Development of an improved risk calculator for complications in proctectomy

Predicted versus actual complications in Australian women undergoing post-mastectomy breast reconstruction: a retrospective cohort study using the BRA Score tool

INTRODUCTION

The Breast Reconstruction Risk Assessment (BRA) Score tool is a risk calculator developed to predict the risk of complications in individual patients undergoing breast reconstruction. It was developed in a North American population exclusively undergoing immediate breast reconstruction. This study sought to assess the predictions of the BRA Score tool against the measured outcomes of surgery for an Australian public hospital population, including both immediate and delayed reconstructions.

METHOD

This was a retrospective cohort study of data from women at a single Australian public teaching hospital unit. Data from the Flinders Breast Reconstruction Database was retrieved and compared to BRA Scores calculated for each patient. Receiver operating curve area under the curve analysis was performed as well as Brier scores to compare predicted versus observed complications.

RESULTS

BRA Score predictions were reasonable or good (C-statistic >0.7, Brier score <0.09) for the complications of overall surgical complications, surgical site infection (SSI) and seroma at 30 days, and similarly accurate for prediction of the same complications for implant reconstructions at 12 months. There were similar findings between delayed and immediate reconstructions.

CONCLUSION

The BRA Score risk calculator is valid to detect some risks in both patients undergoing immediate and delayed breast reconstruction in an Australian public hospital setting. SSI is the best predicted complication and is well-predicted across both autologous and prosthetic reconstruction types.

Impact of past surgical history on perioperative outcomes in gynecologic surgery

OBJECTIVE

We sought to determine if past surgical history is associated with perioperative outcomes for patients undergoing hysterectomy.

METHODS

A retrospective cohort study was conducted at a single, tertiary, academic health system of women who underwent hysterectomy from May 2016 - May 2017. Past surgical history (PSH) involving any abdominal or pelvic surgery, baseline demographics and perioperative outcomes were collected. For purposes of analyses, PSH was defined using three algorithms: 1) any prior abdominopelvic surgery, 2) having had abdominopelvic surgeries likely to cause adhesive disease, 3) anatomic location of prior PSH (none; pelvic; abdominal; or abdominal+pelvic). Descriptive, bivariable and multivariable analyses were performed.

RESULTS

1256 patients underwent hysterectomy. In adjusted analyses, PSH defined by any prior abdominopelvic surgery was associated with length of stay (LOS) (2.1 days (95%CI 1.9, 2.2) vs. 1.8 (95%CI 1.6, 2.0), (p=0.02)). PSH of procedures likely to cause adhesive disease was associated with greater estimated blood loss (EBL) (243.2 mL (95%CI 208.1, 278.3) vs. 189.0 (95%CI 1734, 204.7), (p=0.01)), longer LOS (2.5 days (95%CI 2.2, 2.8) vs. 1.9 (95%CI 1.7, 2.0), (p<0.01)), and more readmissions (OR 2.4, 95%CI 1.3, 4.5) (p<0.01). PSH defined by anatomic location revealed a trend (p=0.07) towards greater EBL in those with prior pelvic or abdominal+pelvic surgery compared to none or abdominal only, whereas LOS, readmissions and operative times did not differ. Increased total number of prior open surgeries was associated with operative time (p<0.0001), EBL (p<0.0001), hospital LOS (p<0.0001) and readmission (p=0.026).

CONCLUSIONS

Prior abdominopelvic surgery is associated with worse perioperative outcome measures in women undergoing hysterectomy.

Beyond 30 Days: A Risk Calculator for Longer Term Outcomes of Prosthetic Breast Reconstruction

Background

Despite growing use of surgical risk calculators, many are limited to 30-day outcomes due to the constraints of their underlying datasets. Because complications of breast reconstruction can occur well beyond 30 days after surgery, we endeavored to expand the Breast Reconstruction Risk Assessment (BRA) Score to prediction of 1-year complications after primary prosthetic breast reconstruction.

Methods

We examined our prospective intrainstitutional database of prosthetic breast reconstructions from 2004 to 2015. Patients without 1-year follow-up were excluded. Pertinent patient variables include those enumerated in past iterations of the BRA Score. Outcomes of interest include seroma, surgical site infection (SSI), implant exposure, and explantation occurring within 1 year of tissue expander placement. Risk calculators were developed for each outcome using multivariate logistic regression models and made available online at www.BRAScore.org. Internal validity was assessed using C-statistic, Hosmer-Lemeshow test, and Brier score.

