The CHA2DS2-VASC Score Predicts Mortality in Patients Undergoing Coronary Angiography
by
Nicholay Teodorovich
1,*,
Gera Gandelman
1,
Michael Jonas
1,
Yakov Fabrikant
1,
Michael Sraia Swissa
2,
Sara Shimoni
1,
Jacob George
1 and
Moshe Swissa
1 1
Kaplan Medical Center, Rehovot and the Hebrew University, Jerusalem 7661041, Israel
2
Shari-Zedek Medical Center, and the Hebrew University, Jerusalem 9103102, Israel
*
Author to whom correspondence should be addressed.
Life 2023, 13(10), 2026; https://doi.org/10.3390/life13102026
Submission received: 1 September 2023
/
Revised: 24 September 2023
/
Accepted: 26 September 2023
/
Published: 9 October 2023
(This article belongs to the Special Issue Coronary Artery Disease from Pathogenetic Mechanisms to Postoperative Prognosis Research)
Abstract
:Background: The CHA2DS2-VASC score is used to predict the risk of thromboembolic complications in patients with atrial fibrillation (AF). We hypothesized that the CHA2DS2-VASC score can be used to predict mortality in patients undergoing coronary angiography. Methods and Results: This was a prospective study of 990 patients undergoing coronary angiography. The median follow-up was 2294 days. The patients were categorized into two groups according to their CHA2DS2-VASC score: group I had scores <4 and group II had scores ≥4 (527 (53.2%) and 463 (46.8%), respectively). A Kaplan–Meier analysis demonstrated a significant association between the CHA2DS2-VASC score and mortality (69/527 (13.1%) vs. 179/463 (38.7%) for group I vs. group II, respectively, p < 0.0001). The association remained significant in patients with and without AF, reduced and preserved LVEF, normal and reduced kidney function, and with and without ACS (p < 0.009 to p < 0.0001 for all). In the Cox regression model, which combined the CHA2DS2-VASC score, the presence of AF, LVEF, anemia, and renal insufficiency, an elevated CHA2DS2-VASC score of ≥4 was independently associated with higher mortality (HR 2.12, CI 1.29–3.25, p = 0.001). Conclusions: The CHA2DS2VASC score is a simple and reliable mortality predictor in patients undergoing coronary angiography and should be used for the initial screening for such patients.
1. Introduction
The CHA2DS2-VASC score was developed to predict the probability of stroke in patients with atrial fibrillation and guide their anticoagulation therapy [1,2,3]. It represents a refinement of the previously used CHADS2 score, providing superior risk stratification [2]. Recently, the use of CHA2DS2-VASC has expanded and was demonstrated to predict the development of atrial fibrillation [4,5], left atrial dysfunction [6], ablation outcomes [7], estimate stroke severity [8,9] and its mechanism [10], and predict the occurrence of stroke in patients without atrial fibrillation [11,12,13,14]. CHA2DS2-VASC also correlates with the presence of the coronary artery disease [15,16,17], pulmonary embolism [18], and mortality [14,19,20,21,22,23,24,25]. In patients with established coronary artery disease, the CHA2DS2-VASC score has been demonstrated to predict the development of atrial fibrillation [26,27,28], ischemic severity [29,30], and stroke [27,31,32,33,34]. CHA2DS2-VASC also been shown to estimate the prognosis and predict the mortality of these patients [34,35,36,37,38,39,40,41]. However, almost all studies were done on patients with acute coronary syndromes. There is a paucity of data considering the usefulness of the CHA2DS2-VASC score to predict mortality in patients with the coronary artery disease in a nonurgent setting.
We hypothesized that the CHA2DS2-VASC score can be a useful tool to predict mortality in patients undergoing coronary angiography in both urgent (i.e., ACS) and elective scenarios.
2. Materials and Methods
This is a single center prospective observational study of 990 consecutive patients who underwent coronary angiography at the Kaplan Medical Center, Rehovot, Israel. The data were collected from the patients and their medical records at the time of admission. Informed consent was obtained from all patients. The computerized records and the national population registry database were used in the follow-up. The data included age, sex, coronary risk factors, detailed history of coronary artery disease, presence of atrial fibrillation, presence of heart failure, previous stroke and PVD, laboratory and echocardiographic data, indication for coronary angiography, its result, and the details of the intervention, among others.
