Predictive Value of CHADS₂, CHA₂DS₂-VASc and R₂-CHADS₂ Scores for Short- and Long-Term Major Adverse Cardiac Events in Non-ST-Segment Elevation Myocardial Infarction

Abstract

Background: Non-ST-elevation myocardial infarction (NSTEMI) carries a poor prognosis, and accurately prognostication has significant clinical importance. In this study, we analyzed the predictive value of the CHADS₂, CHA₂DS₂-VASc, and R₂-CHADS₂ scores for major adverse cardiac events (MACE) following percutaneous coronary intervention (PCI) in patients with NSTEMI using data from a prospective multicenter registry.

Methods and Results: The registry included 440 consecutive patients with NSTEMI and coronary artery disease who underwent successful PCI. Patients were clinically followed for up to 3 years or until the occurrence of MACE. MACE was defined as a composite of all-cause death and nonfatal MI. During the follow-up period, 55 patients (12.5%) experienced MACE. Risk analysis of MACE occurrence, adjusted for the multivariable model, demonstrated a significant increase in risk with higher CHADS₂, CHA₂DS₂-VASc, and R₂-CHADS₂ scores. Kaplan-Meier analysis showed a higher incidence of MACE in patients with higher CHADS₂, CHA₂DS₂-VASc, and R₂-CHADS₂ scores, both in the short- and long-term periods.

Conclusions: Patients with NSTEMI and higher CHADS₂, CHA₂DS₂-VASc, and R₂-CHADS₂ scores displayed a greater incidence of MACE.

Recently, the prevalence of acute coronary syndrome (ACS), which has been relatively rare in Japan, has been on the rise.¹ Furthermore, although the incidence of ACS is decreasing in Europe and the USA,² in Japan it has remained relatively stable.³ The declining incidence of ST-elevation myocardial infarction (STEMI) among patients with ACS in the USA and Europe is attributed to improved cardiac disease risk management.⁴ Non-STEMI (NSTEMI), which is projected to increase in Japan in the future, reportedly has a poorer prognosis than STEMI because NSTEMI has more coronary risk factors,^5–7 and lower rates of optimal medical therapy initiation after onset.⁷

Both the Thrombolysis in Myocardial Infarction (TIMI) risk score and Global Registry of Acute Coronary Events (GRACE) risk score have been reported as useful for predicting the long-term prognosis of high-risk patients with NSTEMI,^8,9 but their complexity in practical clinical application has been noted. The CHADS₂ score was originally developed as a risk assessment tool for predicting embolism in patients with atrial fibrillation (AF) and has gained widespread recognition and application.¹⁰ The CHA₂DS₂-VASc and R₂-CHADS₂ scores were also introduced to improve predictive accuracy for embolism.^11,12 Previous studies have shown utility in predicting prognosis after percutaneous coronary intervention (PCI) and in patients with STEMI.^13–15 However, none have reported the prognostic value of these scores for patients with NSTEMI. Therefore, in this study, we analyzed data from the FUJISUN registry, a multicenter registry, to investigate the utility of CHADS₂, CHA₂DS₂-VASc and R₂-CHADS₂ scores for risk assessment in patients with NSTEMI.

Methods

Study Patients

This cohort study retrospectively analyzed data extracted from the FUJISUN registry, a prospective multicenter cohort registry conducted at 6 Japanese sites. The registry is registered at https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000054027 under unique identifier UMIN000047369. As previously described, this registry aims to investigate prognostic factors following PCI.¹⁶ A total of 7,391 consecutive patients who underwent PCI for coronary artery disease (CAD) at any of the participating hospitals between May 2008 and December 2019 were included in the registry. The study protocol received approval from the ethics committee at each site and adhered to the principles outlined in the 1975 Declaration of Helsinki. Informed consent requirements were waived owing to the retrospective nature of this analysis. Inclusion criterion encompassed PCI for NSTEMI, whereas exclusion criteria comprised unsuccessful PCI, age <20 years, and non-participation in follow-up. Patients were clinically followed for up to 3 years or until an event occurred.

