Preoperative Cardiac Evaluation and Perioperative Cardiac Therapy in Patients Undergoing Open Surgery for Abdominal Aortic Aneurysms: Effects on Cardiovascular Outcome

The comparative and added prognostic value of biomarkers to the Revised Cardiac Risk Index for preoperative prediction of major adverse cardiac events and all-cause mortality in patients who undergo noncardiac surgery

BACKGROUND

The Revised Cardiac Risk Index (RCRI) is a widely acknowledged prognostic model to estimate preoperatively the probability of developing in-hospital major adverse cardiac events (MACE) in patients undergoing noncardiac surgery. However, the RCRI does not always make accurate predictions, so various studies have investigated whether biomarkers added to or compared with the RCRI could improve this.

OBJECTIVES

Primary: To investigate the added predictive value of biomarkers to the RCRI to preoperatively predict in-hospital MACE and other adverse outcomes in patients undergoing noncardiac surgery. Secondary: To investigate the prognostic value of biomarkers compared to the RCRI to preoperatively predict in-hospital MACE and other adverse outcomes in patients undergoing noncardiac surgery. Tertiary: To investigate the prognostic value of other prediction models compared to the RCRI to preoperatively predict in-hospital MACE and other adverse outcomes in patients undergoing noncardiac surgery.

SEARCH METHODS

We searched MEDLINE and Embase from 1 January 1999 (the year that the RCRI was published) until 25 June 2020. We also searched ISI Web of Science and SCOPUS for articles referring to the original RCRI development study in that period.

SELECTION CRITERIA

We included studies among adults who underwent noncardiac surgery, reporting on (external) validation of the RCRI and: - the addition of biomarker(s) to the RCRI; or - the comparison of the predictive accuracy of biomarker(s) to the RCRI; or - the comparison of the predictive accuracy of the RCRI to other models. Besides MACE, all other adverse outcomes were considered for inclusion.

DATA COLLECTION AND ANALYSIS

We developed a data extraction form based on the CHARMS checklist. Independent pairs of authors screened references, extracted data and assessed risk of bias and concerns regarding applicability according to PROBAST. For biomarkers and prediction models that were added or compared to the RCRI in ≥ 3 different articles, we described study characteristics and findings in further detail. We did not apply GRADE as no guidance is available for prognostic model reviews.

MAIN RESULTS

We screened 3960 records and included 107 articles.   Over all objectives we rated risk of bias as high in ≥ 1 domain in 90% of included studies, particularly in the analysis domain. Statistical pooling or meta-analysis of reported results was impossible due to heterogeneity in various aspects: outcomes used, scale by which the biomarker was added/compared to the RCRI, prediction horizons and studied populations.  Added predictive value of biomarkers to the RCRI Fifty-one studies reported on the added value of biomarkers to the RCRI. Sixty-nine different predictors were identified derived from blood (29%), imaging (33%) or other sources (38%). Addition of NT-proBNP, troponin or their combination improved the RCRI for predicting MACE (median delta c-statistics: 0.08, 0.14 and 0.12 for NT-proBNP, troponin and their combination, respectively). The median total net reclassification index (NRI) was 0.16 and 0.74 after addition of troponin and NT-proBNP to the RCRI, respectively. Calibration was not reported. To predict myocardial infarction, the median delta c-statistic when NT-proBNP was added to the RCRI was 0.09, and 0.06 for prediction of all-cause mortality and MACE combined. For BNP and copeptin, data were not sufficient to provide results on their added predictive performance, for any of the outcomes. Comparison of the predictive value of biomarkers to the RCRI  Fifty-one studies assessed the predictive performance of biomarkers alone compared to the RCRI. We identified 60 unique predictors derived from blood (38%), imaging (30%) or other sources, such as the American Society of Anesthesiologists (ASA) classification (32%). Predictions were similar between the ASA classification and the RCRI for all studied outcomes. In studies different from those identified in objective 1, the median delta c-statistic was 0.15 and 0.12 in favour of  BNP and NT-proBNP alone, respectively, when compared to the RCRI, for the prediction of MACE. For C-reactive protein, the predictive performance was similar to the RCRI. For other biomarkers and outcomes, data were insufficient to provide summary results. One study reported on calibration and none on reclassification. Comparison of the predictive value of other prognostic models to the RCRI   Fifty-two articles compared the predictive ability of the RCRI to other prognostic models. Of these, 42% developed a new prediction model, 22% updated the RCRI, or another prediction model, and 37% validated an existing prediction model. None of the other prediction models showed better performance in predicting MACE than the RCRI. To predict myocardial infarction and cardiac arrest, ACS-NSQIP-MICA had a higher median delta c-statistic of 0.11 compared to the RCRI. To predict all-cause mortality, the median delta c-statistic was 0.15 higher in favour of ACS-NSQIP-SRS compared to the RCRI. Predictive performance was not better for CHADS₂, CHA₂DS₂-VASc, R₂CHADS₂, Goldman index, Detsky index or VSG-CRI compared to the RCRI for any of the outcomes. Calibration and reclassification were reported in only one and three studies, respectively.