Baseline patient clinical characteristics and procedural data were compared between patients in the two groups, according to the CHA2DS2-VASC score. The chi-square test was used for dichotomous variables, and an independent t-test was used for continuous variables. Data are expressed as the mean ± SD or frequency and percentage when appropriate. The correlation of the ascending (0–9) values of the CHA2DS2-VASC score with mortality was determined with the chi-square test, and the optimal cutoff value of the CHA2DS2-VASC score for mortality prediction was done with c-statistics. Cumulative event proportions were calculated by the Kaplan–Meier method, and the outcome differences of the two CHA2DS2-VASC groups were assessed with the log-rank test. Cox regression was utilized to access the independent value of the CHA2DS2-VASC score for mortality prediction. The covariates included in the multivariate model were identified using candidate variables that were predictive of the endpoint in the univariate analysis and were unbalanced between the two groups. The individual components of the CHA2DS2-VASC score were omitted from the multivariate model. A p-value <0.05 was considered significant. After analysis of the whole patient population, a Kaplan–Meier survival analysis was used to assess the survival in the specific subgroups of patients according to the presence or absence of AF, CHF, ACS, or CKD. Data were analyzed using SPSS statistical software version 21 and Medcalc version 17.5.5.3.
3. Results
Nine hundred and ninety consecutive patients undergoing coronary angiography electively or for acute coronary syndromes were followed up for a median of 2294 days. The distribution of the CHA2DS2-VASC scores is shown in Table 1. The mean CHADSVASC score was 3.35 ± 1.71, and the median was 3.0. Due to the low number of patients with CHA2DS2-VASC scores of 8 and 9, we combined the patients with scores 7 and above into one group. Mortality increased with the increasing CHA2DS2-VASC scores up to 6, with a similar rate in patients with scores 7+.
After Bonferroni correction, a significant (p < 0.05) difference in mortality was observed between CHA2DS2-VASC scores in the 0–3, 4, and 5–7 groups. All individual components of the CHA2DS2-VASC score, apart from previous stroke, were significantly associated with mortality (Table 2). In the multivariate analysis, all individual components of the CHA2DS2-VASC score, besides gender and previous stroke, were significantly associated with mortality.
C statistics demonstrated the superiority of the CHA2DS2VASC score of 4 vs. 3 or 5 as the optimal cutoff for mortality prediction with an AUC = 0.67 (shown in Figure 1).
Based on that data, we divided the patients into two groups, according to their CHA2DS2-VASC scores (<4 and equal or ≥4). Patients with CHA2DS2-VASC scores < 4 were younger, had a lower incidence of prior coronary or vascular disease, and better renal function. They were less likely to have atrial fibrillation, obstructive CAD, and calcified lesions on their coronary angiography. The two groups were not significantly different in left ventricular function and acute coronary syndrome (ACS) as an indication for a coronary angiogram. The patients with CHA2DS2-VASC ≥ 4 had three-fold higher mortality than the patients in group I. The details of the differences between the groups are shown in Table 3.
A univariate analysis demonstrated a significant association of the elevated CHA2DS2-VASC score with mortality. Increased mortality was also associated with elevated age, the presence of hypertension, diabetes, heart failure, peripheral vascular disease, atrial fibrillation, renal failure, coronary artery calcification, decreased ejection fraction, significant diastolic dysfunction (elevated filling pressure), aortic stenosis, and anemia. Of note, the history of the myocardial infarction, previous PCI or CABG, acute coronary syndrome as a reason for coronary angiography, and the presence of obstructive coronary artery disease were not associated with increased mortality. A detailed description of the association of different demographic, clinical, laboratory, and angiographic variables with mortality is shown in Table 4.
The Kaplan–Meier analysis demonstrated a significant association (p < 0.0001) between the CHA2DS2-VASC score and mortality in general and when divided as CHA2DS2-VASC scores <4 vs. CHA2DS2-VASC scores ≥4: 69/527 (13.1%) vs. 179/463 (38.7%), respectively, p < 0.0001, as shown in Figure 2A,B).
In the Cox regression model, which combined the CHA2DS2-VASC score, presence of AF, LVEF, anemia, presence of aortic stenosis, and decreased GFR (<60 mL/min), an elevated CHA2DS2-VASC score of ≥4 was independently associated with higher mortality (hazard ratio 2.14, CI 1.40–3.256, p = <0.0001, as shown in Table 5).
