Impact of a Risk Calculator on Risk Perception and Surgical Decision Making: A Randomized Trial

Length of Stay Prediction Models for Oral Cancer Surgery: Machine Learning, Statistical and ACS-NSQIP

OBJECTIVE

Accurate prediction of hospital length of stay (LOS) following surgical management of oral cavity cancer (OCC) may be associated with improved patient counseling, hospital resource utilization and cost. The objective of this study was to compare the performance of statistical models, a machine learning (ML) model, and The American College of Surgeons National Surgical Quality Improvement Program's (ACS-NSQIP) calculator in predicting LOS following surgery for OCC.

MATERIALS AND METHODS

A retrospective multicenter database study was performed at two major academic head and neck cancer centers. Patients with OCC who underwent major free flap reconstructive surgery between January 2008 and June 2019 surgery were selected. Data were pooled and split into training and validation datasets. Statistical and ML models were developed, and performance was evaluated by comparing predicted and actual LOS using correlation coefficient values and percent accuracy.

RESULTS

Totally 837 patients were selected with mean patient age being 62.5 ± 11.7 [SD] years and 67% being male. The ML model demonstrated the best accuracy (validation correlation 0.48, 4-day accuracy 70%), compared with the statistical models: multivariate analysis (0.45, 67%) and least absolute shrinkage and selection operator (0.42, 70%). All were superior to the ACS-NSQIP calculator's performance (0.23, 59%).

CONCLUSION

We developed statistical and ML models that predicted LOS following major free flap reconstructive surgery for OCC. Our models demonstrated superior predictive performance to the ACS-NSQIP calculator. The ML model identified several novel predictors of LOS. These models must be validated in other institutions before being used in clinical practice.

LEVEL OF EVIDENCE

3 Laryngoscope, 134:3664-3672, 2024.

Predicting Risk of Post-Operative Morbidity and Mortality following Gynaecological Oncology Surgery (PROMEGO): A Global Gynaecological Oncology Surgical Outcomes Collaborative Led Study

The medical complexity of surgical patients is increasing, and surgical risk calculators are crucial in providing high-value, patient-centered surgical care. However, pre-existing models are not validated to accurately predict risk for major gynecological oncology surgeries, and many are not generalizable to low- and middle-income country settings (LMICs). The international GO SOAR database dataset was used to develop a novel predictive surgical risk calculator for post-operative morbidity and mortality following gynecological surgery. Fifteen candidate features readily available pre-operatively across both high-income countries (HICs) and LMICs were selected. Predictive modeling analyses using machine learning methods and linear regression were performed. The area-under-the-receiver-operating characteristic curve (AUROC) was calculated to assess overall discriminatory performance. Neural networks (AUROC 0.94) significantly outperformed other models (p < 0.001) for evaluating the accuracy of prediction across three groups, i.e., minor morbidity (Clavien-Dindo I-II), major morbidity (Clavien-Dindo III-V), and no morbidity. Logistic-regression modeling outperformed the clinically established SORT model in predicting mortality (AUROC 0.66 versus 0.61, p < 0.001). The GO SOAR surgical risk prediction model is the first that is validated for use in patients undergoing gynecological surgery. Accurate surgical risk predictions are vital within the context of major cytoreduction surgery, where surgery and its associated complications can diminish quality-of-life and affect long-term cancer survival. A model that requires readily available pre-operative data, irrespective of resource setting, is crucial to reducing global surgical disparities.

Clinical Decision Support for Surgery: A Mixed Methods Study on Design and Implementation Perspectives From Urologists

OBJECTIVE

To assess urologist attitudes toward clinical decision support (CDS) embedded into the electronic health record (EHR) and define design needs to facilitate implementation and impact. With recent advances in big data and artificial intelligence (AI), enthusiasm for personalized, data-driven tools to improve surgical decision-making has grown, but the impact of current tools remains limited.

METHODS

A sequential explanatory mixed methods study from 2019 to 2020 was performed. First, survey responses from the 2019 American Urological Association Annual Census evaluated attitudes toward an automatic CDS tool that would display risk/benefit data. This was followed by the purposeful sampling of 25 urologists and qualitative interviews assessing perspectives on CDS impact and design needs. Bivariable, multivariable, and coding-based thematic analysis were applied and integrated.

RESULTS

Among a weighted sample of 12,366 practicing urologists, the majority agreed CDS would help decision-making (70.9%, 95% CI 68.7%-73.2%), aid patient counseling (78.5%, 95% CI 76.5%-80.5%), save time (58.1%, 95% CI 55.7%-60.5%), and improve patient outcomes (42.9%, 95% CI 40.5%-45.4%). More years in practice was negatively associated with agreement (P <.001). Urologists described how CDS could bolster evidence-based care, personalized medicine, resource utilization, and patient experience. They also identified multiple implementation barriers and provided suggestions on form, functionality, and visual design to improve usefulness and ease of use.

CONCLUSION

Urologists have favorable attitudes toward the potential for clinical decision support in the EHR. Smart design will be critical to ensure effective implementation and impact.

Influence of the type of anatomic resection on anastomotic leak after surgery for colon cancer

INTRODUCTION

Anastomotic leak (AL) after colon cancer resection is feared by surgeons because of its associated morbidity and mortality. Considerable research has been directed at predictive factors for AL, but not the anatomic type of colonic resection. Anecdotally, certain types of resection are associated with higher leak rates although there remains a paucity of data on this. This study aimed to determine the AL rate for different types of colon cancer resection to inform decisions regarding the choice of operation.

METHODOLOGY

Retrospective analysis of Bowel Cancer Outcome Registry (BCOR) for all colonic cancer resections with anastomosis between January 2007 and December 2020. Demographic, patient, tumour and outcome data were analysed. AL rates were compared among the different colonic procedures with both univariate and multivariate analysis.

RESULTS

20 191 patients who underwent resection with anastomosis for cancer were included in this study. Of these 535 (2.6%) suffered ALs. While the univariate analysis found male sex, procedure type, symptomatic cancers, emergency surgery, unsupervised registrars, conversion to open surgery, medical complications and higher TNM staging were associated with AL, multivariate analysis, found only procedure type remained a significant predictor of AL (total colectomy (OR 4.049, P<0.001), subtotal colectomy (OR 2.477, P<0.001) and extended right hemicolectomy (OR 2.171, P < 0.001)).

CONCLUSION

AL is more common in extended colonic resections. With growing evidence of similar oncological outcomes between subtotal colectomy and left hemicolectomy for splenic flexure cancers, more limited resections should be considered. The type of colonic resection should be integrated into prediction tools for AL.

Perceived vs Actual Shared Decision-Making Behavior Among Urologists: A Convergent, Parallel, Mixed-Methods Study of Self-Reported Practice

OBJECTIVE

To evaluate the association between self-perceived use of shared decision-making among urologists with use of validated prediction tools and self-described surgical decision-making.