AUTHORS' CONCLUSIONS

Studies included in this review suggest that the predictive performance of the RCRI in predicting MACE is improved when NT-proBNP, troponin or their combination are added. Other studies indicate that BNP and NT-proBNP, when used in isolation, may even have a higher discriminative performance than the RCRI. There was insufficient evidence of a difference between the predictive accuracy of the RCRI and other prediction models in predicting MACE. However, ACS-NSQIP-MICA and ACS-NSQIP-SRS outperformed the RCRI in predicting myocardial infarction and cardiac arrest combined, and all-cause mortality, respectively. Nevertheless, the results cannot be interpreted as conclusive due to high risks of bias in a majority of papers, and pooling was impossible due to heterogeneity in outcomes, prediction horizons, biomarkers and studied populations. Future research on the added prognostic value of biomarkers to existing prediction models should focus on biomarkers with good predictive accuracy in other settings (e.g. diagnosis of myocardial infarction) and identification of biomarkers from omics data. They should be compared to novel biomarkers with so far insufficient evidence compared to established ones, including NT-proBNP or troponins. Adherence to recent guidance for prediction model studies (e.g. TRIPOD; PROBAST) and use of standardised outcome definitions in primary studies is highly recommended to facilitate systematic review and meta-analyses in the future.

Preoperative Consultations

Preoperative consultation is an important intervention that likely has most benefits for intermediate-risk to high-risk patients undergoing major surgery. Consultation rates are likely increasing and there is significant practice variation in the use of consultation. Consultations should be available within a well-organized and coordinated process of preoperative assessment. Preoperative consults should be accessible to anesthesia and surgical teams involved in the procedure and to the providers involved in postoperative care. The role of preoperative consultation should evolve as a rational approach and emerge as a value-based service. New payment methodologies are likely to facilitate appropriate use of this important resource.

Frequency of concomitant ischemic heart disease and risk factor analysis for an early postoperative myocardial infarction after elective abdominal aortic aneurysm repair

Purpose

We aimed to see the frequency of concomitant ischemic heart disease (IHD) in Korean patients with abdominal aortic aneurysm (AAA) and to determine risk factors for an early postoperative acute myocardial infarction (PAMI) after elective open or endovascular AAA repair.

Methods

We retrospectively reviewed a database of patients who underwent elective AAA repair over the past 11 years. Patients were classified into 3 groups: control group; group I, medical IHD treatment; group II, invasive IHD treatment. Rates of PAMI and mortality at 30 days were compiled and compared between groups according to the type of AAA repair.

Results

Six hundred two elective repairs of infrarenal or juxtarenal AAAs were enrolled in this study. The patients were classified into control group (n = 398, 66.1%), group I (n = 73, 12.1%) and group II (n = 131, 21.8%). PAMI developed more frequently after open surgical repair (OSR) than after endovascular aneurysm repair (EVAR) (5.4% vs. 1.3%, P = 0.012). In OSR patients (n = 373), PAMI developed 2.1% in control group, 18.0% in group I and 7.1% in group II (P < 0.001). In EVAR group (n = 229), PAMI developed 0.6% in control group, 4.3% in group I and 2.2% in group II (P = 0.211). On the multivariable analysis of risk factors of PAMI, PAMI developed more frequently in patients with positive functional stress test.

Conclusion

The prevalence of concomitant IHD was 34% in Korean AAA patients. The risk of PAMI was significantly higher after OSR compared to EVAR and in patients with IHD compared to control group. Though we found some risk factors for PAMI, these were not applied to postoperative mortality rate.

