Can the American College of Surgeons Risk Calculator Predict 30-day Complications After Spine Surgery?

McCarthy, Michael H.; Singh, Partik; Nayak, Rusheel; Maslak, Joseph P.; Jenkins, Tyler J.; Patel, Alpesh A.; Hsu, Wellington K.

doi:10.1097/brs.0000000000003340

Cited by 18 publications

(10 citation statements)

References 23 publications

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“…This risk calculator has been demonstrated to be an effective tool in other orthopedic subspecialties, including joint arthroplasty and spine. 17,26 Patients with diabetes and Charcot foot arthropathy represent a unique population of patients with multiple medical comorbidities. 19,20,22 Their quality of life is severely negatively impacted by the acquired deformity.…”

Section: Introductionmentioning

confidence: 99%

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Risk Reduction and Perioperative Complications in Patients With Diabetes and Multiple Medical Comorbidities Undergoing Charcot Foot Reconstruction

et al. 2021

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Background: Modern patient safety programs focus on medical optimization of patients prior to surgery, regional anesthesia when possible, and hospitalist-orthopedic co-management during the perioperative period. Methods: Eighty-five consecutive patients with diabetes and multiple medical comorbidities underwent surgical reconstruction for acquired deformities secondary to Charcot foot arthropathy with circular ring fixation between 2016 and 2019. All patients participated in a standardized risk reduction program that included medical optimization prior to surgery, regional anesthesia whenever possible, and hospitalist-orthopedic co-management during the perioperative period. Charts were retrospectively reviewed for medical comorbidities, complications, and length of stay. The American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) Risk Calculator was used to retrospectively calculate their predicted perioperative risk. Results: On multivariable analysis, longer lengths of stay were associated with low preoperative hemoglobin values (rate ratio [RR], 1.36; P = .01) and congestive heart failure (RR, 1.42; P = .02). There were 22 (26%) complications, though only 10 (12%) were serious. These included acute kidney injury ( n = 6), sepsis ( n = 2), 1 cardiac event, and 1 pulmonary embolism. Overall, the accuracy of predicting a complication using the ACS NSQIP Risk Calculator was 74% (95% CI, 63%-85%), which was comparable to the accuracy of predicting a complication using only patients’ congestive heart failure and pin-tract infection statuses ( c = 74%, 95% CI, 62%-86%). Discussion: Medical optimization of patients with diabetes and multiple medical comorbidities prior to elective complex reconstruction orthopedic surgery allows the surgery to be performed with a predictable risk for perioperative complications. Preoperative anemia and congestive heart failure are associated with longer hospitalizations in this patient group. The ACS NSQIP Risk Calculator appears to be a reliable predictor of complications during the perioperative period. This study demonstrates that reconstructive surgery in this complex patient population can be accomplished with a reasonable exposure to perioperative risk. Level of Evidence: Level IV, retrospective case series.

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Section: Introductionmentioning

confidence: 99%

“…This risk calculator has been demonstrated to be an effective tool in other orthopedic subspecialties, including joint arthroplasty and spine. 17,26…”

Section: Introductionmentioning

confidence: 99%

Risk Reduction and Perioperative Complications in Patients With Diabetes and Multiple Medical Comorbidities Undergoing Charcot Foot Reconstruction

et al. 2021

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“…The ACS NSQIP have implemented regular auditing procedures that have yielded data with excellent reliability that has continued to improve over time [11]. Additionally, the database has been utilized extensively to identify the incidence of and risk factors for a variety of short-term complications following a variety of orthopaedic procedures [12][13][14].…”

Section: Data Sourcementioning

confidence: 99%

Determining the incidence and risk factors for short-term complications following distal biceps tendon repair

