Prevalent cardiac, renal and cardiorenal damage in patients with advanced abdominal aortic aneurysms

Predictive factors for major adverse cardiac and cerebrovascular events in octogenarians after elective endovascular aneurysm repair

OBJECTIVES

The aim of this study was to identify risk factors of major adverse cardiac and cerebrovascular events (MACCE) in octogenarians who received elective endovascular aneurysm repair (EVAR).

METHODS

Consecutive patients aged ≥ 80 years undergoing elective EVAR from 2009 to 2020 were retrospectively evaluated. The primary outcome was long-term MACCE. All independent risk factors for outcomes were determined by multivariate logistic analysis or Cox regression analysis.

RESULTS

A total of 163 patients were enrolled in this study. The median age was 81 (interquartile range, IQR, 80-84) years and 85.9% (140/163) of them were male. MACCE happened in 2.5% (4/163) patients within 30 days. With median follow-up of 28 (IQR, 15-46) months, the incidence of long-term MACCE was 26.4% (43/163). Arrythmia was significantly associated with long-term MACCE (hazard ratio, HR = 2.64, 95% confidence interval, CI, 1.16-6.03, P = .021). Carotid artery disease was found a significant association with 2-year MACCE (odd ratio, OR = 6.50, 95% CI, 1.07-39.51, P = .042). Besides, we found that arrythmia and congestive heart failure (CHF) were predictors for overall survival (arrythmia, HR = 2.56, 95% CI, 1.05-6.28, P = .039; CHF, HR = 8.96, 95% CI, 2.12-37.79, P = .003).

CONCLUSIONS

EVAR in octogenarians had acceptable perioperative risk and long-term outcome. Considering high risk of 2-year MACCE, intervention strategy should be more cautious for patients with carotid artery disease. Octogenarians with arrythmia and CHF should receive stricter postoperative management in case of MACCE.

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.

[Surgical treatment of patients with abdominal aortic aneurysm and ischaemic heart disease]

Presented herein are the results of treatment of 137 patients with infrarenal aneurysms of the abdominal portion of the aorta in a combination with ischaemic heart disease. Severity of lesions to the coronary bed and the risk of cardiac complications were assessed according to the SYNTAX score. Depending on severity of angina pectoris and the clinical course of infrarenal aortic aneurysms, we used different tactical approaches to operative treatment of patients. In a low risk of coronary complications, we performed isolated prosthetic repair or endoprosthetic reconstruction of the abdominal aorta. In patients with haemodynamically significant lesions of the coronary bed and positive non-invasive tests, the first stage consisted in coronary artery bypass grafting or stenting of coronary arteries taking into account the risk of cardiac complications according to the SYNTAX Score. The second stage consisted in prosthetic repair or endoprosthetic reconstruction of the abdominal aorta. The terms of the second stage differed and were determined by the course of abdominal aortic aneurysms. In symptomatic large aneurysms (more than 8 cm), prosthetic repair of the abdominal aorta was carried out within 2 weeks after previous stenting of coronary arteries. Simultaneous myocardial revascularization and abdominal aortic reconstruction were performed only in patients with severe angina pectoris, lesions of the trunk of the left coronary artery, three-vessel lesions of the coronary bed, high risk of cardiac complications according to the SYNTAX Score and a complicated or symptomatic course of an infrarenal aortic aneurysm. During implantation of stent grafts into the abdominal aorta there were neither lethal outcomes nor cardiac complications. In open operations, the 30-day mortality rate amounted to 2.2%, with the 5-year survival rate of 92%.

Association of simple renal cysts and chronic kidney disease with large abdominal aortic aneurysm

Background

Abdominal aortic aneurysms (AAA) primarily affect men over 65 years old who often have many other diseases, with similar risk factors and pathobiological mechanisms to AAA. The aim of this study was to assess the prevalence of simple renal cysts (SRC), chronic kidney disease (CKD), and other kidney diseases (e.g. nephrolithiasis) among patients presenting with AAA.

Methods

Two groups of patients (97 AAA and 100 controls), with and without AAA, from the Surgical Clinic Charité, Berlin, Germany, were selected for the study. The control group consisted of patients who were evaluated for a kidney donation (n = 14) and patients who were evaluated for an early detection of a melanoma recurrence (n = 86). The AAA and control groups were matched for age and sex. Medical records were analyzed and computed tomography scans were reviewed for the presence of SRC and nephrolithiasis.

Results

SRC (74% vs. 57%; p<0.016) and CKD (30% vs. 8%; p<0.001) were both more common among AAA than control group patients. On multivariate analysis, CKD, but not SRC, showed a strong association with AAA.

Conclusions

Knowledge about pathobiological mechanisms and association between CKD and AAA could provide better diagnostic and therapeutic approaches for these patients.

Comorbidities Associated with Large Abdominal Aortic Aneurysms

Background  Abdominal aortic aneurysm has become increasingly important owing to demographic changes. Some other diseases, for example, cholecystolithiasis, chronic obstructive pulmonary disease, and hernias, seem to co-occur with abdominal aortic aneurysm. The aim of this retrospective analysis was to identify new comorbidities associated with abdominal aortic aneurysm.

