National Surgical Quality Improvement Program Variables Research Articles

701 A Modified Frailty Index to Predict Adverse Outcomes After Decompressive Hemicraniectomy for Acute Ischemic Stroke

INTRODUCTION: Surgical decision-making for decompressive hemicraniectomy (DHC) is challenging because of the heterogeneity of health status and the paucity of tools for predicting the operative risk of DHC for malignant edema following acute infarction. METHODS: The 2008–2018 National Surgical Quality Improvement Program (NSQIP) data set was accessed for patients undergoing DHC for Acute ischemic stroke (AIS) based on Current Procedural Terminology (CPT) codes. We used a modified frailty index (mFI) based on eleven preoperative clinical NSQIP variables. The outcomes assessed were 30-day occurrences of adverse events. RESULTS: A total of 394 patients were identified in the database, there were 55 (14%) patients with mFI 0, 118 patients (30%) with mFI 0.09, 115(29.2 %) with mFI 0.18 and 106 (27%) patients with mFI = 0.27. The rate of return to the operating room for a second procedure significantly increased from 4/55 (7.3%) in patients with mFI 0 to 23/106 (31.1%) in patients with mFI = 0.27. The discharge disposition was significantly different in patients with higher mFI (mFI > 0.27), with only 6/106 (5.7%) discharged to home versus 8/55 (14.5%) with mFI 0. Multivariate logistic regression analysis showed that compared to age, gender, ASA class, and pre albumin levels, mFI was a better predictor of the development of pneumonia (OR 6.278, 95 % CI 1.8, 22.0, p = 0.004) and return to the operating room (OR 4.0, 95 % CI 1.2 ,13.4, p = 0.02). CONCLUSIONS: A higher mFI was associated with an increased risk of return to the operating room and worse discharge disposition. The mFI is based on easily identifiable patient characteristics and can be an additional tool to improve perioperative risk stratification in elderly patients considered for DHC after AIS.

Development and Validation of a Multivariable Prediction Model for Postoperative Intensive Care Unit Stay in a Broad Surgical Population

Despite limited capacity and expensive cost, there are minimal objective data to guide postoperative allocation of intensive care unit (ICU) beds. The Surgical Risk Preoperative Assessment System (SURPAS) uses 8 preoperative variables to predict many common postoperative complications, but it has not yet been evaluated in predicting postoperative ICU admission. To determine if the SURPAS model could accurately predict postoperative ICU admission in a broad surgical population. This decision analytical model was a retrospective, observational analysis of prospectively collected patient data from the 2012 to 2018 American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) database, which were merged with individual patients' electronic health record data to capture postoperative ICU use. Multivariable logistic regression modeling was used to determine how the 8 preoperative variables of the SURPAS model predicted ICU use compared with a model inputting all 28 preoperatively available NSQIP variables. Data included in the analysis were collected for the ACS NSQIP at 5 hospitals (1 tertiary academic center, 4 academic affiliated hospitals) within the University of Colorado Health System between January 1, 2012, and December 31, 2018. Included patients were those undergoing surgery in 9 surgical specialties during the 2012 to 2018 period. Data were analyzed from May 29 to July 30, 2021. Surgery in 9 surgical specialties, including general, gynecology, orthopedic, otolaryngology, plastic, thoracic, urology, vascular, and neurosurgery. Use of ICU care up to 30 days after surgery. A total of 34 568 patients were included in the analytical data set: 32 032 (92.7%) in the cohort without postoperative ICU use and 2545 (7.4%) in the cohort with postoperative ICU use (no ICU use: mean [SD] age, 54.9 [16.6] years; 18 188 women [56.8%]; ICU use: mean [SD] age, 60.3 [15.3] years; 1333 men [52.4%]). For the internal chronologic validation of the 7-variable SURPAS model, data from 2012 to 2016 were used as the training data set (n = 24 250, 70.2% of the total sample size of 34 568) and data from 2017 to 2018 were used as the test data set (n = 10 318, 29.8% of the total sample size of 34 568). The C statistic improved in the test data set compared with the training data set (0.933; 95% CI, 0.924-0.941 vs 0.922; 95% CI, 0.917-0.928), whereas the Brier score was slightly worse in the test data set compared with the training data set (0.045; 95% CI, 0.042-0.048 vs 0.045; 95% CI, 0.043-0.047). The SURPAS model compared favorably with the model inputting all 28 NSQIP variables, with both having good calibration between observed and expected outcomes in the Hosmer-Lemeshow graphs and similar Brier scores (model inputting all variables, 0.044; 95% CI, 0.043-0.048; SURPAS model, 0.045; 95% CI, 0.042-0.046) and C statistics (model inputting all variables, 0.929; 95% CI, 0.925-0.934; SURPAS model, 0.925; 95% CI, 0.921-0.930). Results of this decision analytical model study revealed that the SURPAS prediction model accurately predicted postoperative ICU use across a diverse surgical population. These results suggest that the SURPAS prediction model can be used to help with preoperative planning and resource allocation of limited ICU beds.

