractures. Discrimination was good for predicting death (femoral fracture), fair for readmission (femoral fracture), serious complication (multiple rib fractures), and any complication (multiple rib fractures), but poor in all other outcomes and diagnoses. Calibration and accuracy were adequate for all three diagnoses (p-value for Hosmer-Lemeshow test >0.05 and Brier scores <0.25). ConclusionPerformance of the ACS NSQIP SRC in the studied cohort was variable for all three diagnoses. Although it underestimated the risk of most outcomes, calibration and accuracy seemed generally adequate. For most outcomes, adequate diagnostic performance and discrimination could not be confirmed.

Evaluation of the ACS NSQIP surgical risk calculator in patients undergoing common bile duct exploration.

The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) surgical risk calculator is a risk stratification tool to help predict risks of postoperative complications, which is important for informed decision-making. The purpose of this study was to evaluate the accuracy of the calculator in predicting postoperative complications in patients undergoing common bile duct (CBD) exploration. A retrospective chart review was completed for 305 patients that underwent open and laparoscopic CBD exploration at a single institution from 2010 to 2018. Patient demographics and preoperative risk factors were entered into the calculator, and the predicted complication risks were compared with observed complication rates. Brier score, C-statistic, and Hosmer-Lemeshow regression analysis were used to assess discrimination and calibration. The observed rate exceeded the predicted rate for any complication (35.1% vs. 21%), return to operating room (5.9% vs. 3.6%), death (3.3% vs. 1%), and sepsis (3% vs. 2.4%). The model performed best in predicting serious complication (Brier 0.087, C-statistic 0.818, Hosmer-Lemeshow 0.695), surgical site infection (Brier 0.068, C-statistic 0.670, Hosmer-Lemeshow 0.292), discharge to rehabilitation facility (Brier 0.041, C-statistic 0.907, Hosmer-Lemeshow 0.638), and death (Brier 0.028, C-statistic 0.898, Hosmer-Lemeshow 0.004). In multivariable analysis, there was no statistically significant predicted complication type that affected the type of surgery. The calculator was accurate in predicting serious complication, surgical site infection, discharge to rehabilitation facility, and death. However, the model displayed poor predictive ability in all other complications that were analyzed.

Hypoalbuminemia improves the ACS-NSQIP surgical risk calculator for gastrectomy

BackgroundThe ACS-NSQIP Surgical Risk Calculator (SRC) is used to predict surgical outcomes, but its accuracy in gastrectomy has been questioned.1,2 We investigated if adding hypoalbuminemia enhances its predictive ability in gastrectomy. MethodsWe identified gastrectomy patients from the ACS-NSQIP database from 2005 to 2019. We constructed pairs of logistic regression models: one with the existing 21 preoperative risk factors from the SRC and another with the addition of hypoalbuminemia. We evaluated improvement using Likelihood Ratio Test (LRT), Brier scores, and c-statistics. ResultsOf 18,070 gastrectomy patients, 34.5 ​% had hypoalbuminemia. Hypoalbuminemia patients had 2.34 higher odds of mortality and 1.79 higher odds of morbidity. Adding hypoalbuminemia to the RC model statistically improved predictions for mortality, cumulative morbidity, pulmonary, renal, and wound complications (LRT p ​< ​0.001). It did not improve predictions for cardiac complications (LRT p ​= ​0.11) ConclusionHypoalbuminemia should be considered as an additional variable to the ACS-NSQIP SRC for gastrectomy.

Accuracy of the ACS NSQIP Surgical Risk Calculator for Predicting Postoperative Complications in Gastric Cancer Following Open Gastrectomy.

The prediction of complications before gastric surgery is of utmost importance in shared decision making and proper counseling of the patient in order to minimize postoperative complications. Our aim was to evaluate the predictive validity of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) risk calculator in gastric cancer patients who underwent gastrectomy. Preoperative assessment data of 432 patients were retrospectively reviewed and manually entered into the calculator. The accuracy of the calculator was evaluated using Pearson's chi-squared test, C-statistic, Brier score, and Hosmer-Lemeshow test. The lowest Brier scores were observed in urinary tract infection, renal failure, venous thromboembolism, pneumonia, and cardiac complications. Best results were obtained for predicting sepsis, discharge to rehabilitation facility, and death (low Brier scores, C-statistic >.7, and Hosmer-Lemeshow P > .05). The calculator had a strong performance in predicting sepsis, discharge to the rehabilitation facility, and death. However, it performed poor in predicting the most commonly observed events (any or serious complication and surgical site infection).