METHODS

This is a convergent mixed methods study of these parallel data from two modules (Shared Decision Making and Validated Prediction tools) within the 2019 American Urological Association (AUA) Annual Census. The shared decision-making (SDM) module queried aspects of SDM that urologists regularly used. The validated prediction tools module queried whether urologists regularly used, trusted, and found prediction tools helpful. Selected respondents to the 2019 AUA Annual Census underwent qualitative interviews on their surgical decision-making.

RESULTS

In the weight sampled of 12,312 practicing urologists, most (77%) reported routine use of SDM, whereas only 30% noted regular use of validated prediction tools. On multivariable analysis, users of prediction tools were not associated with regular SDM use (31% vs 28%, P = .006) though was associated with use of decision aids f (32% vs 26%, P < .001). Shared decision-making emerged thematically with respect to matching treatment options, prioritizing goals, and navigating challenging decisions. However, the six specific components of shared decision-making ranged in their mentions within qualitative interviews.

CONCLUSION

Most urologists report performing SDM as supported by its thematic presence in surgical decision-making. However, only a minority use validated prediction tools and urologists infrequently mention specific SDM components. This discrepancy provides an opportunity to explore how urologists perform SDM and can be used to support integrated strategies to implement SDM more effectively in clinical practice.

Development and Validation of Prediction Models and Risk Calculators for Posthepatectomy Liver Failure and Postoperative Complications Using a Diverse International Cohort of Major Hepatectomies

OBJECTIVE

The study aim was to develop and validate models to predict clinically significant posthepatectomy liver failure (PHLF) and serious complications [a Comprehensive Complication Index (CCI)>40] using preoperative and intraoperative variables.

BACKGROUND

PHLF is a serious complication after major hepatectomy but does not comprehensively capture a patient's postoperative course. Adding the CCI as an additional metric can account for complications unrelated to liver function.

METHODS

The cohort included adult patients who underwent major hepatectomies at 12 international centers (2010-2020). After splitting the data into training and validation sets (70:30), models for PHLF and a CCI>40 were fit using logistic regression with a lasso penalty on the training cohort. The models were then evaluated on the validation data set.

RESULTS

Among 2192 patients, 185 (8.4%) had clinically significant PHLF and 160 (7.3%) had a CCI>40. The PHLF model had an area under the curve (AUC) of 0.80, calibration slope of 0.95, and calibration-in-the-large of -0.09, while the CCI model had an AUC of 0.76, calibration slope of 0.88, and calibration-in-the-large of 0.02. When the models were provided only preoperative variables to predict PHLF and a CCI>40, this resulted in similar AUCs of 0.78 and 0.71, respectively. Both models were used to build 2 risk calculators with the option to include or exclude intraoperative variables ( PHLF Risk Calculator; CCI>40 Risk Calculator ).

CONCLUSIONS

Using an international cohort of major hepatectomy patients, we used preoperative and intraoperative variables to develop and internally validate multivariable models to predict clinically significant PHLF and a CCI>40 with good discrimination and calibration.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Risk Perceptions and Risk Thresholds Among Surgeons in the Management of Intraductal Papillary Mucinous Neoplasms

OBJECTIVES

We aimed to determine whether surgeon variation in management of intraductal papillary mucinous neoplasm (IPMN) is driven by differences in risk perception and quantify surgeons' risk threshold for changing their recommendations.

BACKGROUND

Surgeons vary widely in management of IPMN.

METHODS

We conducted a survey of members of the Americas HepatoPancreatoBiliary Association, presented participants with 2 detailed clinical vignettes and asked them to choose between surgical resection and surveillance. We also asked them to judge the likelihood that the IPMN harbors cancer and that the patient would have a serious complication if surgery was performed. Finally, we asked surgeons to rate the level of cancer risk at which they would change their treatment recommendation. We examined the association between surgeons' treatment recommendations and their risk perception and risk threshold.

RESULTS

One hundred fifty surgeons participated in the study. Surgeons varied in their recommendations for surgery [19% for vignette 1 (V1) and 12% for V2] and in their perception of the cancer risk (interquartile range: 2%-10% for V1 and V2) and risk of surgical complications (V1 interquartile range: 10%-20%, V2 20-30%). After adjusting for surgeon characteristics, surgeons who were above the median in cancer risk perception were 22 percentage points (27% vs 5%) more likely to recommend resection than those who were below the median (95% CI: 11%-4%; P <0.001). The median risk threshold at which surgeons would change their recommendation was 15% (V1 and V2). Surgeons who recommended surgery had a lower risk threshold for changing their recommendation than those who recommended surveillance (V1: 10.0 vs 15.0, P =0.06; V2: 7.0 vs 15.0, P =0.05).

CONCLUSIONS

The treatment that patients receive for IPMNs depends greatly on how their surgeons perceive the risk of cancer in the lesion. Efforts to improve cancer risk prediction for IPMNs may lead to decreased variations in care.

Preoperative Risk Stratification in Esophageal Cancer Surgery: Comparing Risk Models with the Clinical Judgment of the Surgeon

BACKGROUND

Numerous prediction models estimating the risk of complications after esophagectomy exist but are rarely used in practice. The aim of this study was to compare the clinical judgment of surgeons using these prediction models.

METHODS

Patients with resectable esophageal cancer who underwent an esophagectomy were included in this prospective study. Prediction models for postoperative complications after esophagectomy were selected by a systematic literature search. Clinical judgment was given by three surgeons, indicating their estimated risk for postoperative complications in percentage categories. The best performing prediction model was compared with the judgment of the surgeons, using the net reclassification improvement (NRI), category-free NRI (cfNRI), and integrated discrimination improvement (IDI) indexes.

RESULTS

Overall, 159 patients were included between March 2019 and July 2021, of whom 88 patients (55%) developed a complication. The best performing prediction model showed an area under the receiver operating characteristic curve (AUC) of 0.56. The three surgeons had an AUC of 0.53, 0.55, and 0.59, respectively, and all surgeons showed negative percentages of cfNRIevents and IDIevents, and positive percentages of cfNRInonevents and IDIevents. This indicates that in the group of patients with postoperative complications, the prediction model performed better, whereas in the group of patients without postoperative complications, the surgeons performed better. NRIoverall was 18% for one surgeon, while the remainder of the NRIoverall, cfNRIoverall and IDIoverall scores showed small differences between surgeons and the prediction models.

CONCLUSION

Prediction models tend to overestimate the risk of any complication, whereas surgeons tend to underestimate this risk. Overall, surgeons' estimations differ between surgeons and vary between similar to slightly better than the prediction models.