The 5-Factor Modified Frailty Index in the Geriatric Surgical Population.

The modified frailty index (mFI-11) is a National Surgical Quality Improvement Program (NSQIP)-based 11-factor index that has been proven to adequately reflect frailty and predict mortality and morbidity. In the past years, certain NSQIP variables have been removed from the database; as of 2015, only 5 out of the original 11 factors remain. While the predictive power and usefulness of this 5-factor index (mFI-5) has been proven in previous work, it has yet to be studied in the geriatrics population. The goal of our study was to compare the mFI-5 to the mFI-11 in terms of value and predictive ability for mortality, postoperative infection, and unplanned 30-day readmission for patients aged 65years and older. Spearman's Rho was calculated to compare the value, and unadjusted and adjusted logistic regressions were created for three outcomes in nine surgical subspecialties. Correlation coefficients were above .86 across all surgical specialties except for cardiac surgery. Adjusted and unadjusted models showed similar C-statistics for mFI-5 and 11. Overall predictive values of geriatric mFI-5 and mFI-11 were lower than those for the general population but still had effective predictive value for mortality and post-operative complications (C-Stat ≥ .7) and weak predictive value for 30-day readmission. The mFI-5 is an equally effective predictor as the mFI-11 in all subspecialties and an effective predictor of mortality and postoperative complication in the geriatric population. This index has credibility for future use to study frailty within NSQIP, within other databases, and for clinical assessment and use.

Prescriptive analytics for reducing 30-day hospital readmissions after general surgery.

New financial incentives, such as reduced Medicare reimbursements, have led hospitals to closely monitor their readmission rates and initiate efforts aimed at reducing them. In this context, many surgical departments participate in the American College of Surgeons National Surgical Quality Improvement Program (NSQIP), which collects detailed demographic, laboratory, clinical, procedure and perioperative occurrence data. The availability of such data enables the development of data science methods which predict readmissions and, as done in this paper, offer specific recommendations aimed at preventing readmissions. This study leverages NSQIP data for 722,101 surgeries to develop predictive and prescriptive models, predicting readmissions and offering real-time, personalized treatment recommendations for surgical patients during their hospital stay, aimed at reducing the risk of a 30-day readmission. We applied a variety of classification methods to predict 30-day readmissions and developed two prescriptive methods to recommend pre-operative blood transfusions to increase the patient's hematocrit with the objective of preventing readmissions. The effect of these interventions was evaluated using several predictive models. Predictions of 30-day readmissions based on the entire collection of NSQIP variables achieve an out-of-sample accuracy of 87% (Area Under the Curve-AUC). Predictions based only on pre-operative variables have an accuracy of 74% AUC, out-of-sample. Personalized interventions, in the form of pre-operative blood transfusions identified by the prescriptive methods, reduce readmissions by 12%, on average, for patients considered as candidates for pre-operative transfusion (pre-operative hematoctic <30). The prediction accuracy of the proposed models exceeds results in the literature. This study is among the first to develop a methodology for making specific, data-driven, personalized treatment recommendations to reduce the 30-day readmission rate. The reported predicted reduction in readmissions can lead to more than $20 million in savings in the U.S. annually.

Better characterization of operation for ulcerative colitis through the National surgical quality improvement program: A 2-year audit of NSQIP-IBD

IntroductionThere is little consensus of quality measurements for restorative proctocolectomy with ileal pouch-anal anastomosis(RPC-IPAA) performed for ulcerative colitis(UC). The National Surgical Quality Improvement Program(NSQIP) cannot accurately classify RPC-IPAA staged approaches. We formed an IBD-surgery registry that added IBD-specific variables to NSQIP to study these staged approaches in greater detail. MethodsWe queried our validated database of IBD surgeries across 11 sites in the US from March 2017 to March 2019, containing general NSQIP and IBD-specific perioperative variables. We classified cases into delayed versus immediate pouch construction and looked for independent predictors of pouch delay and postoperative Clavien-Dindo complication severity. Results430 patients received index surgery or completed pouches. Among completed pouches, 46(28%) and 118(72%) were immediate and delayed pouches, respectively. Significant predictors for delayed pouch surgery included higher UC surgery volume(p = 0.01) and absence of colonic dysplasia(p = 0.04). Delayed pouch formation did not significantly predict complication severity. ConclusionsOur data allows improved classification of complex operations. Curating disease-specific variables allows for better analysis of predictors of delayed versus immediate pouch construction and postoperative complication severity. Short summaryWe applied our previously validated novel NSIP-IBD database for classifying complex, multi-stage surgical approaches for UC to a degree that was not possible prior to our collaborative effort. From this, we describe predictive factors for delayed pouch formation in UC RPC-IPAA with the largest multicenter effort to date.

