Review of an emergency general surgery process improvement program at a verified military trauma center

Background The burden of frail patients undergoing emergency general surgery (EGS) is increasing rapidly and this population is particularly susceptible to postoperative cardiopulmonary complications and mortality. We aimed to determine the association between frailty, as defined by the previously described modified frailty index (mFI), and postoperative respiratory complications (unplanned reintubation, pneumonia, and prolonged ventilation), cardiac complications (myocardial infarction and cardiac arrest), and mortality. We also sought to identify the most significant determinants of frailty in the highest risk patients based on the specific variables comprising the mFI. Methods We performed a retrospective observational analysis of the prospectively collected American College of Surgeons National Surgical Quality Improvement Program database. Files from 2005 to 2015 identified 132,765 inpatients who underwent EGS. mFI scores were calculated for each patient. The effect of increasing frailty on unplanned reintubation, pneumonia, prolonged ventilation, myocardial infarction, cardiac arrest, and mortality was evaluated using bivariate analysis. Multivariable logistic regression was used to compare mFI with additional predictor variables including race, gender, physical status as defined by the American Society of Anesthesiologists, disseminated cancer, renal failure, smoking status, sepsis, wound presence/classification, dyspnea, and previous ventilator dependence. Results Unplanned reintubation, pneumonia, prolonged ventilation, myocardial infarction, cardiac arrest, and mortality were significantly associated with frailty, and the odds of each postoperative complication increased with increasing mFI score. Of the frailest patients (mFI ≥3) that experienced cardiopulmonary complications or mortality, the variables of the mFI that contributed most to frailty were hypertension requiring medication and functional status before surgery. Conclusions A higher mFI score is associated with increased odds of postoperative cardiopulmonary complications and mortality in the EGS population. Specific variables of the mFI can also provide valuable information for assessing odds in the frailest patients undergoing EGS.

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A calculator for mortality following emergency general surgery based on the American College of Surgeons National Surgical Quality Improvement Program database

Journal of Trauma and Acute Care Surgery ◽

10.1097/ta.0000000000001451 ◽

2017 ◽

Vol 82 (6) ◽

pp. 1094-1099 ◽

Cited By ~ 16

Author(s):

Ivy N. Haskins ◽

Patrick J. Maluso ◽

Mary E. Schroeder ◽

Richard L. Amdur ◽

Khashayar Vaziri ◽

...

Keyword(s):

Quality Improvement ◽

General Surgery ◽

Quality Improvement Program ◽

Emergency General Surgery ◽

Improvement Program ◽

Surgical Quality ◽

American College Of Surgeons

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Comparison of Outcomes Between the National Surgical Quality Improvement Program and an Emergency General Surgery Registry

Journal for Healthcare Quality ◽

10.1097/jhq.0000000000000262 ◽

2020 ◽

Vol Publish Ahead of Print ◽

Author(s):

Robert W. DesPain ◽

William J. Parker ◽

Angela T. Kindvall ◽

Peter A. Learn ◽

Eric A. Elster ◽

...

Keyword(s):

Quality Improvement ◽

General Surgery ◽

Quality Improvement Program ◽

Emergency General Surgery ◽

Improvement Program ◽

Surgical Quality

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Protocol for the derivation and external validation of a 30-day mortality risk prediction model for older patients having emergency general surgery (PAUSE score—Probability of mortality Associated with Urgent/emergent general Surgery in oldEr patients score)

BMJ Open ◽

10.1136/bmjopen-2019-034060 ◽

2020 ◽

Vol 10 (1) ◽

pp. e034060

Author(s):

Simon Feng ◽

Carl Van Walraven ◽

Manoj Lalu ◽

Husein Moloo ◽

Reilly Musselman ◽

...

Keyword(s):

Research Ethics ◽

Risk Prediction ◽

General Surgery ◽

Older Patients ◽

Prediction Models ◽

External Validation ◽

Population Based ◽

Future Research ◽

Emergency General Surgery ◽

Improvement Program

IntroductionPeople 65 years and older represent the fastest growing segment of the surgical population. Older age is associated with doubling of risk when undergoing emergency general surgery (EGS) procedures and often coexists with medical complexity and considerations of end-of-life care, creating prognostic and decisional uncertainty. Combined with the time-sensitive nature of EGS, it is challenging to gauge perioperative risk and ensure that clinical decisions are aligned with the patient values. Current preoperative risk prediction models for older EGS patients have major limitations regarding derivation and validation, and do not address the specific risk profile of older patients. Accurate and externally validated models specific to older patients are needed to inform care and decision making.Methods and analysisWe will derive, internally and externally validate a multivariable model to predict 30-day mortality in EGS patients >65 years old. Our derivation sample will be individuals enrolled in the National Surgical Quality Improvement Program (NSQIP) database between 2012 and 2016 having 1 of 7 core EGS procedures. Postulated predictor variables have been identified based on previous research, clinical and epidemiological knowledge. Our model will be derived using logistic regression penalised with elastic net regularisation and ensembled using bootstrap aggregation. The resulting model will be internally validated using k-fold cross-validation and bootstrap validation techniques and externally validated using population-based health administrative data. Discrimination and calibration will be reported at each step.Ethics and disseminationEthics for NSQIP data use was obtained from the Ottawa Hospital Research Ethics Board; external validation will use routinely collected anonymised data legally exempt from research ethics review. The final risk score will be published in a peer-reviewed journal. We plan to further disseminate the model as an online calculator or application for clinical use. Future research will be required to test the clinical application of the final model.

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Effect Of Trauma Center Status on 30-Day Outcomes After Emergency General Surgery

Journal of the American College of Surgeons ◽

10.1016/j.jamcollsurg.2010.12.001 ◽

2011 ◽

Vol 212 (3) ◽

pp. 277-286 ◽

Cited By ~ 29

Author(s):

Angela M. Ingraham ◽

Mark E. Cohen ◽

Mehul V. Raval ◽

Clifford Y. Ko ◽

Avery B. Nathens

Keyword(s):

General Surgery ◽

Trauma Center ◽

Emergency General Surgery

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

Trauma Surgery & Acute Care Open ◽

10.1136/tsaco-2018-000244 ◽

2019 ◽

Vol 4 (1) ◽

pp. e000244 ◽

Cited By ~ 2

Author(s):

Michael P DeWane ◽

Kimberly A Davis ◽

Kevin M Schuster ◽

Adrian A Maung ◽

Robert D Becher

Keyword(s):

Septic Shock ◽

General Surgery ◽

Temporal Trends ◽

Early Period ◽

Early Death ◽

Colon Resection ◽

Early Mortality ◽

Emergency General Surgery ◽

Improvement Program ◽

New Onset

BackgroundThe 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.MethodsThis 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.ResultsA 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.ConclusionsNearly 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 evidenceLevel III. Study type: Prognostic.

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