Estimating risk of adverse cardiac event after vascular surgery using currently available online calculators.
The decision to proceed with vascular surgical interventions requires evaluation of cardiac risk. Recently, several online risk calculators were created to predict outcomes and to lead to a more informed conversation between surgeons and patients. The objective of this study was to compare and further validate these online calculators with actual adverse cardiac outcomes at a single institution.
All patients from January 2011 through December 2015 undergoing carotid endarterectomy (CEA), infrainguinal lower extremity bypass, open abdominal aortic aneurysm (AAA) repair, and endovascular aneurysm repair (EVAR) on the vascular surgical service were included using the Society for Vascular Surgery Vascular Quality Initiative database at our health system. Additional information was collected through retrospective chart review. Each patient was entered through three online risk calculators: (1) the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) estimates the risk of cardiac arrest and myocardial infarction (MI); (2) the Revised Cardiac Risk Index (RCRI) estimates risk of MI, pulmonary edema, ventricular fibrillation, primary cardiac arrest, and complete heart block; and (3) the Vascular Study Group of New England (VSGNE) Cardiac Risk Index estimates risk of postoperative MI only. Observed adverse cardiac events (ACEs) were compared with expected values for each calculator using a χ2 goodness-of-fit test. Institutional Review Board exemption was obtained.
A total of 856 cases were included: 350 CEAs, 210 infrainguinal bypasses, 77 open AAA repairs, and 219 EVARs. For CEA, no risk calculator showed statistically significant variation from the observed values (NSQIP, P = .45; RCRI, P = .17; VSGNE, P = .24). For infrainguinal bypass, NSQIP slightly underpredicted adverse events (P = .054), RCRI strongly underpredicted (P = .002), and VSGNE showed no difference (P = .42). For open AAA repair, NSQIP (P = .51) and VSGNE (P = .98) were adequate predictors, but RCRI strongly underpredicted the adverse events (P ≤ .0001). Finally, EVAR cardiac outcomes showed greater adverse events than predicted by all three calculators (NSQIP, P = .02; RCRI, P = .0002; and VSGNE, P = .025). Pooled data for the entire group documented that the VSGNE proved an accurate tool for prediction (P = .34), whereas ACEs were underpredicted by NSQIP (P = .0055) and RCRI (P ≤ .001).
Although online cardiac risk calculators of adverse surgical events are easy to use and to reference in broad surgical decision-making, there is significant variability in their predictability at the procedure and institutional level. Our data suggest that ACEs often occur at a higher rate than expected on the basis of calculated risks profiles, thus creating a platform for future discussion about preoperative evaluation and postoperative care decision-making models.
Moses DA
,Johnston LE
,Tracci MC
,Robinson WP 3rd
,Cherry KJ
,Kern JA
,Upchurch GR Jr
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Adverse cardiac events after vascular surgery are prevalent despite negative results of preoperative stress testing.
Cardiac risk assessment is a critical component of vascular disease management before surgical intervention. The predictive risk reduction of a negative cardiac stress test result remains poorly defined. The objective of this study was to compare the incidence of postoperative cardiac events among patients with negative stress test results vs those who did not undergo testing.
We reviewed all patients who underwent elective open abdominal aortic aneurysm repair, suprainguinal bypass, endovascular aneurysm repair (EVAR), carotid endarterectomy (CEA), and infrainguinal bypass within the Vascular Study Group of New England from 2003 to 2017. We excluded patients with positive stress test results (n = 3312) and studied two mutually exclusive groups: elective surgery patients with a negative stress test result and elective surgery patients with no stress test (total n = 26,910). The primary outcome was a composite of in-hospital postoperative cardiac events (dysrhythmia, heart attack, heart failure) or death.
A preoperative stress test was obtained in 66.3% of open repairs, 42.8% of suprainguinal bypasses, 37.1% of EVARs, 36.0% of CEAs, and 31.2% of infrainguinal bypasses. The proportion of patients receiving a preoperative stress test varied widely across centers, from 37.1% to 80.0%. The crude odds ratio of in-hospital postoperative cardiac event or death was 1.37 (95% confidence interval [CI], 1.07-1.76) for open repair and 1.52 (CI, 1.13-2.03) for suprainguinal bypass, indicating that patients with negative stress test results before these procedures were 37% and 52% more likely to suffer a postoperative event or die compared with patients selected to proceed directly to surgery without testing. Conversely, the crude odds ratio was 0.92 (CI, 0.66-1.29) for EVAR, 0.92 (CI, 0.70-1.21) for CEA, and 1.13 (CI, 0.90-1.40) for infrainguinal bypass, indicating that patients undergoing these procedures had a similar likelihood of sustaining an event whether they had a negative stress test result or proceeded directly to surgery without a stress test.
The use of cardiac stress testing before vascular surgery varies widely throughout New England. Whereas patients are often appropriately selected to proceed directly to surgery, a negative preoperative stress test result should not assuage the concern for an adverse outcome as these patients retain a substantial likelihood of cardiac events, especially after large-magnitude procedures.
Columbo JA
,Barnes JA
,Jones DW
,Suckow BD
,Walsh DB
,Powell RJ
,Goodney PP
,Stone DH
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External validation of Vascular Study Group of New England risk predictive model of mortality after elective abdominal aorta aneurysm repair in the Vascular Quality Initiative and comparison against established models.
