Reconstructive approaches to oncologic upper and lower extremity resection in pediatric populations: A retrospective NSQIP-P analysis of 428 patients

INTRODUCTION

Tumors of the soft tissue and bone in the upper and lower extremities are more common in pediatric populations than the general adult population and often require surgical resection or amputation. This retrospective study characterizes reconstructive approaches to such cases and subsequent postoperative outcomes.

METHODS

All oncologic upper and lower extremity resection or amputation cases from 2013-2022 were identified in the NSQIP Pediatric database. Reconstructive approaches for each case were characterized. The main outcome of interest was the occurrence of ≥1 postoperative complication. Predictors of flap reconstruction and predictors of postoperative complications were assessed with stepwise logistic regression (p<0.05).

RESULTS

The final cohort comprised 428 cases. Most common reconstructive approaches included pedicled flaps (24.3%) and complex closure (8.9%). The rate of flap reconstruction increased from 4.4% in 2013-2016 to 34.6% in 2020-2022. Malignant tumors (odds ratio [OR]: 23.2, 95% confidence interval [CI]: 9.32-57.8) predicted higher likelihood of flap reconstruction than benign tumors, and proximal region (OR: 0.27, 95% CI: 0.15-0.51) predicted lower likelihood of flap reconstruction. Postoperative complications occurred in 19.9% of cases. Malignant tumors (OR: 4.39, 95% CI: 2.18-8.85) predicted higher likelihood of complications, and small soft tissue tumors (OR: 0.33, 95% CI: 0.14-0.77) predicted lower likelihood of complications than bone tumors.

CONCLUSION

Pediatric flap reconstruction of extremity tumors is largely reserved for cases with high oncologic burden and osseous tumors in the distal anatomical regions, including the tibia/fibula and forearm. Future work may assess flap reconstruction in other anatomical areas.

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

INTRODUCTION

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.

METHODS

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.

RESULTS

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).

CONCLUSION

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).

How surgeons use risk calculators and non-clinical factors for informed consent and shared decision making: A qualitative study

BACKGROUND

The discussion of risks, benefits, and alternatives to surgery with patients is a defining component of informed consent. As shared-decision making has become central to surgeon-patient communication, risk calculators have emerged as a tool to aid communication and decision-making. To optimize informed consent, it is necessary to understand how surgeons assess and communicate risk, and the role of risk calculators in this process.

METHODS

We conducted interviews with 13 surgeons from two institutions to understand how surgeons assess risk, the role of risk calculators in decision-making, and how surgeons approach risk communication during informed consent. We performed a qualitative analysis of interviews based on SRQR guidelines.

RESULTS

Our analysis yielded insights regarding (a) the landscape and approach to obtaining surgical consent; (b) detailed perceptions regarding the value and design of assessing and communicating risk; and (c) practical considerations regarding the future of personalized risk communication in decision-making. Above all, we found that non-clinical factors such as health and risk literacy are changing how surgeons assess and communicate risk, which diverges from traditional risk calculators.

CONCLUSION

Principally, we found that surgeons incorporate a range of clinical and non-clinical factors to risk stratify patients and determine how to optimally frame and discuss risk with individual patients. We observed that surgeons' perception of risk communication, and the importance of eliciting patient preferences to direct shared-decision making, did not consistently align with patient priorities. This study underscored criticisms of risk calculators and novel decision-aids - which must be addressed prior to greater adoption.

Can the American College of Surgeons NSQIP Surgical Risk Calculator Accurately Predict Adverse Postoperative Outcomes in Emergency Abdominal Surgery? An Italian Multicenter Analysis

BACKGROUND

The American College of Surgeons NSQIP surgical risk calculator provides an estimation of 30-day postoperative adverse outcomes. It is useful in the identification of high-risk patients needing clinical optimization and supports the informed consent process. The purpose of this study is to validate its predictive value in the Italian emergency setting.

STUDY DESIGN

Six Italian institutions were included. Inclusion diagnoses were acute cholecystitis, appendicitis, gastrointestinal perforation or obstruction. Areas under the receiving operating characteristic curves, Brier score, Hosmer-Lemeshow index, and observed-to-expected event ratio were measured to assess both discrimination and calibration. Effect of the Surgeon Adjustment Score on calibration was then tested. A patient's personal risk ratio was obtained, and a cutoff was chosen to predict mortality with a high negative predicted value.

RESULTS

A total of 2,749 emergency procedures were considered for the analysis. The areas under the receiving operating characteristic curve were 0.932 for death (0.921 to 0.941, p < 0.0001; Brier 0.041) and 0.918 for discharge to nursing or rehabilitation facility (0.907 to 0.929, p < 0.0001; 0.070). Discrimination was also strong (area under the receiving operating characteristic curve >0.8) for renal failure, cardiac complication, pneumonia, venous thromboembolism, serious complication, and any complication. Brier score was informative (<0.25) for all the presented variables. The observed-to-expected event ratios were 1.0 for death and 0.8 for discharge to facility. For almost all other variables, there was a general risk underestimation, but the use of the Surgeon Adjustment Score permitted a better calibration of the model. A risk ratio >3.00 predicted the onset of death with sensitivity = 86%, specificity = 77%, and negative predicted value = 99%.

CONCLUSIONS

The American College of Surgeons NSQIP surgical risk calculator has proved to be a reliable predictor of adverse postoperative outcomes also in Italian emergency settings, with particular regard to mortality. We therefore recommend the use of the surgical risk calculator in the multidisciplinary care of patients undergoing emergency abdominal surgery.

An Ounce of Prediction is Worth a Pound of Cure: Risk Calculators in Breast Reconstruction

Preoperative risk calculators provide individualized risk assessment and stratification for surgical patients. Recently, several general surgery–derived models have been applied to the plastic surgery patient population, and several plastic surgery–specific calculators have been developed. In this scoping review, the authors aimed to identify and critically appraise risk calculators implemented in postmastectomy breast reconstruction.

Evaluating the Inaccuracy of the National Surgical Quality Improvement Project Surgical Risk Calculator in Plastic Surgery: A Meta-analysis of Short-Term Predicted Complications

BACKGROUND

Preoperative surgical risk assessment is a major component of clinical decision making. The ability to provide accurate, individualized risk estimates has become critical because of growing emphasis on quality metrics benchmarks. The American College of Surgeons National Surgical Quality Improvement Project (NSQIP) Surgical Risk Calculator (SRC) was designed to quantify patient-specific risk across various surgeries. Its applicability to plastic surgery is unclear, however, with multiple studies reporting inaccuracies among certain patient populations. This study uses meta-analysis to evaluate the NSQIP SRC's ability to predict complications among patients having plastic surgery.

