Impact of Risk Stratification on Clinical Outcomes in Patients With Acute Coronary Syndrome　― A Systematic Review ―

Rie Aoyama; Kazuya Tateishi; Toshiaki Mano; Kiyotaka Hao; Takuya Taniguchi; Sunao Kojima; Marina Arai; Yuichiro Minami; Masashi Yokose; Akihito Tanaka; Kunihiro Matsuo; Junichi Yamaguchi; Teruo Noguchi; Yasushi Tsujimoto; Toshikazu Funazaki; Tetsuya Matoba; Yoshio Tahara; Hiroshi Nonogi; Migaku Kikuchi; for the Japan Resuscitation Council (JRC) Emergency Cardiovascular Care (ECC) Acute Coronary Syndrome (ACS) Task Force and the Guideline Editorial Committee on behalf of the Japanese Circulation Society (JCS) Emergency and Critical Care Committee

doi:10.1253/circrep.CR-25-0162

Abstract

Background: Risk scores have been developed to determine the treatment strategies and predict the prognosis of acute coronary syndromes (ACS). It remains unclear whether risk score-guided management improves prognosis. Therefore, this systematic review aimed to evaluate whether the use of risk scores to assess the acute severity of illness affects the prognosis of adult patients with ACS.

Methods and Results: We conducted a systematic review and meta-analysis to evaluate whether risk score-guided management improves clinical outcomes in patients with ACS. We searched MEDLINE, the Cochrane Central Register of Controlled Trials (CENTRAL), and Web of Science up to November 30, 2024, and included randomized controlled trials comparing risk score-based care with standard care. Two cluster randomized trials, using the Global Registry of Acute Coronary Events risk score (GRS), were identified, with a total of 5,368 patients. A systematic review adjusted for clustering revealed no significant differences in clinical outcomes, including in-hospital and 1-year mortality, in-hospital cardiac arrest, in-hospital recurrent ischemia, in-hospital and 1-year heart failure, and early invasive angiography.

Conclusions: Risk score-guided management of patients with ACS using risk scores, particularly the GRS, did not consistently lead to improved clinical outcomes. Further research is needed to assess whether risk score-guided management can improve patient outcomes.

Central Figure

The prognosis of patients with acute coronary syndromes (ACS) has significantly improved over the past few decades, mainly because of the widespread implementation of early reperfusion strategies and evidence-based pharmacological therapies.¹^–³ Before reperfusion therapy was established as the initial treatment for ACS, treatment of ACS in the intensive care unit (ICU) or coronary care unit (CCU) was associated with improved outcomes.⁴

Since early revascularization has been established and the prognosis for ACS has improved significantly, various guidelines⁵^–⁷ recommend stratifying patients with ACS, assessing clinical outcomes, and making decisions regarding the timing of treatment, such as invasive coronary angiography or ICU/CCU admission. Several scoring systems have been proposed for risk assessment.⁸^–¹²

The thrombolysis in myocardial infarction (TIMI) risk score predicts the prognosis of patients with non-ST-segment elevation acute coronary syndromes (NSTE-ACS), particularly the risk of acute myocardial infarction (AMI) and death within 2 weeks,¹⁰ and the Platelet glycoprotein IIb/IIIa in Unstable angina: Receptor Suppression Using Integrilin (PURSUIT) risk score predicts 30-day mortality in patients with ST-segment elevation myocardial infarction (STEMI).¹³ The Global Registry of Acute Coronary Events (GRACE) risk score was highly accurate in predicting in-hospital and 6-month post-discharge all-cause mortality in patients with ACS.¹³^–¹⁶ The Acute Physiology and Chronic Health Evaluation (APACHE) score¹⁷^,¹⁸ has been reported to assess severity and predict outcome in patients admitted to the ICU. Several risk scores have been proposed and have shown high accuracy in predicting outcomes such as in-hospital and all-cause mortality, and observational studies have validated the GRACE risk score (GRS) in various patient populations and for various clinical outcomes.

While risk score-based assessments have demonstrated high accuracy in predicting outcomes such as in-hospital mortality and all-cause mortality,¹⁹^–²² it remains unclear whether the use of risk scoring systems reduces adverse clinical outcomes. Accordingly, this review was conducted to determine whether severity assessment using risk scores influences the prognosis of patients with ACS.

