Performance Comparison Between SURPAS and ACS NSQIP Surgical Risk Calculator in Pulmonary Resection

Comparison of a risk calculator with frailty indices in patients undergoing lung cancer resection

INTRODUCTION

Perioperative risk stratification is an essential component of preoperative planning for cancer surgery. While frailty has gained attention for its utility in risk stratification, no studies have directly compared it to existing risk calculators. Therefore, the objective of this study was to compare the risk stratification of the American College of Surgeons Surgical Risk Calculator (ACS-SRC), the Revised Risk Analysis Index (RAI-rev), and the Modified Frailty Index (5-mFI). The primary outcomes were 30-day postoperative morbidity, 30-day postoperative mortality, unplanned readmission, unplanned reoperation, and discharge disposition other-than-home.

METHODS

Patients undergoing anatomic lung resection for primary, non-small cell lung cancer were identified within the American College of Surgeons National Quality Improvement Program (ACS NSQIP) database. The ACS-SRC, RAI-rev, and 5-mFI tools were used to predict adverse postoperative events. Tools were compared for discrimination in the primary outcomes.

RESULTS

9663 patients undergoing anatomic lung resection for cancer between 2012 and 2014 were included. The cohort was 53.1% female. Median age at diagnosis was 67 (interquartile range = 59-74) years. Cardiothoracic surgeons performed 89% and general surgeons performed 11.0% of the operations. Perioperative morbidity and mortality rates were 10.9% (n = 1048) and 1.6% (n = 158). Rates of 30-day postoperative unplanned readmission and reoperation were 7.5% (n = 725) and 4.8% (n = 468). The ACS-SRC had the highest discrimination for all measured outcomes, as measured by the area under the receiver operating curve (AUC) and corresponding confidence interval (95% confidence interval [CI]). This included perioperative mortality (AUC = 0.74, 95% CI = 0.71-0.78), compared to RAI-rev (AUC = 0.66, 95% CI = 0.62-0.69) and 5-mFI (AUC = 0.61, 95% CI = 0.57-0.65; p < 0.001). The RAI-rev and 5-mFI had similar discrimination for all measured outcomes.

CONCLUSION

ACS-SRC was the perioperative risk stratification tool with the highest predictive discrimination for adverse, 30-day, postoperative events for patients with cancer treated with anatomic lung resection.

Major Perioperative Cardiac Risk Assessment: A Review for Cardio-Oncologists and Perioperative Physicians

The Revised Cardiac Risk Index (RCRI) and the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) preoperative risk assessment tools are the most widely used methods for quantifying the risk of major negative perioperative cardiac outcomes that a patient may face during and after noncardiac surgery. However, these tools were created to include as wide a range of surgical factors as possible; thus, some predictive accuracy is sacrificed when it comes to certain surgical subpopulations. In this review, we explore the various surgical oncology patient populations for whom these assessment tools can be reliably applied and for whom they demonstrate poor reliability.

Strategies to reduce morbidity following pleurectomy and decortication for malignant pleural mesothelioma

BACKGROUND

Pleurectomy and decortication (PD) in malignant pleural mesothelioma has a high morbidity mostly associated with aspiration pneumonia (PNA), deep vein thrombosis (DVT), and foreign catheter sepsis. We instituted four strategies to reduce these complications and report our experience.

METHODS

This was a retrospective review of patients who underwent PD at the University of Pennsylvania between 2015 and 2022. Our patients underwent standard of care PD in addition to tracheostomy and gastrostomy/jejunostomy tube with therapeutic anticoagulation (AC) leading up to surgery. Measured outcomes were postoperative PNA, DVT, and sepsis. The predicted risk of those same outcomes had patients not undergone the interventions was calculated based on the American College of Surgeons (ACS) surgical risk calculator (SRC). A McNemar's test was used to determine whether the risk of having PNA, DVT and sepsis differed between the two subgroups.

RESULTS

Fifty-five patients were included in the study. The mean age was 70 years (SD 6.2) with a mean of 21 (SD 19) pack-years of smoking. PNA, DVT, and catheter-related sepsis occurred in 12, four, and seven patients, respectively. Upon using the ACS SRC prediction model of the nonintervention group, PNA, DVT and catheter related sepsis was predicted to occur in 24 (paired data OR 5, 95% CI: 1.4-17.2; McNemar's test p = 0.008), 14 (paired data OR 3.5, 95% CI: 1.15-10.6; McNemar's test p = 0.03), and 17 (paired OR 3, 95% CI: 1.09-8.3; McNemar's test p = 0.04) patients, respectively.