Evaluation of the ACS-NSQIP Surgical Risk Calculator in Patients with Hepatic Metastases from Colorectal Cancer Undergoing Liver Resection

BackgroundThe American College of Surgeons National Surgical Quality Improvement Program surgical risk calculator (ACS-NSQIP SRC) has been designed to predict morbidity and mortality and help stratify surgical patients. This study evaluates the performance of the SRC for patients undergoing surgery for colorectal liver metastases (CRLM). MethodsSRC was retrospectively computed for patients undergoing liver or simultaneous colon and liver surgery for colorectal cancer (CRC) in two high tertiary referral centres from 2011 to 2020. C-statistics and Brier score were calculated as a mean of discrimination and calibration respectively, for both group and for every level of surgeon adjustment score (SAS) for liver resections in case of simultaneous liver-colon surgery. An AUC ≥ 0.7 shows acceptable discrimination; a Brier score next to 0 means the prediction tool has good calibration. ResultsFour hundred ten patients were included, 153 underwent simultaneous resection, and 257 underwent liver-only resections. For simultaneous surgery, the ACS-NSQIP SRC showed good calibration and discrimination only for cardiac complication (AUC = 0.720, 0.740, and 0.702 for liver resection unadjusted, SAS-2, and SAS-3 respectively; 0.714 for colon resection; and Brier score = 0.04 in every case). For liver-only surgery, it only showed good calibration for cardiac complications (Brier score = 0.03). The SRC underestimated the incidence of overall complications, pneumonia, cardiac complications, and the length of hospital stay. ConclusionsACS-NSQIP SRC showed good predicting capabilities only for 1 out of 5 evaluated outcomes; therefore, it is not a reliable tool for patients undergoing liver surgery for CRLM, both in the simultaneous and staged resections.

Surgical mortality in patients in extremis: futility in emergency abdominal surgery

BackgroundThe number of older patients with multiple comorbidities in the emergency service is increasingly frequent, which implies the risk of incurring in futile surgical interventions. Some interventions generate false expectations of survival or quality of life in patients and families and represent a negligible therapeutic benefit in patients whose chances of survival are minimal. In order to address this dilemma, we describe mortality in a cohort of patients undergoing emergency laparotomy with a risk ≥ 75% per the ACS NSQIP Surgical Risk Calculator.MethodsA retrospective observational study was designed to analyze postoperative mortality and factors associated with postoperative mortality in a cohort of patients undergoing emergency laparotomy between January 2018 and December 2021 in a high-complexity hospital who had a mortality risk ≥ 75% per the ACS NSQIP Surgical Risk Calculator.ResultsA total of 890 emergency laparotomies were performed during the study period, and 50 patients were included for the analysis. Patient median age was 82.5 (IQR: 18.25) years old and 33 (66.00%) were male. The most frequent diagnoses were mesenteric ischemia 21 (42%) and secondary peritonitis 18 (36%). Mortality in the series was 92%. Twenty-four (54.34%) died within the first 24 h of the postoperative period; 11 (23.91%) within 72 h and 10 (21.73%) within 30 days. APACHE II and SOFA scores were statistically significantly higher in patients who died.ConclusionsAll available tools should be used to make decisions, with the most reliable and objective information possible, and be particularly vigilant in patients at extreme risk (mortality risk greater than 75% according to ACS NSQIP Surgical Risk Calculator) to avoid futility and its consequences. The available information should be shared with the patient, the family, or their guardians through an assertive and empathetic communication strategy. It is necessary to insist on a culture of surgical ethics based on reflection and continuous improvement in patient care and to know how to accompany them in order to have a proper death.