METHODS

OVID MEDLINE and PubMed were searched for all studies evaluating the predictive accuracy of the NSQIP SRC in plastic surgery, including oncologic reconstruction, ventral hernia repair, and body contouring. Only studies directly comparing SCR predicted to observed complication rates were included. The primary measure of SRC prediction accuracy, area under the curve (AUC), was assessed for each complication via DerSimonian and Laird random-effects analytic model. The I2 statistic, indicating heterogeneity, was judged low (I2 < 50%) or borderline/unacceptably high (I2 > 50%). All analyses were conducted in StataSE 16.1 (StataCorp LP, College Station, Tex).

RESULTS

Ten of the 296 studies screened met criteria for inclusion (2416 patients). Studies were classified as follows: (head and neck: n = 5, breast: n = 1, extremity: n = 1), open ventral hernia repair (n = 2), and panniculectomy (n = 1). Predictive accuracy was poor for medical and surgical complications (medical: pulmonary AUC = 0.67 [0.48-0.87], cardiac AUC = 0.66 [0.20-0.99], venous thromboembolism AUC = 0.55 [0.47-0.63]), (surgical: surgical site infection AUC = 0.55 [0.46-0.63], reoperation AUC = 0.54 [0.49-0.58], serious complication AUC = 0.58 [0.43-0.73], and any complication AUC = 0.60 [0.57-0.64]). Although mortality was accurately predicted in 2 studies (AUC = 0.87 [0.54-0.99]), heterogeneity was high with I2 = 68%. Otherwise, heterogeneity was minimal (I2 = 0%) or acceptably low (I2 < 50%) for all other outcomes.

CONCLUSIONS

The NSQIP Universal SRC, aimed at offering individualized quantifiable risk estimates for surgical complications, consistently demonstrated poor risk discrimination in this plastic surgery-focused meta-analysis. The limitations of the SRC are perhaps most pronounced where complex, multidisciplinary reconstructions are needed. Future efforts should identify targets for improving SRC reliability to better counsel patients in the perioperative setting and guide appropriate healthcare resource allocation.

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

BACKGROUND

Distal 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.

METHODS

56 (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.

RESULTS

Complications 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).

CONCLUSIONS

Distal 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.

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

INTRODUCTION

Proximal femur replacement (PFR) in the setting of tumor resection is associated with a high rate of postoperative complication. The online American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) surgical risk calculator is approved by the Center of Medicare and Medicaid services to estimate 30-day postoperative complications. This study was to determine if the ACS-NSQIP can predict postoperative complications following PFR.

METHODS

We reviewed 103 (61 male and 42 female) patients undergoing PFR using the Current Procedural Terminology (CPT) codes available in the calculator: 27125 (hemiarthroplasty), 27130 (total hip), 27132 (conversion to total hip), 27134 (revision total hip), 27137 (revision acetabulum), 27138 (revision femur), and 27365 (excision tumor hip). The predicted rates of complications were compared with the observed rates.

RESULTS

Complications occurred in 54 (52%) of patients, with the predicted risk based on CPT codes: 27125 (21.5%); 27130 (7.8%); 27132 (16.6%), 27134 (17.8%), 27137 (14.4%), 274138 (22.7%), and 27365 (16.2%). The calculator was a poor predictor of complications (27125, area under the curve [AUC] 0.576); (27130, AUC 0.489); (27132, AUC 0.490); (27134, AUC 00.489); (27137, AUC 0.489); (27138, AUC 0.471); and (27365, AUC 0.538).

CONCLUSION

Oncologic PFR is known for complications. The ACS-NSQIP does not adequately predict the incidence of complications, and therefore cannot reliably be used in their shared decision-making process preoperative.

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

BACKGROUND

The American College of Surgeon (ACS) Surgical Risk Calculator is an online tool that helps surgeons estimate the risk of postoperative complications for numerous surgical procedures across several surgical specialties.

METHODS

We evaluated the predictive performance of the calculator in 385 cancer patients undergoing breast surgery. Calculator-predicted complication rates were compared with observed complication rates; calculator performance was evaluated using calibration and discrimination analyses.

RESULTS

The mean calculator-predicted rates for any complication (4.1%) and serious complication (3.2%) were significantly lower than the observed rates (11.2% and 5.2%, respectively). The area under the curve was 0.617 for any complication and 0.682 for serious complications. p Values for the Hosmer-Lemeshow test were significant (<.05) for both outcomes. Brier scores were 0.102 for any complication and 0.048 for serious complication.

CONCLUSIONS

The ACS risk calculator is not an ideal tool for predicting individual risk of complications following breast surgery in a Mexican cohort. The most valuable use of the calculator may reside in its role as an aid for patient-led surgery planning. The possibility of introducing breast surgery-specific data could improve the performance of the calculator. Furthermore, a disease-specific calculator could provide more accurate predictions and include complications more frequently found in breast cancer surgery.

The American College of Surgeons National Quality Improvement Program Incompletely Captures Implant-Based Breast Reconstruction Complications

BACKGROUND

Implant-based breast reconstruction (IBR) accounts for 70% of postmastectomy reconstructions in the United States. Improving the quality of surgical care in IBR patients through accurate measurements of outcomes is necessary. The purpose of this study is to compare the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) data from our institution to our complete institutional health records database.

METHODS

Data were collected and recorded for all patients undergoing IBR at our institution from 2015 to 2017. The data were completely identified and compared with our institutional NSQIP database for demographics and complications.

RESULTS

The electronic health records data search identified 768 IBR patients in 3 years and NSQIP reported on 229 (30%) patients. Demographics were reported similarly among the 2 databases. Rates of tissue expander/implant infections (5.9% vs 1.8%; P = 0.003) and wound dehiscence (3.5% vs 0.4%; P = 0.003) were not reported similarly between our database and NSQIP. However, the rates of hematoma (2.7% vs 1.8%) and skin flap necrosis (2.5% vs 1.8%) were comparable between the two databases. In our database, 43% of all complications presented after 30 days of surgery, beyond NSQIP's capture period.

CONCLUSIONS

Databases built on partial sampling, such as the NSQIP, may be useful for demographic analyses, but fall short of providing data for complications after IBR, such as infections and wound dehiscence. These results highlight the utility and importance of complete databases. National comparisons of clinical outcomes for IBR should be interpreted with caution when using partial databases.

A Comparison of Common Plastic Surgery Operations Using the NSQIP and TOPS Databases

Both the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) and the American Society of Plastic Surgeons Tracking Operations and Outcomes for Plastic Surgeons (TOPS) databases track 30-day outcomes.

Methods

Using the 2008-2016 TOPS and NSQIP databases, we compared patient characteristics and postoperative outcomes for 5 common plastic surgery procedures. A weighted TOPS population was used to mirror the NSQIP population in clinical and demographic characteristics to compare postoperative outcomes.