Methods

The Japan Resuscitation Council (JRC) ACS Task Force for the JRC Guidelines 2025 was established by the Japanese Circulation Society and the Japanese Society of Internal Medicine. Following discussions with the Guidelines Editorial Committee, the Population, Intervention, Comparator, Outcome, Study design, and Time frame (PICOST) framework was adopted to guide the systematic review.

P (population): Adult patients (age ≥18 years) diagnosed with acute coronary syndrome.

I (interventions): Standard care with evaluation by risk score.

C (comparators, controls): Standard care without evaluation by risk score.

O (outcomes): n-hospital mortality, in-hospital cardiac arrest, 1-year all-cause mortality, 1-year cardiovascular mortality, in-hospital recurrent ischemia, in-hospital congestive heart failure, 1-year heart failure, and early invasive angiography.

S (study design): Randomized controlled trials (RCTs) published in English; review articles were excluded.

T (time frame): All literature published until November 30, 2024.

This systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and registered with the International Prospective Register of Systematic Reviews (PROSPERO; ID CRD42024556040).²³^,²⁴

Search Strategies

Literature search strategies were developed using Medical Subject Headings (MeSH) and relevant keywords related to ACS, hospitalization, and risk score stratification. The complete search strategy is provided in the Supplementary Appendix. A systematic search of published studies was conducted in MEDLINE, the Cochrane Central Register of Controlled Trials (CENTRAL), and Web of Science to identify relevant articles published from database inception through to November 30, 2024. We included full-text, human studies published in English before November 30, 2024.

Study Selection and Definitions

The study population included adult patients with ACS admitted in an emergency setting. No restrictions were placed on country of origin; however, only studies published in English were included. Studies were eligible for inclusion if they satisfied all of the following criteria: (1) RCT; (2) included patients diagnosed with ACS; and (3) compared risk score stratification care vs. standard care without risk score assessment.

Data Extraction and Management

The following data were extracted: author name(s), article title, journal name, publication year, URL, and abstract. After removing duplicates, the study titles and abstracts were independently screened by 2 reviewers (R.A., K.T.) based on predefined inclusion criteria. In cases of uncertainty, the full text was independently reviewed by the same 2 reviewers. Any disagreements regarding study inclusion or exclusion were resolved through discussion, with final adjudication by a third independent reviewer (T. Mano).

Assessment of the Risk of Bias

The risk of bias in each study and outcome was assessed using the Cochrane Risk of Bias 2 (RoB 2) tool.²⁵ RoB 2 evaluates bias across 5 domains: (1) bias arising from the randomization process; (2) bias because of deviations from intended interventions; (3) bias because of missing outcome data; (4) bias in measurement of the outcome; and (5) bias in the selection of the reported result. Each domain was rated as having ‘low risk’, ‘high risk’, or ‘some concerns’ regarding the bias. Pairs of experienced reviewers (K.T., R.A.) independently evaluated the risk of bias in all included studies. For each domain, studies were categorized as having a ‘low’, ‘high’, or ‘unclear’ risk of bias. A domain was rated as ‘high risk’ if bias was present and likely to affect the outcomes, and ‘low risk’ if bias was absent or present but unlikely to affect the outcomes.

Rating Certainty of Evidence

We applied the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach to assess the certainty of the evidence regarding the potential benefits of risk assessment in patients with ACS.²⁶^,²⁷ The certainty of evidence was rated as ‘high’, ‘moderate’, ‘low’, or ‘very low’ based on the following domains: risk of bias, inconsistency, indirectness, imprecision, and publication bias.

Statistical Analysis

For cluster-RCTs, we adjusted the sample size and number of events to account for clustering using the design effect. The design effect was calculated using the formula: Design effect = 1 + (M − 1) × ICC, where M is the average cluster size and ICC is the intra-cluster correlation coefficient. We used the ICC values reported in the original studies. Adjusted effective sample size and event counts were used in the meta-analysis to avoid unit analysis errors.²⁸

The results were synthesized using a random-effects model to facilitate the pooling of the estimated treatment effects. Dichotomous outcomes were reported as risk ratios (RRs) with corresponding 95% confidence intervals (CIs). Heterogeneity among studies for each outcome was assessed using the I² statistic to quantify inconsistency,²⁹ and was considered substantial if the source of heterogeneity could not be identified and the I² value was ≥50%. A funnel plot was constructed to assess the potential publication bias. All statistical analyses were performed using Review Manager (RevMan) version 5.4.

