Performance of Copeptin for Early Diagnosis of Acute Coronary Syndromes: A Systematic Review and Meta-Analysis of 14,139 Patients

Diagnosis of acute coronary syndrome (ACS) based on copeptin level may enable one to confirm or rule-out acute myocardial infarction (AMI) with higher sensitivity and specificity, which may in turn further reduce mortality rate and decrease the economic costs of ACS treatment. We conducted a systematic review and meta-analysis to investigate the relationship between copeptin levels and type of ACS. We searched Scopus, PubMed, Web of Science, Embase, and Cochrane to locate all articles published up to 10 October 2021. We evaluated a meta-analysis with random-effects models to evaluate differences in copeptin levels. A total of 14,139 patients (4565 with ACS) were included from twenty-seven studies. Copeptin levels in AMI and non-AMI groups varied and amounted to 68.7 ± 74.7 versus 14.8 ± 19.9 pmol/L (SMD = 2.63; 95% CI: 2.02 to 3.24; p < 0.001). Copeptin levels in the AMI group was higher than in the unstable angina (UAP) group, at 51.9 ± 52.5 versus 12.8 ± 19.7 pmol/L (SMD = 1.53; 95% CI: 0.86 to 2.20; p < 0.001). Copeptin levels in ST-elevation myocardial infarction (STEMI) versus non-ST elevation myocardial infarction (NSTEMI) patient groups were 54.8 ± 53.0 versus 28.7 ± 46.8 pmol/L, respectively (SMD = 1.69; 95% CI: = 0.70 to 4.09; p = 0.17). In summary, elevated copeptin levels were observed in patients with ACS compared with patients without ACS. Given its clinical value, copeptin levels may be included in the assessment of patients with ACS as well as for the initial differentiation of ACS.


Introduction
Acute coronary syndromes (ACS) represent the leading cause of morbidity and mortality worldwide [1] and although the relative incidences of ST-elevation myocardial infarction (STEMI) and non-ST elevation myocardial infarction (NSTEMI) are decreasing

Search Strategy
We search evidence up to 10 October 2021 in the following databases: Scopus, PubMed, Web of Science, Embase, and Cochrane. The search was conducted using the following terms: "copeptin" OR "copeptins" OR "Glycopeptides" OR "Glycopeptide" OR "Cterminal provasopressin" AND "acute myocardial infarction" OR "AMI" OR "myocardial infarction" OR "MI" OR "STEMI" OR "ST-Elevation" OR "non-ST segment elevation" OR "NSTEMI" OR "ACS" OR "acute coronary syndrome". All references were saved in an EndNote (End Note, Inc, Philadelphia, PA) library used to identify the duplicates. We did not limit the search by language or publication date. We also manually searched the reference list of identified trials for other potentially eligible studies.

Inclusion Criteria
Studies included in this meta-analysis met the following PICOS criteria: (1) PARTICI-PANTS, patients > 18 years of age; (2) INTERVENTION, patients with AMI; (3) COMPAR-ISON, patients without AMI; (4) OUTCOMES, detailed information for copeptin levels; and (5) STUDY DESIGN, randomized controlled trials or observational studies comparing copeptin levels in patients with and without AMI or comparing copeptin levels in patients with different AMI groups.
This review excluded the following types of studies: (1) papers not containing a comparator group; (2) conference or poster papers; (3) reviews; (4) case reports; and (5) articles not containing original data.

Data Extraction
Two authors (L.S. and S.B.) independently reviewed the selected trials and extracted the data of interest. The extraction of data was performed using a pre-piloted Microsoft Excel sheet. We were careful to avoid including data from duplicate publications. In the case of suspected data discrepancies, we contacted the relevant corresponding author directly. Data extracted from eligible trials included the following parameters: (1) study characteristics (i.e., first author's name, year of publication, study location, study design, inclusion and exclusion criteria, and primary findings); (2) participant characteristics in each group (i.e., number of participants, age, sex, comorbidities, and copeptin levels). All detailed information was checked by a third author (L.K.), with disagreements resolved by discussion and consensus.