Results

Nine-hundred three patients met inclusion criteria. Within 1-year, 3.0% of patients experienced seroma, 6.9% infection, 7.1% implant exposure, and 13.2% explantation. Thirty-day, 90-day, and 180-day windows captured 17.6%, 39.5%, and 59.7% of explantations, respectively. One-year risk calculators were developed for each complication of interest, and all demonstrated good internal validity: C-statistics for the 5 models ranged from 0.674 to 0.739, Hosmer-Lemeshow tests were uniformly nonsignificant, and Brier scores ranged from 0.027 to 0.154.

Conclusions

Clinically significant complications of prosthetic breast reconstruction usually occur beyond the 30-day window following tissue expander placement. To better reflect long-term patient experiences, the BRA Score was enhanced with individualized risk models that predicted 1-year complications after prosthetic reconstruction (BRA Score XL). All models performed as well as, if not better than, the original BRA Score models and other popular risk calculators such as the CHA₂DS₂VASc Score. The patient-friendly BRA Score XL risk calculator is available at www.brascore.org to facilitate operative decision-making and heighten the informed consent process for patients.

ACS-NSQIP risk calculator predicts cohort but not individual risk of complication following colorectal resection

OBJECTIVE

Compare the ACS-NSQIP risk calculator with institutional risk for colorectal surgery.

METHODS

Actual and predicted outcomes were compared for both cohort and individuals.

RESULTS

For the cohort, the risk calculator was accurate for 7/8 outcomes; there were more serious complications than predicted (19.4 vs 14.7%, p < 0.05). Risk calculator Brier scores and null Brier scores were comparable.

PATIENTS

with better outcomes than predicted were current smokers (OR 4.3 95% CI 1.2-15.4), ASA ≥ 3 (OR 10.4, 95% CI 2.8-39.2), underwent total/subtotal colectomy (OR 3.5, 95% CI 1.1-12.2) or operated by Surgeon 2 (OR 2.9, 95% CI 1.4-11.6). Patients with serious complications who had low predicted risk had low ASA (OR 10.5, 95% CI 1.3-82.6), and underwent operation by Surgeon 2 (OR 11.8, 95% CI 2.5, 55.2).

LIMITATIONS

Single center study, sample size may bias subgroup analyses.

CONCLUSIONS

The ACS NSQIP calculator did not predict outcome better than sample risk.

Prospective Validation of the Iowa Rectal Surgery Risk Calculator

BACKGROUND

The Iowa Rectal Surgery Risk Calculator estimates risk for proctectomy procedures. The Iowa Calculator performed well on NSQIP 2010-2011 training and 2005-2009 validation datasets, but was not prospectively validated and did not include low anterior resections. This study sought to demonstrate validity on new independent data, to update the calculator to include low anterior resection, and to compare performance to other risk assessment tools.

METHODS

Non-emergent ACS-NSQIP proctectomy and low anterior resection data from 2010 to 2015 (n = 65,683) were included. The Iowa Calculator generated risk estimates for 30-day morbidity using 2012-2015 data. An Updated Calculator used 2010-2011 training data to include low anterior resection, with validation on 2012-2015 data. NSQIP data provided NSQIP Morbidity Model predictions and a custom web-script collected ACS-NSQIP Online Surgical Risk Calculator predictions for all patients.

RESULTS

Proctectomy morbidity (not including low anterior resection) decreased from 40.4% in 2010-2011 to 37.0% in 2012-2015. Low anterior resection had lower morbidity (22.4% in 2012-15). The Iowa Calculator demonstrated good discrimination and calibration using 2012-2015 data (C-statistic 0.676, deviance + 9.2%). After including low anterior resection, the Updated Iowa Calculator performed well during training (c-statistic 0.696, deviance 0%) and validation (C-statistic 0.706, deviance + 7.9%). The Updated Iowa Calculator had significantly better discrimination and calibration than morbidity predictions from the ACS Online Calculator (C-statistic 0.693, P < 0.001, deviance - 28.1%) and NSQIP General/Vascular Surgery Model (C-statistic 0.703, P < 0.05, deviance - 40.8%).

