Predictive Value of Stress Testing, Revised Cardiac Risk Index, and Functional Status in Patients Undergoing Noncardiac Surgery

Preoperative evaluation of the elderly patient

Nowadays, the pre-operative evaluation of older patients is a critical step in the decision-making process. Clinical assessment and care planning should be considered a whole process rather than separate issues. Clinicians should use validated tools for pre-operative risk assessment of older patients to minimize surgery-related morbidity and mortality and enhance care quality. Traditional pre-operative consultation often fails to capture the pathophysiological and functional profiles of older patients. The elderly's pre-operative evaluation should be focused on determining the patient's functional reserve and reducing any possible peri-operative risk. Therefore, older adults may benefit from the Comprehensive Geriatric Assessment (CGA) that allows clinicians to evaluate several aspects of elderly life, such as depression and cognitive disorders, social status, multi-morbidity, frailty, geriatric syndromes, nutritional status, and polypharmacy. Despite the recognized challenges in applying the CGA, it may provide a realistic risk assessment for post-operative complications and suggest a tailored peri-operative treatment plan for older adults, including pre-operative optimization strategies. The older adults' pre-operative examination should not be considered a mere stand-alone, that is, an independent stage of the surgical pathway, but rather a vital step toward a personalized therapeutic approach that may involve professionals from different clinical fields. The aim of this review is to revise the evidence from the literature and highlight the most important items to be implemented in the pre-operative evaluation process in order to identify better all elderly patients' needs.

The financial implications of cardiac stress testing prior to abdominal aortic aneurysm repair

BACKGROUND

The utilization and cost-effectiveness of stress testing before abdominal aortic aneurysm (AAA) repair remains insufficiently studied. We examined the variation and financial implications of stress testing, and their association with major adverse cardiovascular events (MACE).

METHODS

We studied patients who underwent elective endovascular (EVAR) or open AAA repair (OAR) at Vascular Quality Initiative centers from 2015 to 2019. We grouped centers into quintiles of preoperative stress testing frequency. We calculated the risk of postoperative MACE, a composite of in-hospital myocardial infarction, heart failure, or death, for each center-quintile. We obtained charges for stress tests locally and applied these to the cohort to estimate charges per 1000 patients.

RESULTS

We studied 32,459 patients (EVAR: 27,978; OAR: 4481; 283 centers). Stress test utilization varied across quintiles from 13.0% to 68.6% (median: 36.8%) before EVAR and 15.9% to 85.0% (median: 59.4%) before OAR. The risk of MACE was 1.4% after EVAR and 10.2% after OAR. There was a trend towards more common MACE after EVAR among centers with higher utilization of stress testing: 0.9% among centers in the lowest quintile, versus 1.7% in the highest quintile (p-trend = 0.068). There was no association between MACE and stress testing frequency for OAR (p-trend = 0.223). The estimated financial charges for stress testing before EVAR ranged from $125,806 per 1000 patients at 1^st-quintile centers, to $665,975 at 5^th-quintile centers. Charges before OAR ranged from $153,861 at 1^st-quintile centers, to $825,473 at 5^th-quintile centers.

CONCLUSION

Stress test use before AAA repair is highly variable and associated with substantial cost, with an unclear association with postoperative MACE. This highlights the need for improved stress testing paradigms prior to surgery.

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.

Actual Issues of the Cardiac Complications Risk Assessment and Correction in Non-Cardiac Surgery

Worldwide, more than 200 million non-cardiac surgeries are performed annually, and this number is constantly increasing; cardiac complications are the leading cause of death in such surgeries. So, in a multicenter study conducted in 27 countries, cardiovascular complications were present in 68% of cases of death in the postoperative period. Registers of recent years have shown that the number of such complications remains high, for example, with a dynamic assessment of troponins, perioperative myocardial damage was detected in 13-18% of cases. This review provides a critical analysis of the step-by-step algorithm for assessing cardiac risk of non-cardiac operations considering the emergence of new publications on this topic. The review discusses new data on risk assessment scales, functional state assessment, the use of non-invasive tests, biomarkers, the role of preventive myocardial revascularization in the preoperative period, and drug therapy. The issues of non-cardiac operations after percutaneous coronary intervention, perioperative myocardial damage are considered separately. The review emphasizes the difficulties in obtaining evidence, conducting randomized clinical trials in this section of medicine, which do not allow obtaining unambiguous conclusions in most cases and lead to inconsistencies and ambiguities in the recommendations of various expert groups. This review will help practitioners navigate this issue and help to use the optimal diagnostic and treatment strategy before performing non-cardiac surgery.