Subgroup Analysis
We applied the Kaplan–Meier survival analysis to the different subgroups of the initial study cohort. The association between the CHA2DS2-VASC score (<4 vs. ≥4) and mortality remained significant in patients with and without AF (p < 0.009 and p < 0.0001, respectively), as shown in Figure 3A, with reduced and preserved LVEF (p < 0.0001 and p = 0.001, respectively), as shown in Figure 3B, normal and reduced GFR (p = 0.002 and p < 0.0001, respectively), as shown in Figure 3C, with and without ACS (p < 0.0001 for both groups), as shown in Figure 3D, and with nonobstructive and obstructive CAD on their coronary angiography (p < 0.0001 for both groups), as shown in Figure 3E.
Also, when the previously described Cox regression model (CHA2DS2-VASC score, presence of AF, LVEF, aortic stenosis, anemia, and presence of reduced GFR) was applied to the same groups, elevated CHA2DS2VASC scores of ≥4 were independently associated with higher mortality in most of the defined subgroups (shown in Table 6).
To further examine the usefulness of the CHA2DS2-VASC score for mortality prediction in this group of patients, we compared it with the CHADS2 score and also with two scoring models, which, in addition to the CHA2DS2-VASC score components, used the presence of atrial fibrillation and renal failure (shown to be independent predictors of mortality in these patients). The CHA2DS2-VASCAR score had two additional points for the presence of AF and renal failure (creatinine above 1.1 mg/dL), whereas the CHA2DS2-VASCAR2 score gave an additional point to severe renal failure (creatinine above 2.0 mg/dL). The distribution of mortality according to these scores is shown in Table 7. According to this data, the cutoff values of these scores to discriminate between low and high mortality were 2 for the CHADS2 score vs. 4 for the CHA2DS2-VASCAR and CHA2DS2-VASCAR2 scores (Table 7D).
The comparison of the ROC curves using the DeLonge method demonstrated that the CHADS2 score performed numerically less well than the other scores, with lower c-statistics almost reaching statistical significance. There was no difference between the CHA2DS2-VASC, CHA2DS2-VASCAR, and CHA2DS2-VASCAR2 scores in the predictive capability (Figure 4).
4. Discussion
The major findings in our study are:
- There was an independent association between increased CHA2DS2-VASC scores and mortality in patients undergoing coronary angiography.
- This association was present across multiple subgroups of patients with different clinical characteristics.
Although CHADS2 and CHA2DS2-VASC scores were initially developed to predict stroke in patients with atrial fibrillation [1,2,3], they were later used to predict multiple cardiovascular outcomes in different categories of patients [7,8,11,12,13,14,18,19,20,21,23,25,26,27,29,30,31,34,35,36,37,38,39,40,41,42].
In our study, a higher (≥4) CHA2DS2-VASC score was associated with more significant obstructive coronary artery disease, both in frequency (68.0% vs. 47.6%) and severity (3 vessel CAD present in 44.2% vs. 23.3%). Coronary calcification was also much more frequent in patients with higher scores (31.9% vs. 13.9%). Similar findings were reported by Uysal et al. [29] in STEMI patients and by Cetin et al. [30] in patients who underwent coronary angiography. We used the presence of obstructive CAD and 3-Vessel CAD as markers of significant atherosclerotic coronary disease, because both Gensini and Synthax scores, used by Cetin et al. [30] and Uysal et al. [29], are rarely used in routine clinical practice.
The most important finding of our study was the ability of the CHA2DS2-VASC score to predict mortality in a real-life patient population undergoing coronary angiography, as demonstrated by the survival Kaplan–Meier analysis.
Unlike Uysal et al. [29] and Cetin et al. [30], who used modified scores, we used unmodified CHA2DS2-VASC scores for our analysis due to its widespread acceptance and convenience. There was a linear association between the CHA2DS2-VASC score and mortality from 0 to 6–7 and above. After determining the optimal cutoff value (≥4), its c-statistics (0.670) was better than cited by Puurunen et al. [36] and similar to that of Chan et al. [11]. Additionally, the CHA2DS2-VASC score performs similar to other scores, such as Gensini (AOC = 0.63–0.67) [42] and SYNTAX scores (AOC = 0.62–0.67) [43,44], even when used with clinical and biomarker enhancements. It also performed similar to GRACE (AOC = 0.69) [45] and better than TIMI scores (AOC = 0.52) [44]. This was also demonstrated in the study by Huahg et al. [46]. This further validates the use of CHA2DS2-VASC scores for mortality prediction.
