Diagnostic and prognostic value of troponins and natriuretic peptides in syncope: a systematic review and meta-analysis

Introduction

Syncope is characterized by a sudden, short-lived loss of consciousness due to reduced blood flow to the brain, with individuals typically experiencing a quick and complete recovery without intervention (1,2). Syncope is a frequent event in the general population (3). In the United States, syncope events are prevalent, with over 1.3 million occurrences reported annually (4). Syncope is a common reason for presentations to the emergency department (ED), accounting for approximately 1.7 million ED visits in 2019 (1). Syncope can have devastating consequences, resulting in injuries, accidents or even death (5,6). Syncope can be categorized into neurocardiogenic, cardiac, and orthostatic hypotension types, with neurocardiogenic syncope being the most common and having a favorable prognosis; in contrast, cardiac syncope is associated with a higher incidence and mortality rate (7). Therefore, identifying patients at risk of cardiac syncope and predicting poor prognosis may be crucial to effective risk stratification and improvement of prognosis.

Previous studies have reported several biomarkers for syncope. Copeptin can serve as a diagnostic and prognostic biomarker in the ED for patients presenting with syncope (8,9). Patients with suspected neurocardiogenic syncope exhibit significantly different adenosine blood concentrations compared to the healthy population (10). Patients with the low adenosine phenotype of neurocardiogenic syncope exhibit low adenosine plasma levels (11). A study suggests an association between adenosine dysfunction and neuroendocrine syncope (12). Brain natriuretic peptide (BNP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) are quantitative biomarkers that reflect hemodynamic stress on the heart, released in response to elevated ventricular dimensions and pressures, often detected in conditions related to syncope (13,14). Concentrations of BNP and NT-proBNP reliably identify significant cardiac conditions and are predictive of subsequent cardiac events such as arrhythmias and mortality, applicable to individuals who appear to be healthy and to those with a diagnosed cardiac condition (15-18). High-sensitivity cardiac troponins T (hs-cTnT) and I (hs-cTnI), along with BNP and NT-proBNP, serve as critical biomarkers that can delineate cardiac dysfunction and predict adverse cardiac outcomes in syncope patients, providing essential clinical insights for risk stratification in both those with known cardiac disease and those without (19-21). At present, a systematic review has been conducted to explore the prognostic role of BNP and high-sensitivity troponin for patients with syncope (18). Another meta-analysis has assessed the predictors of short-term outcomes following syncope, and troponin was not clearly defined (4). Despite recent advances in the field, there is a notable gap in the current literature regarding a comprehensive assessment of both the diagnostic accuracy and prognostic significance of BNP, NT-proBNP, hs-cTnT, and hs-cTnI in the context of syncope evaluation.

Consequently, this systematic review and meta-analysis is designed to provide a comprehensive evaluation of the diagnostic and prognostic capabilities of BNP, NT-proBNP, hs-cTnT, and hs-cTnI in cases of syncope, aiming to enhance clinical understanding and management of syncope through these cardiac biomarkers. We present this article in accordance with the PRISMA-DTA reporting checklist (22) (available at https://cdt.amegroups.com/article/view/10.21037/cdt-24-485/rc).

Methods

Search strategy

Two independent authors conducted a comprehensive search of the literature in PubMed, Embase, the Cochrane Library, and Web of Science databases, covering all records up to June 20, 2023. Appendix 1 shows search strategies.

The inclusion criteria for this study were conducted based on PICOS principle: (I) P (Population): patients with syncope; (II) I (Intervention) and C (Comparison): studies considering biomarkers including BNP, NT-proBNP, hs-cTnT, and hs-cTnI; (III) O (Outcome): diagnostic outcomes focused on cardiac syncope. Prognostic outcomes included adverse events within a certain period after hospitalization for syncope or pre-syncope, such as all-cause mortality and severe cardiovascular events (IV) S (Study Design): prospective or retrospective cohort studies; (V) Language: English literature.

The exclusion criteria for this study were defined by the following: (I) conference abstracts, case reports, correspondence, editorials, narrative reviews, systematic reviews, and meta-analyses; (II) studies involving animal models; (III) articles that failed to supply sufficient data to determine metrics; (IV) registered studies, patent documents, conference papers, duplicate articles, and irrelevant articles.