Survival curve identifies critical period for postoperative mortality in cardiac patients undergoing emergency general surgery

The number of non-cardiac major surgeries carried out has significantly increased in recent years to around 200 million procedures carried out annually. Approximately 30% of patients submitted to non-cardiac surgery present some form of cardiovascular comorbidity. In emergency situations, with less surgery planning time and greater clinical severity, the risks become even more significant. The aim of this study is to determine the incidence and clinical outcomes in patients with cardiovascular disease submitted to non-cardiac surgical procedures in a single cardiovascular referral center. This is a prospective cohort study of patients with cardiovascular disease submitted to non-cardiovascular surgery. All procedures were carried out by the same surgeon, between January 2006 and January 2018. 240 patients included were elderly, 154 were male (64%), 8 patients presented two diagnoses. Of the resulting 248 procedures carried out, 230 were emergency (92.8%). From the data obtained it was possible to estimate the day from which the occurrence of mortality is less probable in the postoperative phase. Our research evaluated the epidemiological profile of the surgeries and we were able to estimate the survival and delimit the period of greatest risk of mortality in these patients. The high rate of acute mesenteric ischemia was notable, a serious and frequently fatal condition.

Preoperative Dobutamine Stress Echocardiography and Clinical Factors for Assessment of Cardiac Risk after Noncardiac Surgery

BACKGROUND

The role of dobutamine stress echocardiography (DSE) in the risk stratification of patients undergoing noncardiac surgery in the current era is unclear. The aim of this study was to evaluate the yield of DSE and the additive role of DSE to clinical criteria for preoperative risk stratification of patients undergoing noncardiac surgery.

METHODS

The study included 4,494 patients undergoing DSE ≤90 days before noncardiac surgery. The primary outcome was a composite of postoperative myocardial infarction, cardiac arrest, and all-cause mortality ≤30 days after noncardiac surgery.

RESULTS

The overall 30-day postoperative cardiac event rate was 2.3%. The mortality rate was 0.9% overall and 0.7% and 1.3% after normal and abnormal results on DSE, respectively. Among clinical variables, the modified Revised Cardiac Risk Index score demonstrated the strongest association with postoperative risk (P < .001). Patients with Revised Cardiac Risk Index scores of ≥3 had an event rate of 7.5%. The event rates for patients with wall motion score index ≥1.7 at baseline, left ventricular ejection fractions <40% at peak stress, or ischemic thresholds <70% of age-predicted maximal heart rate were 7.1%, 8.6%, and 7.9%, respectively. After adjusting for clinical variables, the overall result of DSE (P < .001), baseline and peak-stress wall motion score index (P < .001 and P = .014, respectively), peak-stress left ventricular ejection fraction (P < .001), and the number of ischemic segments (P = .027) were all associated with postoperative cardiac events. Incremental multivariate analysis demonstrated that an overall abnormal result on DSE, added to clinical variables, was associated with an increased risk for postoperative cardiac events (odds ratio, 2.07; 95% CI, 1.35-3.17; P < .001).

CONCLUSIONS

Baseline and peak-stress findings on preoperative DSE add to the prognostic utility of clinical variables for stratifying cardiac risk after noncardiac surgery.

Preoperative Assessment of Older Adults

Older patients undergoing surgery have reduced physiologic reserve caused by the combined impact of physiologic age-related changes and the increased burden of comorbid conditions. The preoperative assessment of older patients is directed at evaluating the patient's functional reserve and identifying opportunities to minimize any potential for complications. In addition to a standard preoperative evaluation that includes cardiac risk and a systematic review of systems, the evaluation should be supplemented with a review of geriatric syndromes. Age-based laboratory testing protocols can lead to unnecessary testing, and all testing should be requested if indicated by underlying disease and surgical risk.