Results

Literature Search

Figure 1 shows a flow diagram of the study adapted from the PRISMA statement.²³^,²⁴ We identified 10,326 studies in the PubMed, Web of Science, and Cochrane Library databases.

Figure 1.

Flow diagram summarizing the evidence search and study selection.

Four studies were assessed for eligibility based on the titles and abstracts. The full-text review led to the exclusion of 2 studies owing to the clinical trial protocol (n=1) and inappropriate intervention (n=1). Finally, a systematic review of 2 cluster-RCTs comparing risk score-stratification care vs. standard care was conducted.

Study Characteristics

The characteristics of the included studies are summarized in Table 1.

Table 1.

Study Characteristics and Findings

Author, year, country	Name of study	Patients	Comparison	No. patients	In-hospital				1 year			Early invasive angiography
Author, year, country	Name of study	Patients	Comparison	No. patients	Mortality	Cardiac arrest	Recurrent ischemia	Congestive heart failure	Cardiovascular mortality	All-cause mortality	Heart failure	Early invasive angiography
Chew et al. (2021)³⁰ multi-country	AGRIS	2,318 patients with ACS	Standard treatment is given without risk stratification using the GRS	1,183	22 (1.9)	20 (1.7)	94 (7.9)	89 (7.5)		87 (8.0)	115 (10.6)	989 (83.6)
Chew et al. (2021)³⁰ multi-country	AGRIS	2,318 patients with ACS	Routine risk stratification using the GRS	1,135	19 (1.7)	34 (3.0)	18 (1.6)	101 (8.9)		54 (5.2)	120 (11.5)	1,042 (91.8)
Gale et al. (2023)³¹ UK	UKGRIS	3,050 patients with NSTEMI	Patient management without risk stratification using the GRS	1,610					50 (4.0)		71 (5.9)	266 (16.5)
Gale et al. (2023)³¹ UK	UKGRIS	3,050 patients with NSTEMI	Patient management with risk stratification using the GRS	1,440					43 (3.8)		42 (3.7)	287 (19.9)

Unless indicated otherwise, data are presented as n (%). ACS, acute myocardial infarction; GRACE, Global Registry of Acute Coronary Events; GRS, GRACE risk score; NSTEMI, non-ST-segment elevation myocardial infarction.

Chew et al.³⁰ conducted a prospective cluster (hospital level), randomized, open-label, blinded-endpoint (PROBE) clinical trial with 2,318 patients with ACS to assess the effect of routine GRS implementation on guideline-indicated treatments and clinical outcomes of hospitalized patients.

Early invasive angiography and in-hospital events included mortality, recurrent ischemia, cardiac arrest, and congestive heart failure. Early invasive treatment and recurrent ischemia were increased compared with the standard care group (early invasive treatment: GRS 1,042 [91.8%] of 1,135 vs. standard 989 [83.6%] of 1,183, OR 2.17, 95% CI 1.22–3.87, P=0.008; recurrent ischemia: GRS 18 [1.6%] of 1,135 vs. standard 94 [7.9%] of 1,183, OR 0.21, 95% CI 0.07–0.68, P=0.009). However, there were no significant differences in the other outcomes. One-year critical outcomes of all-cause mortality and heart failure have also been reported. In 1 year, 96 patients in the GRS group and 91 patients in the standard care group had not been followed up; the reasons for this are unknown. GRS intervention was not associated with a reduction in 1-year critical outcomes of all-cause mortality and heart failure (1-year all-cause mortality: GRS 54 [5.2%] of 1,044 vs. standard care 87 [8.0%] of 1,087, OR 0.60, 95% CI 0.32–1.15, P=0.12; 1-year heart failure: GRS 120 [11.5%] of 1,044 vs. standard care 115 [10.6%] of 1,087, OR 1.16, 95% CI 0.58–2.30, P=0.68), and this study was stopped prematurely owing to futility.

Furthermore, in the subanalysis of high-risk patients (GRS >118), the incidence of 1-year all-cause mortality was significantly lower randomized to the GRS intervention, but a lower rate of mortality (GRS 30 [4.5%] of 668 vs. standard care 56 [8.8%] of 639, OR 0.44, 95% CI 0.21–0.91, P=0.03). GRS implementation was associated with an increase in early invasive treatment and a reduction in in-hospital recurrent ischemia but did not affect other outcomes. In high-risk patients, it was only associated with a decrease in 1-year mortality.