Data collection and assessment of quality

Data extraction from the eligible studies was performed independently by two researchers and included details about the first author, year of publication, study methodology, demographic characteristics of the participants, total number of participants, average age, percentage of female participants, methods of biomarker assessment, specific biomarkers measured, their cut-off values for diagnosis, reference standards utilized, and the outcomes reported in the studies. Any inconsistencies in the data extraction process were addressed through joint discussion and consensus.

The diagnostic precision of the selected studies was appraised with the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool, designed to scrutinize the potential bias and the clinical relevance of the research findings (23). The evaluation of bias risk was conducted across four key domains: the selection of patients, the application of the index test, the utilization of the reference standard, and the sequence and timing of conducting these tests. The clinical applicability was similarly assessed based on the same trio of elements: patient selection, the index test, and the reference standard. For each criterion, a judgment was made as high risk, low risk, or unclear.

Statistical analysis

The statistical analyses for this study were performed utilizing Meta-disc 1.4. To address the heterogeneity issue in our data, we have employed the random-effect model based on the DerSimonian-Laird method. This model effectively captures unobserved effects that may influence the dependent variable, providing a more accurate representation of the data structure. The diagnostic metrics for the cardiac biomarkers were computed using Meta-disc 1.4, which enabled the calculation of sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). The software was also utilized to generate the summary receiver operating characteristic (SROC) curves. From these curves, the areas under the curve (AUCs) along with the respective 95% confidence intervals (CIs) were extracted. A strong positive correlation between the logarithm of SEN and the logarithm of (1 − SPE), as indicated by the Spearman correlation coefficient, was interpreted as evidence of a threshold effect. Subgroup analyses were conducted based on the follow-up time. The threshold for statistical significance was established at a P value of less than 0.05, based on a two-sided test.

Results

Study selection and characteristics

In total, 2,048 articles were retrieved. Following the exclusion of duplicate records, 2,041 articles advanced to the initial screening phase based on their titles and abstracts. From this pool, 98 articles were selected for further evaluation through full-text assessment. Ultimately, this analysis included 16 articles (14,15,24-37) that encompassed 12,547 subjects. The process of study selection is depicted in Figure 1. The eligible studies spanned publications from 2004 to 2023, with 13 being prospective cohort studies and 3 being retrospective in design. Table 1 details the characteristics of the included studies. The study quality assessment was summarized in Table 2. Specifically, most studies had low risk in patient selection, index test, and reference standard domains. However, some studies showed high or unclear risk in certain areas, such as the index test in Christ 2015 (25) and the reference standard in Clark 2019 (26). Overall, the studies generally demonstrated low risk in both bias and clinical applicability, ensuring the robustness of the findings.

Figure 1 Flow chart of study selection.

Diagnostic performance of the biomarkers for cardiac syncope

BNP

Three studies (14,28,36) of 1,621 subjects provided information on the diagnostic performance of BNP for cardiac syncope. The Spearman correlation coefficient for BNP was −0.500 with a P value of 0.67, suggesting no threshold effect was present. The overall SEN was 0.80, with a 95% CI from 0.75 to 0.84. The AUC was pooled at 0.86, with a 95% CI from 0.82 to 0.91, as detailed in Table 3 and illustrated in Figure 2.

Figure 2 SROC curve of BNP in the diagnosis of cardiac syncope. The central blue line indicates the overall diagnostic performance. The blue lines on either side show the 95% confidence intervals for the AUC. Red circles represent individual study data points, with size proportional to the study’s sample size. AUC, area under the curve; BNP, brain-type natriuretic peptide; SE, standard error; SROC, summary receiver operating characteristic.

NT-proBNP

The diagnostic ability of NT-proBNP for cardiac syncope was shown in four studies (14,29-31) with 2,746 individuals. The Spearman correlation coefficient for NT-proBNP was −0.400, with a P value of 0.60, indicating no significant threshold effect. The pooled SEN was 0.85, encompassing a 95% CI from 0.82 to 0.88. The AUC for NT-proBNP was pooled at 0.81, with a 95% CI from 0.63 to 0.99, as summarized in Table 3 and depicted in Figure 3.