CONCLUSION

When applied to new independent data, the Iowa Calculator supplies accurate risk estimates. The Updated Iowa Calculator includes low anterior resection, and both are prospectively validated. Risk estimation by the Iowa Calculators was superior to ACS-provided risk tools.

Evaluating Mastectomy Skin Flap Necrosis in the Extended Breast Reconstruction Risk Assessment Score for 1-Year Prediction of Prosthetic Reconstruction Outcomes

BACKGROUND

Rates of mastectomy for breast cancer treatment and immediate reconstruction continue to rise. With increasing scrutiny on outcomes and patient satisfaction, there is an impetus for providers to be more deliberate in appropriate patient selection for breast reconstruction. The Breast Reconstruction Risk Assessment (BRA) Score was developed for prediction of complications after primary prosthetic breast reconstruction, focusing on calculating risk estimations for a variety of complications based on individual patient demographic and perioperative characteristics. In this study, we evaluated mastectomy skin flap necrosis (MSFN) as a function of patient characteristics to validate the BRA Score.

STUDY DESIGN

We examined our prospective intra-institutional database of prosthetic breast reconstructions from 2004 to 2015. The end point of interest was 1-year occurrence of MSFN after stage I tissue expander placement.

RESULTS

Nine hundred and three patients were included; 50% underwent bilateral reconstruction. Median follow-up was 23 months. Mean 1-year complication rates were as follows: MSFN 12.4%, seroma 3.0%, infection 6.9%, dehiscence/exposure 7.1%, and explantation 13.2%. Statistically significantly higher rates of MSFN were found in older patients, smokers, patients with postoperative infections, patients with hypertension, and patients who used aspirin. Neoadjuvant or adjuvant chemotherapy and radiation, diabetes, and seroma formation did not have a statistically significant impact on necrosis rates.

CONCLUSIONS

The BRA Score was expanded to estimate complication risk after tissue expander placement up to 1 year postoperatively. The risk of MSFN as calculated by the BRA Score: Extended Length is consistent with published studies demonstrating increased risk with specific comorbidities, and further validates expansion of the BRA score risk calculator.

Examining the validity of the ACS-NSQIP Risk Calculator in plastic surgery: lack of input specificity, outcome variability and imprecise risk calculations

American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) created the Surgical Risk Calculator, to allow physicians to offer patients a risk-adjusted 30-day surgical outcome prediction. This tool has not yet been validated in plastic surgery. A retrospective analysis of all plastic surgery-specific complications from a quality assurance database from September 2013 through July 2015 was performed. Patient preoperative risk factors were entered into the ACS Surgical Risk Calculator, and predicted outcomes were compared with actual morbidities. The difference in average predicted complication rate versus the actual rate of complication within this population was examined. Within the study population of patients with complications (n=104), the calculator accurately predicted an above average risk for 20.90% of serious complications. For surgical site infections, the average predicted risk for the study population was 3.30%; this prediction was proven only 24.39% accurate. The actual incidence of any complication within the 4924 patients treated in our plastic surgery practice from September 2013 through June 2015 was 1.89%. The most common plastic surgery complications include seroma, hematoma, dehiscence and flap-related complications. The ACS Risk Calculator does not present rates for these risks. While most frequent outcomes fall into general risk calculator categories, the difference in predicted versus actual complication rates indicates that this tool does not accurately predict outcomes in plastic surgery. The ACS Surgical Risk Calculator is not a valid tool for the field of plastic surgery without further research to develop accurate risk stratification tools.

Risk of Surgical Site Infection Varies Based on Location of Disease and Segment of Colorectal Resection for Cancer

BACKGROUND

Current quality-monitoring initiatives do not accurately evaluate surgical site infections based on type of surgical procedure.

OBJECTIVE

This study aimed to characterize the effect of the anatomical site resected (right, left, rectal) on wound complications, including superficial, deep, and organ space surgical site infections, in patients who have cancer.

SETTINGS

Data were retrieved from the American College of Surgeons National Surgical Quality Improvement Program database.

DESIGN

This study was designed to determine the independent risk associated with the anatomical location of cancer resection for all subtypes of surgical site infection. Statistical methods included the Fisher exact test, the χ test, and univariable and multivariable analyses for each outcome of interest.