Study Protocol

In this study, we analyzed the time to the first major adverse cardiac event (MACE), which was prospectively evaluated over a 3-year period starting from the index date, defined as the date of the initial PCI when patients were enrolled in the registry. MACE was defined as a composite of all-cause death and nonfatal MI. Nonfatal MI was characterized by typical ischemic chest pain, a creatine kinase-MB level at least twice the upper limit of normal, a troponin T level >0.1 ng/mL, or evident ischemic changes apparent on the ECG at the time of the event; with discharge occurring while the patient was alive. NSTEMI was defined as typical ACS symptoms and troponin T elevation without ECG changes indicative of STEMI. To remove the “immortal time bias” in the occurrence of MACE, the landmark analysis was performed at 30 days after the index PCI and thereafter to analyze short- and long-term prognosis, respectively.

Hypertension was defined as systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg during hospitalization, or pre-admission treatment for high blood pressure. Diabetes mellitus (DM) was defined as casual glucose level ≥200 mg/dL, fasting plasma glucose level ≥126 mg/dL, hemoglobin A1c level ≥6.5% (National Glycohemoglobin Standardization Program), or pre-admission use of antidiabetic drugs. Peripheral artery disease was defined as an ankle-brachial index <0.9 or a history of peripheral artery revascularization. Stroke was defined as a history of symptomatic brain dysfunction attributed to a vascular cause. Congestive heart failure (CHF) was defined as resting dyspnea with progressive fluid retention necessitating diuretic treatment.

Blood samples for assessing blood glucose, lipids, and B-type natriuretic peptide (BNP) levels were collected from a peripheral vein early in the morning a few days before discharge. Medications were prescribed at the discretion of the physician in charge and recorded at discharge following the index PCI. Patients received standard medical treatment upon admission,¹⁷ which was continued throughout the follow-up period. Instructions regarding optimal lifestyle changes and diet were provided before discharge and were reinforced throughout the follow-up period. Information on comorbidities, PCI procedures, and outcomes were collected from each center. Clinical follow-up information was obtained through clinical visits, telephone surveys, validated questionnaires, and discussions with referring physicians. All endpoint data were carefully reviewed by the investigators for accuracy, consistency, and completeness of follow-up. Data verification, statistical analyses, and data file security were overseen by a single investigator (T.H.).

Exposure and Laboratory Measurements

Body mass index (BMI) was calculated as the weight in kilograms divided by the height in meters squared. Abdominal circumference (AC) was measured at the level of the umbilicus at the end of normal expiration in a standing position. Plasma BNP levels were measured using an immunoradiometric assay (Shionogi Pharmaceutical, Osaka, Japan). Low-density lipoprotein cholesterol (LDL-C) levels were calculated using the Friedewald formula.¹⁸ The estimated glomerular filtration rate (eGFR) was calculated as: eGFR = 194 × serum creatinine^−1.094 × age^−0.287 × 0.739 (if female).¹⁹ Echocardiography was performed a few days before discharge, and the left ventricular ejection fraction (LVEF) was calculated using the motion mode method with the Teichholz formula. Low LVEF was defined as <40%.

Definition of CHADS₂, CHA₂DS₂-VASc and R₂-CHADS₂ Scores

The CHADS₂ score was calculated as the sum of CHF, hypertension, age ≥75 years, DM as 1 point and previous stroke or transient ischemic attack as 2 points. The CHA₂DS₂-VASc score included 1 point each for female sex, age 65–74 years, and vascular disease, in addition to the CHADS₂ score. The R₂-CHADS₂ score added 2 points for renal failure to the CHADS₂ score, with renal failure defined as eGFR ≤60 mL/min. These scores were calculated from the data obtained at the index admission. Each score was categorized into 3 groups: low (CHADS₂ score ≤1, CHA₂DS₂-VASc score ≤2, R₂-CHADS₂ score ≤2), middle (CHADS₂ score 2–3, CHA₂DS₂-VASc score 3–4, R₂-CHADS₂ score 3–4), and high (CHADS₂ score ≥4, CHA₂DS₂-VASc score ≥5, R₂-CHADS₂ score ≥5).