Figure 3 SROC curve of NT-proBNP in the diagnosis of cardiac syncope. The central blue line indicates the overall diagnostic performance. The blue lines on either side show the 95% confidence intervals for the AUC. Red circles represent individual study data points, with size proportional to the study’s sample size. AUC, area under the curve; NT-proBNP, N-terminal pro-B-type natriuretic peptide; SE, standard error; SROC, summary receiver operating characteristic.

hs-cTnT

Three studies (14,25,31) involving 2,864 patients assessed the diagnostic value of hs-cTnT for cardiac syncope. The Spearman correlation coefficient for hs-cTnT was −0.500 with a P value of 0.67, suggesting the absence of a threshold effect. The pooled SEN was 0.75, within a 95% CI of 0.71 to 0.78. The AUC for hs-cTnT was pooled at 0.72, with a 95% CI from 0.54 to 0.90, as detailed in Table 3 and shown in Figure 4.

Figure 4 SROC curve of hs-cTnT in the diagnosis of cardiac syncope. The central blue line indicates the overall diagnostic performance. The blue lines on either side show the 95% confidence intervals for the AUC. Red circles represent individual study data points, with size proportional to the study’s sample size. AUC, area under the curve; hs-cTnT, high-sensitivity cardiac troponin T; SE, standard error; SROC, summary receiver operating characteristic.

hs-cTnI

The diagnostic performance of hs-cTnI for cardiac syncope was evaluated by two studies (14,29) on 1,590 patients. The SEN was 0.80, with a 95% CI of 0.75 to 0.85. The SPE was 0.64, within a 95% CI of 0.61 to 0.67. The PLR was 2.24, with a 95% CI from 2.03 to 2.47. The NLR was 0.31, with a 95% CI ranging from 0.24 to 0.40. The DOR was calculated to be 7.34, with a 95% CI of 5.26 to 10.25, as summarized in Table 3.

Predictive performance of the biomarkers for adverse outcomes

BNP

Four studies (15,27,33,34) of 1,398 subjects provided data on the predictive capability of BNP for adverse outcomes. A threshold effect was observed in this result. The pooled AUC was 0.82, with a 95% CI from 0.73 to 0.91, as detailed in Table 3 and illustrated in Figure 5. Upon subgroup analysis based on follow-up duration, different results were noted. For follow-up times of ≤1 month, the pooled SEN was 0.41, with a 95% CI from 0.32 to 0.50. The pooled SPE was 0.95, within a 95% CI of 0.93 to 0.96. The pooled PLR was 6.82, with a 95% CI from 4.79 to 9.71. The pooled NLR was 0.64, with a 95% CI from 0.55 to 0.74. The pooled DOR was 10.55, with a 95% CI of 6.56 to 16.95. For follow-up times greater than 1 month, a decrease in SPE, PLR, NLR, and DOR was observed, as indicated in Table 3.

Figure 5 SROC curve of BNP in the prediction of adverse outcomes. The central blue line indicates the overall diagnostic performance. The blue lines on either side show the 95% confidence intervals for the AUC. Red circles represent individual study data points, with size proportional to the study’s sample size. AUC, area under the curve; BNP, brain-type natriuretic peptide; SE, standard error; SROC, summary receiver operating characteristic.

NT-proBNP

The predictive ability of NT-proBNP for adverse outcomes was shown in four studies (24,26,30,32) with 7,086 individuals. The Spearman correlation coefficient for NT-proBNP was 1.000 with a P value less than 0.001, indicating a threshold effect. The pooled AUC was 0.80, with a 95% CI from 0.74 to 0.85, as detailed in Table 3 and depicted in Figure 6. For the subgroup with a follow-up of ≤1 month, the pooled SEN was 0.88, with a 95% CI from 0.85 to 0.91. For the subgroup with a follow-up of >1 month, the pooled SEN was 0.69, with a 95% CI from 0.58 to 0.78, as summarized in Table 3.