Quality Assessment
A systematic assessment of bias in the included studies was performed using the Cochrane criteria [16,17]. For this purpose, a tool for Risk Of Bias In Non-randomized Studies-of Interventions (ROBINS-I) [18] was used. ROBINS-I examines seven domains of bias owing to the following: (1) confounding; (2) selection of participants; (3) the classification of interventions; (4) deviations from intended interventions; (5) missing data; (6) measurement of outcomes; and (7) the selection of the reported result. The overall ROBINS-I judgment at domain and study level was attributed to the criteria specified in the ROBVIS tool [19]. The risk of bias (RoB) was performed independently by three reviewers (A.G., L.K., and M.L.); disagreements were resolved by a third reviewer (L.S.) if necessary.

Statistical Analysis
All analyses were performed using Cochranre Review Manager (ver. 5.4, Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen, Denmark). The Mantel-Haenszel method was used to analyze dichotomous outcomes, and results are reported as odds ratios (ORs) or risk ratios (RRs) with a 95% confidence interval (CI). Continuous outcome differences were analyzed using an inverse variance model with a 95% CI, and values are reported as mean difference (MD). When the continuous outcome was reported in a study as median, range, and interquartile range, we estimated means and standard deviations using the formula described by Hozo et al. [16].
We quantified heterogeneity in each analysis by the tau-squared and I-squared statistics. Heterogeneity was detected with the chi-squared test with n − 1 degree of freedom, which was expressed as I 2 . Values of I 2 >50% and >75% were considered to indicate moderate and significant heterogeneity among studies, respectively. A random-effects model was used to pool study results independently of the p-value for heterogeneity or I 2 [17]. All p-values were two-tailed and considered significant if <0.05.

Study Selection
Among the included trials, the mean age of patients with and without ACS varied and amounted to 66.1 ± 10.4 versus 62.2 ± 12.7 years, respectively. Males accounted for 71.5% of patients in the ACS group compared with 59.3% in the patients without ACS group. The details of the included studies are summarized in Tables 1 and S1.   Among the included trials, the mean age of patients with and without ACS varied and amounted to 66.1 ± 10.4 versus 62.2 ± 12.7 years, respectively. Males accounted for 71.5% of patients in the ACS group compared with 59.3% in the patients without ACS group. The details of the included studies are summarized in Table 1 and Table S1.

Discussion
According to our study, copeptin assessment is a strong diagnostic tool in patients with AMI thanks to its high negative predictive value (NPV). Ruling out healthy individuals reporting at least chest pain may increase the efficacy of work in the emergency department. However, it was found that a combination of copeptin and hs-cTnT is even more sensitive to rule out NSTEMI, compared with both of those markers tested independently [41]. It was also shown that the double-testing approach has an excellent NPV for short-term risk stratification, and such a strategy is able to improve a triage system in an emergency department. Other authors also showed that copeptin measurement alone exhibits inferior results towards its combination with either N-terminal pro b-type natriuretic peptide (NT-proBNP) or troponin. Although, according to the latest ESC Guidelines, routine measurement of additional biomarkers for diagnostic purposes is not recommended, and assessment of copeptin may add a substantial value to (less sensitive) cardiac troponin [31,47]. Copeptin could be used as a marker to diagnose AMI, but so far, further studies are required to evaluate its potential superiority over the currently available markers of AMI. Three studies [22,29,42] reported copeptin levels in STEMI versus NSTEMI patient groups, which were 54.8 ± 53.0 versus 28.7 ± 46.8 pmol/L (SMD = 1.69; 95% CI: = 0.70 to 4.09; I 2 = 98%; p = 0.17; Figure 4). Three studies [22,29,42] reported copeptin levels in STEMI versus NSTEMI patient groups, which were 54.8 ± 53.0 versus 28.7 ± 46.8 pmol/L (SMD = 1.69; 95%CI: = 0.70 to 4.09; I 2 = 98%; p = 0.17; Figure 4).