Results

We identified 154,181 cases. Compared with NSQIP patients, TOPS patients were more likely to be younger (47.9 versus 50.0 years), have American Society of Anesthesiologists class I-II (92.1% versus 74.6%), be outpatient (66.0% versus 49.3%), and be smokers (18.7% versus 11.7%). TOPS had extensive missing data: body mass index (40.6%), American Society of Anesthesiologists class (34.9%), diabetes (39.3%), and smoking status (37.2%). NSQIP was missing <1% of all shared categories except race (15.6%). The entire TOPS cohort versus only TOPS patients without missing data had higher rates of dehiscence (5.1% versus 3.5%) and infection (2.1% versus 1.7%). TOPS versus NSQIP patients had higher dehiscence rates (5.1% versus 1.0%) but lower rates of return to the operating room (3.1% versus 6.6%), infection (2.1% versus 3.0%), and medical complications (0.3% versus 2.2%). Nonweighted and weighted TOPS cohorts had similar 30-day outcomes.

Conclusions

NSQIP and TOPS populations are different in characteristics and outcomes, likely due to differences in collection methodology and the types physicians using the databases. The strengths of each dataset can be used together for research and quality improvement.

Assessment of the American College of Surgeons surgical risk calculator of outcomes after hepatectomy for liver tumors: Results from a cohort of 950 patients

BACKGROUND

The American College of Surgeons National Surgical Quality Improvement Program's (ACS-NSQIP) calculator has been endorsed to counsel patients regarding complications. The aim of this study was to assess its ability to predict outcomes after hepatectomy.

METHODS

Outcomes generated by the ACS-NSQIP were recorded in a consecutive cohort of patients. By using established classifications of complications, post-hepatectomy insufficiency and bile leak, the calculator was tested by the comparison of expected versus observed rates of events. The performance of the calculator was tested by using c-statistic and Brier score.

RESULTS

950 patients who underwent hepatectomy between January 2014 and June 2019 were included. Predicted rates were significantly lower than actual rates: the mean ACS-NSQIP morbidity was 17.97% ± 8.4 vs. actual 37.01% ± 0.56 (P < 0.001); the mean ACS-NSQIP mortality was 0.91% ± 1.48 vs. actual 1.76% ± 0.11 (P < 0.001). Predicted length of stay (LOS) was significantly shorter: mean ACS-NSQIP was 5.81 ± 1.66 days vs. actual 10.91 ± 4.6 days (P < 0.001). Post-hepatectomy liver insufficiency and bile leak were recorded in 6.8% and 11.9% of patients, respectively. These events were not expressed by the calculator. C-statistic and Brier scores showed low performance of the calculator.

CONCLUSION

The calculator underestimates the risks of complications, mortality and LOS after hepatectomy. Refinements of the ACS-NSQIP model that account for organ-specific risks should be considered.

Performance of the American College of Surgeons NSQIP Surgical Risk Calculator for Total Gastrectomy

BACKGROUND

To encourage implementation of the American College of Surgeons (ACS) NSQIP Risk Calculator for total gastrectomy for gastric cancer, its predictive performance for this specific procedure should be validated. We assessed its discriminatory accuracy and goodness of fit for predicting 12 adverse outcomes.

STUDY DESIGN

Data were collected on all patients with gastric cancer who underwent total gastrectomy with curative intent at Memorial Sloan Kettering Cancer Center between 2002 and 2017. Preoperative risk factors from the electronic medical record were manually inserted into the ACS-NSQIP Risk Calculator. Predictions for adverse outcomes were compared with observed outcomes by Brier scores, c-statistics, and Hosmer-Lemeshow p value.

RESULTS

In a total of 452 patients, the predicted rate of all complications (29%) was lower than the observed rate (45%). Brier scores varied between 0.017 for death and 0.272 for any complication. C-statistics were moderate (0.7-0.8) for death and renal failure, good (0.8-0.9) for cardiac complication, and excellent (≥0.9) for discharge to nursing or rehabilitation facility. Hosmer-Lemeshow p value found poor goodness of fit for pneumonia only.

CONCLUSIONS

For adverse outcomes after total gastrectomy with curative intent in gastric cancer patients, performance of the ACS-NSQIP Risk Calculator is variable. Its predictive performance is best for cardiac complications, renal failure, death, and discharge to nursing or rehabilitation facility.

The Toronto Sarcoma Flap Score: A Validated Wound Complication Classification System for Extremity Soft Tissue Sarcoma Flap Reconstruction

BACKGROUND

Flap reconstruction plays an important role in limb preservation after wide resection of extremity soft tissue sarcoma (ESTS), but can be associated with high rates of postoperative wound complications. Currently, no standardized system exists for the classification of these complications. This study aimed to develop a standardized classification system for wound complications after ESTS flap reconstruction.

METHODS

Outcomes of ESTS flap reconstructions were analyzed in a retrospective cohort of 300 patients. All wound- and flap-related complications were identified and categorized. Based on these data, a scoring system was developed and validated with a prospective cohort of 100 patients who underwent ESTS flap reconstruction.

RESULTS

A 10-point scoring system was developed based on the level of intervention required to treat each complication observed in the retrospective cohort. Raters applied the scoring system to the prospective patient cohort. Validation studies demonstrated excellent inter-rater and intra-rater reliability (weighted Cohen's kappa range, 0.82 [95% CI, 0.5-1.0] to 0.99 [95% CI, 0.98-1.0] and 0.95 [95% CI, 0.84-1.0] to 0.97 [95% CI, 0.92-1.0], respectively). The majority of the raters reported the score to be simple, objective, and reproducible (respective mean scores, 4.76 ± 0.43, 4.53 ± 0.62, and 4.56 ± 0.56 on 5-point Likert scales).

CONCLUSION

The Toronto Sarcoma Flap Score (TSFS) is a simple and objective classification system with excellent inter- and intra-rater reliability. Universal adoption of the TSFS could standardize outcome reporting in future studies and aid in the establishment of clinical benchmarks to improve the quality of care in sarcoma reconstruction.

Retroperitoneal sarcoma perioperative risk stratification: A United States Sarcoma Collaborative evaluation of the ACS-NSQIP risk calculator

BACKGROUND

The ACS-NSQIP risk calculator predicts perioperative risk. This study tested the calculator's ability to predict risk for outcomes following retroperitoneal sarcoma (RPS) resection.

METHODS

The United States Sarcoma Collaborative database was queried for adults who underwent RPS resection. Estimated risk for outcomes was calculated twice in the risk calculator, once using sarcoma-specific CPT codes and once using codes indicative of most comorbid organ resection (eg nephrectomy). ROC curves were generated, with area under the curve (AUC) and Brier scores reported to assess discrimination and calibration. An AUC < 0.6 was considered ineffective discrimination. A negative ▲ Brier indicated improved performance relative to baseline outcome rates.