Goedderz

Plantz

Gerlach

et al. 2022

Clin Shoulder Elbow

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Background: Distal biceps rupture is a relatively uncommon injury that can significantly affect quality of life. Surgical repair has the potential to provide functional improvement for patients. However, early complications following biceps tendon repair are not well described in the literature. This study aims to utilize a verified national surgical database to determine the incidence of and predictors for various short-term complications following distal biceps tendon repair. Methods: The American College of Surgeons’ National Surgical Quality Improvement Program database was used to identify patients undergoing distal biceps repair between January 1, 2011, and December 31, 2017. Patient demographic variables of sex, age, body mass index (BMI), American Society of Anesthesiologists class, functional status, and several comorbidities were reported for each patient, along with various 30-day postoperative complications. Binary logistic regression was used to calculate risk ratios for these complications using patient predictor variables.Results: Early postoperative overall surgical complications (0.5%)—which were mostly infections (0.4%)—and overall medical complications (0.3%) were rare. A risk factor for readmission was diabetes (risk ratio [RR], 4.238; 95% confidence interval [CI], 1.180–15.218). Risk factors for non-home discharge were smoking (RR, 3.006; 95% CI, 1.123–8.044) and 60 years of age (RR, 4.150; 95% CI, 1.611–10.686). Maleness was protective for medical complications (RR, 0.024; 95% CI, 0.005–0.126). Risk factors for surgical complications were obese class II (RR, 4.120; 95% CI, 1.123–15.120]), chronic obstructive pulmonary disease (COPD; RR, 21.981; 95% CI, 3.719–129.924), and inpatient surgery (RR, 8.606; 95% CI, 2.266–32.689). An independent functional status was protective against surgical complications (RR, 0.023; 95% CI, 0.002–0.221).Conclusions: Overall complication rates after distal biceps repair are quite low. Patient demographics (sex, age, BMI, and functional status), medical comorbidities (diabetes, smoking, and COPD), and surgical factors (inpatient versus outpatient surgery) were all predictive of various short-term complications.

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“…A notable tool used for all types of surgeries is the American College of Surgeon’s National Surgical Quality Improvement Program’s (ACS NSQIP) online calculator, which utilizes 21 inputted preoperative factors to predict both LOS and discharge status 17. While met with moderate accuracy for general surgical procedures, numerous studies have shown that it does not provide accurate predictions for patients undergoing spine surgery 18–21…”

mentioning

confidence: 99%

Predictive Models for Length of Stay and Discharge Disposition in Elective Spine Surgery: Development, Validation, and Comparison to the ACS NSQIP Risk Calculator

Arora

Lituiev

Jain

et al. 2022

Spine

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Study Design. A retrospective study at a single academic institution.Objective. The purpose of this study is to utilize machine learning to predict hospital length of stay (LOS) and discharge disposition following adult elective spine surgery, and to compare performance metrics of machine learning models to the American College of Surgeon's National Surgical Quality Improvement Program's (ACS NSQIP) prediction calculator. Summary of Background Data. A total of 3678 adult patients undergoing elective spine surgery between 2014 and 2019, acquired from the electronic health record. Methods. Patients were divided into three stratified cohorts: cervical degenerative, lumbar degenerative, and adult spinal deformity groups. Predictive variables included demographics, body mass index, surgical region, surgical invasiveness, surgical approach, and comorbidities. Regression, classification trees, and least absolute shrinkage and selection operator (LASSO) were used to build predictive models. Validation of the models was conducted on 16% of patients (N = 587), using area under the receiver operator curve (AUROC), sensitivity, specificity, and correlation. Patient data were manually entered into the ACS NSQIP online risk calculator to compare performance. Outcome variables were discharge disposition (home vs. rehabilitation) and LOS (days). Results. Of 3678 patients analyzed, 51.4% were male (n = 1890) and 48.6% were female (n = 1788). The average LOS was 3.66 days. In all, 78% were discharged home and 22% discharged to rehabilitation. Compared with NSQIP (Pearson R 2 = 0.16), the predictions of poisson regression (R 2 = 0.29) and LASSO (R 2 = 0.29) models were significantly more correlated with observed LOS (P = 0.025 and 0.004, respectively). Of the models generated to predict discharge location, logistic regression yielded an AUROC of 0.79, which was statistically equivalent to the AUROC of 0.75 for NSQIP (P = 0.135). Conclusion. The predictive models developed in this study can enable accurate preoperative estimation of LOS and risk of rehabilitation discharge for adult patients undergoing elective spine surgery. The demonstrated models exhibited better performance than NSQIP for prediction of LOS and equivalent performance to NSQIP for prediction of discharge location.

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Can the American College of Surgeons Risk Calculator Predict 30-day Complications After Spine Surgery?

Cited by 18 publications

References 23 publications

Risk Reduction and Perioperative Complications in Patients With Diabetes and Multiple Medical Comorbidities Undergoing Charcot Foot Reconstruction

Risk Reduction and Perioperative Complications in Patients With Diabetes and Multiple Medical Comorbidities Undergoing Charcot Foot Reconstruction

Determining the incidence and risk factors for short-term complications following distal biceps tendon repair

Predictive Models for Length of Stay and Discharge Disposition in Elective Spine Surgery: Development, Validation, and Comparison to the ACS NSQIP Risk Calculator

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