The United Kingdom GRACE Risk Intervention Study (UKGRIS)³¹ was a cluster RCT in which 3,050 patients with suspected NSTE-ACS were randomly assigned to standard care or care according to the GRS and associated guidelines. Early invasive treatment was increased compared with the standard care group (GRS: 287 [19.9%] of 1,440 vs. standard 266 [16.5%] of 1,610, OR 1.26, 95% CI 1.05–1.51, P=0.01). Furthermore, the primary outcomes were 1-year cardiovascular mortality and 1-year heart failure. These outcomes were not significantly improved by GRS.

Risk of Bias

The risks of bias, namely the randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, selection of the reported result, and overall risk, were assessed for each study (Table 2).

Table 2.

Evidence Profile

	No. studies	Study design	Certainty assessment					No. patients		Effect		Certainty	Importance
	No. studies	Study design	Risk of bias	Inconsistency	Indirectness	Imprecision	Other considerations	GRACE	Standard	Relative (95% CI)	Absolute (95% CI)	Certainty	Importance
In-hospital mortality	1	RCT	Not serious	Not serious	Not serious	Very serious^†	None	1/64	1/66	OR 1.03 (0.06–16.85)	0 per 1,000 (14 fewer to 240 more per 1,000)	⊕⊕○○ Low	Critical
1-year all-cause mortality	1	RCT	Serious^‡	Not serious	Not serious	Serious^†	None	3/64	5/66	OR 0.60 (0.14–2.62)	30 fewer per 1,000 (65 fewer to 123 more per 1,000)	⊕⊕○○ Low	Critical
1-year all-cause mortality (AGRIS high risk)	1	RCT	Serious^‡	Not serious	Not serious	Very serious^†,§	None	3/64	5/61	OR 0.55 (0.13–2.41)	37 fewer per 1,000 (71 fewer to 116 more per 1,000)	⊕⊕○○ Low	Critical
1-year cardiovascular mortality	1	RCT	Not serious	Not serious	Not serious	Serious^†	None	11/280	12/305	OR 1.00 (0.43–2.30)	0 per 1,000 (22 fewer to 51 more per 1,000)	⊕⊕⊕○ Moderate	Critical
In-hospital cardiac arrest	1	RCT	Not serious	Not serious	Not serious	Very serious^†	None	2/64	1/66	OR 2.10 (0.19–23.71)	17 more per 1,000 (12 fewer to 344 more per 1,000)	⊕⊕○○ Low	Critical
In-hospital recurrent ischemia	1	RCT	Not serious	Not serious	Not serious	Very serious^†	None	1/64	5/66	OR 0.19 (0.02–1.71)	61 fewer per 1,000 (74 fewer to 54 more per 1,000)	⊕⊕○○ Low	Critical
In-hospital congestive heart failure	1	RCT	Not serious	Not serious	Not serious	Serious^†	None	6/64	5/66	OR 1.26 (0.37–4.36)	20 more per 1,000 (48 fewer to 255 more per 1,000)	⊕⊕⊕○ Moderate	Important
1-year heart failure (AGRIS)	1	RCT	Serious^‡,¶	Not serious	Serious^¶	Serious^†	None	7/64	7/66	OR 1.04 (0.34–3.14)	4 more per 1,000 (70 fewer to 227 fewer per 1,000)	⊕○○○ Very low	Important
1-year heart failure (UKGRIS)	1	RCT	Serious^¶	Not serious	Serious^¶	Serious^†	None	11/280	18/300	OR 0.64 (0.30–1.38)	22 fewer per 1,000 (42 fewer to 23 fewer per 1,000)	⊕○○○ Very low	Important
1-year heart failure (AGRIS high risk)	1	RCT	Serious^†,¶	Not serious	Serious^§,¶	Very serious^†,§	None	10/64	8/61	OR 1.23 (0.45–3.35)	30 more per 1,000 (72 fewer to 308 fewer per 1,000)	⊕○○○ Very low	Important
Early invasive angiography (AGRIS)	1	RCT	Serious^††	Not serious	Not serious	Very serious^†	None	58/64	55/66	OR 1.93 (0.67–5.59)	775 more per 1,000 (275 fewer to 3,825 more per 1,000)	⊕⊕⊕○ Moderate	Important
Early invasive angiography (UKGRIS)	1	RCT	Not serious	Not serious	Not serious	Serious^†	None	58/290	54/325	OR 1.25 (0.83–1.89)	42 more per 1,000 (28 fewer to 148 more per 1,000)	⊕⊕⊕○ Moderate	Important

