NT-proBNP incorporated in prediction rule of major peri-operative adverse cardiac event in non-cardiac surgery

ESAIC focused guideline for the use of cardiac biomarkers in perioperative risk evaluation

BACKGROUND

In recent years, there has been increasing focus on the use of cardiac biomarkers in patients undergoing noncardiac surgery.

AIMS

The aim of this focused guideline was to provide updated guidance regarding the pre-, post- and combined pre-and postoperative use of cardiac troponin and B-type natriuretic peptides in adult patients undergoing noncardiac surgery.

METHODS

The guidelines were prepared using Grading of Recommendations Assessment Development and Evaluation (GRADE) methodology. This included the definition of critical outcomes, a systematic literature search, appraisal of certainty of evidence, evaluation of biomarker measurement in terms of the balance of desirable and undesirable effects including clinical outcomes, resource use, health inequality, stakeholder acceptance, and implementation. The panel differentiated between three different scopes of applications: cardiac biomarkers as prognostic factors, as tools for risk prediction, and for biomarker-enhanced management strategies.

RESULTS

In a modified Delphi process, the task force defined 12 critical outcomes. The systematic literature search resulted in over 25,000 hits, of which 115 full-text articles formed the body of evidence for recommendations. The evidence appraisal indicated heterogeneity in the certainty of evidence across critical outcomes. Further, there was relevant gradient in the certainty of evidence across the three scopes of application. Recommendations were issued and if this was not possible due to limited evidence, clinical practice statements were produced.

CONCLUSION

The ESAIC focused guidelines provide guidance on the perioperative use of cardiac troponin and B-type natriuretic peptides in patients undergoing noncardiac surgery, for three different scopes of application.

The Predictive Value of Serum NT-proBNP on One-Year All-Cause Mortality in Geriatrics Hip Fracture: A Cohort Study

Objective This study evaluated the association between N-terminal prohormone of brain natriuretic peptide (NT-proBNP) concentration and one-year mortality in geriatric patients with intertrochanteric and femoral neck fractures receiving the operative treatment. Methods Consecutive age ≥65 years patients with hip fractures were screened between January 2015 and September 2019. Demographic and clinical characteristics of the patients were collected. The multivariate logistic regression models were used to identify the association between preoperative NT-proBNP concentrations and mortality. All analyses were performed using EmpowerStats and the R software. Result One thousand two hundred nineteen patients were included in the study. The average age was 79.73±6.65 years (range 66-99 years). The mean NT-proBNP concentration was 616.09±1086.85 ng/L (median 313.40 ng/L, range 16.09-20123.00 ng/L). The follow-up was 35.39±15.09 months (median 35.78 months, range 0.10-80.14 months). One hundred and eleven (9.1%) patients died within one year. After adjusting for confounding factors, multivariate logistic regression models showed a curved association between preoperative NT-proBNP concentration and one-year mortality. When the NT-proBNP concentration was below 1099 ng/L, the mortality increased by 10% (OR=1.10, 95%CI: 1.03-1.17, P=0.0025) when NT-proBNP increased by 100 ng/L. When the NT-proBNP concentration was above 1099 ng/L, the mortality did not increase anymore when NT-proBNP increased (OR=1.00, 95%CI: 0.99-1.02, P=0. 7786). Thus, NT-proBNP was a valuable indicator to predict high one-year mortality in practice. Conclusion The NT-proBNP concentrations were nonlinearly associated with mortality in elderly hip fractures with a saturation effect, and NT-proBNP was a risk indicator of all-cause mortality. A well-designed controlled trial to show the role of mortality by decreasing the concentration of NT-proBNP is needed in the future.

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 cardiac screening using NT-proBNP in obese patients 50 years and older undergoing bariatric surgery: a study of 310 consecutive patients

Background

Obesity is associated with cardiovascular (CV) risk factors and diseases. Because bariatric surgery is increasingly performed in relatively elderly patients, a risk for pre- and postoperative CV complications exists.

Objectives

We aimed to assess the value of plasma N-terminal-probrain natriuretic peptide (NT-proBNP) as a CV screening tool.

Setting

High-volume bariatric center.

Methods

Between June 2019 and January 2020, all consecutive bariatric patients 50 years and older underwent preoperative NT-proBNP assessment in this cohort study to screen for CV disease. Patients with elevated NT-proBNP (≥125 pg/mL) were referred for further cardiac evaluation, including electrocardiography and echocardiography.

Results

We included 310 consecutive patients (median age, 56 years; 79% female; body mass index = 43±6.5 kg/m²). A history of CV disease was present in 21% of patients, mainly atrial fibrillation (7%) and coronary artery disease (10%). A total of 72 patients (23%) had elevated NT-proBNP levels, and 67 of them underwent further cardiac workup. Of these 67 patients, electrocardiography (ECG) showed atrial fibrillation in 7 patients (10%). On echocardiography, 3 patients had left ventricular ejection fraction (LVEF) <40%, 9 patients had LVEF 40%–49%, and 13 patients had LVEF ≥50% with structural and/or functional remodeling. In 2 patients, elevated NT-proBNP prompted workup leading to a diagnosis of coronary artery disease and consequent percutaneous coronary intervention in 1 patient.

Conclusions

Elevated NT-proBNP levels are present in 23% of patients 50 years and older undergoing bariatric surgery. In 37% of them, there was echocardiographic evidence for structural and/or functional remodeling. Further studies are needed to assess if these preliminary results warrant routine application of NT-proBNP to identify patients at risk for CV complications after bariatric surgery.

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This study assessed NT-proBNP as a cardiac screening tool in bariatric patients.

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Elevated NT-proBNP levels were present in 23% of patients ≥50 years.

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In 37% of them (n=25), echocardiography showed LV dysfunction or heart failure.

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NT-proBNP is a non-invasive tool that can detect new CV diseases in bariatric patients