RESULTS

In total, 482 patients were identified with a 42.3% 90-day complication rate. Discrimination was poor for all outcomes except "all complications" and "renal failure." Baseline outcome rates were better predictors than calculator estimates except for "discharge to nursing or rehab facility" and "renal failure." Replacing sarcoma-specific CPT codes with resection-specific codes did not improve performance.

CONCLUSION

The ACS-NSQIP risk calculator poorly predicted outcomes following RPS resection. Changing sarcoma-specific CPT to resection-specific codes did not improve performance. Comorbidities in the calculator may not effectively capture perioperative risk. Future work should evaluate a sarcoma-specific calculator.

Is the ACS-NSQIP Risk Calculator Accurate in Predicting Adverse Postoperative Outcomes in the Emergency Setting? An Italian Single-center Preliminary Study

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.

Analysis and Review of Automated Risk Calculators Used to Predict Postoperative Complications After Orthopedic Surgery

PURPOSE OF REVIEW

To discuss the automated risk calculators that have been developed and evaluated in orthopedic surgery.

RECENT FINDINGS

Identifying predictors of adverse outcomes following orthopedic surgery is vital in the decision-making process for surgeons and patients. Recently, automated risk calculators have been developed to quantify patient-specific preoperative risk associated with certain orthopedic procedures. Automated risk calculators may provide the orthopedic surgeon with a valuable tool for clinical decision-making, informed consent, and the shared decision-making process with the patient. Understanding how an automated risk calculator was developed is arguably as important as the performance of the calculator. Additionally, conveying and interpreting the results of these risk calculators with the patient and its influence on surgical decision-making are paramount. The most abundant research on automated risk calculators has been conducted in the spine, total hip and knee arthroplasty, and trauma literature. Currently, many risk calculators show promise, but much research is still needed to improve them. We recommend they be used only as adjuncts to clinical decision-making. Understanding how a calculator was developed, and accurate communication of results to the patient, is paramount.

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

BACKGROUND AND OBJECTIVES

The ACS-NSQIP surgical risk calculator is an online tool that estimates the risk of postoperative complications. Sacrectomies for chordoma are associated with a high rate of complications. This study was to determine if the ACS-NSQIP calculator can predict postoperative complications following sacrectomy.

METHODS

Sixty-five (42 male, 23 female) patients who underwent sacrectomy were analyzed using the Current Procedural Terminology (CPT) codes: 49215 (excision of presacral/sacral tumor), 63001 (laminectomy of sacral vertebrae), 63728 (laminectomy for biopsy/excision of sacral neoplasm) and 63307 (sacral vertebral corpectomy for intraspinal lesion). The predicted rates of complications were compared to the observed rates.

RESULTS

Complications were noted in 44 (68%) patients. Of the risk factors available to input to the ACS-NSQIP calculator, tobacco use (OR, 20.4; P < .001) was predictive of complications. The predicted risk of complications based off the CPT codes were: 49215 (16%); 63011 (6%); 63278 (11%) and 63307 (15%). Based on ROC curves, the use of the ACS-NSQIP score were poor predictors of complications (49215, AUC 0.65); (63011, AUC 0.66); (63307, AUC 0.67); (63278, AUC 0.64).

CONCLUSION

The ACS-NSQIP calculator was a poor predictor of complications and was marginally better than a coin flip in its ability to predict complications following sacrectomy for chordoma.

Assessing the Feasibility and Effects of Introducing the USA National Surgical Quality Improvement Program on Clinical Outcomes and Cost in Saudi Arabia: An Observational Study

Introduction

This study aimed at introducing a systematic clinical registry to assess the outcomes of surgical performances and the associated costs of surgical complications in hospitals of Saudi Arabia.

Materials and Methods

This was an observational retrospective cohort study. Three large Saudi public hospitals from different regions participated in the study. A systematic sample consisting of 2077 medical records was retrospectively reviewed after being received from the hospitals' surgical wards. The inclusion criteria of the study were inpatients of the surgical cases, patients older than 18 years, and those who underwent major surgery under general anesthesia. The occurrence of adverse events in surgical wards and the direct costs associated with these surgical adverse events were estimated. Results were reported in terms of odds ratio and 95% confidence interval. A value of p < 0.05 was considered statistically significant.

Results

Introducing the systematic clinical registry to assess surgical outcomes and complications across multiple hospital sites is feasible. The findings of the study suggest that some areas are exemplary and others need improvement, such as sepsis cases, renal failure, ventilator use for more than 48 h, urinary tract infection, surgical site infection (SSI), length of stay after colorectal surgery, and rehospitalization. Additional costs from surgical complications in Riyadh only were approximately 0.5 million Saudi Arabian Riyal (127,764.40 USD) during that year. Most of the additional costs were due to sepsis and SSI.

Conclusion

Empirical evidence derived from the idea of introducing a National Surgical Quality Improvement Program might be generally applicable to other countries in the region and worldwide, and can be used to measure surgical adverse events and track interventions over time. As a result, quality improvement initiatives could be identified to be implemented immediately focusing on preventing several surgical adverse events. A future study is needed to explore the underlying factors that contribute to the occurrence of surgical adverse events to be prevented and/or mitigated.

Morbid Obesity Is Associated With an Increased Risk of Wound Complications and Infection After Lower Extremity Soft-tissue Sarcoma Resection

BACKGROUND

Obesity is associated with wound complications after lower extremity surgery. Excision of soft-tissue sarcomas is urgent, and unlike the elective surgery, obesity cannot be modified preoperatively. The purpose of this study was to evaluate the effect of obesity on treatment outcome.

METHODS

Six hundred fifty-three patients (343 men; mean age, 56 ± 18 years) with a lower extremity soft-tissue sarcoma were reviewed. The mean body mass index (BMI) was 27.1 ± 5.7 kg/m, with 189 obese patients (29%) having a BMI of ≥30 kg/m and 27 morbidly obese patients (4%) having a BMI of ≥40 kg/m. Complications and functional and oncologic outcomes were compared between groups.

RESULTS

Two hundred eighty-five patients (40%) sustained a postoperative complication, most commonly a dehiscence (n = 175; 24%) and infection (n = 147; 21%). On multivariate analysis, morbid obesity was associated with wound complications (P = 0.002) and infection (P = 0.01). Morbid obesity was not associated with local tumor recurrence (P = 0.56). No difference was found in the mean Toronto Extremity Salvage Score (P = 0.11) or Musculoskeletal Tumor Society (P = 0.41) scores between the groups.

DISCUSSION

Morbid obesity was associated with postoperative wound complications and infection. However, after surgery, obese patients can expect no difference in oncologic outcome, with an excellent functional result.