The Impact Of Frailty On Patients Undergoing Liver Resection For Colorectal Liver Metastasis: A Review Of The National Surgical Quality Improvement Program

Presenter: Jacqueline Dauch MD | University of Arizona Background: Frailty is highly prevalent in patients with malignancy and is associated with high risk of morbidity and mortality after operative interventions. However, the impact of frailty on patients undergoing liver resection for metastatic colorectal cancer has not been studied. The aim of this study was to assess the impact of frailty on short term outcomes after liver resection in patients with metastatic colorectal cancer to the liver. Methods: We performed a 4 year analysis of the National Surgical Quality Improvement Program (NSQIP) participant user files. All patients undergoing hepatectomy for metastatic colorectal cancer between 2014-2017 were reviewed. The 5-item Modified Frailty Index (mFI) was calculated using NSQIP variables. We included all patients with complete mFI information in the analysis. Patients were divided into three categories based on the mFI (0= no frailty indicators, 1=one frailty indicator, 2=two or more frailty indicator). Outcome measures in house included minor and major morbidity as defined by the Clavien-Dindo classification (I/II vs III/IV), 30 day mortality, need for readmission, unfavorable discharge (not to home), bile leak and liver failure. Results: A total of 5230 patients were included in the analysis. 2737 (52%) had a mFI score of 0, 1839 (35%) had a mFI score of 1, and 654 (13%) had a mFI score of 2 or more. On multivariate analysis and after adjusting for potential cofounders such as age, sex, race/ethnicity, BMI, ASA class, preoperative albumin, neoadjuvant chemotherapy and extent of surgery (minor vs major ); patients with a mFI score of 2 or over were more likely than those with mFI of 0 to experience minor morbidity (OR 1.47, 95% CI 1.14-1.91, p<0.01), major morbidity (OR 1.82, 95% CI 1.29-2.55, p<0.01), readmission (OR 1.56 95% CI 1.10-2.23, p<0.01), non-home discharge (OR 2.81, 95% CI 1.74-4.50, p<0.01), and bile leak (OR 1.64 95% CI.05-2.54, p=0.03). Those with a mFI score of 1 were more likely than those with mFI 0 to experience non-home discharge (OR 1.54 95% CI 1.03-2.31 p=0.04) and liver failure (OR 1.63, 95% CI 1.14-2.45, p<0.01). Conclusion: Frailty is associated with increased risk of morbidity, unfavorable discharge, readmission and bile leak in patients undergoing liver resection for metastatic colorectal cancer. We recommend the use of the 5-item Modified Frailty Index to guide risk stratification, optimization and counseling.

Comparison of administrative data and the American College of Surgeons National Surgical Quality Improvement Program data in a New South Wales Hospital.

The National Surgical Quality Improvement Program (NSQIP) is widely used in North America for benchmarking. In 2015, NSQIP was introduced to four New South Wales public hospitals. The aim of this study is to investigate the agreement between NSQIP and administrative data in the Australian setting; to compare the performance of models derived from each data set to predict 30-day outcomes. The NSQIP and administrative data variables were mapped to select variables available in both data sets where coding may be influenced by interpretation of the clinical information. These were compared for agreement. Logistic regression models were fitted to estimate the probability of adverse outcomes within 30 days. Models derived from NSQIP and administrative data were compared by receiver operating characteristic curve analysis. A total of 2240 procedures over 21 months had matching records. Functional status demonstrated poor agreement (kappa 0.02): administrative data recorded only one (1%) patient with partial- or total-dependence as recorded by NSQIP data. The American Society of Anesthesiologists class demonstrated excellent agreement (kappa 0.91). Other perioperative variables demonstrated poor to fair agreement (kappa 0.12-0.61). Predictive model based on NSQIP data was excellent at predicting mortality but was less accurate for complications and readmissions. The NSQIP model was better in predicting mortality and complications (receiver operating characteristic curve 0.93 versus 0.87; P = 0.029 and 0.71 versus 0.64; P = 0.027). There is poor agreement between NSQIP data and administrative data. Predictive models associated with NSQIP data were more accurate at predicting surgical outcomes than those from administrative data. To drive quality improvement in surgery, high-quality clinical data are required and we believe that NSQIP fulfils this function.

Association of Hospital Altitude and Postoperative Infectious Complications After Major Operations.