Current use of the National Surgical Quality Improvement Program surgical risk calculator in academic surgery: a mixed-methods study

Background

This study aims to quantitatively assess use of the NSQIP surgical risk calculator (NSRC) in contemporary surgical practice and to identify barriers to use and potential interventions that might increase use.

Materials and methods

We performed a cross-sectional study of surgeons at seven institutions. The primary outcomes were self-reported application of the calculator in general clinical practice and specific clinical scenarios as well as reported barriers to use.

Results

In our sample of 99 surgeons (49.7% response rate), 73.7% reported use of the NSRC in the past month. Approximately half (51.9%) of respondents reported infrequent NSRC use (<20% of preoperative discussions), while 14.3% used it in ≥40% of preoperative assessments. Reported use was higher in nonelective cases (30.2% vs 11.1%) and in patients who were ≥65 years old (37.1% vs 13.0%), functionally dependent (41.2% vs 6.6%), or with surrogate consent (39.9% vs 20.4%). NSRC use was not associated with training status or years in practice. Respondents identified a lack of influence on the decision to pursue surgery as well as concerns regarding the calculator's accuracy as barriers to use. Surgeons suggested improving integration to workflow and better education as strategies to increase NSRC use.

Conclusions

Many surgeons reported use of the NSRC, but few used it frequently. Surgeons reported more frequent use in nonelective cases and frail patients, suggesting the calculator is of greater utility for high-risk patients. Surgeons raised concerns about perceived accuracy and suggested additional education as well as integration of the calculator into the electronic health record.

Geriatric assessment and treatment decision-making in surgical oncology

PURPOSE OF REVIEW

Present an approach for surgical decision-making in cancer that incorporates geriatric assessment by building upon the common categories of tumor, technical, and patient factors to enable dual assessment of disease and geriatric factors.

RECENT FINDINGS

Conventional preoperative assessment is insufficient for older adults missing important modifiable deficits, and inaccurately estimating treatment intolerance, complications, functional impairment and disability, and death. Including geriatric-focused assessment into routine perioperative care facilitates improved communications between clinicians and patients and among interdisciplinary teams. In addition, it facilitates the detection of geriatric-specific deficits that are amenable to treatment. We propose a framework for embedding geriatric assessment into surgical oncology practice to allow more accurate risk stratification, identify and manage geriatric deficits, support decision-making, and plan proactively for both cancer-directed and non-cancer-directed therapies. This patient-centered approach can reduce adverse outcomes such as functional decline, delirium, prolonged hospitalization, discharge to long-term care, immediate postoperative complications, and death.

SUMMARY

Geriatric assessment and management has substantial benefits over conventional preoperative assessment alone. This article highlights these advantages and outlines a feasible strategy to incorporate both disease-based and geriatric-specific assessment and treatment when caring for older surgical patients with cancer.

Association Between Postoperative Complications and Long-term Survival After Non-cardiac Surgery Among Veterans

OBJECTIVE

To evaluate the relationship between postoperative complications and long-term survival.

SUMMARY AND BACKGROUND

Postoperative complications remain a significant driver of healthcare costs and are associated with increased perioperative mortality, yet the extent to which they are associated with long-term survival is unclear.

METHODS

National cohort study of Veterans who underwent non-cardiac surgery using data from the Veterans Affairs Surgical Quality Improvement Program (2011-2016). Patients were classified as having undergone outpatient, low-risk inpatient, or high-risk inpatient surgery. Patients were categorized based on number and type of complications. The association between the number of complications (or the specific type of complication) and risk of death was evaluated using multivariable Cox regression with robust standard errors using a 90-day survival landmark.

RESULTS

Among 699,002 patients, complication rates were 3.0%, 6.1%, and 18.3% for outpatient, low-risk inpatient, and high-risk inpatient surgery, respectively. There was a dose-response relationship between an increasing number of complications and overall risk of death in all operative settings [outpatient surgery: no complications (ref); one-hazard ratio (HR) 1.30 (1.23 - 1.38); multiple-HR 1.61 (1.46 - 1.78); low-risk inpatient surgery: one-HR 1.34 (1.26 - 1.41); multiple-HR 1.69 (1.55 - 1.85); high-risk inpatient surgery: one-HR 1.14 (1.10 - 1.18); multiple-HR 1.42 (1.36 - 1.48)]. All complication types were associated with risk of death in at least 1 operative setting, and pulmonary complications, sepsis, and clostridium difficile colitis were associated with higher risk of death across all settings. Conclusions: Postoperative complications have an adverse impact on patients' long-term survival beyond the immediate postoperative period. Although most research and quality improvement initiatives primarily focus on the perioperative impact of complications, these data suggest they also have important longer-term implications that merit further investigation.

Factors Influencing Physician Prognosis: A Scoping Review

Introduction. Prognosis is an essential component of informed consent for medical decision making. Research shows that physicians display discrepancies in their prognostication, leading to variable, inaccurate, optimistic, or pessimistic prognosis. Factors driving these discrepancies and the supporting evidence have not been reviewed systematically. Methods. We undertook a scoping review to explore the literature on the factors leading to discrepancies in medical prognosis. We searched Medline (Ovid) and Embase (Ovid) databases for peer-reviewed articles from 1970 to 2017. We included articles that discussed prognosis variation or discrepancy and where factors influencing prognosis were evaluated. We extracted data outlining the participants, methodology, and prognosis discrepancy information and measured factors influencing prognosis. Results. Of 4,723 articles, 73 were included in the final analysis. There was significant variability in research methodologies. Most articles showed that physicians were pessimistic regarding patient outcomes, particularly in early trainees and acute care specialties. Accuracy rates were similar across all time periods. Factors influencing prognosis were clustered in 4 categories: patient-related factors (such as age, gender, race, diagnosis), physician-related factors (such as age, race, gender, specialty, training and experience, attitudes and values), clinical situation-related factors (such as physician-patient relationship, patient location, and clinical context), and environmental-related factors (such as country or hospital size). Discussion. Obtaining accurate prognostic information is one of the highest priorities for seriously ill patients. The literature shows trends toward pessimism, especially in early trainees and acute care specialties. While some factors may prove difficult to change, the physician's personality and psychology influence prognosis accuracy and could be tackled using debiasing strategies. Exposure to long-term patient outcomes and a multidisciplinary practice setting are environmental debiasing strategies that may warrant further research.

Highlights

Literature on discrepancies in physician's prognostication is heterogeneous and sparse.Literature shows that physicians are mostly pessimistic regarding patient outcomes.Literature shows that a physician's personality and psychology influence prognostic accuracy and could be improved with evidence-based debiasing strategies.Medical specialty strongly influences prognosis, with specialties exposed to acutely ill patients being more pessimistic, whereas specialties following patients longitudinally being more optimistic.Physicians early in their training were more pessimist than more experienced physicians.