^†Due to the small number of analyzed RCTs or the small number of events, imprecision was judged to be ‘very serious’ or ‘serious’. ^‡In the AGRIS, there were unknown cases that could not be followed up for up to 1 year, and the risk of bias was judged to be ‘serious’. ^§The AGRIS high-risk subgroup was defined as GRACE score >140, but the event rate was similar to that of the overall population, limiting the differential effects of stratification, and imprecision was judged to be ‘very serious’ or ‘serious’. ^¶The definition of heart failure at 1 year differed between studies, and the risk of bias and indirectness were judged to be ‘serious’. ^††There was patient selection bias, and the risk of bias was judged to be ‘serious’. AGRIS, Australian GRACE Risk Intervention Study; CI, confidence interval; GRACE, Global Registry of Acute Coronary Events; OR, odds ratio; RCT, randomized controlled trial; UKGRIS, United Kingdom GRACE Risk Intervention Study.

The Australian GRACE Risk Intervention Study (AGRIS) had a high risk of bias because of loss to follow up and concerns about deviation from the intended intervention. The AGRIS and UGRIS studies did not publish details on the definitions of heart failure and myocardial infarction, and there may have been gaps in the number of events. These were considered to have a high risk of bias in GRADE indirectness.

Outcomes

A forest plot of the results is shown in Figure 2. Both studies were cluster-RCT; after adjusting for sample size and number of events to account for cluster effects, a meta-analysis was performed. The AGRIS enrolled patients, including those with STEMI, whereas the UKGRIS excluded patients with STEMI. Baseline risk profiles and invasive treatment rates differed significantly between the 2 studies. Therefore, although the 2 studies had common outcomes (early invasive coronary angiography and heart failure), they were not integrated, and separate analyses were performed.

Figure 2.

Forest plots of the incidence of in-hospital mortality, 1-year all-cause mortality, 1-year cardiovascular mortality, in-hospital cardiac arrest, in-hospital recurrent ischemia, in-hospital congestive heart failure, 1-year heart failure, and early invasive angiography. AGRIS, Australian GRACE Risk Intervention Study; CI, confidence interval; GRACE, Global Registry of Acute Coronary Events; UKGRIS, United Kingdom GRACE Risk Intervention Study.

Only 1 RCT was identified for the critical outcomes of in-hospital mortality, 1-year cardiovascular mortality, and 1-year all-cause mortality. Regarding in-hospital mortality, 1 (1.6%) of 64 patients in the GRS group and 1 (1.5%) of 66 patients in the standard care group died. Regarding 1-year cardiovascular mortality, 11 (3.9%) of 280 patients in the GRS group and 12 (3.9%) of 305 patients in the standard care group died. Regarding 1-year all-cause mortality, 3 (4.7%) of 64 patients in the GRS group and 5 (7.8%) of 66 patients in the standard care group died. Regarding the 1-year all-cause mortality in the AGRIS high-risk group, 3 (4.7%) of 64 patients in the GRS group and 5 (8.2%) of 61 patients in the standard care group died.

No statistically or clinically significant differences in mortality outcomes were observed between the GRS intervention and standard care groups. The observed absolute difference in 1-year all-cause mortality for the AGRIS high-risk subgroup was 37 per 1,000, with wide confidence intervals (−71 to +116 per 1,000), crossing both potential benefit and harm. This should be interpreted as ‘no clear difference’ in mortality risk, and the certainty of the evidence was downgraded for imprecision.

Notably, although the AGRIS high-risk subgroup was defined as having a GRACE score >140, the control event rate was nearly identical to that of the overall AGRIS population (5/61 vs. 5/66), suggesting that risk stratification using this threshold may not have resulted in a meaningful separation of clinical risk.