DISCUSSION

Patients undergoing tracheostomy creation, therapeutic AC at the time of diagnosis, and gastrostomy tube placement had a reduced risk of aspiration PNA, DVT, and catheter sepsis.

Preoperative Prediction of Unplanned Reoperation in a Broad Surgical Population

INTRODUCTION

Unplanned reoperation is an undesirable outcome with considerable risks and an increasingly assessed quality of care metric. There are no preoperative prediction models for reoperation after an index surgery in a broad surgical population in the literature. The Surgical Risk Preoperative Assessment System (SURPAS) preoperatively predicts 12 postoperative adverse events using 8 preoperative variables, but its ability to predict unplanned reoperation has not been assessed. This study's objective was to determine whether the SURPAS model could accurately predict unplanned reoperation.

METHODS

This was a retrospective analysis of the American College of Surgeons' National Surgical Quality Improvement Program adult database, 2012-2018. An unplanned reoperation was defined as any unintended operation within 30 d of an initial scheduled operation. The 8-variable SURPAS model and a 29-variable "full" model, incorporating all available American College of Surgeons' National Surgical Quality Improvement Program nonlaboratory preoperative variables, were developed using multiple logistic regression and compared using discrimination and calibration metrics: C-indices (C), Hosmer-Lemeshow observed-to-expected plots, and Brier scores (BSs). The internal chronological validation of the SURPAS model was conducted using "training" (2012-2017) and "test" (2018) datasets.

RESULTS

Of 5,777,108 patients, 162,387 (2.81%) underwent an unplanned reoperation. The SURPAS model's C-index of 0.748 was 99.20% of that for the full model (C = 0.754). Hosmer-Lemeshow plots showed good calibration for both models and BSs were similar (BS = 0.0264, full; BS = 0.0265, SURPAS). Internal chronological validation results were similar for the training (C = 0.749, BS = 0.0268) and test (C = 0.748, BS = 0.0250) datasets.

CONCLUSIONS

The SURPAS model accurately predicted unplanned reoperation and was internally validated. Unplanned reoperation can be integrated into the SURPAS tool to provide preoperative risk assessment of this outcome, which could aid patient risk education.

Predicting Non-home Discharge After Lung Surgery: Analysis of the General Thoracic Surgery Database

BACKGROUND

Anticipating the need for non-home discharge (NHD) enables improved patient counseling and expedites placement, potentially reducing length of stay and hospital readmission. The objective of this study was to create a simple, preoperative, clinical prediction tool for NHD using The Society of Thoracic Surgeons General Thoracic Surgery Database (STS GTSD).

METHODS

The STS GTSD was queried for patients who underwent elective anatomic lung cancer resection between 2009 and 2019. Exclusion criteria included age <18 years, percentage predicted diffusion capacity of the lung for carbon monoxide <20% or >150%, N3 or M1 disease, incomplete datasets, and mortality. The primary outcome was defined as discharge to an extended care, transitional care, rehabilitation center, or another hospital. Multivariable logistic regression was used to select risk factors and a nomogram for predicting risk of NHD was developed. The approach was cross-validated in 100 replications of a training set consisting of randomly selected two-thirds of the cohort and a validation set of remaining patients.

RESULTS

A total of 35 948 patients from the STS GTSD met inclusion criteria. Final model variables used to derive the nomogram for NHD risk prediction included age (P < .001), percentage predicted diffusion capacity of the lung for carbon monoxide (P < .001), open surgery (P < .001), cerebrovascular history (P < .001), and Zubrod score (P < .001). The receiver operating characteristic curve, using sensitivities and specificities of the model, yielded area under the curve of 0.74. In 100 replicated cross-validations, out-of-sample area under the curve ranged from 0.72-0.76.

CONCLUSIONS

Using readily available preoperative variables, our nomogram prognosticates the risk of NHD after anatomic lung resection with good discriminatory ability. Such risk stratification can enable improved patient counseling and facilitate better planning of patients' postoperative needs.