The multivariate analysis done with the Cox regression model demonstrated that the CHA2DS2-VASC score was associated with a two-fold increase in mortality independent from renal function, LVEF, anemia, aortic stenosis, the presence of acute coronary syndrome, obstructive CAD, and atrial fibrillation.
Several studies have previously demonstrated the prognostic value of CHADS2 and/or CHA2DS2-VASC scores in predicting mortality and MACE in patients with CAD. Most of them [34,35,38,40] studied patients with acute coronary syndrome; however, others included nonurgent patients undergoing coronary angiography or outpatients [11,36,43]. Some studies included only patients with atrial fibrillation [36], some without AF [11], and others demonstrated the values of the CHADS2 and CHA2DS2-VASC scores in all patients [29,35,38,40]. Crandall et al. [43] and Poçi et al. [34] demonstrated the prognostic value of the CHADS2 score separately for both groups of patients (with and without AF). Our Kaplan–Meier analysis demonstrated that the same is true for the CHA2DS2-VASC score. However, in our study, beyond demonstrating the usefulness of the CHA2DS2-VASC score to predict mortality in both patients with and without atrial fibrillation, the Kaplan–Meier analysis demonstrated the impact of the CHA2DS2-VASC score as a predictor of mortality in different categories of patients, i.e., normal vs. reduced LVEF, with ACS vs. elective coronary angiography, with normal or reduced kidney function, and with and without obstructive coronary artery disease. This demonstrated the applicability of the CHA2DS2-VASC score in mortality prediction.
We also demonstrated that modification of the CHA2DS2-VASC score to include renal failure (CHA2DS2-VASCR and CHA2DS2-VASCR2) does not provide superior results in terms of the effective discrimination between patients with an increased vs. not increased risk of mortality. Such scores are cumbersome to calculate and not more useful than the familiar CHA2DS2-VASC score. This was also similar to the results of the study by study by Huahg et al. [46], where similar R2CHA2DS2-VASC scores were developed, but the discriminative capability to predict mortality was similar to CHA2DS2-VASC scores. It should be noted, however, that the mean CHADSVASC score was much lower in the patients studied by Huang [46] than in our study (2.4 vs. 3.4). Our study demonstrated that the CHA2DS2-VASC score is useful in predicting mortality in sicker and older patients.
The multivariate analysis performed in these subgroups demonstrated independent predictions of mortality in all subgroups, apart from patients with preserved LVEF, AF, and the absence of obstructive CAD (even there, a trend was demonstrated, which would probably have reached significance with a larger number of patients).
In summary, our results demonstrate that CHA2DS2-VASC scores done before coronary angiography can reliably predict mortality in diverse categories of patients. Although other risk score models (like Gensini and GRACE) have been developed to predict outcomes in patients with MI, the advantage of the CHA2DS2-VASC score is its simplicity to calculate. Moreover, the CHA2DS2-VASC score is useful not only in AMI but also in elective coronary angiography patients. The CHA2DS2-VASC score is an attractive tool for prognosis prediction in patients undergoing coronary angiography due to its simplicity, its good predictive capability, and its applicability in many different subgroups of patients.
Limitations
First of all, this is a single center observational study with an inherent selection bias. Secondly, only a limited number of patients were involved in this registry. Additionally, the population registry database used to assess survival did not state the diagnosis or whether the death was from cardiac or noncardiac cause.
5. Conclusions
The CHA2DS2-VASC score can be used as a reliable mortality predictor in patients undergoing coronary angiography. Its prediction is valid in patients with and without atrial fibrillation, preserved and reduced left ventricular function, with and without renal failure, and in both elective and urgent angiography.
Author Contributions
N.T., G.G., Y.F. and M.S.S. were involved with data acquisition; M.J., G.G. and J.G. contributed to the conception and design of the work; N.T. did the original draft and, together with M.S.S., the data analysis; N.T., M.S., S.S. and J.G. were involved in the data interpretation and draft revising; and M.S. and J.G. were involved in the final approval. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the Kaplan Medical Center in 2010, approval number 109-10.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The data were securely preserved on a dedicated server at the Kaplan Medical Center. According to the Clalit HMO policy, the release of data to a third party is restricted. Denominated data might be provided to a third party (i.e., editors and reviewers) after obtaining permission from the legal department of the medical center.