Only 1 RCT identified the critical outcomes of in-hospital cardiac arrest and in-hospital recurrent ischemia. Regarding in-hospital cardiac arrest, 2 (3.1%) of 64 patients in the GRS group and 1 (1.5%) of 66 patients in the standard care group experienced in-hospital arrest. Regarding in-hospital recurrent ischemia, 1 (1.6%) of 64 patients in the GRS group and 5 (7.8%) of 66 patients in the standard care group experienced in-hospital recurrent ischemia. No significant differences were observed between the GRS intervention and standard care groups in terms of important outcomes such as in-hospital cardiac arrest and in-hospital recurrent ischemia. The effectiveness of the GRS intervention was not confirmed.

Each RCT was analyzed for important outcomes of in-hospital and 1-year congestive heart failure. Regarding in-hospital congestive heart failure, 6 (9.4%) of 64 patients in the GRS group and 5 (7.8%) of 66 patients in the standard care group showed in-hospital congestive heart failure. Regarding 1-year heart failure in the AGRIS, 7 (10.9%) of 64 patients in the GRS group and 7 (10.6%) of 66 patients in the standard care group showed 1-year heart failure. Regarding 1-year heart failure in the UKGRIS, 11 (3.9%) of 280 patients in the GRS group and 18 (6.0%) of 300 patients in the standard care group showed 1-year heart failure. Regarding 1-year heart failure in the AGRIS high-risk sub-study, 10 (15.9%) of 64 patients in the GRS group and 8 (13.1%) of 61 patients in the standard care group showed 1-year heart failure. No significant differences were observed between the GRS intervention and standard care groups in terms of important outcomes, such as in-hospital and 1-year congestive heart failure, and the effectiveness of the GRS intervention was not confirmed.

The important outcomes of early invasive angiography were evaluated. Regarding early invasive angiography in the AGRIS, 58 (90.6%) of 64 patients in the GRS group and 55 (83.3%) of 66 patients in the standard care group underwent early invasive angiography. Regarding early invasive angiography in the UKGRIS, 58 (20.0%) of 290 patients in the GRS group and 54 (16.6%) of 325 patients in the standard care group underwent early invasive angiography. No significant differences were observed between the GRS intervention and standard care groups in terms of early invasive angiography, and the effectiveness of the GRS intervention was not confirmed.

Certainty of Evidence

We assessed the certainty of the evidence for each outcome and summarized the evidence profiles in Table 2. The level of evidence was considered low because the patient outcome definition differed between the 2 groups, and I² >50% and variation in point estimation.

Discussion

This systematic review and meta-analysis evaluated whether risk score-guided management, specifically using GRS, improves clinical outcomes in patients with ACS. Although risk scores such as GRACE have demonstrated strong predictive accuracy for mortality and myocardial infarction,³² our findings highlight a critical distinction between predictive performance and clinical utility. The implementation of risk scores may change clinical decision-making (e.g., increasing early invasive procedures) but does not necessarily lead to improved patient-centered outcomes.

Two cluster-RCTs (AGRIS and UKGRIS) were included in this review. The AGRIS enrolled patients, including those with STEMI, whereas the UKGRIS excluded patients with STEMI. Baseline risk profiles and invasive treatment rates differed significantly between the 2 studies. Both trials originally reported a higher rate of early invasive angiography in the GRS-guided groups. However, after adjusting for clustering effects in our meta-analysis, no significant difference was observed in the early invasive angiography rates between the intervention and control groups.

The AGRIS reported a reduction in in-hospital recurrent ischemia with GRS-guided care and increased adherence to guideline-recommended invasive therapies. However, this did not translate into a significant reduction in 1-year all-cause mortality or heart failure in the overall population. A potential mortality benefit was observed in the high-risk subgroup (GRS >118). However, this was exploratory and should be interpreted with caution. Similarly, the UKGRIS found an increase in early invasive therapy in the GRS group, but no improvement in 1-year cardiovascular mortality or heart failure.

Importantly, both trials had methodological issues, including high loss to follow up, unclear endpoint definitions, and protocol deviations, leading to concerns about indirectness and imprecision. The early termination of both studies further reduces the certainty of the evidence.