Statistical Analysis

Data are expressed as median, interquartile range (25th and 75th percentiles), frequency (%), hazard ratio (HR), or 95% confidence interval. Continuous variables were compared using the Mann-Whitney U test, and categorical variables were compared between groups using Pearson’s chi-square analysis, Fisher’s exact test, or the Wilcoxon signed-rank test, as appropriate. Correlations between clinical variables and event-free survival were tested using the Kaplan-Meier method, log-rank tests, and Cox proportional hazard regression. Landmark analysis was used to evaluate the relative risk of MACE occurrence in surviving patients after day 30. During multivariate analysis, backward stepwise Cox regression was used for variable selection in the study sample. In the multivariate model, we included the following covariates, considering multicollinearity: intra-aortic balloon pump (IABP), rotational atherectomy, multivessel disease, hemodialysis and low LVEF. During Cox regression analysis, the incidence of MACE in the low-score group served as the reference level, and the HRs of the other groups were analyzed by comparing them with the HR of the low-score group. Receiver operating characteristic (ROC) analysis was performed to compare the predictive power for the CHADS₂, CHA₂DS₂-VASc and R₂-CHADS₂ scores. Statistical significance was defined as P<0.05, and all statistical analyses were performed using SPSS version 26 (IBM Corp., Armonk, NY, USA).

Results

Study Patients

Initially, 7,391 consecutive patients who underwent PCI registered in the FUJISUN registry were included. Of them, 553 had NSTEMI and met the study criteria. Based on the exclusion criteria, 23 patients with failed PCI and 90 patients never followed-up were subsequently excluded (Figure 1). The remaining 440 patients were included in this study. All participants were part of a prospective registry examining the incidence of MACE after the index date. The median follow-up period was 22 months (interquartile range, 8–36 months). During the follow-up period, 55 MACE occurred, comprising 51 all-cause deaths and 4 nonfatal MIs. Of the 51 deaths, 23 were cardiac-related and 28 were noncardiac. The clinical characteristics of the patients are summarized in Table 1. According to the CHADS₂ scores, 130 (29.5%) patients were classified into the low-score group, 249 (56.6%) into the middle-score group, and 61 (13.9%) into the high-score group. Similarly, based on the CHA₂DS₂-VASc and R₂-CHADS₂ scores, 163 (37.0%) and 212 (48.2%) patients were classified in the low-score group, 191 (43.4%) and 116 (26.4%) in the middle-score group, and 86 (19.5%) and 112 (25.5%) in the high-score group, respectively.

Figure 1.

Patient enrolment. PCI, percutaneous coronary intervention; NSTEMI, non-ST-elevation myocardial infarction; UAP, unstable angina pectoris.

Table 1.