Predictive value of the ACS NSQIP calculator for head and neck reconstruction free tissue transfer

BACKGROUND

Predictive models to forecast the likelihood of specific outcomes after surgical intervention allow informed shared decision-making by surgeons and patients. Previous studies have suggested that existing general surgical risk calculators poorly forecast head and neck surgical outcomes. However, no large study has addressed this question while subdividing subjects by surgery performed.

OBJECTIVES

To determine the accuracy of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Surgical Risk Calculator in estimating length of hospital stay and risk of postoperative complications after free tissue transfer surgery.

STUDY DESIGN

A retrospective chart review of patients at one institution was performed using Current Procedural Terminology codes for anterolateral thigh (ALT) flap, fibula free flap (FFF), and radial forearm free flap (RFFF) reconstruction. Output data from the ACS NSQIP surgical risk calculator were compared with the observed rates in our patients.

METHODS

Incidences of cardiac complications, pneumonia, venous thromboembolism, return to the operating room, and discharge to skilled nursing facility (SNF) were compared to predicted incidences. Length of stay was also compared to the predicted length of stay.

RESULTS

Three hundred thirty-six free flap reconstructions with 197 ALT flaps, 85 RFFFs, and 54 FFFFs were included. Brier scores were calculated using ACS NSQIP forecast and actual incidences. No Brier score was <0.01 for the entire sample or any subgroup, which indicates that the NSQIP risk calculator does not accurately forecast outcomes after free tissue reconstruction.

CONCLUSION

The ACS NSQIP failed to accurately forecast postoperative outcomes after head and neck free flap reconstruction for the entire sample or subgroup analyses.

LEVEL OF EVIDENCE

4 Laryngoscope, 130:679-684, 2020.

Predicting complications in immediate microvascular breast reconstruction: Validity of the breast reconstruction assessment (BRA) surgical risk calculator

BACKGROUND

The Breast Reconstruction Assessment (BRA)-score is a disease-specific risk calculator that estimates the likelihood of postoperative complications in an individual patient. The tool has not been previously externally validated in microvascular breast reconstruction. The purpose of this study was to evaluate the efficacy of the calculator in patients who underwent microvascular reconstruction at a single specialist institution.

METHODS

Data from 415 patients who had immediate microvascular breast reconstruction were entered into the calculator. The predicted and observed rates of surgical complications, medical complications, reoperation, and total or partial flap failure were compared. The accuracy of the calculator was assessed using statistical measures of calibration and discrimination.

RESULTS

The calculator accurately predicted the proportion of patients who would experience surgical complications and reoperations but overestimated the rates of medical complications and flap failures. The C-statistics were low for all four prediction models (0.49-0.59), suggesting weak discriminatory power, and the Brier scores were relatively high (0.09-0.44), indicating poor correlation between predicted and actual probability of complications.

CONCLUSION

These results suggest that the BRA score cannot accurately identify patients at risk for complications following immediate microvascular breast reconstruction at our institution.

Predicting Postoperative Complications after Acute Care Surgery: How Accurate is the ACS NSQIP Surgical Risk Calculator?

The ACS NSQIP Surgical Risk Calculator (SRC) is an evidence-based clinical tool commonly used for evaluating postoperative risk. The goal of this study was to validate SRC-predicted complications by comparing them with observed outcomes in the acute care surgical setting. In this study, pre- and postoperative data from 1693 acute care surgeries (hernia repair, enterolysis, intestinal incision/excision and enterectomy, gastrectomy, debridement, colectomy, appendectomy, cholecystectomy, gastrorrhaphy, and incision and drainage of soft tissue, breast abscesses, and removal of foreign bodies) performed at a Level I trauma center over a five-year time period were abstracted. Predictions for any and serious complications were based on SRC were compared with observed outcomes using various measures of diagnostic. When evaluated as one group, the SRC had good discriminative power for predicting any and serious complications after acute care surgeries (Area Under the Curve (AUC) 0.79, 0.81). In addition, the SRC met Brier score requirements for an informative model overall. However, the predictive accuracy of the SRC varied for various procedures within the acute care patient population. For serious complications, the diagnostic measures ranged from an AUC of 0.61 and negative likelihood ratio of 0.716 for incision & drainage soft tissue to AUC of 0.91 and negative likelihood ratio of 0.064 for gastrorrhaphy. Length of stay was significantly underestimated by the SRC overall (8.56 days, P < 0.01) and for individual procedures. The SRC performs well at predicting complications after acute care surgeries overall; however, there is great variability in performance between procedure types. Further refinements in risk stratification may improve SRC predictions.

Scoping Review of the National Surgical Quality Improvement Program in Plastic Surgery Research

BACKGROUND

The National Surgical Quality Improvement Program (NSQIP) is a robust, high-quality surgical outcomes database that measures risk-adjusted 30-day outcomes of surgical interventions. The purpose of this scoping review is to describe how the NSQIP is being used in plastic surgery research.

METHODS

A comprehensive electronic literature search was completed in PubMed, Embase, MEDLINE, and CINAHL. Two reviewers independently reviewed articles to determine their relevance using predefined inclusion criteria. Articles were included if they utilized NSQIP data to conduct research in a domain of plastic surgery or analyzed surgical procedures completed by plastic surgeons. Extracted information included the domain of plastic surgery, country of origin, journal, and year of publication.

RESULTS

A total of 106 articles met the inclusion criteria. The most common domain of plastic surgery was breast reconstruction representing 35% of the articles. Of the 106 articles, 95% were published within the last 5 years. The Plastic and Reconstructive Surgery journal published most of the (59%) NSQIP-related articles. All of the studies were retrospective. Of note, there were no articles on burns and only one study on trauma as the domain of plastic surgery.

CONCLUSION

This scoping review describes how NSQIP data are being used to analyze plastic surgery interventions and outcomes in order to guide quality improvement in 106 articles. It demonstrates the utility of NSQIP in the literature, however also identifies some limitations of the program as it applies to plastic surgery.

Validation of the American College of Surgeons National Surgical Quality Improvement Program Risk Model for Patients Undergoing Panniculectomy

Panniculectomy procedures have been reported to significantly improve quality of life, increase mobility, and improve hygiene in patients with a significant pannus formation. The primary aims of this study were to determine which preoperative risk factors may be used to differentiate postoperative complication rate among patient cohorts and to validate utilization of the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) risk calculator in patients undergoing panniculectomies.

METHODS

This retrospective study included all patients who underwent a panniculectomy procedure at our institution from 2005 to 2016. Baseline characteristics, preoperative risk factors, medical comorbidities, and postoperative complications were collected via retrospective chart review.

RESULTS

Two hundred sixty-four patients who underwent a panniculectomy were identified. The odds ratios of any postoperative complication were 8.26, 7.76, and 16.6 for patients with classes 1, 2, and 3 obesity, respectively (P < 0.05). Statistical modeling was utilized to evaluate the predictive performance of the ACS-NSQIP Surgical Risk Calculator. We calculated the C-statistic for the ACS-NSQIP model to be only 0.61, indicating that although the model is associated with the risk of complication, it does not have a strong predictive value for this particular procedure.