ACS-NSQIP – Surgical risk calculator accurately predicts outcomes of laparotomy in a prospective study at a tertiary hospital in Tanzania

Introduction: The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) surgical risk calculator is excellent in predicting postoperative complications. Validation in resource-limited settings and applicability in gastrointestinal surgery is still unclear. Objective: The study aimed to determine the accuracy of the ACS-NSQIP surgical risk calculator in predicting the 30days postoperative adverse outcomes among patients who underwent laparotomy. Methods: A Single hospital-based, prospective cohort study was done at Muhimbili National Hospital in Tanzania from April 2021 to December 2021 recruiting patients aged 18 and above who underwent primary laparotomy. SR calculator variables were obtained from patients and entered manually to categorize patients into low and high-risk. Patients were followed up for thirty days for the outcome. The predicted risk was compared with actual occurrence to obtain personal risk ratios. The c-statistics of &gt; 0.7, Brier of score &lt; 0.25 and Index of Prediction Accuracy score were used for discrimination, accuracy, and usefulness of the model respectively. Results: ACS -NSQIP SR-Calculator discriminated well the risks of cardiac complications, re-laparotomy, Anastomotic leak, and death (c-statistic &gt; 0.7) Poor discrimination was observed for the length of hospital stay (c-statistics 0.518). However, SR-calculator shows high calibration potential for all complications with a Brier score &lt; 0.25 (0.002 - 0.144) and an IPA score ranging from 0.225 - 0.969. Conclusion: The ACS -NSQIP SR-calculator accurately predicted postoperative outcomes for patients requiring laparotomy. SR-Calculator is a reliable tool for preoperative shared decision-making and counseling. The model should be adopted to strengthen the healthcare system in a low-income country. What is already known about this subject?  The ACS NSQIP surgical risk calculator is accurate in predicting the outcome of the Surgical procedure.  ACS NSQIP surgical risk calculator was validated in the USA  The SRC is associated with surgical care improvement whenever applied. What are the new findings?  The SRC accurately predicted the 30-day outcomes associated with primary laparotomy except for the length of hospital stay, discharge for other services, and veno-thromboembolic events.  The risk ratio (RR) provides a preliminary estimation of specific complications for a single patient.  Index of prediction Accuracy (IPA) reliably summarizes the discrimination and calibration of the ACS-NSQIP-SR-Calculator.  The SRC can be validated in a resource-limited setting and can be a source of surgical care improvement. How might these results affect future research or surgical practice?  The results of this study will provide a comparison between our institution and other international situations where a calculator had been tested and surgical service improvement locally. Our findings will provide insights into our loco-regional surgical institutions in the low-income country to conduct cross-specialties and institutional research toward the adoption of ACS-NSQIP-SRC into National surgical improvement programs. Informative to the surgical community on the performance of the SR-calculator outside the USA.

What's New in Musculoskeletal Tumor Surgery.

What's New in Musculoskeletal Tumor Surgery.

Risk Prediction for Complications in Inflammatory Bowel Disease Surgery: External Validation of the American College of Surgeons' National Surgical Quality Improvement Program Surgical Risk Calculator.

Many patients with inflammatory bowel disease [IBD] require surgery during their disease course. Having individual risk predictions available prior to surgery could aid in better informed decision making for personalised treatment trajectories in IBD surgery. The American College of Surgeons National Surgical Quality Improvement Program [ACS NSQIP] has developed a surgical risk calculator that calculates risks for postoperative outcomes using 20 patient and surgical predictors. We aimed to validate the calculator for IBD surgery to determine its accuracy in this patient cohort. Predicted risks were calculated for patients operated for IBD between December 2017 and January 2022 at two tertiary centres and compared with actual outcomes within 30 postoperative days. Predictive performance was assessed for several postoperative complications, using metrics for discrimination and calibration. Risks were calculated for 508 patient trajectories undergoing surgery for IBD. Incidence of any complication, serious complications, reoperation, and readmission were 32.1%, 21.1%, 15.2%, and 18.3%, respectively. Of 212 patients with an anastomosis, 19 experienced leakage [9.0%]. Discriminative performance and calibration were modest. Risk prediction for any complication, serious complication, reoperation, readmission, and anastomotic leakage had a c statistic of 0.605 (95% confidence interval [CI] 0.534-0.640), 0.623 [95% CI 0.558-0.688], 0.590 [95% CI 0.513-0.668], 0.621 [95% CI 0.557-0.685], and 0.574 [95% CI 0.396-0.751], respectively, and a Brier score of 0.240, 0.166, 0.138, 0.152, and 0.113, respectively. The accuracy of risks calculated by the ACS NSQIP Surgical Risk Calculator was deemed insufficient for patients undergoing surgery for IBD, generally underestimating postoperative risks. Recalibration or additional variables could be necessary to predict risks in this cohort.