Development and validation of a prediction model for conversion of outpatient to inpatient surgery

BACKGROUND

Unplanned hospital admission after intended outpatient surgery is an undesirable outcome. We aimed to develop a prediction model that estimates a patient's risk of conversion from outpatient surgery to inpatient hospitalization.

METHODS

This was a retrospective analysis using the American College of Surgeons National Surgical Quality Improvement Program database, 2005 to 2018. Conversion from outpatient to inpatient surgery was defined as having outpatient surgery and >1 day hospital stay. The Surgical Risk Preoperative Assessment System was developed using multiple logistic regression on a training dataset (2005-2016) and compared to a model using the 26 relevant variables in the American College of Surgeons National Surgical Quality Improvement Program. The Surgical Risk Preoperative Assessment System was validated using a testing dataset (2017-2018). Performance statistics and Hosmer-Lemeshow plots were compared. Two high-risk definitions were compared: (1) the maximum Youden index, and (2) the cohort above the tenth decile of risk on the Hosmer-Lemeshow plot. The sensitivities, specificities, positive predictive values, negative predictive values, and accuracies were compared.

RESULTS

In all, 2,822,379 patients were included; 3.6% of patients unexpectedly converted to inpatient. The 6-variable Surgical Risk Preoperative Assessment System model performed comparably to the 26-variable American College of Surgeons National Surgical Quality Improvement Program model (c-indices = 0.818 vs. 0.823; Brier scores = 0.0308 vs 0.0306, respectively). The Surgical Risk Preoperative Assessment System performed well on internal validation (c-index = 0.818, Brier score = 0.0341). The tenth decile of risk definition had higher specificity, positive predictive values, and accuracy than the maximum Youden index definition, while having lower sensitivity.

CONCLUSION

The Surgical Risk Preoperative Assessment System accurately predicted a patient's risk of unplanned outpatient-to-inpatient conversion. Patients at higher risk should be considered for inpatient surgery, while lower risk patients could safely undergo operations at ambulatory surgery centers.

Surgeons' risk perception in ASD surgery: The value of objective risk assessment on decision making and patient counselling

BACKGROUND

Surgeons often rely on their intuition, experience and published data for surgical decision making and informed consent. Literature provides average values that do not allow for individualized assessments. Accurate validated machine learning (ML) risk calculators for adult spinal deformity (ASD) patients, based on 10 year multicentric prospective data, are currently available. The objective of this study is to assess surgeon ASD risk perception and compare it to validated risk calculator estimates.

METHODS

Nine ASD complete (demographics, HRQL, radiology, surgical plan) preoperative cases were distributed online to 100 surgeons from 22 countries. Surgeons were asked to determine the risk of major complications and reoperations at 72 h, 90 d and 2 years postop, using a 0-100% risk scale. The same preoperative parameters circulated to surgeons were used to obtain ML risk calculator estimates. Concordance between surgeons' responses was analyzed using intraclass correlation coefficients (ICC) (poor < 0.5/excellent > 0.85). Distance between surgeons' and risk calculator predictions was assessed using the mean index of agreement (MIA) (poor < 0.5/excellent > 0.85).

RESULTS

Thirty-nine surgeons (74.4% with > 10 years' experience), from 12 countries answered the survey. Surgeons' risk perception concordance was very low and heterogeneous. ICC ranged from 0.104 (reintervention risk at 72 h) to 0.316 (reintervention risk at 2 years). Distance between calculator and surgeon prediction was very large. MIA ranged from 0.122 to 0.416. Surgeons tended to overestimate the risk of major complications and reintervention in the first 72 h and underestimated the same risks at 2 years postop.

CONCLUSIONS

This study shows that expert surgeon ASD risk perception is heterogeneous and highly discordant. Available validated ML ASD risk calculators can enable surgeons to provide more accurate and objective prognosis to adjust patient expectations, in real time, at the point of care.

Risk Aversion, Organ Utilization and Changing Behavior

Improving organ acceptance and utilization rates is critical to ensure we maximize usage of donated organs as a scarce resource. Many factors underlie unnecessary discard of viable organs. Declined transplantation opportunities for candidates is associated with increased wait-list mortality. Technological advancements in organ preservation may help bridge the gap between donation and utilization, but an overlooked obstacle is the practice of risk aversion by transplant professionals when decision-making under risk. Lessons from behavioral economics, where experimental work has outlined the impact of loss or risk aversion on decision-making, have not been translated to transplantation. Many external factors can influence decision-making when accepting or utilizing organs, which are potentially amendable if external conditions are improved. However, attitudes and perceptions to risk for transplant professionals can pervade decision-making and influence behaviour. If we wish to change this behavior, then the underlying nature of decision-making under risk when accepting or utilizing organs must be studied to facilitate the design of targeted behavior change interventions to convert risk aversion to risk tolerance. To ensure optimal use of donated organs, we need more research into decision-making under risk.

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.

Inner Deliberations of Surgeons Treating Critically-ill Emergency General Surgery Patients: A Qualitative Analysis

BACKGROUND

30% of elderly patients who require emergency general surgery (EGS) die in the year after the operation. Preoperative discussions can determine whether patients receive preference-sensitive care. Theoretically, surgeons frame their conversations after systematically assessing the risks and benefits of management options based on the clinical characteristics of each case. However, little is known about how surgeons actually deliberate about those options.

OBJECTIVE

To identify variables that influence surgeons' assessment of management options for critically-ill EGS patients.

METHODS

We conducted semi-structured interviews with 40 general surgeons in western Pennsylvania who worked in a variety of hospital settings. Interviews explored perioperative decision-making by asking surgeons to think aloud about selected memorable cases and a standardized case vignette of a frail patient with acute mesenteric ischemia. We used constant comparative methods to analyze interview transcripts and inductively developed a framework for the decision-making process.

RESULTS

Surgeons averaged 13 years (standard deviation (SD) 10.4) of experience; 40% specialized in trauma/acute care surgery. Important themes regarding the main topic of "perioperative decision-making" included many considerations beyond the clinical characteristics of cases. Surgeons described the importance of variables ranging from the availability of institutional resources to professional norms. Surgeons often remarked on their desire to achieve individual flow, team efficiency, and concordant expectations of treatment and prognosis with patients.

CONCLUSIONS

This is the first study to explore how surgeons decide among management options for critically-ill EGS patients. Surgeons' decision-making reflected a broad array of clinical, personal, and institutional variables. Effective interventions to ensure preference-sensitive care for EGS patients must address all of these variables.

Performance evaluation of scoring systems for predicting post-operative hypertension cure in primary aldosteronism

OBJECTIVE

Hypertension cure following adrenalectomy in unilateral primary aldosteronism is not guaranteed. Its likelihood is associated with pre-operative parameters, which have been variably combined in six different predictive scoring systems. The relative performance of these systems is currently unknown. The objective of this work was to identify the best performing scoring system for predicting hypertension cure following adrenalectomy for primary aldosteronism.