Figure 6 SROC curve of NT-proBNP in the prediction of adverse outcomes. The central blue line indicates the overall diagnostic performance. The blue lines on either side show the 95% confidence intervals for the AUC. Red circles represent individual study data points, with size proportional to the study’s sample size. AUC, area under the curve; NT-proBNP, N-terminal pro-B-type natriuretic peptide; SE, standard error; SROC, summary receiver operating characteristic.

hs-cTnT

Four studies (25,26,32,37) involving 7,370 patients assessed the predictive value of hs-cTnT for adverse outcomes. The Spearman correlation coefficient for hs-cTnT, at −0.200 with a P value of 0.80, pointed to the absence of a threshold effect. In terms of diagnostic metrics, the pooled SEN was 0.58, covering a 95% CI from 0.54 to 0.62. The SPE was at 0.71, with a 95% CI ranging from 0.70 to 0.72. The PLR was 1.95, with a 95% CI between 1.66 and 2.30. Conversely, the NLR was 0.58. The DOR was calculated to be 3.44, with a 95% CI of 2.44 to 4.85. The AUC was pooled at 0.71, with a 95% CI spanning from 0.61 to 0.80, as outlined in Table 3 and visualized in Figure 7.

Figure 7 SROC curve of hs-cTnT in the prediction of adverse outcomes. The central blue line indicates the overall diagnostic performance. The blue lines on either side show the 95% confidence intervals for the AUC. Red circles represent individual study data points, with size proportional to the study’s sample size. AUC, area under the curve; hs-cTnT, high-sensitivity cardiac troponin T; SE, standard error; SROC, summary receiver operating characteristic.

hs-cTnI

The predictive performance of hs-cTnI for adverse outcomes was evaluated by one study (35) on 528 subjects. The SEN was recorded at 0.27, with a 95% CI from 0.18 to 0.36. The SPE was 0.84, within a 95% CI of 0.79 to 0.88. The PLR was 1.64, with a 95% CI ranging from 1.06 to 2.53. The NLR was 0.87, encompassing a 95% CI from 0.76 to 1.00. The DOR was calculated to be 1.88, with a 95% CI from 1.07 to 3.30, as presented in Table 3.

Discussion

The present findings showed that BNP and NT-proBNP had good diagnostic performances for cardiac syncope, both with great SEN, and BNP and NT-proBNP exhibited good predictive capabilities for adverse outcomes in patients with syncope or pre-syncope, with BNP having high SPE and NT-proBNP having high SEN. Based on these findings, BNP and NT-proBNP may be applied in the diagnosis and prognostic assessment of syncope.

Thiruganasambandamoorthy et al. (18) evaluated the prognostic performance of contemporary troponin, BNP, and high-sensitivity troponin in the risk stratification of syncope, and found that BNP and high-sensitivity troponin had good diagnostic capabilities for cardiovascular events in adults with syncope. Gibson et al. (4) performed a meta-analysis to investigate predictive factors for serious short-term (≤30 days) outcomes among patients with syncope, and cardiac biomarkers, troponin, and BNP were identified to be associated with cardiac dysfunction in syncope. The above studies did not subdivide BNP and troponin, and the diagnostic value of specific BNP and troponin has not been studied in a comprehensive manner. Accordingly, this study incorporated the latest research findings and investigated the diagnostic and prognostic capabilities of BNP, NT-proBNP, and hs-cTnT/hs-cTnI in syncope. In terms of diagnosing cardiac syncope, both BNP and NT-proBNP showed strong diagnostic capabilities with AUCs of 0.86 and 0.81, respectively; the sensitivities for BNP and NT-proBNP were 0.80 and 0.85, respectively. BNP, which mirrors the hemodynamic stress on the heart, is secreted by the cardiac tissue in response to elevated cardiac volumes and pressures (14,38,39). Given that cardiac syncope arises from diminished cardiac output attributable to arrhythmias or structural heart diseases, BNP could be instrumental in distinguishing cardiac syncope from its non-cardiac counterparts (30). Several investigations have identified a link between increased levels of BNP and undiagnosed cardiac arrhythmias (40-42). Additionally, cardiac syncope induced by severe aortic stenosis or ventricular tachycardia is more intimately associated with the hemodynamic impact of the cardiac condition, making it more accurately predictable with the aid of biomarkers such as BNP or NT-proBNP (43-45). In terms of prognostic value, BNP and NT-proBNP demonstrated efficacy in forecasting negative outcomes in instances of syncope or near-syncope, with AUCs of 0.82 and 0.80, respectively; the SPE of BNP was 0.92, and the SEN of NT-proBNP was 0.85. Consistently, BNP was reported as a potential good prognostic marker in syncope (46). Elevated levels of NT-proBNP, as indicated by prior research, are indicative of long-term cardiac events (47-49). Syncope or near-syncope can be the initial symptom of certain heart-related conditions, indicating a higher likelihood of severe outcomes. Studies have demonstrated that increased levels of NT-proBNP are a reliable indicator of the potential for subsequent heart issues, including acute myocardial infarction, pulmonary embolism, and acute heart failure exacerbation (50-52).