Validation of the ACS NSQIP surgical risk calculator in older patients with colorectal cancer undergoing elective surgery

BackgroundFor clinical decision making it is important to identify patients at risk for adverse outcomes after colorectal cancer (CRC) surgery, especially in the older population. Because the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) surgical risk calculator is potentially useful in clinical practice, we performed an external validation in a Dutch multicenter cohort of patients ≥70 years undergoing elective non-metastatic CRC surgery. MethodsWe compared the ACS NSQIP calculator mean predicted risk to the overall observed rate of anastomotic leakage, return to operation room, pneumonia, discharge not to home, and readmission in our cohort using a one-sample Z-test. Calibration plots and receiver operating characteristic (ROC) curves were used to determine the calculator's performance. ResultsSix hundred eighty-two patients were included. Median age was 76.2 years. The ACS NSQIP calculator accurately predicted the overall readmission rate (predicted: 8.6% vs. observed: 7.8%, p = 0.456), overestimated the rate of discharge not to home (predicted:11.2% vs. observed: 7.0% p = 0.005) and underestimated the observed rate of all other outcomes. The calibration plots showed poor calibration for all outcomes. The ROC-curve showed an area under the curve (AUC) of 0.75 (95% confidence interval [CI] 0.67–0.83) for pneumonia and 0.70 (0.62–0.78) for discharge not to home. The AUC for all other outcomes was poor. ConclusionsThe ACS NSQIP surgical risk calculator had a poor individual risk prediction (calibration) for all outcomes and only a fair discriminative ability (discrimination) to predict pneumonia and discharge not to home. The calculator might be considered to identify patients at high risk of pneumonia and discharge not to home to initiate additional preoperative interventions.

The ACS-NSQIP Surgical Risk Calculator as a Predictor of Mortality in a Series of Surgical Covid-19 Patients.

The ACS-NSQIP Surgical Risk Calculator as a Predictor of Mortality in a Series of Surgical Covid-19 Patients.

Utility of Surgical Risk Calculators in Spine Surgery in Patients Aged Over 80 Years: Analysis of SpineSage and ACS NSQIP.

Retrospective cohort study. To validate the predictive accuracy of both the SpineSage and ACS-NSQIP surgical risk calculators in patients over the age of 80years, undergoing spine surgery for any reason. We included 210 consecutive patients treated with single-stage spine surgery at our institution between 2009 and 2019. The demographic details and preoperative characteristics of each patient were collected and reviewed for entry into both the SpineSage and ACS risk calculators. The estimated risk supplied by these calculators was compared to the observed rate of complications post-surgery. The main method of comparison was using receiver operating characteristic (ROC) curve analysis. Complications were identified in 51 patients (24%). Most patients underwent surgery for a degenerative cause (71%), with the majority of procedures performed on the lumbosacral spine (66%). Receiver operating characteristic (ROC) curves were calculated to compare the outcomes of each tool. Area under the curve (AUC) analysis showed similar predictive accuracy between SpineSage and ACS when predicting overall complications (0.688; P < .001 vs 0.634; P = .021). AUC analysis demonstrated that SpineSage had better predictive accuracy when estimating risk of major complications (0.778; P = .037 vs 0.675; P = .001). For the prediction of risks associated with spine surgery in those aged >80years, SpineSage appears to be preferable to the ACS-NSQIP surgical risk calculator in this single centre cohort, SpineSage was more accurate in predicting the risk of serious medical complications. The accuracy of both of these tools could still be improved upon.

The American College of Surgeons National Surgical Quality Improvement Program surgical risk calculator is not reliable in predicting complications and length of stay after primary total hip arthroplasty at an institution implementing clinical pathways.