DESIGN

Retrospective analysis in a single tertiary referral centre.

PATIENTS

Eighty-seven adult patients with unilateral primary aldosteronism who had undergone adrenalectomy between 2004 and 2018 for whom complete data sets were available to calculate all scoring systems.

MEASUREMENTS

Prediction of hypertension cure by each of the six scoring systems.

RESULTS

Hypertension cure was achieved in 36/87 (41.4%) patients within the first post-operative year, which fell to 18/71 (25.4%) patients at final follow-up (median 53 months, P = .002). Analysis of receiver operating characteristic area under the curves for the different scoring systems identified a difference in performance at early, but not late, follow-up. For all systems, the area under the curve was lower at early compared with late follow-up and compared to performance in the cohorts in which they were originally defined.

CONCLUSIONS

No single scoring system performed significantly better than all others when applied in our cohort, although two did display particular advantages. It remains to be determined how best such scoring systems can be incorporated into the routine clinical care of patients with PA.

The Association Between Risk Aversion of Surgeons and Their Clinical Decision-Making

BACKGROUND

The extent to which a surgeon's risk aversion influences their clinical decisions remains unknown. We assessed whether a surgeon's attitude toward risk ("risk aversion") influences their surgical decisions and whether the relationship can be explained by differences in surgeons' perception of treatment risks and benefits.

MATERIALS AND METHODS

We presented a series of detailed clinical vignettes to a national sample of surgeons (n = 1,769; 13.4% adjusted response rate) and asked them to complete an instrument that measured how risk averse they are within their clinical practice (scale 6-36; higher number indicates greater risk aversion). For each vignette, participants rated their likelihood of recommending an operation and judged the likelihood of complications or full recovery. We examined whether differences in perceived likelihood of complications versus recovery could explain why risk-averse surgeons may be less likely to recommend an operation.

RESULTS

Surgeons varied in their self-reported risk aversion score (median = 25, interquartile range[22,28]). Scores did not differ by level of surgeon experience or gender. Risk-averse surgeons were significantly less likely to recommend an operation for patients with exactly the same condition (65.5% for surgeons in highest quartile of risk aversion versus 62.3% for lowest quartile; P = 0.02). However, after controlling for surgeons' perception of the likelihood of complications versus recovery, there was no longer a significant association between surgeons' risk aversion and the decision to recommend an operation (64.7% versus 64.8%; P = 0.96).

CONCLUSIONS

Surgeons vary widely in their self-reported risk aversion. Risk-averse surgeons were significantly less likely to recommend an operation, a finding that was explained by a higher perceived probability of post-operative complications than their colleagues.

Observation Rather than Surgery for Benign Parotid Tumors: Why, When, and How

Surgery is the preferred treatment of benign parotid lesions, but it carries a risk of complications. Therefore, the approach toward the surgery of these lesions should seek to avoid complications. There are no guidelines or recommendations for when not to operate. Integration of comorbidities and other factors shift the scales from surgery toward observation in a small subset of patients presenting with parotid tumors. When observation is chosen, the patient should be followed frequently and cautiously, and the surgeon should be prepared to change strategy to surgical excision if in doubt.

Risk assessment in aortic aneurysm repair by medical specialists versus the American College of Surgeons National Surgical Quality Improvement Program risk calculator outcomes

Objective

The aim of this online clinical vignette-based survey study was to compare risk assessments by vascular surgeons, anaesthesiologists and interventional radiologists involved in treating patients with aortic aneurysms in the Netherlands with the NSQIP risk calculator outcomes.

Methods

Participants, recruited using purposive sampling, provided their estimation of the likelihood of postoperative complications and events following aortic surgery in five fictional cases. These cases were subsequently scored using the NSQIP calculator. The risk assessments were statistically analysed using the ANOVA and student t-test.

Results

All participating specialists i.e. twelve vascular surgeons, ten interventional radiologists and ten anaesthesiologists completed the survey. In the vast majority of outcomes and vignettes, no significant differences were found between various specialists, whereas significant differences were found between the NSQIP risk calculator outcomes and the combined risk assessments of the specialists. Overall, specialist risk assessments differ from the NSQIP, but neither particularly higher nor lower compared to the risk calculator.

Conclusions

Risk assessment by vascular surgeons, anaesthesiologists and interventional radiologists differs significantly with NSQIP risk calculator outcomes, within the framework of both endovascular and open aortic aneurysm repair. Based on these results, implementing the NSQIP risk calculator in preoperative workup could be of added value in both patient planning as well as adequately informing patients for obtaining consent.

Estimating prognosis for traumatic brain injury patients in a low-resource setting: how do providers compare to the CRASH risk calculator?

OBJECTIVE

Traumatic brain injury (TBI), a burgeoning global health concern, is one condition that could benefit from prognostic modeling. Risk stratification of TBI patients on presentation to a health facility can support the prudent use of limited resources. The CRASH (Corticosteroid Randomisation After Significant Head Injury) model is a well-established prognostic model developed to augment complex decision-making. The authors' current study objective was to better understand in-hospital decision-making for TBI patients and determine whether data from the CRASH risk calculator influenced provider assessment of prognosis.

METHODS

The authors performed a choice experiment using a simulated TBI case. All participant doctors received the same case, which included a patient history, vitals, and physical examination findings. Half the participants also received the CRASH risk score. Participants were asked to estimate the patient prognosis and decide the best next treatment step. The authors recruited a convenience sample of 28 doctors involved in TBI care at both a regional and a national referral hospital in Uganda.

RESULTS

For the simulated case, the CRASH risk scores for 14-day mortality and an unfavorable outcome at 6 months were 51.4% (95% CI 42.8%, 59.8%) and 89.8% (95% CI 86.0%, 92.6%), respectively. Overall, participants were overoptimistic when estimating the patient prognosis. Risk estimates by doctors provided with the CRASH risk score were closer to that score than estimates made by doctors in the control group; this effect was more pronounced for inexperienced doctors. Surgery was selected as the best next step by 86% of respondents.

CONCLUSIONS

This study was a novel assessment of a TBI prognostic model's influence on provider estimation of risk in a low-resource setting. Exposure to CRASH risk score data reduced overoptimistic prognostication by doctors, particularly among inexperienced providers.

Predicting in-hospital mortality after traumatic brain injury: External validation of CRASH-basic and IMPACT-core in the national trauma data bank

BACKGROUND

Traumatic brain injury (TBI) prognostic prediction models offer value to individualized treatment planning, systematic outcome assessments and clinical research design but require continuous external validation to ensure generalizability to different settings. The Corticosteroid Randomization After Significant Head Injury (CRASH) and International Mission on Prognosis and Analysis on Clinical Trials in TBI (IMPACT) models are widely available but lack robust assessments of performance in a current national sample of patients. The purpose of this study is to assess the performance of the CRASH-Basic and IMPACT-Core models in predicting in-hospital mortality using a nationwide retrospective cohort from the National Trauma Data Bank (NTDB).