DISCUSSION

This study is one of the first to characterize postoperative complication rate based on extremum of body mass index for panniculectomy patients. Our results show that the utilization of the ACS-NSQIP Risk Calculator in this particular patient population underestimates the complication risk as a whole, which may necessitate the future development of a separate risk assessment model for this procedure.

Thirty-Day Outcomes Following Surgical Decompression of Thoracic Outlet Syndrome

BACKGROUND

Surgical thoracic outlet syndrome (TOS) management involves decompression of the neurovascular structures by releasing the anterior and/or middle scalene muscles, resection of the first and/or cervical ribs, or a combination. Various surgical approaches (transaxillary, supraclavicular, infraclavicular, and transthoracic) have been used with varying rates of complications. The purpose of this study was to evaluate early postoperative outcomes following surgical decompression for TOS. We hypothesized that first and/or cervical rib resection would be associated with increased 30-day complications and health care utilization.

METHODS

The American College of Surgeons National Surgical Quality Improvement Program database was reviewed for all TOS cases of brachial plexus surgical decompression in the region of the thoracic inlet from 2005 to 2013.

RESULTS

There were 225 patients (68% females; mean age: 36.4 years ± 12.1; 26% body mass index [BMI] ⩾ 30). There were 205 (91%) patients who underwent first and/or cervical rib resection (±scalenectomy), and 20 (9%) underwent rib-sparing scalenectomy. Compared with rib-sparing scalenectomy, rib resection was associated with longer operative time and hospital stays ( P < .001). In the 30 days postoperatively, 8 patients developed complications (rib-scalenectomy, n = 7). Only patients with rib resection returned to the operating room (n = 10) or were readmitted (n = 9).

CONCLUSIONS

Early postoperative complications are infrequent after TOS decompression. Rib resection is associated with longer surgical times and hospital stays. Future studies are needed to assess the association between early and long-term outcomes, surgical procedure, and health care utilization to determine the cost-effectiveness of the various surgical interventions for TOS.

Morbid Obesity Increases the Risk of Postoperative Wound Complications, Infection, and Repeat Surgical Procedures Following Upper Extremity Limb Salvage Surgery for Soft Tissue Sarcoma

BACKGROUND

Obesity is a known risk factor for wound complications; however, unlike elective upper extremity procedures, where obesity can be modified preoperatively, excision of soft tissue sarcomas (STSs) is not elective, and as such, obesity cannot be modified. There is a paucity of data concerning the impact of obesity on wound healing in upper extremity sarcoma surgery.

METHODS

A total of 261 (159 males and 102 females) patients with a STS of the upper extremity from 2006-2014 were reviewed. The mean age and body mass index (BMI) were 56 (18-97) years and 26.6 (15.4-40.8) kg/m², respectively. Sixty-nine patients (26%) were classified as obese (BMI ⩾30 kg/m²): class I (obese, BMI = 30-34.9 kg/m²; n = 48, 18%), class II (severely obese, BMI = 35.0-39.9 kg/m²; n = 16, 6%), and class III (morbidly obese, BMI ≥ 40 kg/m²; n = 5, 2%). Functional outcomes were also compared between obese and nonobese patients using the Musculoskeletal Tumor Society (MSTS) 1993 rating system and Toronto Extremity Salvage Scores (TESS).

RESULTS

Forty-nine patients (19%) sustained a wound dehiscence, delayed healing, or infection. Class III obesity increased the risk of wound complications (hazard ratio [HR] = 8.19, 95% confidence interval [CI] = 1.96-22.96, P < .001) and infection (HR = 10.09, 95% CI = 1.60-34.83, P = .01). There was no difference in the mean TESS (93 vs 90, P = .13) or MSTS93 (95 vs 93, P = .39) between obese and nonobese patients.

CONCLUSIONS

The results of this study indicate morbid obesity significantly increased the risk of a postoperative wound complication and infection. However, following upper extremity limb salvage surgery, obese patients should expect to have excellent functional outcome.

Assessment of the NSQIP Surgical Risk Calculator in Predicting Microvascular Head and Neck Reconstruction Outcomes

Objective

This study evaluated the accuracy of the Surgical Risk Calculator (SRC) of the ACS NSQIP (American College of Surgeons National Surgical Quality Improvement Program) in predicting head and neck microvascular reconstruction outcomes.

Study Design

Retrospective analysis.

Setting

Tertiary medical center.

Subjects and Methods

A total of 561 free flaps were included in the analysis. The SRC-predicted 30-day rates of postoperative complications, hospital length of stay (LOS), and rehabilitation discharge were compared with the actual rates and events. The SRC’s predictive value was examined with Brier scores and receiver operating characteristic area under the curve.

Results

A total of 425 myocutaneous, 134 osseous (84 fibula, 47 scapula, and 3 iliac crest), and 2 omental free flaps were included in this study. All perioperative complications evaluated had area under the curve values ≤0.75, ranging from 0.480 to 0.728. All but 2 postoperative complications had Brier scores >0.01. SRC-predicted LOS was 9.4 ± 2.38 days (mean ± SD), which did not strongly correlate with the actual LOS of 11.98 ± 9.30 days ( r = 0.174, P < .0001).

Conclusion

The SRC is a poor predictor for surgical outcome among patients undergoing microvascular head and neck reconstruction.

Evaluating the National Surgical Quality Improvement Program-Pediatric Surgical Risk Calculator for Pediatric Craniosynostosis Surgery

BACKGROUND

The American College of Surgeons' National Surgical Quality Improvement Program-Pediatric (NSQIP-P) risk calculator was developed based on national data. There have been no studies assessing the risk calculator's performance in pediatric neurosurgery. The authors aimed to evaluate the predictions from the risk calculator compared to our single institution experience in craniosynostosis surgery.

METHODS

Outcomes from craniosynostosis surgeries performed between 2012 and 2016 at our academic pediatric hospital were evaluated using the NSQIP-P risk calculator. Descriptive statistics were performed comparing predicted 30-day postoperative events and clinically observed outcomes. The performance of the calculator was evaluated using the Brier score and receiver operating characteristic curve (ROC).

RESULTS

A total of 202 craniosynostosis surgeries were included. Median age was 0.74 years (range 0.15-6.32); 66% were males. Blood transfusion occurred in 162/202 patients (80%). The following clinical characteristics were statistically correlated with surgical complications: American Society of Anesthesiologists physical status classification >1 (P < 0.001), central nervous system abnormality (P < 0.001), syndromic craniosynostosis (P = 0.001), and redo operations (P = 0.002). Postoperative events occurred in <3%, including hardware breakage, tracheal-cartilaginous sleeve associated with critical airway, and surgical site infection. The calculator performed well in predicting any complication (Brier = 0.067, ROC = 73.9%), and for pneumonia (Brier = 0.0049, ROC 99%). The calculator predicted a low rate of cardiac complications, venous thromboembolism, renal failure, reintubation, and death; the observed rate of these complications was 0.