Beyond individual outcomes, our findings raise questions about the utility of risk scores in guiding clinical care pathways such as ICU/CCU admission. Before reperfusion therapy was established as the initial treatment for ACS, treatment in the ICU/CCU was associated with improved outcomes. However, with the advent of rapid reperfusion therapy, the risk of ACS patients developing complications requiring ICU/CCU admission has decreased. A retrospective cohort study⁴ showed that ICU admission improved 30-day mortality in patients with STEMI but not in those with non-ST-segment elevation myocardial infarction (NSTEMI), suggesting that uniform ICU use may no longer be beneficial. Current guidelines recommend ICU/CCU admission for high-risk ACS patients but do not define what constitutes ‘high-risk’.⁵^–⁷ This led the JRC ACS Task Force to explore whether risk scores such as the GRS could aid in ICU/CCU admission decision-making.³³ Early invasive strategies have been shown to improve outcomes in high-risk NSTEMI patients with a GRACE score ≥140.³⁴^–³⁶ However, in the present review, no consistent benefit was observed across all outcomes in patients stratified as high-risk using the GRS. One possible explanation for this discrepancy is that patients with a GRS >140 often present with obvious clinical features of high-risk ACS, such as hemodynamic instability or significant electrocardiogram changes, which may prompt clinicians to pursue early invasive management, regardless of the use of formal risk scoring. In this context, GRS may provide limited additional value. Nevertheless, risk scores remain valuable in settings where clinical judgment alone may be insufficient, such as institutions with less experience in ACS management or where cardiology specialists are not readily available. In such environments, structured risk stratification tools, such as the GRS, may assist in identifying high-risk patients who would be under-recognized and undertreated. Future studies are warranted to explore the impact of risk score implementation in specific clinical contexts.

Given that both of the included studies used only the GRS and differed in patient populations (e.g., inclusion or exclusion of patients with STEMI), the generalizability of our findings is limited. First, the number of included trials was small, and outcome matching across studies was insufficient. Therefore, caution is warranted when interpreting the results of this meta-analysis. Our results do not demonstrate a consistent benefit of risk score-guided care for ACS, either in-hospital or at 1-year follow up. However, further research is needed – particularly studies that test other risk scores or evaluate the use of risk stratification to guide ICU/CCU admission – to determine whether risk-based decision-making can improve outcomes for patients with ACS.

Study Limitations

The present study has several limitations. First, in both RCTs, outcome information was collected using data from electronic medical records; however, detailed determination of endpoints may not have been possible, and there may have been misclassification of events. Second, the GRS recommendations for patient treatment were applied, which may have promoted more intensive treatment. Third, baseline characteristics were unbalanced between the 2 study groups. The UKGRIS excluded patients with STEMI, whereas the AGRIS included more patients at high risk for Killip grade 4 cardiogenic shock, and differences in patient background may have influenced the results. Fourth, there were unknown cases lost to follow up for up to 1 year in the AGRIS, which may have affected the power of the study and led to an overall low certainty of evidence. Last, therapeutic interventions were performed regardless of the baseline, and the GRS may not have been involved in secondary prevention, which may have been influenced by health service structure, workforce, and funding models.

Conclusions

This systematic review found that risk score-guided management in patients with ACS, particularly using GRS, was not associated with increased use of early invasive angiography or improvements in in-hospital and 1-year clinical outcomes. This review highlights the limitations of the current evidence supporting the usefulness of risk score-guided management in ACS care. Further studies are needed to clarify whether management strategies based on risk stratification can improve clinical outcomes.

Acknowledgments

The authors thank Mr. Shunya Suzuki and Ms. Tomoko Nagaoka, librarians at Dokkyo Medical University, Tochigi, Japan, for their assistance in searching for articles. This work was supported by the Japan Resuscitation Council, Japanese Circulation Society, MHLW grant no. 24FA1017, and the Intramural Research Fund for Cardiovascular Disease of the National Cerebral and Cardiovascular Center (23-B-7).

Disclosures

T. Matoba is a member of Circulation Reports’ Editorial Team. T. Matoba reported research grants from Amgen. T. Mano received research grants from Abbott Medical Japan. The other authors declare no conflicts of interest with regard to this article.

Data Availability

The deidentified participant data will be shared on a request basis. Please contact the corresponding author directly to request data sharing.