METHODS

The 2016 NTDB was used to analyze an adult cohort with moderate-severe TBI (Glasgow Coma Scale [GCS] ≤ 12, head Abbreviated Injury Scale of 2-6). Observed in-hospital mortality or discharge to hospice was compared to the CRASH-Basic and IMPACT-Core models' predicted probability of 14-day or 6-month mortality, respectively. Performance measures included discrimination (area under the receiver operating characteristic curve [AUC]) and calibration (calibration plots and Brier scores). Further sensitivity analysis included patients with GCS ≤ 14 and considered patients discharged to hospice to be alive at 14-days.

RESULTS

A total of 26,228 patients were included in this study. Both models demonstrated good ability in differentiating between patients who died and those who survived, with IMPACT demonstrating a marginally greater AUC (0.863; 95% CI: 0.858 - 0.867) than CRASH (0.858; 0.854 - 0.863); p < 0.001. On calibration, IMPACT overpredicted at lower scores and underpredicted at higher scores but had good calibration-in-the-large (indicating no systemic over/underprediction), while CRASH consistently underpredicted mortality. Brier scores were similar (0.152 for IMPACT, 0.162 for CRASH; p < 0.001). Both models showed slight improvement in performance when including patients with GCS ≤ 14.

CONCLUSION

Both CRASH-Basic and IMPACT-Core accurately predict in-hospital mortality following moderate-severe TBI, and IMPACT-Core performs well beyond its original GCS cut-off of 12, indicating potential utility for mild TBI (GCS 13-15). By demonstrating validity in the NTDB, these models appear generalizable to new data and offer value to current practice in diverse settings as well as to large-scale research design.

The Association of Coloproctology of Great Britain and Ireland consensus guidelines in emergency colorectal surgery

AIM

There is a requirement for an expansive and up to date review of the management of emergency colorectal conditions seen in adults. The primary objective is to provide detailed evidence-based guidelines for the target audience of general and colorectal surgeons who are responsible for an adult population and who practise in Great Britain and Ireland.

METHODS

Surgeons who are elected members of the Association of Coloproctology of Great Britain and Ireland Emergency Surgery Subcommittee were invited to contribute various sections to the guidelines. They were directed to produce a pathology-based document using literature searches that were systematic, comprehensible, transparent and reproducible. Levels of evidence were graded. Each author was asked to provide a set of recommendations which were evidence-based and unambiguous. These recommendations were submitted to the whole guideline group and scored. They were then refined and submitted to a second vote. Only those that achieved >80% consensus at level 5 (strongly agree) or level 4 (agree) after two votes were included in the guidelines.

RESULTS

All aspects of care (excluding abdominal trauma) for emergency colorectal conditions have been included along with 122 recommendations for management.

CONCLUSION

These guidelines provide an up to date and evidence-based summary of the current surgical knowledge in the management of emergency colorectal conditions and should serve as practical text for clinicians managing colorectal conditions in the emergency setting.

Evolution of Risk Calculators and the Dawn of Artificial Intelligence in Predicting Patient Complications

Risk calculators are an underused tool for surgeons and trainees when determining and communicating surgical risk. We summarize some of the more common risk calculators and discuss their evolution and limitations. We also describe artificial intelligence models, which have the potential to help clinicians better understand and use risk assessment.

Variability in clinicians' understanding and reported methods of identifying high-risk surgical patients: a qualitative study

Background

High-risk patients presenting for surgery require complex decision-making and perioperative management. However, given there is no gold standard for identifying high-risk patients, doing so may be challenging for clinicians in practice. Before a gold standard can be established, the state of current practice must be determined. This study aimed to understand how working clinicians define and identify high-risk surgical patients.

Methods

Clinicians involved in the care of high-risk surgical patients at a public hospital in regional Australia were interviewed as part of an ongoing study evaluating a new shared decision-making process for high-risk patients. The new process, Patient-Centred Advanced Care Planning (PC-ACP) engages patients, families, and clinicians from all relevant specialties in shared decision-making in line with the patient’s goals and values. The semi-structured interviews were conducted before the implementation of the new process and were coded using a modified form of the ‘constant comparative method’ to reveal key themes. Themes concerning patient risk, clinician’s understanding of high risk, and methods for identifying high-risk surgical patients were extricated for close examination.

Results

Thirteen staff involved in high-risk surgery at the hospital at which PC-ACP was to be implemented were interviewed. Analysis revealed six sub-themes within the major theme of factors related to patient risk: (1) increase in high-risk patients, (2) recognising frailty, (3) risk-benefit balance, (4) suitability and readiness for surgery, (5) avoiding negative outcomes, and (6) methods in use for identifying high-risk patients. There was considerable variability in clinicians’ methods of identifying high-risk patients and regarding their definition of high risk. This variability occurred even among clinicians within the same disciplines and specialties.

Conclusions

Although clinicians were confident in their own ability to identify high-risk patients, they acknowledged limitations in recognising frail, high-risk patients and predicting and articulating possible outcomes when consenting these patients. Importantly, little consistency in clinicians’ reported methods for identifying high-risk patients was found. Consensus regarding the definition of high-risk surgical patients is necessary to ensure rigorous decision-making.

Report of a Quality Improvement Program for Reducing Postoperative Complications by Using a Surgical Risk Calculator in a Cohort of General Surgery Patients

PURPOSE

The study investigates whether postoperative complications in elective surgery can be reduced by using a risk calculator via raising the awareness of the surgeon in a preoperative briefing. Postoperative complications like wound infections or pneumonia result in a high burden for healthcare systems. Multiple quality improvement programs address this problem like the ACS NSQIP Surgical Risk Calculator^® (SRC).

METHODS

To determine whether the preoperative usage of the SRC could reduce inpatient postoperative complications, two groups of 832 patients each were compared using propensity score matching. The SRC was employed retrospectively in the period 2012/2013 in one group ("Retro") and prospectively in the other group ("Prosp") in the period 2014/2015. Actual inpatient postoperative complications were classified by SRC complication categories and compared with the Clavien-Dindo complication classification system (Dindo et al. in Ann Surg 240:205-213, 2004).

RESULTS

Comparing SRC "serious complication" and SRC "any complication," a nonsignificant increase in the "Prosp"-group was apparent (serious complication: 6.6% vs. 8.5%, p = 0.164; any complication: 8.5% vs. 9.7%, p = 0.444).