CONCLUSIONS

The risk calculator demonstrated reasonable ability to predict the low number of perioperative complications in patients undergoing craniosynostosis surgery with a composite complications outcome. Efforts to improve the calculator may include further stratification based on procedure-specific risk factors.

Predicting complications of major head and neck oncological surgery: an evaluation of the ACS NSQIP surgical risk calculator

Background

The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) universal surgical risk calculator is an online tool intended to improve the informed consent process and surgical decision-making. The risk calculator uses a database of information from 585 hospitals to predict a patient’s risk of developing specific postoperative outcomes.

Methods

Patient records at a major Canadian tertiary care referral center between July 2015 and March 2017 were reviewed for surgical cases including one of six major head and neck oncologic surgeries: total thyroidectomy, total laryngectomy, hemiglossectomy, partial glossectomy, laryngopharyngectomy, and composite resection. Preoperative information for 107 patients was entered into the risk calculator and compared to observed postoperative outcomes. Statistical analysis of the risk calculator was completed for the entire study population, for stratification by procedure, and by utilization of microvascular reconstruction. Accuracy was assessed using the ratio of predicted to observed outcomes, Receiver Operating Characteristics (ROC), Brier score, and the Wilcoxon signed–ranked test.

Results

The risk calculator accurately predicted the incidences for 11 of 12 outcomes for patients that did not undergo free flap reconstruction (NFF group), but was less accurate for patients that underwent free flap reconstruction (FF group). Length of stay (LOS) analysis showed similar results, with predicted and observed LOS statistically different in the overall population and FF group analyses (p = 0.001 for both), but not for the NFF group analysis (p = 0.764). All outcomes in the NFF group, when analyzed for calibration, met the threshold value (Brier scores < 0.09). Risk predictions for 8 of 12, and 10 of 12 outcomes were adequately calibrated in the FF group and the overall study population, respectively. Analyses by procedure were excellent, with the risk calculator showing adequate calibration for 7 of 8 procedural categories and adequate discrimination for all calculable categories (6 of 6).

Conclusion

The NSQIP-RC demonstrated efficacy for predicting postoperative complications in head and neck oncology surgeries that do not require microvascular reconstruction. The predictive value of the metric can be improved by inclusion of several factors important for risk stratification in head and neck oncology.

Flap reconstruction does not increase complication rates following surgical resection of extremity soft tissue sarcoma

BACKGROUND

Flap reconstruction plays an essential role in the surgical management of extremity soft tissue sarcoma (ESTS) for many patients. But flaps increase the duration and complexity of the surgery and their contribution to overall morbidity is unclear. This study directly compares the complication rates in patients with ESTS undergoing either flap reconstruction or primary wound closure and explores contributing factors.

METHODS

Eight hundred and ninety-seven patients who underwent ESTS resection followed by primary closure (631) or flap reconstruction (266) were included in this study. Data on patient, tumour and treatment variables and post-operative medical and surgical complications were collected. Univariate and multivariate regression analyses were performed to identify independent predictors of complications.

RESULTS

Post-operative complications occurred in 33% of patients. Flap patients were significantly older, had more advanced disease and were more likely to require neoadjuvant chemo- and radiotherapy. There was no significant difference in complication rates following flap reconstruction compared to primary closure on multivariate analysis (38 vs 30.9% OR 1.12, CI 0.77-1.64, p = 0.53). Pre-operative radiation and distal lower extremity tumour location were significant risk factors in patients who underwent primary wound closure but not in those who had flap reconstruction. Patients with comorbidities, increased BMI and systemic disease were at increased risk of complications following flap reconstruction.

CONCLUSIONS

Flap reconstruction is not associated with increased post-operative complications following ESTS resection. Flaps may mitigate the effects of some risk factors in selected patients.

National Surgical Quality Improvement Program surgical risk calculator poorly predicts complications in patients undergoing radical cystectomy with urinary diversion

PURPOSE

To evaluate the accuracy of the American College of Surgeons National Surgical Quality Improvement Programs (ACS-NSQIP) surgical risk calculator in patients undergoing radical cystectomy (RC) with urinary diversion.

MATERIALS AND METHODS

Preoperative characteristics of patients who underwent RC with ileal conduit or orthotropic neobladder (ONB) between 2007 and 2016 were entered into the proprietary online ACS-NSQIP calculator to generate 30-day predicted risk profiles. Predicted and observed outcomes were compared by measuring Brier score (BS) and area under the receiver operating characteristic curve (AUC).

RESULTS

Of 954 patients undergoing RC, 609 (64%) received ileal conduit and 345 (36%) received ONB. The calculator underestimated most risks by 10%-81%. The BSs exceeded the acceptable threshold of 0.01 and AUC were less than 0.8 for all outcomes in the overall cohort. The mean (standard deviation) predicted vs. observed length of stay was 9 (1.5) vs. 10.6 (7.4) days (Pearson's r = 0.09). Among patients who received ONB, adequate BS (<0.01) was observed for pneumonia, cardiac complications, and death. The receiver operating characteristic curve analysis revealed moderate accuracy of calculator for cardiac complications (AUC = 0.69) and discharge to rehab center (AUC = 0.75) among patients who underwent RC with ONB.

CONCLUSIONS

The universal ACS-NSQIP calculator poorly predicts most postoperative complications among patients undergoing RC with urinary diversion. A procedure-specific risk calculator is required to better counsel patients in the preoperative setting and generate realistic quality measures.

Predictive validity of the ACS-NSQIP surgical risk calculator in geriatric patients undergoing lumbar surgery

The risk calculator of the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) has been shown to be useful in predicting postoperative complications. In this study, we aimed to evaluate the predictive value of the ACS-NSQIP calculator in geriatric patients undergoing lumbar surgery.A total of 242 geriatric patients who underwent lumbar surgery between January 2014 and December 2016 were included. Preoperative clinical information was retrospectively reviewed and entered into the ACS-NSQIP calculator. The predictive value of the ACS-NSQIP model was assessed using the Hosmer-Lemeshow test, Brier score (B), and receiver operating characteristics (ROC, also referred C-statistic) curve analysis. Additional risk factors were calculated as surgeon-adjusted risk including previous cardiac event and cerebrovascular disease.Preoperative risk factors including age (P = .004), functional independence (P = 0), American Society of Anesthesiologists class (ASA class, P = 0), dyspnea (P = 0), dialysis (P = .049), previous cardiac event (P = .001), and history of cerebrovascular disease (P = 0) were significantly associated with a greater incidence of postoperative complications. Observed and predicted incidence of postoperative complications was 43.8% and 13.7% (±5.9%) (P < .01), respectively. The Hosmer-Lemeshow test demonstrated adequate predictive accuracy of the ACS-NSQIP model for all complications. However, Brier score showed that the ACS-NSQIP model could not accurately predict risk of all (B = 0.321) or serious (B = 0.241) complications, although it accurately predicted the risk of death (B = 0.0072); this was supported by ROC curve analysis. The ROC curve also showed that the model had high sensitivity and specificity for predicting renal failure and readmission.The ACS-NSQIP surgical risk calculator is not an accurate tool for the prediction of postoperative complications in geriatric Chinese patients undergoing lumbar surgery.