PATIENTS

All colon and rectal resections for colorectal cancer between 2006 and 2012 were selected. Included were 45,956 patients: 17,993 (39.2%) underwent right colectomy, 11,538 (25.1%) underwent left colectomy, and 16,425 (35.7%) underwent rectal resections.

RESULTS

The overall surgical site infection rate was 12.3%: 3.7% organ space, 1.4% deep, and 7.2% superficial. On multivariable analysis, rectal resection was associated with the greatest odds of overall surgical site infections in comparison with left- or right-sided resections (rectal OR, 1.51; 95% CI, 1.35-1.69 vs left OR, 1.09; 95% CI, 0.97-1.23 vs right OR, 1). Rectal resections were also associated with greater odds of developing a deep surgical site infection than either right (rectal OR, 1.45; 95% CI, 1.06-1.99) or left (OR, 0.89; 95% CI, 0.62-1.27). The likelihood of organ space surgical site infection followed a similar pattern (rectal OR, 1.83; 95% CI 1.49-2.25; left colon, OR, 0.95; 95% CI, 0.75-1.19). Rectal and left resections had increased odds of superficial surgical site infections compared with right resections (rectal OR, 1.31; 95% CI, 1.14-1.51; left OR, 1.19; 95% CI, 1.03-1.37).

LIMITATIONS

This is a retrospective observational study.

CONCLUSIONS

Rectal resections for cancer are independently associated with an increased likelihood of superficial, deep, and organ space infections. The policy on surgical site infections as a quality measure currently in place requires modification to adjust for the location of pathology and, hence, the anatomical segment resected when assessing the risk for type of surgical site infection.

Assessment of the Addition of Hypoalbuminemia to ACS-NSQIP Surgical Risk Calculator in Colorectal Cancer

The aim of this study was to evaluate the benefit of adding hypoalbuminemia to the American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) Surgical Risk Calculator when predicting postoperative outcomes in colorectal cancer patients.The ACS-NSQIP Surgical Risk Calculator offers qualified risk evaluation in surgical decision-making and informed patient consent. To date, malnutrition defined as hypoalbuminemia, an important independent surgical risk factor in colorectal cancer, is not included.This is a retrospective, multi-institutional study of ACS-NSQIP patients (n = 18,532) who received colorectal surgery from 2009 to 2012. Models were constructed for predicting postoperative mortality and morbidity using the risk factors of the ACS-NSQIP Surgical Risk Calculator before and after adding hypoalbuminemia as a risk factor. The 2 models' performance was then compared using c-statistics and Brier scores. The ACS-NSQIP database in 2008 was used for validation of the created models.The prevalence of hypoalbuminemia (27.8%) is higher in colorectal cancer, when compared with other most common cancers. In univariate analyses, hypoalbuminemia was significantly associated with postoperative mortality and morbidity in colorectal cancer patients. In multivariate logistic regression analyses, 15 postoperative complications, including mortality and serious morbidities, were significantly predicted by hypoalbuminemia. Most of the models with hypoalbuminemia showed better performance and validation in predicting postoperative complications than those without hypoalbuminemia.In colorectal cancer, hypoalbuminemia, with levels below 3.5 g/dL, serves as an excellent assessment tool and preoperative predictor of postoperative outcomes. When combined with hypoalbuminemia as a risk factor, the ACS-NSQIP Surgical Risk Calculator offers more accurate information and estimation of surgical risks to patients and surgeons when choosing treatment options.

Risk calculators predict failures of knee and hip arthroplasties: findings from a large health maintenance organization

BACKGROUND

Considering the cost and risk associated with revision Total knee arthroplasty (TKAs) and Total hip arthroplasty (THAs), steps to prevent these operations will help patients and reduce healthcare costs. Revision risk calculators for patients may reduce revision surgery by supporting clinical decision-making at the point of care.

QUESTIONS/PURPOSES

We sought to develop a TKA and THA revision risk calculator using data from a large health-maintenance organization's arthroplasty registry and determine the best set of predictors for the revision risk calculator.