Conflicts of Interest
The authors declare no conflict of interest.
Abbreviations
ACS: acute coronary syndrome; AF: atrial fibrillation; CHF: chronic heart failure; CKD: chronic kidney disease; LVEF: Left ventricular ejection fraction; PVD: peripheral vascular disease; GFR: glomerular filtration rate; CAD: coronary artery disease.
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Figure 1.
Predictive probability of mortality of CHA2DS2-VASC scores of 3, 4, and 5.
Figure 2.
(A) Kaplan–Meier survival analysis according to the CHA2DS2-VASC score. (B) Kaplan–Meier survival analysis according to CHA2DS2-VASC scores < or ≥4.
Figure 2.
(A) Kaplan–Meier survival analysis according to the CHA2DS2-VASC score. (B) Kaplan–Meier survival analysis according to CHA2DS2-VASC scores < or ≥4.
Figure 3.
Kaplan–Meier survival analysis according to CHA2DS2-VASC scores < 4 or ≥4. (A) Patients with and without AF. (B) Patients with preserved and reduced LVEF. (C) Patients with normal and reduced kidney function. (D) Patients with and without acute coronary syndrome. (E) Patients with and without obstructive CAD on their coronary angiography.
Figure 3.
Kaplan–Meier survival analysis according to CHA2DS2-VASC scores < 4 or ≥4. (A) Patients with and without AF. (B) Patients with preserved and reduced LVEF. (C) Patients with normal and reduced kidney function. (D) Patients with and without acute coronary syndrome. (E) Patients with and without obstructive CAD on their coronary angiography.
Figure 4.
Comparison of the ROC curves of the predictive probability of mortality of the CHA2DS2, CHA2DS2-VASC, CHA2DS2-VASCAR, and CHA2DS2-VASCAR2 scores.
Figure 4.
Comparison of the ROC curves of the predictive probability of mortality of the CHA2DS2, CHA2DS2-VASC, CHA2DS2-VASCAR, and CHA2DS2-VASCAR2 scores.
Table 1.
Distribution of patients according to their CHA2DS2-VASC scores.
| CHA2DS2-VASC Score | # of Patients | Percent | Mortality (%) |
|---|---|---|---|
| 0 | 37 | 3.7 | 5.4 |
| 1 | 115 | 11.6 | 7.8 |
| 2 | 176 | 17.8 | 13.6 |
| 3 | 199 | 20.1 | 16.6 |
| 4 | 206 | 20.8 | 33.5 |
| 5 | 150 | 15.2 | 42.0 |
| 6 | 78 | 7.9 | 44.9 |
| 7+ | 29 | 2.9 | 44.8 |
| Total | 990 | 100 | 25.1 |
p-value < 0.001.
Table 2.
Effect of individual components of the CHA2DS2-VASC score on mortality.
| Variable | Mortality If Absent (%) | Mortality If Present (%) | p-Value |
|---|---|---|---|
| Age ≥ 65 | 4.3 | 17.9 | <0.0001 |
| Age ≥ 75 | 8.0 | 23.1 | <0.0001 |
| Female Gender | 11.2 | 16.8 | 0.011 |
| HTN | 5.9 | 15.3 | <0.0001 |
| DM | 9.8 | 17.0 | <0.0001 |
| Vascular Disease | 9.7 | 15.0 | 0.009 |
| CHF | 10.0 | 29.9 | <0.0001 |
| Previous stroke | 12.3 | 18.1 | 0.082 |
Abbreviations: HTN: hypertension, DM: diabetes mellitus, and CHF: chronic heart failure.
Table 3.