Methods  We compared 100 patients with abdominal aortic aneurysms and 100 control patients. Their preoperative computed tomographic scans were examined by two investigators independently, for the presence of hernias, diverticulosis, and cholecystolithiasis. Medical records were also reviewed. Statistical analysis was performed using univariate analysis and multiple logistic regression analysis.

Results  The aneurysm group had a higher frequency of diverticulosis ( p  = 0.008). There was no significant difference in the occurrence of hernia ( p  = 0.073) or cholecystolithiasis ( p  = 1.00). Aneurysm patients had a significantly higher American Society of Anesthesiology score (2.84 vs. 2.63; p  = 0.015) and were more likely to have coronary artery disease ( p  < 0.001), congestive heart failure ( p  < 0.001), or chronic obstructive pulmonary disease ( p  < 0.001). Aneurysm patients were more likely to be former ( p  = 0.034) or current ( p  = 0.006) smokers and had a significantly higher number of pack years ( p  < 0.001). Aneurysm patients also had a significantly poorer lung function. In multivariate analysis, the following factors were associated with aneurysms: chronic obstructive pulmonary disease (odds ratio, OR = 12.24; p  = 0.002), current smoking (OR = 4.14; p  = 0.002), and coronary artery disease (OR = 2.60; p  = 0.020).

Conclusions  Our comprehensive analysis identified several comorbidities associated with abdominal aortic aneurysms. These results could help to recognize aneurysms earlier by targeting individuals with these comorbidities for screening.

Risk factors for postoperative renal dysfunction following open surgical repair of abdominal aortic aneurysms retrospective analysis

Objectives

To identify the risk factors for postoperative renal dysfunction after open surgical repair (OSR) of abdominal aortic aneurysms (AAAs) and to establish a scoring system.

Results

The overall 30-day mortality rates were 22.0%(ruptured) vs 2.6% (unruptured), respectively. For the ruptured group, the independent risk factors were hemodynamic instability (P = 0.002) blood loss >1 L (P = 0.041) and preoperative creatinine >150 μmol/L (P < 0.001). By contrast, for the unruptured group, factors were smoking (P = 0.028), blood loss >1 L (P = 0.018), and antihypertensive drugs (P < 0.001). The areas under the curve of the WCRDA scoring system are 0.794 (95% confidence interval (CI) 0.686–0.902, P < 0.001) and 0.811 (95% CI 0.691–0.932, P < 0.001) for the ruptured and unruptured groups, respectively.

Conclusions

Hemodynamic instability, blood loss >1 L and Hb <90 g/L are independent risk factors for postoperative renal dysfunction following rAAA OSR, whereas smoking, blood loss >1 L, and antihypertensive drugs are independent risk factors. WCRDA performs well in predicting postoperative renal dysfunction.

Materials and Methods

287 patients from the Vascular Department of West China Hospital, Sichuan University, who were planned to perform OSR for AAA from November 2003 to January 2017. 274 patients underwent OSR for AAA were finally included in the study. A total of 118 patients had ruptured AAA and 156 unruptured AAA.

The patients were divided into the ruptured and unruptured groups. Logistic regression was used to identify the independent risk factors for postoperative renal dysfunction. The receiver operating characteristic curve was used to evaluate the scoring system.

Chronic Kidney Disease Is Positively and Diabetes Mellitus Is Negatively Associated with Abdominal Aortic Aneurysm

BACKGROUND AND AIMS

Chronic kidney disease (CKD) and diabetes mellitus (DM) are considered as risk factors for cardiovascular diseases. The purpose of this study was to clarify the relationship of CKD and DM with the presence of abdominal aortic aneurysm (AAA).

METHODS

We enrolled 261 patients with AAA (AAA+) and age-and-sex matched 261 patients without AAA (AAA-) at two hospitals between 2008 and 2014, and examined the association between the risk factors and the presence of AAA. Furthermore, in order to investigate the prevalence of AAA in each group, we enrolled 1126 patients with CKD and 400 patients with DM.

RESULTS

The presence of CKD in patients with AAA+ was significantly higher than that in patients with AAA- (AAA+; 65%, AAA-; 52%, P = 0.004). The presence of DM in patients with AAA+ was significantly lower than that in patients with AAA- (AAA+; 17%, AAA-; 35%, P < 0.001). A multivariate logistic regression analysis demonstrated that hypertension, ischemic heart disease and CKD were independent determinants, whereas, DM was a negatively independent determinant, for the presence of AAA. The prevalence of AAA in patients with CKD 65 years old and above was 5.1%, whereas, that in patients with DM 65 years old and above was only 0.6%.

CONCLUSION

CKD is a positively associated with the presence of AAA. In contrast, DM is a negatively associated with the presence of AAA in Japanese population.

Blood transfusion and coagulation management

Despite impressive progress in surgical technique, aortic surgery is still associated with relatively high morbidity and mortality. One of the most important contributors to this phenomenon is the triad of bleeding, anemia, and transfusion. All three factors are known to influence the outcome of aortic surgery to a great extent. However, over the last few years a multidisciplinary, multimodal concept has been established, which enables the physician to avoid bleeding, anemia, and transfusion as much as possible. The concept of "patient blood management" combines several established measures with the potential to improve perioperative outcome. This chapter describes these measures with regard to aortic surgery and assesses their respective efficacy.