METHODS

Revision risk calculators for THAs and TKAs were developed using a patient cohort from a total joint replacement registry and data from a large US integrated healthcare system. The cohort included all patients who had primary procedures performed in our healthcare system between April 2001 and July 2008 and were followed until January 2014 (TKAs, n = 41,750; THAs, n = 22,721), During the study period, 9% of patients (TKA = 3066/34,686; THA=1898/20,285) were lost to followup and 7% died (TKA= 2350/41,750; THA=1419/20,285). The outcome of interest was revision surgery and was defined as replacement of any component for any reason within 5 years postoperatively. Candidate predictors for the revision risk calculator were limited to preoperative patient demographics, comorbidities, and procedure diagnoses. Logistic regression models were used to identify predictors and the Hosmer-Lemeshow goodness-of-fit test and c-statistic were used to choose final models for the revision risk calculator.

RESULTS

The best predictors for the TKA revision risk calculator were age (odds ratio [OR], 0.96; 95% CI, 0.95-0.97; p < 0.001), sex (OR, 0.84; 95% CI, 0.75-0.95; p = 0.004), square-root BMI (OR, 1.05; 95% CI, 0.99-1.11; p = 0.140), diabetes (OR, 1.32; 95% CI, 1.17-1.48; p < 0.001), osteoarthritis (OR, 1.16; 95% CI, 0.84-1.62; p = 0.368), posttraumatic arthritis (OR, 1.66; 95% CI, 1.07-2.56; p = 0.022), and osteonecrosis (OR, 2.54; 95% CI, 1.31-4.92; p = 0.006). The best predictors for the THA revision risk calculator were sex (OR, 1.24; 95% CI, 1.05-1.46; p = 0.010), age (OR, 0.98; 95% CI, 0.98-0.99; p < 0.001), square-root BMI (OR, 1.07; 95% CI, 1.00-1.15; p = 0.066), and osteoarthritis (OR, 0.85; 95% CI, 0.66-1.09; p = 0.190).

CONCLUSIONS

Study model parameters can be used to create web-based calculators. Surgeons can enter personalized patient data in the risk calculators for identification of risk of revision which can be used for clinical decision making at the point of care. Future prospective studies will be needed to validate these calculators and to refine them with time.

LEVEL OF EVIDENCE

Level III, prognostic study.

Differences in short-term outcomes among patients undergoing IPAA with or without preoperative radiation: a National Surgical Quality Improvement Program analysis

BACKGROUND

Single-institution studies demonstrate a correlation between preoperative pelvic radiation and poor long-term pouch function after IPAA. The rarity of the radiated pelvis before these procedures limits the ability to draw conclusions on the effects of preoperative radiation on short-term outcomes, which may contribute to long-term pouch dysfunction.

OBJECTIVE

The purpose of this work was to better understand the impact of pelvic radiation on short-term outcomes in patients undergoing IPAA.

DESIGN

We conducted a retrospective review of the American College of Surgeons National Surgical Quality Improvement Program database (2005-2011).

SETTINGS

The study was conducted at all participating NSQIP institutions.

PATIENTS

The cohort was composed of patients undergoing nonemergent IPAA procedures.

MAIN OUTCOME MEASURES

Proportions of patients experiencing postoperative complications within 30 days were compared by Fisher exact and Wilcoxon rank-sum tests based on whether they received preoperative radiation. Multivariate logistic regression models controlled for the effects of multiple risk factors.

RESULTS

Included were 3172 patients receiving IPAA; 162 received pelvic radiation. The postoperative complication rate was not significantly different in patients receiving pelvic radiation versus not receiving pelvic radiation (p = 0.06). In a subset of patients with cancer diagnoses (n = 598), 157 received pelvic radiation; complication rates were not significantly different (p = 0.16). Patients receiving pelvic radiation had significantly lower rates of sepsis in both the overall and cancer diagnosis groups (p = 0.005 and p = 0.047), a finding which persisted after controlling for the effects of multiple risk factors (multivariate p values = 0.030 and 0.047).

LIMITATIONS

This was a retrospective database design with short-term follow-up.

CONCLUSIONS

Patients who received radiation before IPAA had no difference in overall 30-day complication rates but had significantly lower rates of sepsis when compared with patients not receiving pelvic radiation. The perceived inferior long-term pouch function in patients undergoing preoperative pelvic radiation does not appear to be attributable to increases in 30-day complications.