Baseline patient characteristics according to the CHA2DS2VASC scores.
| Variable | Total Patients 990 (100%) | Patients with CHA2DS2-VASC < 4 527 (53.2%) | Patients with CHA2DS2-VASC ≥ 4 463 (46.8%) | p-Value |
|---|---|---|---|---|
| Age | 68.1 ± 11.7 | 61.7 ± 10.7 | 75.43 ± 8.71 | <0.0001 |
| Female | 30.3 | 18.0 | 44.3 | <0.0001 |
| AF | 19.6 | 12.4 | 27.8 | <0.0001 |
| DM | 43.6 | 25.9 | 63.7 | <0.0001 |
| HTN | 75.8 | 59.0 | 94.8 | <0.0001 |
| Dyslipidemia | 70.6 | 65.1 | 76.9 | <0.0001 |
| Previous MI | 22.3 | 18.5 | 26.5 | 0.003 |
| Previous PCI | 33.5 | 29.7 | 37.9 | 0.007 |
| Previous CABG | 22.8 | 15.4 | 31.0 | <0.0001 |
| Previous CVA | 9.7 | 0.4 | 20.1 | <0.0001 |
| PVD | 6.1 | 3.7 | 8.7 | 0.001 |
| CHF | 14.3 | 8.2 | 21.2 | <0.0001 |
| GFR < 60 mL/min/1.73 m2 | 43.2 | 21.1 | 68.0 | <0.0001 |
| ACS | 49.1 | 48.5 | 49.7 | 0.727 |
| Obstructive CAD | 57.2 | 47.6 | 68.0 | <0.0001 |
| 3 Vessel CAD | 33.0 | 23.3 | 44.2 | <0.0001 |
| Calcified plaques | 22.2 | 13.9 | 31.9 | <0.0001 |
| Elevated LV filling pressure | 32.3 | 21.9 | 42.8 | <0.0001 |
| EF > 50% | 48.2 | 49.5 | 46.8 | 0.461 |
| Anemia (HB < 13 g/dL) | 43.1 | 27.4 | 60.7 | <0.0001 |
| AS | 19.5 | 11.9 | 28.0 | <0.001 |
| BMI | 28.7 ± 5.2 | 28.7 ± 5.1 | 28.7 ± 5.23 | 0.869 |
| EF | 49.3 ± 9.9 | 49.8 ± 9.4 | 48.8 ± 10.4 | 0.170 |
| Mortality | 25.1 | 13.1 | 38.7 | <0.0001 |
Continuous values are presented as the mean ± standard deviation. Dichotomic variables are presented as the percentage of the total number of patients in the relevant rubric. Abbreviations: AF: atrial fibrillation, HTN: hypertension, DM: diabetes mellitus, MI: myocardial infarction, PCI: percutaneous coronary intervention, CABG: coronary artery bypass graft, CVA: cerebrovascular accident, PVD: peripheral vascular disease, CHF: chronic heart failure, GFR: glomerular filtration rate, ACS: acute coronary syndrome, CAD: coronary artery disease, LV: left ventricular, EF: ejection fraction, AS: aortic stenosis, and BMI: body mass index.
Table 4.
Univariate analysis of the association of different variables with mortality.
| Variable | Total Patients 990 (%) | Alive 742 (74.9%) | Deceased 249 (25.1%) | p Value |
|---|---|---|---|---|
| Age | 68.1 ± 11.7 | 65.9 ± 11.5 | 74.9 ± 9.7 | <0.0001 |
| Female | 30.3 | 29.4 | 33.1 | 0.274 |
| AF | 19.6 | 15.5 | 31.9 | <0.0001 |
| DM | 43.6 | 40.9 | 51.6 | 0.004 |
| HTN | 75.8 | 73.0 | 84.3 | <0.0001 |
| Dyslipidemia | 70.6 | 70.4 | 71.4 | 0.750 |
| Previous MI | 22.3 | 22.5 | 21.6 | 0.779 |
| Previous PCI | 33.5 | 32.7 | 36.2 | 0.311 |
| Previous CABG | 22.8 | 21.0 | 28.0 | 0.023 |
| Previous CVA | 9.7 | 8.8 | 12.2 | 0.08 |
| PVD | 6.1 | 3.6 | 13.4 | <0.0001 |
| CHF | 14.3 | 9.5 | 28.5 | <0.0001 |
| GFR < 60 mL/min/1.73 m2 | 43.2 | 33.3 | 72.8 | <0.0001 |
| ACS | 49.1 | 47.9 | 52.5 | 0.125 |
| Obstructive CAD | 57.2 | 56.2 | 60.1 | 0.285 |