Comparison of Clinical Characteristics Between Patients With and Without MACE

	Overall (n=440)	With MACE (n=55)	Without MACE (n=385)	P value
Age (years)	71 [63, 79]	81 [75, 85]	70 [62, 78]	<0.001
Male	349 (79.3)	40 (72.7)	309 (80.3)	0.21
BMI	23.5 [21.1, 25.6]	22.8 [19.5, 24.9]	23.5 [21.4, 25.8]	<0.01
AC	85 [78, 90]	82 [75, 88]	85 [80, 90]	0.04
Hypertension	319 (72.5)	38 (69.1)	281 (73.0)	0.52
DM	202 (45.9)	32 (58.2)	170 (44.2)	0.06
Hemodialysis	10 (2.3)	4 (7.3)	6 (1.6)	0.03
PAD	14 (3.2)	3 (5.5)	11 (2.9)	0.40
Stroke	43 (9.8)	12 (21.8)	31 (8.1)	<0.01
Current smoking	142 (32.3)	10 (18.2)	132 (34.3)	0.02
HbA1c, %	6.0 [5.6, 6.6]	6.3 [5.9, 6.9]	6.0 [5.6, 6.6]	<0.01
TG, mg/dL	103 [69, 148]	102 [67, 133]	104 [70, 149]	0.53
HDL-C, mg/dL	46 [39, 57]	44 [35, 54]	46 [39, 57]	0.14
LDL-C, mg/dL	114 [92, 140]	100 [83, 124]	116 [93, 142]	<0.01
eGFR, mL/min/1.73 m2	62 [48, 78]	50 [36, 64]	64 [50, 78]	<0.001
BNP, pg/mL	103 [43, 308]	480 [123, 1,033]	87 [37, 249]	<0.001
LVEF <40%	73 (16.6)	25 (45.5)	48 (12.5)	<0.001
NYHA Class				<0.001
I	265 (60.2)	17 (30.9)	248 (64.4)
II	85 (19.3)	10 (18.2)	75 (19.5)
III	41 (9.3)	8 (14.5)	33 (8.6)
IV	49 (11.1)	20 (36.4)	29 (7.5)
Medications
Aspirin	429 (97.5)	51 (92.7)	378 (98.2)	0.04
P2Y12 inhibitor	401 (91.1)	43 (78.2)	358 (93.0)	0.001
OAC	28 (6.4)	8 (14.5)	20 (5.2)	0.02
β-blocker	169 (38.4)	16 (29.1)	153 (39.7)	0.14
CCB	148 (33.6)	11 (20.0)	137 (35.6)	0.02
ACE-I	79 (18.0)	5 (9.1)	74 (19.2)	0.09
ARB	198 (45.0)	20 (36.4)	178 (46.2)	0.19
Statin	314 (71.4)	21 (38.2)	293 (76.1)	<0.001
DPP4 inhibitor	58 (13.2)	5 (9.1)	53 (13.8)	0.40
Insulin	26 (5.9)	4 (7.3)	22 (5.7)	0.55
PCI variables
Access site				0.04
Radial	187 (42.5)	15 (27.3)	172 (44.7)
Femoral	223 (50.7)	36 (65.5)	187 (48.6)
Other	30 (6.8)	4 (7.3)	26 (6.8)
No. of diseased vessels				<0.001
1	238 (54.1)	12 (21.8)	226 (58.7)
2	123 (28.0)	21 (38.2)	102 (26.5)
3	79 (18.0)	22 (40.0)	57 (14.8)
LMCA disease	38 (8.6)	20 (36.4)	18 (4.7)	<0.001
IABP	51 (11.6)	16 (29.1)	35 (9.1)	<0.001
Rotational atherectomy	7 (1.6)	3 (5.5)	4 (1.0)	0.04
Use of DES	271 (61.6)	38 (69.1)	233 (60.5)	0.22
No. of stents				0.15
0	22 (5.0)	1 (1.8)	21 (5.5)
1	302 (68.6)	45 (81.8)	257 (66.8)
2	101 (23.0)	8 (14.5)	93 (24.2)
≥3	15 (1.8)	1 (1.8)	14 (3.6)
Stent diameter, mm	3.0 [3.0, 3.5]	3.0 [3.0, 3.5]	3.0 [3.0, 3.5]	0.50
Stent length, mm	24 [18, 33]	20 [16, 33]	24 [18, 34]	0.54

Data are expressed as the median [25–75th percentile] or the number (%) of patients. AC, abdominal circumference; ACE-I, angiotensin converting enzyme inhibitor; ACS, acute coronary syndrome; ARB, angiotensin II receptor blocker; BMI, body mass index; BNP, B-type natriuretic peptide; CCB, calcium-channel blocker; DES, drug-eluting stent; DM, diabetes mellitus; DPP4, dipeptidyl peptidase-4; eGFR, estimated glomerular filtration rate; HbA1c, hemoglobin A1c; HDL-C, high-density lipoprotein cholesterol; HF, heart failure; IABP, intra-aortic balloon pump; LDL-C, low-density lipoprotein cholesterol; LMCA, left main coronary artery; LVEF, left ventricular ejection fraction; MACE, major adverse cardiac event; NYHA, New York Heart Association; OAC, oral anticoagulant; PAD, peripheral artery disease; PCI, percutaneous coronary intervention; TG, triglyceride.

Comparisons of Baseline Clinical Background With and Without MACE (Table 1)

Age at the index date was significantly higher in patients with MACE. The prevalence of hemodialysis, stroke, and low LVEF was significantly higher in patients with MACE. Conversely, BMI, AC, and current smoking status were significantly lower or less common in patients with MACE. Among the laboratory measurements, HbA1c and BNP levels were significantly higher in patients with MACE, whereas LDL-C levels and eGFR were significantly lower. A higher New York Heart Association (NYHA) class was more common in patients with MACE. Aspirin, P2Y12 inhibitors, calcium-channel blockers (CCB), and statin use were less frequently prescribed in patients with MACE. Among the PCI procedures, the femoral approach, multivessel disease, left main disease, IABP use, and rotational atherectomy were significantly more common in patients with MACE.

