Prognostic value of preoperative N-terminal pro-brain natriuretic peptide in non-cardiac surgery of elderly patients with normal left ventricular systolic function

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 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.

The Influence of Perioperative Fluid Therapy on N-terminal-pro-brain Natriuretic Peptide and the Association With Heart and Lung Complications in Patients Undergoing Colorectal Surgery: Secondary Results of a Clinical Randomized Assessor-blinded Multicenter Trial

OBJECTIVE

To investigate the influence of intravenous (iv) fluid volumes on the secretion of N-terminal-pro-brain natriuretic peptide (NT-Pro-BNP) in colorectal surgical patients and its association with cardiopulmonary complications (CPC). In addition, to examine if preoperative NT-Pro-BNP can predict the risk for postoperative CPC.

METHODS

Blood samples from patients enrolled in a previously published clinical randomized assessor-blinded multicenter trial were analyzed. Included were adult patients undergoing elective colorectal surgery with the American-Society-of-Anesthesiologists-scores of 1-3. Samples from 135 patients were available for analysis. Patients were allocated to either a restrictive (R-group) or a standard (S-group) iv-fluid regimen, commencing preoperatively and continuing until discharge. Blood was sampled every morning until the fourth postoperative day. The primary outcome for this study was NT-Pro-BNP changes and its association with fluid therapy and CPC.

RESULTS

The S-group received more iv-fluid than the R-group on the day-of-surgery [milliliter, median (range) 6485 (4401-10750) vs 3730 (2250-8510); P < 0.001] and on the first postoperative day. NT-Pro-BNP was elevated in the S-group compared with the R-group on all postoperative days [area under the curve: median (interquartile range) pg/mL: 3285 (1697-6179) vs 1290 (758-3719); P < 0.001 and in patients developing CPC vs no-CPC (area under the curve), median (interquartile range): 5196 (1823-9061) vs 1934 (831-5301); P = 0.005]. NT-pro-BNP increased with increasing fluid volumes all days (P < 0.003). Preoperative NT-Pro-BNP predicted CPC [odds ratio (confidence interval): 1.573 (0.973-2.541), P = 0.032; positive predictive value = 0.257, negative predictive value = 0.929].

CONCLUSIONS

NT-pro-BNP increases with iv-fluid volumes given to colorectal surgical patients, and the level of NT-Pro-BNP is associated with CPC. Preoperative NT-Pro-BNP is predictive for CPC, but the diagnostic value is low.Clinicaltrials.gov NCT03537989.

Cardiac Biomarkers Predicting MACE in Patients Undergoing Noncardiac Surgery: A Meta-Analysis

Objective: The present meta-analysis was aimed to systematically evaluate the effectiveness and accuracy of brain natriuretic peptide (BNP), cardiac troponin (cTn), high sensitive C reactive protein (hs-CRP) and CRP for predicting postoperative major adverse cardiovascular events (MACE) in patients undergoing noncardiac surgery.

Methods: A total of 26 relevant studies with 7,877 participants were collected from five databases, namely PubMed, Embase, China National Knowledge Infrastructure (CNKI), CQVIP and the Wanfang Database until August 10, 2018. And the Review Manager Version 5.3 and Stata/SE 12 software were used for data syntheses in the meta-analysis.

Results: Strong relationships of BNP/NT-proBNP, cTnI/cTnT and hs-CRP with MACE were detected in patients undergoing noncardiac surgery, and the five biomarkers all increased the risk of MACE. Compared to normal levels, elevated BNP/NT-proBNP could increase the MACE risk by almost 4-fold [RR:3.92, 95%CI: 3.23–4.75, P < 0.001]; elevated BNP corresponded to a 4.5-fold risk [RR:4.57, 95%CI: 3.37–6.20, P < 0.001]; elevated NT-proBNP led to a 3-fold higher risk [RR:3.48, 95%CI: 2.71–4.46, P < 0.001]. Comparing with normal levels of cTnI/cTnT, increased cTnI/cTnT was associated with nearly 5-fold more higher risk of MACE [RR:5.52, 95%CI: 4.62–6.58, P < 0.001]; elevated cTnI faced a 5-fold risk [RR:5.21, 95%CI: 3.96–6.86, P < 0.001]; elevated cTnT resulted in nearly 6-fold higher risk [RR:5.73, 95%CI: 4.55–7.22, P < 0.001]. The elevation of hs-CRP was associated with nearly 4-fold higher risk of MACE in comparison with normal concentration [RR:3.73, 95%CI: 2.63–5.30, P < 0.001].

Conclusion: According to the results of our meta-analysis, the elevations of BNP/NT-proBNP, cTnI/cTnT, and hs-CRP, pre-operation or post-operation immediately, can predict much higher risk of postoperative MACE in patients undergoing noncardiac surgery.

Postoperative Adverse Cardiovascular Events Associated with Leptin and Adverse Age After Elective Major Non-Cardiac Surgery: An Asian Single-Center Study

BACKGROUND The postoperative adverse cardiovascular events (PACE) after surgery can result in prolonged length of stay and poorer prognosis. The purpose of this Asian single-center study was to investigate the potential predicative role of leptin for PACE in elderly patients undergoing major non-cardiac surgery. MATERIAL AND METHODS The patients in the study were prospectively recruited from a series of elderly patients (≥60 years) undergoing elective major non-cardiac surgery (≥2 hours) in our hospital from June 2013 to June, 2016. The demographic and clinical data and the preoperative serum biomarkers of each participant were recorded in details. Suspected PACE were assessed by the same experienced expert based on clinical, blood, and other accessory tests. The univariate and multiple logistic regression analyses were plotted to evaluate the potential independent predictive factors for PACE. RESULTS A total of 270 elderly patients (145 males and 125 females), undergoing major elective non-cardiac surgery, were finally enrolled in this study. Older age, higher revised cardiac risk index score, higher levels of systolic blood pressure, B-type natriuretic peptide and leptin, the preoperative medication of beta blocker and lipid-lowering agents were positive predictors of PACE by univariate analyses (p<0.05). Our results indicated that preoperative leptin level (OR 1.84, 95% CI 1.08-3.42; p=0.015) and advanced age (OR 0.24, 95% CI 0.09-0.94; p=0.041) were significantly associated with the occurrence of PACE by multiple logistic regression analyses. CONCLUSIONS Preoperative serum leptin level and advanced age were two independent risk factors for PACE among elderly patients undergoing elective major non-cardiac surgery.