| 3 Vessel CAD | 33.0 | 30.8 | 39.6 | 0.015 |
| Calcified | 22.2 | 19.3 | 30.8 | 0.001 |
| Elevated LV filling pressure | 32.3 | 22.6 | 54.8 | <0.0001 |
| EF > 50 | 48.2 | 52.3 | 37.6 | <0.0001 |
| Anemia (HB < 13 g/dL) | 43.1 | 36.1 | 63.1 | <0.0001 |
| AS | 19.5 | 13.9 | 33.8 | <0.0001 |
| CHA2DS2VASC ≥ 4 | 46.8 | 38.3 | 72.2 | <0.0001 |
| BMI | 28.7 ± 5.2 | 28.8 ± 5.0 | 28.3 ± 5.7 | 0.191 |
| EF | 49.3 ± 9.9 | 50.5 ± 9.0 | 46.1 ± 11.3 | <0.0001 |
| CHADS2 Score | 1.84 ± 1.22 | 1.65 ± 1.19 | 2.44 ± 1.13 | <0.0001 |
| CHA2DS2-VASC Score | 3.35 ± 1.71 | 3.05 ± 1.67 | 4.24 ± 1.53 | <0.0001 |
Continuous values are presented as the mean ± standard deviation. Dichotomic variables are presented as the percentage of the total number of patients in the relevant rubric. Abbreviations: AF: atrial fibrillation, HTN: hypertension, DM: diabetes mellitus, MI: myocardial infarction, PCI: percutaneous coronary intervention, CABG: coronary artery bypass graft, CVA: cerebrovascular accident, PVD: peripheral vascular disease, CHF: chronic heart failure, GFR: glomerular filtration rate, ACS: acute coronary syndrome, CAD: coronary artery disease, LV: left ventricular, EF: ejection fraction, AS: aortic stenosis, and BMI: body mass index.
Table 5.
Cox regression multivariate analysis of mortality.
| Variable | Hazard Ratio | CI | p-Value |
|---|---|---|---|
| Atrial fibrillation | 1.23 | 0.85–1.76 | 0.272 |
| CHA2DS2-VASC ≥ 4 | 2.14 | 1.40–3.26 | <0.0001 |
| GFR < 60 mL/min/1.73 m2 | 2.16 | 1.40–3.22 | 0.001 |
| Ejection fraction < 50% | 1.64 | 1.17–2.28 | 0.004 |
| Anemia | 1.51 | 1.06–2.13 | 0.021 |
| Elevated LV filling pressure | 1.95 | 1.40–2.73 | <0.0001 |
| Acute coronary syndrome | 1.08 | 0.78–1.49 | 0.655 |
| Obstructive CAD | 1.07 | 0.76–1.50 | 0.715 |
| Aortic Stenosis | 1.40 | 0.98–2.00 | 0.067 |
Abbreviations: CAD: coronary artery disease.
Table 6.
Cox regression multivariate analysis of mortality: CHA2DS2-VASC score (<4 vs. ≥4) significance in the different prespecified subgroups.
Table 6.
Cox regression multivariate analysis of mortality: CHA2DS2-VASC score (<4 vs. ≥4) significance in the different prespecified subgroups.
| Subgroup | Hazard Ratio | CI | p-Value |
|---|---|---|---|
| Non ACS | 2.11 | 1.13–3.95 | 0.019 |
| ACS | 2.178 | 1.22–3.89 | 0.009 |
| No obstructive CAD | 1.74 | 0.95–3.19 | 0.074 |
| Obstructive CAD | 2.80 | 1.52–5.16 | 0.001 |
| Reduced EF | 2.63 | 1.56–4.41 | <0.0001 |
| Preserved EF | 1.632 | 0.78–3.37 | 0.197 |
| Normal Kidney Function | 2.54 | 1.29–5.00 | 0.007 |
| Reduced Kidney Function | 1.878 | 1.11–3.18 | 0.019 |
| No AF | 2.36 | 1.43–3.91 | 0.001 |
| AF | 1.94 | 0.97–3.86 | 0.06 |
Abbreviations: AF: atrial fibrillation, ACS: acute coronary syndrome, CAD: coronary artery disease, and EF: ejection fraction.
Table 7.
Distribution of mortality according to the CHADS2, CHA2DS2-VASCAR, and CHA2DS2-VASC AR2 scores.
Table 7.