Introduction: The relationship between altitude during treatment and common postoperative infections remains to be established. Based on the inverse relationship between oxygen partial pressure and altitude, we hypothesized that hospital elevation would correlate positively with postoperative infectious complication rates, including surgical site infection (SSI), urinary tract infection (UTI), and pneumonia. Methods: We used an event-enriched population of general, urologic, vascular, plastic-reconstructive, orthopedic, and thoracic patients within the 2016 ACS National Surgical Quality Improvement Program (NSQIP) dataset who underwent procedures with high risk of infectious complications. This yielded 82,172, 175,409, and 88,856 patients from 571, 577, and 570 hospitals for the study of 30-day postoperative SSI, UTI, and pneumonia outcomes respectively. Hospital altitudes were determined using Google Maps. Data were analyzed using univariate (altitude) and multivariate logistic regression, with altitude forced into the model, and forward-selection of NSQIP variables, with adjustment for clustering by hospital. Results: When compared in 1000-foot increments above sea level, hospital altitude had no significant effect on SSI or UTI (odds ratio [OR] = 1.0, p > 0.05). The risk of postoperative pneumonia decreased with increased altitude (OR = 0.93, 95% confidence interval: 0.87-0.99, p = 0.03). Conclusions: Patients and providers should be reassured that there is no increased risk of SSI or UTI at higher altitudes. The decreased risk of postoperative pneumonia was surprising and there exist potential explanations warranting future investigation.

The Use of Older Versus Newer Data in the National Surgical Quality Improvement Program Database Influences the Results of Total Hip Arthroplasty Outcomes Studies.

Introduction:National databases, such as the National Surgical Quality Improvement Program (NSQIP) database, are frequently used for total hip arthroplasty (THA) studies. NSQIP variables and the population included in the database have evolved over time. These changes may influence the results of studies using different periods of data.Methods:THA patients were aggregated from the 2005 to 2010 and 2011 to 2015 NSQIP data sets to define two era groups. Demographic data and 30-day perioperative outcomes were compared between the groups. As an example analysis, multivariate Poisson regression was used to determine the correlation between age and perioperative outcomes for each group.Results:Of 102,411 THA patients identified, 8098 cases were from 2005 to 2010 and 94,313 were from 2011 to 2015. A number of preoperative characteristics and perioperative outcomes were significantly different between the era groups. Multivariate analysis of the 2005 to 2010 group showed that increasing age was significantly associated with urinary tract infection and length of stay (LOS), and multivariate analysis of the 2011 to 2015 group showed that age was significantly associated with urinary tract infection, LOS, 30-day mortality, unplanned reintubation, extended LOS, pneumonia, deep vein thrombosis/thrombophlebitis, blood transfusion, and return to the operating room.Conclusion:Significantly more THA patients were enrolled in the NSQIP in the years between 2005 and 2015. Populations in 2005 to 2010 versus 2011 to 2015 were associated with differences in preoperative characteristics and perioperative outcomes. In an example analysis, it was shown that these differences together lead to different study results and conclusions. This needs to be considered when interpreting and conducting studies using earlier NSQIP data.

Expanding the scope of quality measurement in surgery to include nonoperative care: Results from the American College of Surgeons National Surgical Quality Improvement Program emergency general surgery pilot.

Patients managed nonoperatively have been excluded from risk-adjusted benchmarking programs, including the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP). Consequently, optimal performance evaluation is not possible for specialties like emergency general surgery (EGS) where nonoperative management is common. We developed a multi-institutional EGS clinical data registry within ACS NSQIP that includes patients managed nonoperatively to evaluate variability in nonoperative care across hospitals and identify gaps in performance assessment that occur when only operative cases are considered. Using ACS NSQIP infrastructure and methodology, surgical consultations for acute appendicitis, acute cholecystitis, and small bowel obstruction (SBO) were sampled at 13 hospitals that volunteered to participate in the EGS clinical data registry. Standard NSQIP variables and 16 EGS-specific variables were abstracted with 30-day follow-up. To determine the influence of complications in nonoperative patients, rates of adverse outcomes were identified, and hospitals were ranked by performance with and then without including nonoperative cases. Two thousand ninety-one patients with EGS diagnoses were included, 46.6% with appendicitis, 24.3% with cholecystitis, and 29.1% with SBO. The overall rate of nonoperative management was 27.4%, 6.6% for appendicitis, 16.5% for cholecystitis, and 69.9% for SBO. Despite comprising only 27.4% of patients in the EGS pilot, nonoperative management accounted for 67.7% of deaths, 34.3% of serious morbidities, and 41.8% of hospital readmissions. After adjusting for patient characteristics and hospital diagnosis mix, addition of nonoperative management to hospital performance assessment resulted in 12 of 13 hospitals changing performance rank, with four hospitals changing by three or more positions. This study identifies a gap in performance evaluation when nonoperative patients are excluded from surgical quality assessment and demonstrates the feasibility of incorporating nonoperative care into existing surgical quality initiatives. Broadening the scope of hospital performance assessment to include nonoperative management creates an opportunity to improve the care of all surgical patients, not just those who have an operation. Care management, level IV; Epidemiologic, level III.