Based on the findings of this meta-analysis, BNP and NT-proBNP displayed their diagnostic and prognostic significance in clinical management of syncope, which may add important diagnostic and prognostic information, help improve risk stratification of individuals, and identify patients who may need hospital admission and personalized treatment. Besides, consideration of BNP and NT-proBNP can help refine syncope assessment protocols, plan effective preventive strategies and improve patient outcomes. The application of cardiac biomarkers for prompt risk assessment in ED patients is attractive due to their quick and straightforward nature, potentially reducing the number or duration of hospital stays. Furthermore, recognizing the importance of BNP and NT-proBNP as diagnostic aids for cardiac syncope or mortality and significant cardiac events in patients experiencing syncope or near-syncope, this research supports the integration of these biomarkers into the diagnostic process for patients who present with syncope in the ED.

Our findings hold significant implications for the advancement of clinical practice and future research endeavors. First, we recommend the development of evidence-based diagnostic algorithms that incorporate BNP and NT-proBNP levels as initial screening tools for cardiac syncope in EDs and outpatient clinics. Second, future clinical practice should consider the integration of BNP and NT-proBNP into risk assessment models to predict adverse outcomes in patients presenting with syncope or pre-syncope. Third, future clinical practice should consider the integration of BNP and NT-proBNP into risk assessment models to predict adverse outcomes in patients presenting with syncope or pre-syncope. Fourth, the implementation of point-of-care testing for BNP and NT-proBNP could facilitate rapid decision-making and may be particularly beneficial in settings with limited resources or time-sensitive clinical scenarios. Fifth, given the potential for biomarker-guided management to impact healthcare resource allocation, health economics analyses should be conducted to evaluate the cost-effectiveness of implementing BNP and NT-proBNP testing in syncope management.

It is important to recognize several limitations when interpreting these results. First, one of the key limitations of our study is the variability in the definition of cardiac syncope across the included studies. The variability in the criteria for defining cardiac syncope might lead to biases and impact the comparability of the findings. While we aimed to include studies that met strict inclusion criteria, the differences in definitions reflect the diverse clinical practices and the evolving understanding of cardiac syncope within the medical community. Second, another limitation of our study is the limited number of studies available for analyzing hs-cTnT and hs-cTnI. This constraint may have influenced the statistical power of our results and the generalizability of our conclusions. Future research with larger, more diverse study populations and longitudinal data collection is needed to validate and expand upon our results. Third, the presence of a threshold effect for BNP and NT-proBNP in predicting adverse outcomes is a notable finding of our meta-analysis. This variability arises due to heterogeneity in study designs, patient demographics, and measurement methods. The variability in cut-off values complicates the interpretation of BNP and NT-proBNP and may lead to inconsistencies in clinical decision-making. The lack of a consistent cut-off value highlights the need for standardized protocols for the use of BNP and NT-proBNP in clinical practice. Fourth, the existing literature predominantly reports composite outcomes, which makes it challenging to isolate the predictive value of biomarkers for specific cardiovascular events. This limitation affects the granularity of our analysis and the precision. Future studies with more uniform outcome measures and larger sample sizes are needed to provide clearer insights.

Conclusions

BNP, NT-proBNP, and high-sensitivity troponin have demonstrated robust diagnostic accuracy for cardiac syncope and significant predictive value for adverse outcomes in patients presenting with syncope or pre-syncope. Given these findings, the incorporation of these biomarkers into the diagnostic and prognostic evaluation for syncope is warranted. Our study suggests that by leveraging these biomarkers, clinicians can enhance diagnostic precision and tailor treatment approaches, potentially leading to improved patient outcomes. However, we acknowledge the necessity for further research to determine the most effective integration of these biomarkers into clinical practice and to assess the impact on patient management and healthcare systems.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the PRISMA-DTA reporting checklist. Available at https://cdt.amegroups.com/article/view/10.21037/cdt-24-485/rc

Peer Review File: Available at https://cdt.amegroups.com/article/view/10.21037/cdt-24-485/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://cdt.amegroups.com/article/view/10.21037/cdt-24-485/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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