The authors aimed to: (1) determine how length of stay (LOS) and complication rates changed over the past 10 years, in comparison to values estimated by the ACS-NSQIP surgical risk calculator, at a single private institution open to external surgeons; and (2) determine preoperative patient factors associated with complications. We retrospectively assessed 1018 consecutive patients who underwent primary elective THA over 10 years. We excluded 87 with tumours and 52 with incomplete records. Clinical data of the remaining 879 were used to determine real LOS and rate of 9 adverse events over time, as well as to estimate these values using the risk calculator. Its predictive reliability was represented on receiver operating characteristic curves. Multivariable analyses were performed to determine associations of complications with age, sex, ASA score, diabetes, hypertension, heart disease, smoking and BMI. Over the 10-year period, real LOS and real complication rates decreased considerably, while LOS and complication rates estimated by the surgical risk calculator had little or no change. The difference between real and estimated LOS decreased over time. The overall estimated and real rates of any complication were respectively 3.3% and 2.8%. The risk calculator had fair reliability for predicting any complications (AUC 0.72). Overall estimated LOS was shorter than the real LOS in 764 (86.9%) patients. Multivariable analysis revealed risks of any complication to be greater in patients aged ⩾75 (OR = 4.36, p = 0.002), and with hypertension (OR = 3.13, p = 0.016). Since the implementation of clinical pathways at our institution, real LOS and complication rates decreased considerably, while LOS and complication rates estimated by the surgical risk calculator had little or no change. The difference between real and estimated LOS decreased over time, which could lead some clinicians to reconsider their discharge criteria, knowing that advanced age and hypertension increased risks of encountering complications.

Evaluating Discrimination of ACS-NSQIP Surgical Risk Calculator in Thyroidectomy Patients

The ACS-NSQIP surgical risk calculator (SRC) often guides preoperative counseling, but the rarity of complications in certain populations causes class imbalance, complicating risk prediction. We aimed to compare the performance of the ACS-NSQIP SRC to other classical machine learning algorithms trained on NSQIP data, and to demonstrate challenges and strategies in predicting such rare events. Data from the NSQIP thyroidectomy module ys 2016 - 2018 were used to train logistic regression, Ridge regression and Random Forest classifiers for predicting 2 different composite outcomes of surgical risk (systemic and thyroidectomy-specific). We implemented techniques to address imbalanced class sizes and reported the area under the receiver operating characteristic (AUC) for each classifier including the ACS-NSQIP SRC, along with sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) at a 5% - 15% predicted risk threshold. Of 18,078 included patients, 405 (2.24%) patients suffered systemic complications and 1670 (9.24%) thyroidectomy-specific complications. Logistic regression performed best for predicting systemic complication risk (AUC 0.723 [0.658 - 0.778]); Random Forest with RUSBoost performed best for predicting thyroidectomy-specific complication risk (0.702; 0.674 - 0.726). The addition of optimizations for class imbalance improved performance for all classifiers. Complications are rare after thyroidectomy even when considered as composite outcomes, and class imbalance poses a challenge in surgical risk prediction. Using the SRC as a classifier where intervention occurs above a certain validated threshold, rather than citing the numeric estimates of complication risk, should be considered in low-risk patients.

SIOG2021-0054* - Validation of the ACS NSQIP Surgical Risk Calculator in older patients with colorectal cancer undergoing elective surgery

SIOG2021-0054* - Validation of the ACS NSQIP Surgical Risk Calculator in older patients with colorectal cancer undergoing elective surgery