Risk Assessment of Clinical Parameters in the Occurrence of MACE (Table 2)

Table 2.

COX Proportional Hazards Regression Analysis for Occurrence of MACE

	HR (95% CI)	P value
Age, per 5 years	1.48 (1.29–1.71)	<0.001
Male sex	0.71 (0.39–1.29)	0.26
BMI, per SD	0.66 (0.50–0.88)	<0.01
AC, per SD	0.83 (0.64–1.08)	0.17
Hypertension	0.79 (0.45–1.40)	0.42
DM	1.58 (0.92–2.70)	0.10
Hemodialysis	3.63 (1.31–10.04)	0.01
PAD	1.86 (0.58–5.97)	0.30
Stroke	2.61 (1.38–4.94)	<0.01
Current smoking	0.45 (0.23–0.89)	0.02
HbA1c, per SD	1.25 (0.99–1.58)	0.05
TG, per SD	0.84 (0.61–1.16)	0.30
HDL-C, per SD	0.93 (0.69–1.24)	0.60
LDL-C, per SD	0.62 (0.46–0.84)	<0.01
BNP, per SD	1.43 (1.24–1.64)	<0.001
eGFR, per SD	0.58 (0.45–0.75)	<0.001
LVEF <40%	4.71 (2.77–8.00)	<0.001
NYHA HF classification
I	Ref.	–
II	1.90 (0.87–4.14)	0.11
III	3.01 (1.30–6.97)	0.01
IV	8.26 (4.32–15.79)	<0.001
Medications
Aspirin	0.21 (0.07–0.57)	<0.01
P2Y12 inhibitor	0.31 (0.17–0.60)	<0.001
OAC	2.05 (0.97–4.34)	0.06
β-blocker	0.66 (0.37–1.17)	0.15
CCB	0.42 (0.22–0.82)	0.01
ACE-I	0.48 (0.19–1.19)	0.11
ARB	0.64 (0.37–1.11)	0.11
Statin	0.23 (0.13–0.40)	<0.001
DPP4 inhibitor	0.67 (0.27–1.68)	0.39
Insulin	1.26 (0.46–3.49)	0.65
PCI variables
Access site
Radial	0.56 (0.31–1.02)	0.06
Femoral	1.56 (0.89–2.74)	0.12
Other	1.45 (0.52–4.05)	0.47
No. of diseased vessels
1	Ref.	–
2	3.62 (1.79–7.35)	<0.001
3	6.20 (3.07–12.53)	<0.001
LMCA disease	7.85 (4.53–13.62)	<0.001
IABP	3.85 (2.15–6.90)	<0.001
Rotational atherectomy	4.05 (1.26–13.00)	0.02
Use of DES	1.46 (0.83–2.59)	0.19
No. of stents
0	Ref.	–
1	3.76 (0.52–27.27)	0.19
2	1.89 (0.24–15.08)	0.55
≥3	1.63 (0.10–26.07)	0.73
Stent diameter	1.26 (0.87–1.82)	0.23
Stent length	0.99 (0.97–1.01)	0.39

Data are expressed as the hazard ratio (HR) and 95% confidence interval (CI). SD, standard deviation; ref., reference; other abbreviations as in Table 1.

In the crude analysis of MACE occurrence, a significant increase in risk was observed for older patients, and those on hemodialysis, with a history of stroke, high BNP levels, low LVEFs, higher NYHA classification, multivessel disease or left main disease, and a history of IABP or rotational atherectomy. In contrast, a significant risk reduction in MACE occurrence was observed in patients with higher BMI, current smoking status, higher LDL-C levels, and eGFR under antiplatelet therapy, CCB, and statins.

Risk Assessment Among CHADS₂, CHA₂DS₂-VASc, R₂-CHADS₂ Scores for MACE Occurrence

Kaplan-Meier analysis showed a significantly higher incidence of MACE in the high-score group than in the other score groups in the short-term period (log-rank test, P=0.003 in CHADS₂, P=0.02 in CHA₂DS₂-VASc, P=0.006 in R₂-CHADS₂) (Figure 2). Similar to the short-term period, there was a significantly higher incidence of MACE in the high- and middle-score groups than in the low-score group (log-rank test, P<0.001 in CHADS₂, P<0.001 in CHA₂DS₂-VASc, P<0.001 in R₂-CHADS₂) (Figure 2).

