Patterns of β-blocker initiation in patients undergoing intermediate to high-risk noncardiac surgery

Preoperative β-Blocker Therapy and Stroke or Major Adverse Cardiac Events in Major Abdominal Surgery: A Retrospective Cohort Study

BACKGROUND

Perioperative β-blocker therapy has been associated with increased risk of stroke. However, the association between β-blocker initiation before the day of surgery and the risk of stroke is unknown. The authors hypothesized there would be no association between preoperative β-blocker initiation within 60 days of surgery or chronic β-blockade (more than 60 days) and the risk of stroke in patients undergoing major abdominal surgery.

METHODS

Data on elective major abdominal surgery were obtained from the IBM (USA) Truven Health MarketScan 2005 to 2015 Commercial and Medicare Supplemental Databases. Patients were stratified by β-blocker dispensing exposure: (1) β-blocker-naïve, (2) preoperative β-blocker initiation within 60 days of surgery, and (3) chronic β-blocker dispensing (more than 60 days). The authors compared in-hospital stroke and major adverse cardiac events between the different β-blocker therapy exposures.

RESULTS

There were 204,981 patients who underwent major abdominal surgery. β-Blocker exposure was as follows: perioperative initiation within 60 days of surgery for 4,026 (2.0%) patients, chronic β-blocker therapy for 45,424 (22.2%) patients, and β-blocker-naïve for 155,531 (75.9%) patients. The unadjusted frequency of stroke for patients with β-blocker initiation (0.4%, 17 of 4,026) and chronic β-blocker therapy (0.4%, 171 of 45,424) was greater than in β-blocker-naïve patients (0.2%, 235 of 155,531; P < 0.001). After propensity score weighting, patients initiated on a β-blocker within 60 days of surgery (odds ratio, 0.90; 95% CI, 0.31 to 2.04; P = 0.757) or on chronic β-blocker therapy (odds ratio, 0.86; 95% CI, 0.65 to 1.15; P = 0.901) demonstrated similar stroke risk compared to β-blocker-naïve patients. Patients on chronic β-blocker therapy demonstrated lower adjusted risk of major adverse cardiac events compared to β-blocker-naïve patients (odds ratio, 0.81; 95% CI, 0.72 to 0.91; P = 0.007), despite higher unadjusted absolute event rate (2.6% [1,173 of 45,424] vs. 0.6% [872 of 155,531]).

CONCLUSIONS

Among patients undergoing elective major abdominal surgery, the authors observed no association between preoperative β-blocker initiation within 60 days of surgery or chronic β-blocker therapy and stroke.

EDITOR’S PERSPECTIVE

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.

Perioperative β-Blockers in Patients Undergoing Noncardiac Surgery-Scientific Misconduct and Clinical Guidelines

BACKGROUND

β-blocker use in perioperative period of noncardiac surgeries has been a topic of debate since many years. Earlier studies conducted in the 90s showed decreased cardiac adverse events and improved postoperative outcomes with β-blocker use. Based on this, the ACCF and ESC published guidelines strongly supporting β-blocker use. But contemporaneous studies conducted revealed conflicting evidence and have also proven some of the earlier studies to be fraudulent. Although ACCF guidelines have been updated to partially reflect the changes, ESC guidelines continue to support β-blocker use.

AREAS OF UNCERTAINTY

In light of the ACCF and ESC guidelines supporting β-blocker use in perioperative period of noncardiac surgeries, our aim was to review the available literature and consolidate evidence in this regard.

DATA SOURCES

PubMed search was conducted to include relevant studies between 1950 and 2015.

RESULTS

We reviewed 24 eligible studies and few debates conducted in this regard. Based on our review, our findings were as follows: β-blockers should be continued throughout perioperative period in patients who were on β-blockers before surgery for other indications such as angina, hypertension, and symptomatic arrhythmias. Preoperative β-blockers are indicated in patients undergoing high risk vascular surgery or those having high preoperative Cardiac Risk Index Score. In patients with intermediate-to-low cardiac risk, the proven benefit is not sufficient enough to suggest universal use.

CONCLUSIONS

Based on our review, we conclude that the use of β-blockers in perioperative period of noncardiac surgeries should be determined on an individual basis based on risk-benefit analysis. Guideline organizations should update their recommendations based on new evidence.