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

BackgroundDistal femur replacement (DFR) has become a preferred reconstruction for tumors involving the femur but is associated with known complications. The ACS-NSQIP surgical risk calculator is an online tool developed to estimate postoperative complications in the first 30-days, however, has not been used in patients undergoing DFR. The purpose of this study was determining the utility of the ACS-NSQIP calculator to predict postoperative complications. Methods56 (30 male, 26 female) patients who underwent DFR were analyzed using the CPT codes: 27,365 (Under Excision Procedures on the Femur and Knee Joint), 27,447 (Arthroplasty, knee, condyle and plateau), 27,486 (Revision of total knee arthroplasty, with or without allograft), 27,487 (Revision of total knee arthroplasty, with or without allograft) and 27,488 (Repair, Revision, and/or Reconstruction Procedures on the Femur [Thigh Region] and Knee Joint). The predicted rates of complications were compared to the observed rates. ResultsComplications were noted in 30 (54%) of patients. The predicted risk of complications based off the CPT codes were: 27,356 (14%); 27,447 (5%); 27,486 (7%); 27,487 (8%) and 27,488 (12%). Based on ROC curves, the use of the ACS-NSQIP score were poor predictors of complications (27356, AUC 0.54); (27447, AUC 0.45); (27486, AUC 0.45); (27487, AUC 0.46); (27488, AUC 0.46). ConclusionsDistal femur arthroplasty performed in the setting of oncologic orthopedics is a complex procedure in a “high risk” surgical group. The ACS-NSQIP does not adequately predict the incidence of complications in these patients and cannot be reliably used in the shared decision-making process.

Validation study of the ACS NSQIP surgical risk calculator for two procedures in Japan

IntroductionThe ACS NSQIP Surgical Risk Calculator (SRC) assesses risk to support goal-concordant care. While it accurately predicts US outcomes, its performance internationally is unknown. This study evaluates SRC accuracy in predicting mortality following low anterior resection (LAR) and pancreaticoduodenectomy (PD) in NSQIP patients and accuracy retention when applied to native Japanese patients (National Clinical Database, NCD). MethodsNSQIP (41,260 LAR; 15,114 PD) and NCD cases (61,220 LAR; 27,901 PD) from 2015 to 2017 were processed through the SRC mortality model. Country-specific calibration and discrimination were assessed with and without an intercept correction applied to the Japanese data. ResultsThe SRC exhibited acceptable calibration for LAR and PD when applied to NSQIP data but miscalibration for NCD data. A simple correction to the model intercept, motivated by lower mortality rates in the Japanese data, successfully remediated the miscalibration. ConclusionsThe SRC may inaccurately predict surgical risk when applied to the native Japanese population. An intercept correction method is suggested when miscalibration is encountered; it is simple to implement and may permit effective international use of the SRC.

Comparison of observed vs predicted outcomes from NSQIP for pancreaticoduodenectomy at a pancreatic surgery unit

Introduction: Although the mortality of pancreaticoduodenectomy has decreased significantly over the last few years, with a current 30 day mortality of 1% in NSW hospitals, the morbidity, length of stay and readmission rates remain high when compared to other complex surgical procedures. Our aim was to ascertain accuracy of the ACS NSQIP risk calculator for pancreaticoduodenectomy. Estimating Perioperative risk accurately can allow future patients to make an informed decision about undergoing Pancreaticoduodenectomy; provide a benchmark for safe, high-quality Pancreatic surgery and help target complication-reduction measures for hospital staff. Methods: A retrospective analysis of patients undergoing PancreaticoDuodenectomy at our hospital from July 2015 to July 2017 was performed. Patients found to be inoperable during the procedure or who had subtotal or distal pancreatectomy were excluded. For 5 main parameters, observed outcomes were measured against predicted outcomes using ACS-NSQIP Surgical Risk Calculator for Pancreaticoduodenectomy. Results: During the 24-month period, 45 patients underwent Pancreticodudenectomy for various pathologies, including 16 for pancreatic Adenocarcinoma, 6 for Cholangiocarcinoma, 5 for ampullary adenocarcinoma, 5 NETs, 5 IPMN and 5 others. 30-day mortality was slightly higher than the NSQIP prediction (2 deaths -4.4% vs predicted 1.2% mortality). Return to theatre rate was higher than predicted (8 cases- 17.7% vs 4.3% predicted). There were fewer actual Readmission rates (4.4% vs 11.8% predicted), observed Serious complications (17.7% vs 20.7% predicted) and observed Surgical Site infections (11.1% vs 15.6% predicted). Conclusions: NSQIP Calculator does not accurately predict Observed outcomes for pancreaticoduodenectomy.

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

Clinical case series. 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). 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. 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. 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). 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.