Can we predict postoperative complications in elderly Chinese patients with hip fractures using the surgical risk calculator?

Purpose

Hip fractures are associated with poor prognosis in elderly patients partly due to the high rate of postoperative complications. This study was aimed to investigate whether the surgical risk calculator is suitable for predicting postoperative complications in elderly Chinese patients with hip fractures.

Methods

The incidence of postoperative complications among 410 elderly patients with hip fractures was predicted by the surgical risk calculator and then compared with the actual value. The risk calculator model was evaluated using the following three metrics: Hosmer–Lemeshow test for the goodness-of-fit of the model, receiver operating characteristic curve (ROC) (also referred as C-statistic) for the predictive specificity and sensitivity, and the Brier’s score test for predictive accuracy.

Results

Preoperative risk factors including gender, age, preoperative functional status, American Society of Anesthesiologists grade, hypertension, dyspnea, dialysis, previous cardio-vascular history, and cerebrovascular disease were positively correlated with the incidence of postoperative complications in elderly patients with hip fractures. The predicted complication incidence rate was well matched with the actual complication rate by Hosmer–Lemeshow test. The model had high sensitivity and specificity for predicting the mortality rate of these patients with a C-statistic index of 0.931 (95% CI [0.883, 0.980]). The surgical calculator model had an accuracy of 90% for predicting the reoperation rate (Brier’s score <0.01).

Conclusions

The surgical risk calculator could be useful for predicting mortality and reoperation in elderly patients with hip fracture. Patients and surgeons may use this simple calculator to better manage the preoperative risks.

Predicting Postoperative Complications for Acute Care Surgery Patients Using the ACS NSQIP Surgical Risk Calculator

The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) risk calculator has been used to assist surgeons in predicting the risk of postoperative complications. This study aims to determine if the risk calculator accurately predicts complications in acute care surgical patients undergoing laparotomy. A retrospective review was performed on all patients on the acute care surgery service at a tertiary hospital who underwent laparotomy between 2011 and 2012. The preoperative risk factors were used to calculate the estimated risks of postoperative complications in both the original ACS NSQIP calculator and updated calculator (June 2016). The predicted rate of complications was then compared with the actual rate of complications. Ninety-five patients were included. Both risk calculators accurately predicted the risk of pneumonia, cardiac complications, urinary tract infections, venous thromboembolism, renal failure, unplanned returns to operating room, discharge to nursing facility, and mortality. Both calculators underestimated serious complications (26% vs 39%), overall complications (32.4% vs 45.3%), surgical site infections (9.3% vs 20%), and length of stay (9.7 days versus 13.1 days). When patients with prolonged hospitalization were excluded, the updated calculator accurately predicted length of stay. The ACS NSQIP risk calculator underestimates the overall risk of complications, surgical infections, and length of stay. The updated calculator accurately predicts length of stay for patients <30 days. The acute care surgical population represents a high-risk population with an increased rate of complications. This should be taken into account when using the risk calculator to predict postoperative risk in this population.

An Examination of American College of Surgeons NSQIP Surgical Risk Calculator Accuracy

BACKGROUND

The American College of Surgeons NSQIP offers a Surgical Risk Calculator (SRC) that provides detailed, patient-level, risk assessments for many adverse outcomes to surgeons, patients, and the general public. The SRC calculator was designed to help guide discussion and decisions by providing generally applicable (not hospital-specific) information about surgical risk using easily understood and broadly available preoperative variables. Although large, internal evaluations have shown that the SRC has good accuracy (model discrimination and calibration), external validations have been inconsistent and tend to favor a conclusion of inadequate performance.

STUDY DESIGN

External studies, attempting to validate the SRC, were examined with respect to 3 design features: sample size (small samples reduce reliability), case-mix homogeneity (homogeneity reduces discrimination); and number of institutions providing data (few institutions reduces generalizability). The impact of each feature was then examined in several sets of simulation studies.

RESULTS

Each of the 3 design features has the potential to act as an artifactual cause for apparent SRC predictive failure. In addition, demonstrations that SRC estimates are inferior to those from models that use additional (sometimes operation-specific) predictor variables were seen as not relevant with respect to the SRC's intended scope.

CONCLUSIONS

The SRC predictive failures, reported by studies with the described design limitations, should not be misunderstood as disqualifying the SRC as an accurate and appropriate tool for its intended purpose of providing a general purpose risk calculator, applicable across many surgical domains, using easily understood and generally available predictive information.

Patient, tumour and treatment factors affect complication rates in soft tissue sarcoma flap reconstruction in a synergistic manner

INTRODUCTION

Flap reconstruction plays an essential role in the management of soft tissue sarcoma, facilitating wide resection while maximizing preservation of function. The addition of reconstruction increases the complexity of the surgery and identification of patients who are at high risk for post-operative complications is an important part of the preoperative assessment. This study examines predictors of complications in these patients.

METHODS

294 patients undergoing flap reconstruction following sarcoma resection were evaluated. Data on patient, tumour and treatment variables as well as post-operative complications were collected. Bivariate and multivariate regression analysis was performed to identify independent predictors of complications. Analysis of synergistic interaction between key patient and tumour risk factors was subsequently performed.

RESULTS

A history of cerebrovascular events or cardiac disease were found to be the strongest independent predictors of post-operative complications (OR 14.84, p = 0.003 and OR 5.71, p = 0.001, respectively). Further strong independent tumour and treatment-related predictors were high grade tumours (OR 1.91, p = 0.038) and the need for additional reconstructive procedures (OR 2.78, p = 0.001). Obesity had significant synergistic interaction with tumour resection diameter (RERI 1.1, SI 1.99, p = 0.02) and high tumour grade (RERI 0.86, SI 1.5, p = 0.01). Comorbidities showed significant synergistic interaction with large tumour resections (RERI 0.91, SI 1.83, p = 0.02).

CONCLUSION

Patient, tumour and treatment-related variables contribute to complications following flap reconstruction of sarcoma defects. This study highlights the importance of considering the combined effect of multiple risk factors when evaluating and counselling patients as significant synergistic interaction between variables can further increase the risk of complications.