Discussion
According to our study, copeptin assessment is a strong diagnostic tool in patients with AMI thanks to its high negative predictive value (NPV). Ruling out healthy individuals reporting at least chest pain may increase the efficacy of work in the emergency department. However, it was found that a combination of copeptin and hs-cTnT is even more sensitive to rule out NSTEMI, compared with both of those markers tested independently [41]. It was also shown that the double-testing approach has an excellent NPV for short-term risk stratification, and such a strategy is able to improve a triage system in an emergency department. Other authors also showed that copeptin measurement alone exhibits inferior results towards its combination with either N-terminal pro b-type natriuretic peptide (NT-proBNP) or troponin. Although, according to the latest ESC Guidelines, routine measurement of additional biomarkers for diagnostic purposes is not recommended, and assessment of copeptin may add a substantial value to (less sensitive) cardiac troponin [31,47]. Copeptin could be used as a marker to diagnose AMI, but so far, further studies are required to evaluate its potential superiority over the currently available markers of AMI.

Discussion
According to our study, copeptin assessment is a strong diagnostic tool in patients with AMI thanks to its high negative predictive value (NPV). Ruling out healthy individuals reporting at least chest pain may increase the efficacy of work in the emergency department. However, it was found that a combination of copeptin and hs-cTnT is even more sensitive to rule out NSTEMI, compared with both of those markers tested independently [41]. It was also shown that the double-testing approach has an excellent NPV for short-term risk stratification, and such a strategy is able to improve a triage system in an emergency department. Other authors also showed that copeptin measurement alone exhibits inferior results towards its combination with either N-terminal pro b-type natriuretic peptide (NT-proBNP) or troponin. Although, according to the latest ESC Guidelines, routine measurement of additional biomarkers for diagnostic purposes is not recommended, and assessment of copeptin may add a substantial value to (less sensitive) cardiac troponin [31,47]. Copeptin could be used as a marker to diagnose AMI, but so far, further studies are required to evaluate its potential superiority over the currently available markers of AMI.
In addition to the diagnostic role of copeptin, it acts as a mortality predictor after AMI. In an analysis of 926 patients with AMI, a significant association between the copeptin level and the risk of mortality was found, independently from cortisol and NT-proBNP measurements [44]. Three studies reported a higher level of copeptin in patients with the STEMI compared with the NSTEMI group. That may suggest a positive correlation of copeptin serum concentration with AMI severity. Moreover, the lack of necessity of serial blood sampling is highlighted by some authors [48]. Not only would it reduce the total cost of diagnostic procedures, but also it enables to obviate prolonged monitoring and thus improve the pace of medical care service. Copeptin has been demonstrated to present an acceptable prognostic value for mortality in patients with ACS, but this finding has to be confirmed in a larger multi-marker strategy to evaluate the prognostic value of copeptin for ACS in conjunction and comparison with other well-established biomarkers [44,49].
However, there are some data undermining copeptin utility in the diagnostic path. In some research, it was proved that copeptin measurement substantially does not improve the early diagnosis of AMI and, referring to another study, its accuracy was moderate and inferior to that of hs-cTnT [24,45].
We acknowledge some limitations of our study. Firstly, because of significant heterogeneity of gathered data, it is hard to determine whether the "non-AMI" group was formed by patients suffering from unstable angina, people reporting chest pain at the admission, or healthy individuals. Secondly, the cut-offs for elevated copeptin concentrations differed per study. Therefore, the value of copeptin level in this cohort may be debatable. On this account, it is hard to determine the role of diagnostic and prognostic role of copeptin in AMI. Whereas it seems to be a useful tool, too few data are currently available to classify it as a standard of care, self-sufficient biomarker of AMI. Thereby, further multicenter randomized control trials should be conducted to draw final conclusions.

Conclusions
Elevated copeptin levels were observed in patients with ACS compared with patients without ACS. Given its clinical value, copeptin levels may be included in the assessment of patients with ACS as well as for the initial differentiation of ACS.