Risk factors and pharmacologic prophylaxis for venous thromboembolism in elective spine surgery

Background ContextVenous thromboembolism (VTE) is a known complication after spine surgery, but prophylaxis guidelines are ambiguous for patients undergoing elective spine surgery. PurposeThe objective of this study was to characterize the incidence and risk factors for VTE and the association of pharmacologic prophylaxis with VTE and bleeding complications after elective spine surgery. Study Design/SettingThis is a retrospective cohort study of patients undergoing elective spine surgery in the National Surgical Quality Improvement Program (NSQIP) database and a retrospective cohort analysis at an academic medical center. Patient SampleThis study included 109,609 patients in the NSQIP database from 2005 to 2014 and 2,855 patients at the authors' institution from January 2013 to March 2016 who underwent elective spine surgery. Outcome MeasuresThe incidence and risk factors for VTE were assessed in both cohorts based on the NSQIP criteria. The incidence of bleeding complications requiring reoperation was assessed based on operative reports in the institutional cohort. Materials and MethodsAssociations of patient and procedure factors with VTE were characterized in the NSQIP population. In the single-institution cohort, in addition to NSQIP variables, a chart review was completed to determine the use of VTE prophylaxis, the history of prior VTE, and the incidence of hematoma requiring reoperation. The association of patient and procedure variables, including pharmacologic prophylaxis and history of prior VTE, with VTE and hematoma requiring reoperation were determined with multivariate regression. ResultsAmong 109,609 elective spine surgery patients in NSQIP, independent risk factors for VTE were greater age, male gender, increasing body mass index, dependent functional status, lumbar spine surgery, longer operative time, perioperative blood transfusion, longer length of stay, and other postoperative complications. There were 2,855 patients included in the institutional cohort. Pharmacologic prophylaxis was performed in 56.3% of the institutional patients, of whom 97.1% received unfractionated heparin. When controlling for patient and procedural variables, pharmacologic prophylaxis did not significantly influence the rate of VTE, but was associated with a significant increase in hematoma requiring a return to the operating room (relative risk=7.37, p=.048). ConclusionsPharmacologic prophylaxis, primarily with unfractionated heparin, after elective spine surgery was not associated with a significant reduction in VTE. However, there was a significant increase in postoperative hematoma requiring reoperation among patients undergoing prophylaxis. This raises questions about the routine use of unfractionated heparin for VTE prophylaxis and supports the need for further consideration of risks and benefits of chemoprophylaxis after elective spine surgery.

Frailty is associated with morbidity in adults undergoing elective anterior lumbar interbody fusion (ALIF) surgery

Background ContextPrior studies have suggested no significant differences in functional status and postoperative complications of elderly versus nonelderly patients undergoing posterior lumbar interbody fusion; however, similar studies have not been comprehensively investigated in the setting of anterior lumbar interbody fusion (ALIF). PurposeThe objective was to quantify the ability of the modified Frailty Index (mFI) to predict postoperative events in patients undergoing ALIF. Study DesignSecondary analysis of prospectively collected data. Patient SamplePatients undergoing ALIF in the National Surgical Quality Improvement Program (NSQIP) participant files for the period 2010 through 2014. Outcomes MeasuresOutcome measures included any postoperative complication, return to operating room (OR), and length of stay >5 days. MethodsNSQIP participant files from 2010 to 2014 were used to identify patients undergoing ALIF. The mFI used in the present study is an 11-variable assessment that maps 16 NSQIP variables to 11 variables in the Canadian Study of Health and Ageing Frailty Index. Univariate analysis and multivariable logistic regression models were used to compare the relative strength of association between mFI with outcome variables of interest. ResultsIn total, 3,920 ALIF cases were identified and grouped according to their mFI score: 0 (n=2,025), 0.09 (n=1,382), 0.18 (n=464), or ≥0.27 (n=49). As the mFI increased from 0 (no frailty-associated variables) to 0.27 (4 of 11) or higher, there was a significant stepwise increase in any complication from 10.8% to 32.7%. After multivariable regression analysis, no significant association was found between higher mFI scores with urinary tract infections and venous thromboembolism. High frailty scores were significant predictors of any complication (mFI of ≥0.27 [reference: 0]; OR 2.4; p=.040) and pulmonary complications (mFI score ≥0.27; OR 7.5; p=.001). ConclusionsIn summary, high mFI scores were found to be independently associated with any complication and pulmonary complications in patients who underwent ALIF. The use of mFI together with traditional risk factors may help better identify high-surgical risk patients, which may be useful for preoperative and postoperative care optimization.