Preoperative cardiovascular evaluation in patients undergoing vascular surgery

Vascular surgery is associated with a higher incidence of perioperative cardiovascular morbidity and mortality compared with other noncardiac surgeries. Patients undergoing vascular surgery represent a higher-risk population, usually because of the presence of generalized arterial disease and multiple comorbidities. The overwhelming perioperative cardiac event is myocardial infarction. This article offers a tailored approach to preoperative cardiovascular management for patients undergoing vascular surgery. The use and limitations of well-established guidelines and clinical risk indices for patients undergoing noncardiac surgery are described as it pertains to vascular surgery in particular. Furthermore, the role and benefit of noninvasive stress testing, coronary revascularization, and medical therapy before vascular surgery are discussed.

Coronary risk in candidates for abdominal aortic aneurysm repair: a word of caution

BACKGROUND

Current guidelines do not recommend routine coronary evaluation preceding abdominal aortic aneurysms (AAA) repair in low-risk patients. The purpose of the present study is to report the incidence of coronary lesions in candidates for AAA repair with a Revised Cardiac Risk (Lee) Index (RCRI) < 2, which are usually excluded from preoperative cardiological work-up. Early-term and long-term results of prophylactic myocardial revascularization are also reported.

METHODS

A retrospective, observational, cohort study collecting clinical data on a series of 149 consecutive patients undergoing preoperative coronary angiography and myocardial revascularization (percutaneous coronary intervention, PCI; coronary artery bypass grafting, CABG) before elective open or endovascular AAA repair (January 2005-December 2012).

RESULTS

Severe coronary artery disease (CAD) was revealed in 43 patients (28.9%), who underwent successful myocardial revascularization by means of PCI (n.35) or off-pump CABG (n.8). The incidence of severe CAD in patients resulted at low risk on the basis of risk models was approximately 25%. The incidence of severe CAD in asymptomatic patients was 29.8%. Endovascular (n.52, 35.1%) and open (n.96, 64.9%) AAA repair was performed with low morbidity (0.6%) and mortality (0.6%) in 148 patients. The long-term estimated survival (freedom from fatal cardiovascular events) was 97% at 60 months and 82% at 90 months.

CONCLUSIONS

The incidence of severe correctable CAD is not negligible in low-risk patients scheduled for AAA repair. Waiting for further recommendations based on large population studies of vascular patients, a more extensive indication to coronary angiography and revascularization should be considered in many candidates for AAA repair.

Role of pre-operative multiple gated acquisition scanning in predicting long-term outcome in patients undergoing elective abdominal aortic aneurysm repair

OBJECTIVE

To determine whether resting pre-operative left ventricular ejection fraction (LVEF) estimated by multiple gated acquisition scanning (MUGA) predicts long-term survival in patients undergoing elective abdominal aortic aneurysm (AAA) repair.

METHODS

A retrospective study of MUGA scans which were performed to estimate pre-operative resting LVEF in 127 patients [106 (83 %) males, mean age 74 ± 7.6 years] who underwent elective AAA repair over a period of 4 years from March 2007. We compared outcomes and long-term survival between patients who had a pre-operative LVEF ≤ 40 % (Group 1, n = 60) and LVEF > 40 % (Group 2, n = 67).

RESULTS

Overall 19 (15 %) patients died during the follow-up period (13 patients in group 1 and 6 patients in group 2). 30-day mortality was 8 %. There was no significant difference between group 1 and 2 in terms of patients' mean age or median length of hospital stay (8 days for both groups, p = 0.61). However, group 2 had more females than group 1(18 vs. 3, p = 0.001). Median survival for patients in group 2 was significantly higher than patients in group 1 (1,258 days vs. 1,000 days, p = 0.03). In a Cox regression model which included age, sex, smoking status and LVEF as covariates, only smoking status and LVEF predicted survival [Hazard ratio (HR) = 1.06, p = 0.04 and HR = 0.93, p = 0.00, respectively].

CONCLUSION

This study shows that there is a role for pre-operative MUGA scan assessment of resting LVEF in predicting long-term survival post elective AAA repair and that the lower the pre-operative LVEF the poorer the long-term outcome.