Figure 2.

Kaplan-Meier analysis for primary endpoint. The blue line indicates patients in with the low-score group (CHADS₂ 0–1, CHA₂DS₂-VASc 0–2, R₂-CHADS₂ 0–2). The red line represents patients in the middle-score group (CHADS₂ 2–3, CHA₂DS₂-VASc 3–4, R₂-CHADS₂ 3–4). The green line represents patients in the high-score group (CHADS₂ 4–6, CHA₂DS₂-VASc 5–9, R₂-CHADS₂ 5–8, respectively). The dotted line indicates 30 days after the index PCI procedure. The Kaplan-Meier curve on the left demonstrates the initial survival rate from the index date to 30 days. On the right side, the Kaplan-Meier curve represents the landmark analysis at 30 days after treatment, illustrating the long-term survival rate from 30 days to 3 years. The “P value” indicates the results of log-rank tests comparing the groups. “No. at risk” indicates the number of patients at risk within each score group. MACE, major adverse cardiac event; PCI, percutaneous coronary intervention.

In the univariate Cox hazard regression analysis, the risk of MACE increased by 65%, 50%, and 45% per unit increase in the CHADS₂, CHA₂DS₂-VASc, and R₂-CHADS₂ scores, respectively, when treated as continuous variables. Multivariate analysis also showed significant increases in risk of 34%, 28%, and 28% per unit increase in the CHADS₂, CHA₂DS₂-VASc, and R₂-CHADS₂ scores, respectively.

Each score was divided into 3 groups, and multivariate analyses demonstrated an increased risk of MACE in the high-score group when compared with the low-score group (380% increase in CHADS₂, 268% increase in CHA₂DS₂-VASc, and 343% increase in R₂-CHADS₂ scores) (Table 3).

Table 3.

COX Proportional Hazards Regression Analysis for Occurrence of MACE

	Univariate		Multivariate
	HR (95% CI)	P value	HR (95% CI)	P value
CHADS2
Continuous variable	1.65 (1.39–1.95)	<0.001	1.34 (1.11–1.63)	<0.001
Low group (0–1)	Ref.	–	Ref.	–
Middle group (2–3)	3.14 (1.22–8.08)	0.02	2.01 (0.76–5.30)	0.16
High group (4–6)	9.41 (3.53–25.09)	<0.001	3.80 (1.33–10.82)	0.01
CHA2DS2-VASc
Continuous variable	1.50 (1.31–1.73)	<0.001	1.28 (1.10–1.49)	<0.001
Low group (0–2)	Ref.	–	Ref.	–
Middle group (3–4)	1.85 (0.84–4.07)	0.12	1.35 (0.61–3.00)	0.47
High group (5–9)	6.02 (2.82–12.85)	<0.001	2.68 (1.18–6.08)	0.02
R2-CHADS2
Continuous variable	1.45 (1.28–1.65)	<0.001	1.28 (1.11–1.47)	0.001
Low group (0–2)	Ref.	–	Ref.	–
Middle group (3–4)	2.75 (1.22–6.20)	0.02	2.20 (0.97–4.99)	0.06
High group (5–8)	6.49 (3.18–13.24)	<0.001	3.43 (1.61–7.32)	0.001

Data are expressed as the HR and 95% CI. The adjusted model included IABP use, rotational atherectomy, multivessel disease, hemodialysis, low LVEF. Abbreviations as in Tables 1 and 2.

In the ROC analysis, the area under curve was 0.738, 0.741 and 0.738 for the CHADS₂, CHA₂DS₂-VASc and R₂-CHADS₂ scores, respectively (Supplementary Figure).

Discussion

The results of this study highlighted the prognostic value of the CHADS₂, CHA₂DS₂-VASc, and R₂-CHADS₂ scores in patients with NSTEMI. Although previous research has demonstrated the utility of these scores in patients with CAD and STEMI,^13,14 this study is the first to specifically focus on patients with NSTEMI. Notably, patients with NSTEMI often exhibit a poorer long-term prognosis than those with STEMI and have lower rates of optimal drug therapy implementation after PCI.⁷ Accurate risk assessment in these patients would guide appropriate therapeutic interventions and potentially lead to improved long-term outcomes.