The purpose of this study is to externally validate a recently reported Vascular Study Group of New England (VSGNE) risk predictive model of postoperative mortality after elective abdominal aortic aneurysm (AAA) repair and to compare its predictive ability across different patients' risk categories and against the established risk predictive models using the Vascular Quality Initiative (VQI) AAA sample.
The VQI AAA database (2010-2015) was queried for patients who underwent elective AAA repair. The VSGNE cases were excluded from the VQI sample. The external validation of a recently published VSGNE AAA risk predictive model, which includes only preoperative variables (age, gender, history of coronary artery disease, chronic obstructive pulmonary disease, cerebrovascular disease, creatinine levels, and aneurysm size) and planned type of repair, was performed using the VQI elective AAA repair sample. The predictive value of the model was assessed via the C-statistic. Hosmer-Lemeshow method was used to assess calibration and goodness of fit. This model was then compared with the Medicare, Vascular Governance Northwest model, and Glasgow Aneurysm Score for predicting mortality in VQI sample. The Vuong test was performed to compare the model fit between the models. Model discrimination was assessed in different risk group VQI quintiles.
Data from 4431 cases from the VSGNE sample with the overall mortality rate of 1.4% was used to develop the model. The internally validated VSGNE model showed a very high discriminating ability in predicting mortality (C = 0.822) and good model fit (Hosmer-Lemeshow P = .309) among the VSGNE elective AAA repair sample. External validation on 16,989 VQI cases with an overall 0.9% mortality rate showed very robust predictive ability of mortality (C = 0.802). Vuong tests yielded a significant fit difference favoring the VSGNE over then Medicare model (C = 0.780), Vascular Governance Northwest (0.774), and Glasgow Aneurysm Score (0.639). Across the 5 risk quintiles, the VSGNE model predicted observed mortality significantly with great accuracy.
This simple VSGNE AAA risk predictive model showed very high discriminative ability in predicting mortality after elective AAA repair among a large external independent sample of AAA cases performed by a diverse array of physicians nationwide. The risk score based on this simple VSGNE model can reliably stratify patients according to their risk of mortality after elective AAA repair better than other established models.
Eslami MH
,Rybin DV
,Doros G
,Siracuse JJ
,Farber A
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The Vascular Quality Initiative Cardiac Risk Index for prediction of myocardial infarction after vascular surgery.
The objective of this study was to develop and to validate the Vascular Quality Initiative (VQI) Cardiac Risk Index (CRI) for prediction of postoperative myocardial infarction (POMI) after vascular surgery.
We developed risk models for in-hospital POMI after 88,791 nonemergent operations from the VQI registry, including carotid endarterectomy (CEA; n = 45,340), infrainguinal bypass (INFRA; n = 18,054), suprainguinal bypass (SUPRA; n = 2678), endovascular aneurysm repair (EVAR; n = 18,539), and open abdominal aortic aneurysm repair (OAAA repair; n = 4180). Multivariable logistic regression was used to create an all-procedure and four procedure-specific risk calculators based on the derivation cohort from 2012 to 2014 (N = 61,236). Generalizability of the all-procedure model was evaluated by applying it to each procedure subtype. The models were validated using a cohort (N = 27,555) from January 2015 to February 2016. Model discrimination was measured by area under the receiver operating characteristic curve (AUC), and performance was validated by bootstrapping 5000 iterations. The VQI CRI calculator was made available on the Internet and as a free smart phone app available through QxCalculate.
Overall POMI incidence was 1.6%, with variation by procedure type as follows: CEA, 0.8%; EVAR, 1.0%; INFRA, 2.6%; SUPRA, 3.1%; and OAAA repair, 4.3% (P < .001). Predictors of POMI in the all-procedure model included age, operation type, coronary artery disease, congestive heart failure, diabetes, creatinine concentration >1.8 mg/dL, stress test status, and body mass index (AUC, 0.75; 95% confidence interval [CI], 0.73-0.76). The all-procedure model demonstrated only minimally reduced accuracy when it was applied to each procedure, with the following AUCs: CEA, 0.65 (95% CI, 0.59-0.70); INFRA, 0.69 (95% CI, 0.64-0.73); EVAR, 0.72 (95% CI, 0.65-0.80); SUPRA, 0.62 (95% CI, 0.52-0.72); and OAAA, 0.63 (95% CI, 0.56-0.70). Procedure-specific models had unique predictors and showed improved prediction compared with the all-procedure model, with the following AUCs: CEA, 0.69 (95% CI, 0.66-0.72); INFRA, 0.75 (95% CI, 0.73-0.78); EVAR, 0.76 (95% CI, 0.73-0.80); and OAAA, 0.72 (95% CI, 0.69-0.77). Bias-corrected AUC (95% CI) from internal validation for the models was as follows: all procedures, 0.75 (0.73-0.76); CEA, 0.68 (0.65-0.71); INFRA, 0.74 (0.72-0.76); EVAR, 0.73 (0.70-0.78); and OAAA repair, 0.68 (0.65-0.73).
The VQI CRI is a useful and valid clinical decision-making tool to predict POMI after vascular surgery. Procedure-specific models improve accuracy when they include unique risk factors.
Bertges DJ
,Neal D
,Schanzer A
,Scali ST
,Goodney PP
,Eldrup-Jorgensen J
,Cronenwett JL
,Vascular Quality Initiative
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