Distribution of mortality according to the CHADS2, CHA2DS2-VASCAR, and CHA2DS2-VASC AR2 scores.
| CHADS2 Score | ||||
|---|---|---|---|---|
| CHADS2 Score | Frequency | Percent | Cumulative Percent | Mortality (%) |
| 0 | 142 | 14.4 | 14.4 | 4.2 |
| 1 | 256 | 26.0 | 40.4 | 4.3 |
| 2 | 318 | 32.3 | 72.6 | 12.6 |
| 3 | 188 | 19.1 | 91.7 | 25 |
| 4 | 54 | 5.5 | 97.2 | 27.8 |
| 5 | 28 | 2.8 | 100.0 | 32.1 |
| Total | 986 | 100.0 | 100.0 | 13 |
| CHA2DS2-VASCAR score | ||||
| 0 | 32 | 3.3 | 3.3 | 0 |
| 1 | 102 | 10.6 | 13.9 | 4.9 |
| 2 | 135 | 14.0 | 27.9 | 3.0 |
| 3 | 182 | 18.9 | 46.8 | 4.9 |
| 4 | 154 | 16.0 | 62.8 | 9.1 |
| 5 | 160 | 16.6 | 79.4 | 18.1 |
| 6 | 115 | 11.9 | 91.3 | 24.3 |
| 7 | 57 | 5.9 | 97.2 | 38.6 |
| 8 | 21 | 2.2 | 99.4 | 47.6 |
| 9 | 6 | 0.6 | 100.0 | 66.7 |
| Total | 964 | 100.0 | 100.0 | |
| CHA2DS2-VASCAR2 score | ||||
| 0 | 32 | 3.3 | 3.3 | 0 |
| 1 | 101 | 10.5 | 13.8 | 5.0 |
| 2 | 135 | 14.0 | 27.8 | 3.0 |
| 3 | 178 | 18.5 | 46.3 | 4.5 |
| 4 | 157 | 16.3 | 62.6 | 8.3 |
| 5 | 147 | 15.2 | 77.8 | 18.4 |
| 6 | 123 | 12.8 | 90.6 | 22.8 |
| 7 | 55 | 5.7 | 96.3 | 41.8 |
| 8 | 28 | 2.9 | 99.2 | 39.3 |
| 9 | 7 | 0.7 | 99.9 | 71.4 |
| 10 | 1 | 0.1 | 100.0 | 100 |
| Total | 964 | 100.0 | 100.0 | |
| Comparison between low and high mortality groups according to the aforementioned scores | ||||
| Mortality | ||||
| CHADS2 < 2 | 4.3% | |||
| CHADS2 ≥ 2 | 18.9% | |||
| CHA2DS2-VASC < 4 | 5.3% | |||
| CHA2DS2-VASC ≥ 4 | 21.7% | |||
| CHA2DS2-VASCAR < 4 | 4.0% | |||
| CHA2DS2-VASCAR ≥ 4 | 20.9% | |||
| CHA2DS2-VASCAR2 < 4 | 3.8% | |||
| CHA2DS2-VASCAR2 ≥ 4 | 20.9% | |||
p < 0.0001 for any difference in mortality. p < 0.0001 for all.
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MDPI and ACS Style
Teodorovich, N.; Gandelman, G.; Jonas, M.; Fabrikant, Y.; Swissa, M.S.; Shimoni, S.; George, J.; Swissa, M. The CHA2DS2-VASC Score Predicts Mortality in Patients Undergoing Coronary Angiography. Life 2023, 13, 2026. https://doi.org/10.3390/life13102026
AMA Style
Teodorovich N, Gandelman G, Jonas M, Fabrikant Y, Swissa MS, Shimoni S, George J, Swissa M. The CHA2DS2-VASC Score Predicts Mortality in Patients Undergoing Coronary Angiography. Life. 2023; 13(10):2026. https://doi.org/10.3390/life13102026
Chicago/Turabian StyleTeodorovich, Nicholay, Gera Gandelman, Michael Jonas, Yakov Fabrikant, Michael Sraia Swissa, Sara Shimoni, Jacob George, and Moshe Swissa. 2023. "The CHA2DS2-VASC Score Predicts Mortality in Patients Undergoing Coronary Angiography" Life 13, no. 10: 2026. https://doi.org/10.3390/life13102026
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