Preoperative frailty predicts postoperative complications and mortality in urology patients.

Our objective was to determine the impact of preoperative frailty, as measured by validated Risk Analysis Index (RAI), on the occurrence of postoperative complications after urologic surgeries in a national database comprised of diverse practice groups and cases. The National Surgical Quality Improvement Program (NSQIP) database was queried from 2005 to 2011 for a list of abdominal, vaginal, transurethral and scrotal urological surgeries using Current Procedural Terminology codes. The study population was subdivided into two groups based on the nature of procedures performed: complex procedures (inpatient) and simple procedures (outpatient). Risk Analysis Index score was calculated using preoperative NSQIP variables to determine preoperative frailty. Major postoperative morbidities (pulmonary, cardiovascular, renal and infectious), mortality, return to operating room, discharge destination and readmission to the hospital were examined. The study identified 42,715 patients who underwent urological procedures, 25,693 complex and 17,022 simple procedures. Mean RAI score (range) was 7.75 (0-53). The majority of patients scored low on the RAI (90.57% with RAI<10). As the RAI score increased, there was a significant increase in postoperative complication and mortality rate (both p<0.0001). Similarly, the rate of return to operating room and hospital readmission rate increased as RAI increased (both p<0.0001). Additionally, rate of discharge to home decreased. Interestingly, mortality rate in patients with high RAI did not differ comparing simple to complex procedures (p=0.90), whereas complications were significantly greater in the complex operation (p=0.01). Increase in frailty, as measured by RAI score, is associated with increased postoperative complications and mortality. RAI may allow for rapid identification and counseling of patients who are at high risk of adverse perioperative outcomes.

Use of the modified frailty index to predict 30-day morbidity and mortality from spine surgery.

OBJECTIVE Limited tools exist to stratify perioperative risk in patients undergoing spinal procedures. The modified frailty index (mFI) based on the Canadian Study of Health and Aging Frailty Index (CSHA-FI), constructed from standard demographic variables, has been applied to various other surgical populations for risk stratification. The authors hypothesized that it would be predictive of postoperative morbidity and mortality in patients undergoing spine surgery. METHODS The 2006-2010 National Surgical Quality Improvement Program (NSQIP) data set was accessed for patients undergoing spine surgeries based on Current Procedural Terminology (CPT) codes. Sixteen preoperative clinical NSQIP variables were matched to 11 CSHA-FI variables (changes in daily activities, gastrointestinal problems, respiratory problems, clouding or delirium, hypertension, coronary artery and peripheral vascular disease, congestive heart failure, and so on). The outcomes assessed were 30-day occurrences of adverse events. These were then summarized in groups: any infection, wound-related complication, Clavien IV complications (life-threatening, requiring ICU admission), and mortality. RESULTS A total of 18,294 patients were identified. In 8.1% of patients with an mFI of 0 there was at least one morbid complication, compared with 24.3% of patients with an mFI of ≥ 0.27 (p < 0.001). An mFI of 0 was associated with a mortality rate of 0.1%, compared with 2.3% for an mFI of ≥ 0.27 (p < 0.001). Patients with an mFI of 0 had a 1.7% rate of surgical site infections and a 0.8% rate of Clavien IV complications, whereas patients with an mFI of ≥ 0.27 had rates of 4.1% and 7.1% for surgical site infections and Clavien IV complications, respectively (p < 0.001 for both). Multivariate analysis showed that the preoperative mFI and American Society of Anesthesiologists classification of ≥ III had a significantly increased risk of leading to Clavien IV complications and death. CONCLUSIONS A higher mFI was associated with a higher risk of postoperative morbidity and mortality, providing an additional tool to improve perioperative risk stratification.