Although the TIMI risk score has long been used to predict the prognosis of patients with NSTEMI,⁸ its predictive accuracy is reported to be less robust than that of the GRACE score.²⁰ However, the GRACE score,⁹ known for its excellent predictive power, can be challenging to calculate. The PURSUIT score has also shown usefulness in predicting both short- and long-term prognoses,²¹ but it is not as commonly used in real-world clinical practice.

The CHADS₂ score was originally developed as a predictive tool for cardiogenic embolism in patients with AF,¹⁰ but its simplicity has made it widely recognized and frequently used in clinical practice. In addition to the CHADS₂ score, the CHA₂DS₂-VASc and R₂-CHADS scores were developed to further enhance the predictive accuracy of embolism in AF,^11,12 and they are also widely used in clinical settings. The CHADS₂, CHA₂DS₂-VASc, and R₂-CHADS₂ scores comprehensively encompass the risk factors for cardiovascular disease and have recently demonstrated their utility not only in predicting the risk of embolization in AF, but also in assessing the prognosis of various cardiovascular diseases.^13–15,22 However, the applicability of these scores for predicting short- and long-term prognoses in patients with NSTEMI has not been previously reported.

In this study, the CHADS₂ score, CHA₂DS₂-VASc, and R₂-CHADS₂ scores showed a significant increase in risk with each incremental value. Even when patients were categorized into 3 groups based on their scores, the high-scoring group showed a marked increase in risk compared with the low-scoring group. These findings remained consistent and demonstrated independent prognostic significance even after adjusting for background factors in the multivariate analysis. Furthermore, landmark analysis revealed a similarly unfavorable prognosis for the high-risk group in both the short- and long-term. These results suggest the potential for considering more intensive treatment strategies aimed at improving the prognosis of patients with high CHADS₂, CHA₂DS₂-VASc and R₂-CHADS₂ scores upon admission.

Instead of relying on the complex TIMI or GRACE score in actual NSTEMI treatment, the CHADS₂ score, CHA₂DS₂-VASc score, and the R₂-CHADS₂ score, which in particular is easier and more familiar for daily clinical use, can be used for risk assessment. It offers a practical and valuable approach to clinical practice. In NSTEMI patients who are less optimally treated and have a poorer prognosis,⁷ there is potential for high-risk patients determined by high CHADS₂, CHA₂DS₂-VASc and R₂-CHADS₂ scores to be considered for more intensive medical intervention.

Study Limitations

There are several to be noted. First, it was not a randomized trial, so the possibility of selection bias should be considered. Consequently, the study may have been influenced by various biases and confounders, even after multivariate analysis. Second, there was a bias in unmeasured confounding factors. Unfortunately, this study did not collect data on malignant cancers because its primary aim was to analyze the prognosis of patients who underwent PCI. Therefore, estimating to what extent noncardiac deaths included deaths from malignant cancers remains challenging. Furthermore, the registry did not include factors related to the extent of ST changes at onset and the time from onset to treatment, which are important factors in the treatment of NSTEMI. However, this multicenter registry did not include these items as they are not specific to ACS. Nevertheless, attending physicians applied a standard of care in accordance with general guidelines at their discretion. Furthermore, we should compare how comparatively significant the GRACE and TIMI scores are directly with the CHADS₂, CHA₂DS₂-VASc, and R₂-CHADS₂ scores as predictors of prognosis, but the FUJISUN registry does not have observational variables such as heart rate and ST changes at presentation, so it was difficult to validate the GRACE and TIMI scores in this study.

Conclusions

Patients with NSTEMI and higher CHADS₂, CHA₂DS₂-VASc, and R₂-CHADS₂ scores had a higher incidence of MACE.

Acknowledgments

None.

Sources of Funding

This work was supported by JSPS KAKENHI (grant numbers B2-19390209 and B-22390158).

Disclosures

None.

Conflict of Interest

All authors declare no conflicts of interest.

IRB Information

This study was granted an exemption from requiring ethics approval by University of Yamanashi Ethics Committee because it was a retrospective observational study.

Data Availability

The deidentified participant data will not be shared.

Supplementary Files

Please find supplementary file(s);

https://doi.org/10.1253/circj.CJ-23-0733

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