Continuous Relationship of Operative Duration with Risk of Adverse Perioperative Outcomes and Early Discharge Undergoing Thoracoscopic Lung Cancer Surgery

Background: For thoracoscopic lung cancer surgery, the continuous relationship and the trigger point of operative duration with a risk of adverse perioperative outcomes (APOs) and early discharge remain unknown. Methods: This study enrolled 12,392 patients who underwent this surgical treatment. Five groups were stratified by operative duration: <60 min, 60−120 min, 120−180 min, 180−240 min, and ≥240 min. APOs included intraoperative hypoxemia, delayed extubation, postoperative pulmonary complications (PPCs), prolonged air leakage (PAL), postoperative atrial fibrillation (POAF), and transfusion. A restricted cubic spline (RCS) plot was used to characterize the continuous relationship of operative duration with the risk of APOs and early discharge. Results: The risks of the aforementioned APOs increased with each additional hour after the first hour. A J-shaped association with APOs was observed, with a higher risk in those with prolonged operative duration compared with those with shorter values. However, the probability of early discharge decreased from 0.465 to 0.350, 0.217, and 0.227 for each additional hour of operative duration compared with counterparts (<60 min), showing an inverse J-shaped association. The 90 min procedure appears to be a tipping point for a sharp increase in APOs and a significant reduction in early discharge. Conclusions: Our findings have important and meaningful implications for risk predictions and clinical interventions, and early rehabilitation, for APOs.

Attitudes about use of preoperative risk assessment tools: a survey of surgeons and surgical residents in an academic health system

Background

Formal surgical risk assessment tools have been developed to predict risk of adverse postoperative patient outcomes. Such tools accurately predict common postoperative complications, inform patients and providers of likely perioperative outcomes, guide decision making, and improve patient care. However, these are underutilized. We studied the attitudes towards and techniques of how surgeons preoperatively assess risk.

Methods

Surgeons at a large academic tertiary referral hospital and affiliate community hospitals were emailed a 16-question survey via REDCap (Research Electronic Data Capture) between 8/2019-6/2020. Reminder emails were sent once weekly for three weeks. All completed surveys by surgical residents and attendings were included; incomplete surveys were excluded. Surveys were analyzed using descriptive statistics (frequency distributions and percentages for categorical variables, means, and standard deviations for continuous variables), and Fisher’s exact test and unpaired t-tests comparing responses by surgical attendings vs. residents.

Results

A total of 108 surgical faculty, 95 surgical residents, and 58 affiliate surgeons were emailed the survey. Overall response rates were 50.0% for faculty surgeons, 47.4% for residents, and 36.2% for affiliate surgeons. Only 20.8% of surgeons used risk calculators most or all of the time. Attending surgeons were more likely to use prior experience and current literature while residents used risk calculators more frequently. Risk assessment tools were more likely to be used when predicting major complications and death in older patients with significant risk factors. Greatest barriers for use of risk assessment tools included time, inaccessibility, and trust in accuracy.

Conclusions

A small percentage of surgeons use surgical risk calculators as part of their routine practice. Time, inaccessibility, and trust in accuracy were the most significant barriers to use.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13037-022-00320-1.

Comparison of Preoperative Surgical Risk Estimated by Thoracic Surgeons Versus a Standardized Surgical Risk Prediction Tool

Considerable variability exists between surgeons' assessments of a patient's individual pre-operative surgical risk. Surgical risk calculators are not routinely used despite their validation. We sought to compare thoracic surgeons' prediction of patients' risk of postoperative adverse outcomes versus a surgical risk calculator, the Surgical Risk Preoperative Assessment System (SURPAS). We developed vignettes from 30 randomly selected patients who underwent thoracic surgery in the American College of Surgeons' National Surgical Quality Improvement Program (NSQIP) database. Twelve thoracic surgeons estimated patients' preoperative risks of postoperative morbidity and mortality. These were compared to SURPAS estimates of the same vignettes. C-indices and Brier scores were calculated for the surgeons' and SURPAS estimates. Agreement between surgeon estimates was examined using intraclass correlation coefficients (ICCs). Surgeons estimated higher morbidity risk compared to SURPAS for low-risk patients (ASA classes 1-2, 11.5% vs. 5.1%, p=<0.001) and lower morbidity risk compared to SURPAS for high-risk patients (ASA class 5, 37.6% vs. 69.8%, p<0.001). This trend also occurred in high-risk patients for mortality (ASA 5, 11.1% vs. 44.3%, p<0.001). C-indices for SURPAS vs. surgeons were 0.84 vs. 0.76 (p=0.3) for morbidity and 0.98 vs. 0.85 (p=0.001) for mortality. Brier scores for SURPAS vs. surgeons were 0.1579 vs. 0.1986 for morbidity (p=0.03) and 0.0409 vs. 0.0543 for mortality (p=0.006). ICCs showed that surgeons had moderate risk agreement for morbidity (ICC=0.654) and mortality (ICC=0.507). Thoracic surgeons and patients could benefit from using a surgical risk calculator to better estimate patients' surgical risks during the informed consent process.