Assessing Risk of Critical Care Complications and Mortality in the Elective Bariatric Surgery Population Using a Modified Frailty Index

The rate of surgical complications from bariatric procedures remains low despite an increase in volume. When serious complications occur, they are associated with an increased risk of mortality. The aim of this study is to determine if frail bariatric patients have an increased rate of Clavien level 4 and 5 complications. This study was conducted in participating hospitals in the National Surgical Quality Improvement Program (NSQIP). The NSQIP participant use files were used to identify 104,952 patients undergoing elective bariatric procedures from 2005 to 2012. A previously described modified frailty index (mFI) was calculated based on available NSQIP variables, with a higher index suggesting more frail patients. Postoperative adverse events were stratified to Clavien levels 4 and 5 utilizing a pre-existing mapping scheme. Overall, 1 % of patients undergoing elective bariatric surgery experienced Clavien level 4 complications, and 0.2 % experienced a Clavien level 5 complication (mortality). Univariate analysis demonstrated that frailty was significant for both Clavien level 4 and 5 complications (p < 0.001). The mean mFI for those with Clavien level 4 complications, 0.15, was significantly higher than those without Clavien 4 complications, 0.09 (p < 0.001). Those experiencing mortality had a mean mFI of 0.17 compared to a mean mFI of 0.09 in those without mortality (p < 0.001). Frailty retained the highest odds ratio for both Clavien 4 and 5 complications in multivariate analysis compared to American Society of Anesthesiologist (ASA) class, age, sex, body mass index (BMI), and procedure type. Frailty may be used during patient selection to stratify bariatric surgery patients at high risk for critical care level complications.

Preoperative frailty Risk Analysis Index to stratify patients undergoing carotid endarterectomy

Rapid and objective preoperative assessment of patients undergoing carotid endarterectomy (CEA) remains problematic. Preoperative variables correlate with increased morbidity and mortality, yet no easily implemented tool exists to stratify patients. We determined the relationship between our fully implemented frailty-based bedside Risk Analysis Index (RAI) and complications after CEA. Patients undergoing CEA in the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database from 2005 to 2011 were included. Variables of frailty RAI were matched to preoperative NSQIP variables, and outcomes including stroke, mortality, myocardial infarction (MI), and length of stay were analyzed. We further analyzed patients who were symptomatic and asymptomatic before CEA. With use of the NSQIP database, 44,832 patients undergoing CEA were analyzed (17,696 [39.5%] symptomatic; 27,136 [60.5%] asymptomatic). Increasing frailty RAI score correlated with increasing stroke, death, and MI (P < .0001) as well as with length of stay. RAI demonstrated increasing risk of stroke and death on the basis of risk stratification (low risk [0-10], 2.1%; high risk [>10], 5.0%). Among patients undergoing CEA, 88% scored low (<10) on the RAI. In symptomatic patients, the risk of stroke and death for patients with a score of ≤10 is 2.9%, whereas if the RAI score is 11 to 15, it is 5.0%; 16 to 20, 6.9%; and >21, 8.6%. In asymptomatic patients, the risk of stroke and death for patients with a score of ≤10 is 1.6%, whereas if the RAI score is 11 to 15, it is 2.9%; 16 to 20, 5.2%; and >21, 6.2%. Frailty is a predictor of increased stroke, mortality, MI, and length of stay after CEA. An easily implemented RAI holds the potential to identify a limited subset of patients who are at higher risk for postoperative complications and may not benefit from CEA.

Relative value units poorly correlate with measures of surgical effort and complexity

BackgroundThe relationship between procedural relative value units (RVUs) for surgical procedures and other measures of surgeon effort are poorly characterized. We hypothesized that RVUs would poorly correlate with quantifiable metrics of surgeon effort. MethodsUsing the 2010 American College of Surgeons - National Surgical Quality Improvement Program (NSQIP) database, we selected 11 primary current procedural terminology codes associated with high volume surgical procedures. We then identified all patients with a single reported procedural RVU who underwent nonemergent, inpatient general surgical operations. We used linear regression to correlate length of stay (LOS), operative time, overall morbidity, frequency of serious adverse events (SAEs), and mortality with RVUs. We used multivariable logistic regression using all preoperative NSQIP variables to determine other significant predictors of our outcome measures. ResultsAmong 14,481 patients, RVUs poorly correlated with individual LOS (R2 = 0.05), operative time (R2 = 0.10), and mortality (R2 = 0.35). There was a moderate correlation between RVUs and SAEs (R2 = 0.79) and RVUs and overall morbidity (R2 = 0.75). However, among low- to mid-level RVU procedures (11–35) there was a poor correlation between SAEs (R2 = 0.15), overall morbidity (R2 = 0.05), and RVUs. On multivariable analysis, RVUs were significant predictors of operative time, LOS, and SAEs (odds ratio 1.06, 95% confidence interval: 1.05–1.07), but RVUs were not a significant predictor of mortality (odds ratio 1.02, 95% confidence interval: 0.99–1.05). ConclusionsFor common, index general surgery procedures, the current RVU assignments poorly correlate with certain metrics of surgeon work, while moderately correlating with others. Given the increasing emphasis on measuring and tracking surgeon productivity, more objective measures of surgeon work and productivity should be developed.