CONCLUSION

Use of the SRC neither reduces inpatient postoperative complications nor the severity of complications. The calculations of the SRC rely on a 30-day postoperative follow-up. Poor sensitivity and medium specificity of the SRC showed that the SRC could not make accurate predictions in a short follow-up time averaging 6 days. Alternatively, since the observed complication rate was low in our study, in an environment of already highly implemented risk management tools, reductions in complications are not easily achieved.

Systematic review and narrative synthesis of surgeons' perception of postoperative outcomes and risk

BACKGROUND

The accuracy with which surgeons can predict outcomes following surgery has not been explored in a systematic way. The aim of this review was to determine how accurately a surgeon's 'gut feeling' or perception of risk correlates with patient outcomes and available risk scoring systems.

METHODS

A systematic review was undertaken in accordance with PRISMA guidelines. A narrative synthesis was performed in accordance with the Guidance on the Conduct of Narrative Synthesis In Systematic Reviews. Studies comparing surgeons' preoperative or postoperative assessment of patient outcomes were included. Studies that made comparisons with risk scoring tools were also included. Outcomes evaluated were postoperative mortality, general and operation-specific morbidity and long-term outcomes.

RESULTS

Twenty-seven studies comprising 20 898 patients undergoing general, gastrointestinal, cardiothoracic, orthopaedic, vascular, urology, endocrine and neurosurgical operations were included. Surgeons consistently overpredicted mortality rates and were outperformed by existing risk scoring tools in six of seven studies comparing area under receiver operating characteristic (ROC) curves (AUC). Surgeons' prediction of general morbidity was good, and was equivalent to, or better than, pre-existing risk prediction models. Long-term outcomes were poorly predicted by surgeons, with AUC values ranging from 0·51 to 0·75. Four of five studies found postoperative risk estimates to be more accurate than those made before surgery.

CONCLUSION

Surgeons consistently overestimate mortality risk and are outperformed by pre-existing tools; prediction of longer-term outcomes is also poor. Surgeons should consider the use of risk prediction tools when available to inform clinical decision-making.

Modified Colon Leakage Score to Predict Anastomotic Leakage in Patients Who Underwent Left-Sided Colorectal Surgery

Colon leakage score (CLS) was introduced as a clinical tool to predict anastomotic leakage (AL) in patients who underwent left-sided colorectal surgery, but its clinical validity has not been widely studied. We evaluated the clinical utility of CLS and developed a modified CLS (m-CLS). In total, 566 patients who underwent left-sided colorectal surgery were enrolled and categorized into training (n = 396) and validation (n = 170) sets via random sampling. Using CLS variables, the least absolute shrinkage and selection operator (LASSO) regression model was applied for variable selection and predictive signature building in the training set. The model's performance was validated in the validation set. The predictive powers of m-CLS and CLS were compared by the area under the receiver operating characteristic (AUROC) curve in the overall group. Twenty-three AL events (4.1%) were noted. The AL group had a significantly higher mean CLS than the No Leakage group (12.5 vs. 9.6, p = 0.001). Five clinical variables were selected and used to generate m-CLS. The predictive performance of m-CLS was similar in training and validation sets (AUROC 0.838 vs. 0.803, p = 0.724). In the overall set, m-CLS was significantly predictive of AL and performed better than CLS (AUROC 0.831 vs. 0.701, p = 0.008). In conclusion, LASSO-model-generated m-CLS could predict AL more accurately than CLS.

Rethinking our definition of operative success: predicting early mortality after emergency general surgery colon resection

Background

The postoperative outcomes of emergency general surgery patients can be fraught with uncertainty. Although surgical risk calculators exist to predict 30-day mortality, they are often of limited utility in preparing patients and families for immediate perioperative complications. Examination of trends in mortality after emergent colectomy may help inform complex perioperative decision-making. We hypothesized that risk factors could be identified to predict early mortality (before postoperative day 5) to inform operative decisions.

Methods

This analysis was a retrospective cohort study using the American College of Surgeons National Surgical Quality Improvement Program database (2012-2014). Patients were stratified into three groups: early death (postoperative day 0-4), late death (postoperative day 5-30), and those who survived. Multivariable logistic regression was used to explore characteristics associated with early death. Kaplan-Meier models and Cox regression were used to further characterize their impact.

Results

A total of 18 803 patients were analyzed. Overall 30-day mortality was 12.5% (3316); of these, 37.1% (899) were early deaths. The preoperative factors most predictive of early death were septic shock (OR 3.62, p<0.001), ventilator dependence (OR 2.81, p<0.001), and ascites (OR 1.63, p<0.001). Postoperative complications associated with early death included pulmonary embolism (OR 5.78, p<0.001), presence of new-onset or ongoing postoperative septic shock (OR 4.45, p<0.001) and new-onset renal failure (OR 1.89, p<0.001). Patients with both preoperative and postoperative shock had an overall mortality rate of 47% with over half of all deaths occurring in the early period.

Conclusions

Nearly 40% of patients who die after emergent colon resection do so before postoperative day 5. Early mortality is heavily influenced by the presence of both preoperative and new or persistent postoperative septic shock. These results demonstrate important temporal trends of mortality, which may inform perioperative patient and family discussions and complex management decisions.

Level of evidence

Level III. Study type: Prognostic.

Eye of the beholder: Risk calculators and barriers to adoption in surgical trainees

BACKGROUND

Accurate risk assessment before surgery is complex and hampered by behavioral factors. Underutilized risk-based decision-support tools may counteract these barriers. The purpose of this study was to identify perceptions of and barriers to the use of surgical risk-assessment tools and assess the importance of data framing as a barrier to adoption in surgical trainees.

METHODS

We distributed a survey and risk assessment activity to surgical trainees at four training institutions. The primary outcomes of this study were descriptive risk assessment practices currently performed by residents, identifiable influences and obstacles to adoption, and the variability of preference sets when comparing modified System Usability Scores of a current risk calculator to a purpose-built calculator revision. Risk calculator comparison responses were compared with simple and multivariable regression to identify predictors for preferentiality.

RESULTS

We collected responses from 124 surgical residents (39% response rate). Participants endorsed familiarity with direct verbal communication (100%), sketch diagrams (87%), and brochures (59%). The most contemporary risk communication frameworks, such as best-worst case scenario framing (38%), case-specific risk calculators (43%), and all-procedure calculators (52%) were the least familiar. Usage favored traditional models of communication with only 26% of residents regularly using a strategy other than direct verbal discussion or anatomic sketch diagrams. Barriers limiting routine use included lack of electronic and clinical workflow integration. The mean modified System Usability Scores domain scores were widely dispersed for all domains, and no domain demonstrated one calculator's superiority over another.

CONCLUSION

Risk assessment tools are underutilized by trainees. Of importance, preference sets of clinicians appear to be unpredictable and may benefit more from a customizable, bespoke approach.