Simplified Frailty Index to Predict Adverse Outcomes and Mortality in Vascular Surgery Patients

Frailty has been established as an important predictor of health-care outcomes. We hypothesized that the use of a modified frailty index would be a predictor of mortality and adverse occurrences in vascular surgery patients. Under the data use agreement of the American College of Surgeons, and with institutional review board (IRB) approval, the National Surgical Quality Improvement Program (NSQIP) Participant Utilization File was accessed for the years 2005-2008 for inpatient vascular surgery patients. Using the Canadian Study of Health and Aging Frailty Index (FI), 11 variables were matched to the NSQIP database. An increase in FI implies increased frailty. The outcomes assessed were mortality, wound infection, and any occurrence. We then compared the effect of FI, age, functional status, relative value units (RVU), American Society of Anesthesiology (ASA) score, and wound status on mortality. Statistical analysis was done using chi-square analysis and stepwise logistic regression. A total of 67,308 patients were identified in the database, 3913 wound occurrences, 6691 infections, 12,847 occurrences of all kinds, and 2800 deaths. As the FI increased, postoperative wound infection, all occurrences, and mortality increased (P < 0.001). Stepwise logistic regression using the FI with the NSQIP variables of age, work RVU, ASA class, wound classification, emergency status, and functional status showed FI to have the highest odds ratio (OR) for mortality (OR = 2.058, P < 0.001). A simplified FI can be obtained by easily identifiable patient characteristics, allowing for accurate prediction of postoperative morbidity and mortality in the vascular surgery population.

Effect of including cancer‐specific variables on models examining short‐term outcomes

The American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) generally has not collected cancer-specific variables. Because increasing numbers of studies are using ACS NSQIP data to study cancer surgery, the objectives of the current study were 1) to examine differences between existing ACS NSQIP variables and cancer registry variables, and 2) to determine whether the addition of cancer-specific variables improves modeling of short-term outcomes. Data from patients in the ACS NSQIP and National Cancer Data Base (NCDB) who underwent colorectal resection for cancer were linked (2006-2008). By using regression methods, the relative importance of cancer staging and neoadjuvant therapy variables were assessed along with their effects on morbidity, serious morbidity, and mortality. From 146 hospitals, 11,405 patients were identified who underwent surgery for colorectal cancer (colon, 85%; rectum, 15%). The NCDB metastatic cancer variable and the ACS NSQIP disseminated cancer variables agreed marginally (Cohen kappa coefficient, 0.454). For mortality, only the ACS NSQIP disseminated cancer variable and the NCDB stage IV variable were identified as important predictors; whereas the variables stage I through III, tumor (T)-classification, and lymph node (N)-classification were not selected. Cancer stage variables were inconsistently important for serious morbidity (stage IV, T-classification), superficial surgical site infection (N-classification), venous thromboembolism (metastatic cancer), and pneumonia (T-classification). With respect to neoadjuvant therapy, ACS NSQIP and NCDB variables agreed moderately (kappa, 0.570) and predicted superficial surgical site infection, serious morbidity, and organ space surgical site infection. The model fit was similar regardless of the inclusion of stage and neoadjuvant therapy variables. Although advanced disease stage and neoadjuvant therapy variables were predictors of short-term outcomes, their inclusion did not improve the models.

Predictors of critical care-related complications in colectomy patients using the National Surgical Quality Improvement Program

Colectomy patients experience a broad set of adverse outcomes. Complications requiring critical care support are common in this group. We hypothesized that as frailty increases, the risk of Clavien class IV and V complications will increase in colectomy patients. Using the National Surgical Quality Improvement Program (NSQIP) participant use files for 2005-2009, we identified patients who underwent laparoscopic and open colectomies by Current Procedural Terminology code. Using the Clavien classification for postoperative complications, we identified NSQIP data points most consistent with Clavien class IV requiring intensive care unit (ICU) care or class V complications (death). We used a modified frailty index with 11 variables based on mapping the Canadian Study of Health and Aging Frailty Index and existing NSQIP variables. Logistic regression was performed to acuity adjust the findings. A total of 58,448 colectomies were identified. As frailty index increased from 0 to 0.55, the proportion of those experiencing Clavien class IV or V complications increased from 3.2% at baseline to 56.3%. Variables found to be significant by logistic regression (odds ratio) were frailty index (14.4; p = 0.001), open procedure (2.35; p < 0.001), and American Society of Anesthesiologists class 4 (3.2; p = 0.038) or 5 (7.1; p = 0.001) while emergency operation and wound classification 3 or 4 were not. Complications requiring ICU care represent a significant morbidity in the colectomy patient population. Frailty index seems to be an important predictor of ICU-level complications and death, and laparoscopy seems to be protective.