Risk Factors Associated With Circumferential Resection Margin Positivity in Rectal Cancer: A Binational Registry Study

BACKGROUND

Rectal cancer outcomes have improved with the adoption of a multidisciplinary model of care. However, there is a spectrum of quality when viewed from a national perspective, as highlighted by the Consortium for Optimizing the Treatment of Rectal Cancer data on rectal cancer care in the United States.

OBJECTIVE

The aim of this study was to assess and identify predictors of circumferential resection margin involvement for rectal cancer across Australasia.

DESIGN

A retrospective study from a prospectively maintained binational colorectal cancer database was interrogated.

SETTINGS

This study is based on a binational colorectal cancer audit database.

PATIENTS

Clinical information on all consecutive resected rectal cancer cases recorded in the registry from 2007 to 2016 was retrieved, collated, and analyzed.

MAIN OUTCOME MEASURES

The primary outcome measure was positive circumferential resection margin, measured as a resection margin ≤1 mm.

RESULTS

A total of 3367 patients were included, with 261 (7.5%) having a positive circumferential resection margin. After adjusting for hospital and surgeon volume, hierarchical logistic regression analysis identified a 6-variable model encompassing the independent predictors, including urgent operation, abdominoperineal resection, open technique, low rectal cancer, T3 to T4, and N1 to N2. The accuracy of the model was 92.3%, with an receiver operating characteristic of 0.783 (p < 0.0001). The quantitative risk associated with circumferential resection margin positivity ranged from <1% (no risk factors) to 43% (6 risk factors).

LIMITATIONS

This study was limited by the lack of recorded long-term outcomes associated with circumferential resection margin positivity.

CONCLUSIONS

The rate of circumferential resection margin involvement in patients undergoing rectal cancer resection in Australasia is low and is influenced by a number of factors. Risk stratification of outcome is important with the increasing demand for publicly accessible quality data. See Video Abstract at http://links.lww.com/DCR/A512.

Defining the Intrinsic Cardiac Risks of Operations to Improve Preoperative Cardiac Risk Assessments

Background

Current preoperative cardiac risk stratification practices group operations into broad categories, which might inadequately consider the intrinsic cardiac risks of individual operations. We sought to define the intrinsic cardiac risks of individual operations and to demonstrate how grouping operations might lead to imprecise estimates of perioperative cardiac risk.

Methods

Elective operations (based on Common Procedural Terminology codes) performed from January 1, 2010 to December 31, 2015 at hospitals participating in the American College of Surgeons National Surgical Quality Improvement Program were studied. A composite measure of perioperative adverse cardiac events was defined as either cardiac arrest requiring cardiopulmonary resuscitation or acute myocardial infarction. Operations’ intrinsic cardiac risks were derived from mixed-effects models while controlling for patient mix. Resultant risks were sorted into low-, intermediate-, and high-risk categories, and the most commonly performed operations within each category were identified. Intrinsic operative risks were also examined using a representative grouping of operations to portray within-group variation.

Results

Sixty-six low, 30 intermediate, and 106 high intrinsic cardiac risk operations were identified. Excisional breast biopsy had the lowest intrinsic cardiac risk (overall rate, 0.01%; odds ratio, 0.11; 95% CI, 0.02 to 0.25) relative to the average, whereas aorto-bifemoral bypass grafting had the highest (overall rate, 4.1%; odds ratio, 6.61; 95% CI, 5.54 to 7.90). There was wide variation in the intrinsic cardiac risks of operations within the representative grouping (median odds ratio, 1.40; interquartile range, 0.88 to 2.17).

Conclusions

A continuum of intrinsic cardiac risk exists among operations. Grouping operations into broad categories inadequately accounts for the intrinsic cardiac risk of individual operations.

Barriers and facilitators to orthopaedic surgeons' uptake of decision aids for total knee arthroplasty: a qualitative study

OBJECTIVES

The demand for total knee arthroplasty (TKA) is increasing. Differentiating who will derive a clinically meaningful improvement from TKA from others is a key challenge for orthopaedic surgeons. Decision aids can help surgeons select appropriate candidates for surgery, but their uptake has been low. The aim of this study was to explore the barriers and facilitators to decision aid uptake among orthopaedic surgeons.

DESIGN

A qualitative study involving face-to-face interviews. Questions were constructed on the Theoretical Domains Framework to systematically explore barriers and facilitators.

SETTING

One tertiary hospital in Australia.

PARTICIPANTS

Twenty orthopaedic surgeons performing TKA.

OUTCOME MEASURES

Beliefs underlying similar interview responses were identified and grouped together as themes describing relevant barriers and facilitators to uptake of decision aids.

RESULTS

While prioritising their clinical acumen, surgeons believed a decision aid could enhance communication and patient informed consent. Barriers identified included the perception that one's patient outcomes were already optimal; a perceived lack of non-operative alternatives for the management of end-stage osteoarthritis, concerns about mandatory cut-offs for patient-centred care and concerns about the medicolegal implications of using a decision aid.

CONCLUSIONS

Multifaceted implementation interventions are required to ensure that orthopaedic surgeons are ready, willing and able to use a TKA decision aid. Audit/feedback to address current decision-making biases such as overconfidence may enhance readiness to uptake. Policy changes and/or incentives may enhance willingness to uptake. Finally, the design/implementation of effective non-operative treatments may enhance ability to uptake by ensuring that surgeons have the resources they need to carry out decisions.

American College of Surgeons NSQIP Risk Calculator Accuracy for Emergent and Elective Colorectal Operations

BACKGROUND

The American College of Surgeons NSQIP has developed a risk calculator (RC) to assist patients and surgeons with difficult decisions. The aim of this analysis was to determine the accuracy of the RC in patients undergoing elective and emergent colorectal operations.

STUDY DESIGN

From January 2013 through December 2015, seventy-five patients undergoing emergent colorectal operations were paired by date with 75 patients having elective colorectal operations. Patient data were entered into the RC. Actual postoperative outcomes, derived from NSQIP data, were compared with those predicted by the RC.

RESULTS

Emergent and elective patients differed (p < 0.05) with respect to age, functional status, American Society of Anesthesiologists class, steroid use, wound class, COPD, and chronic renal insufficiency. The RC accurately predicted outcomes in elective patients. Outcomes were significantly worse (p < 0.05) after the emergent operations. In emergent cases, the RC underestimated serious complications and length of stay and overestimated discharge to a skilled nursing facility (all p < 0.05).

CONCLUSIONS

The American College of Surgeons NSQIP RC accurately predicts outcomes for elective colorectal operations. Predicted and actual outcomes are significantly better in patients undergoing elective colon operations compared with those undergoing emergent procedures. The RC should be used with caution in emergent cases, as it has the potential to underestimate serious complications and length of stay, and overestimate discharge to skilled nursing facility. Refinement of the tool to include procedure complexity and diagnosis terms might improve its accuracy in emergent cases.