Supplementary Files

Please find supplementary file(s);

https://doi.org/10.1253/circrep.CR-25-0162

References

1. Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380: 2095–2128.
2. Puymirat E, Simon T, Cayla G, Cottin Y, Elbaz M, Coste P, et al. Acute myocardial infarction: Changes in patient characteristics, management, and 6-month outcomes over a period of 20 years in the FAST-MI program (French Registry of Acute ST-Elevation or Non-ST-Elevation Myocardial Infarction) 1995 to 2015. Circulation 2017; 136: 1908–1919.
3. Jernberg T, Johanson P, Held C, Svennblad B, Lindbäck J, Wallentin L. Association between adoption of evidence-based treatment and survival for patients with ST-elevation myocardial infarction. JAMA 2011; 305: 1677–1684.
4. Valley TS, Iwashyna TJ, Cooke CR, Sinha SS, Ryan AM, Yeh RW, et al. Intensive care use and mortality among patients with ST elevation myocardial infarction: Retrospective cohort study. BMJ 2019; 365: l1927.
5. Byrne RA, Rossello X, Coughlan JJ, Barbato E, Berry C, Chieffo A, et al. 2023 ESC guidelines for the management of acute coronary syndromes. Eur Heart J 2023; 44: 3720–3826.
6. Kimura K, Kimura T, Ishihara M, Nakagawa Y, Nakao K, Miyauchi K, et al. JCS 2018 guideline on diagnosis and treatment of acute coronary syndrome. Circ J 2019; 83: 1085–1196.
7. Rao SV, O’Donoghue ML, Ruel M, Rab T, Tamis-Holland JE, Alexander JH, et al. 2025 ACC/AHA/ACEP/NAEMSP/SCAI guideline for the management of patients with acute coronary syndromes: A report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation 2025; 151: e771–e862.
8. Shavadia JS, Chen AY, Fanaroff AC, de Lemos JA, Kontos MC, Wang TY. Intensive care utilization in stable patients with ST-segment elevation myocardial infarction treated with rapid reperfusion. JACC Cardiovasc Interv 2019; 12: 709–717.
9. Hamm CW, Goldmann BU, Heeschen C, Kreymann G, Berger J, Meinertz T. Emergency room triage of patients with acute chest pain by means of rapid testing for cardiac troponin T or troponin I. N Engl J Med 1997; 337: 1648–1653.
10. Antman EM, Cohen M, Bernink PJ, McCabe CH, Horacek T, Papuchis G, et al. The TIMI risk score for unstable angina/non-ST elevation MI: A method for prognostication and therapeutic decision making. JAMA 2000; 284: 835–842.
11. Pollack CV Jr, Sites FD, Shofer FS, Sease KL, Hollander JE. Application of the TIMI risk score for unstable angina and non-ST elevation acute coronary syndrome to an unselected emergency department chest pain population. Acad Emerg Med 2006; 13: 13–18.
12. Scirica BM, Morrow DA, Budaj A, Dalby AJ, Mohanavelu S, Qin J, et al. Ischemia detected on continuous electrocardiography after acute coronary syndrome: Observations from the MERLIN-TIMI 36 (Metabolic Efficiency With Ranolazine for Less Ischemia in Non-ST-Elevation Acute Coronary Syndrome-Thrombolysis In Myocardial Infarction 36) trial. J Am Coll Cardiol 2009; 53: 1411–1421.
13. Boersma E, Pieper KS, Steyerberg EW, Wilcox RG, Chang WC, Lee KL, et al. Predictors of outcome in patients with acute coronary syndromes without persistent ST-segment elevation: Results from an international trial of 9461 patients. The PURSUIT Investigators. Circulation 2000; 101: 2557–2567.
14. Granger CB, Goldberg RJ, Dabbous O, Pieper KS, Eagle KA, Cannon CP, et al. Predictors of hospital mortality in the global registry of acute coronary events. Arch Intern Med 2003; 163: 2345–2353.
15. Eagle KA, Lim MJ, Dabbous OH, Pieper KS, Goldberg RJ, Van de Werf F, et al. A validated prediction model for all forms of acute coronary syndrome: Estimating the risk of 6-month postdischarge death in an international registry. JAMA 2004; 291: 2727–2733.
16. Fox KA, Dabbous OH, Goldberg RJ, Pieper KS, Eagle KA, Van de Werf F, et al. Prediction of risk of death and myocardial infarction in the 6 months after presentation with acute coronary syndrome: Prospective multinational observational study (GRACE). BMJ 2006; 333: 1091.
17. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: A severity of disease classification system. Crit Care Med 1985; 13: 818–829.
18. Zimmerman JE, Kramer AA, McNair DS, Malila FM. Acute Physiology and Chronic Health Evaluation (APACHE) IV: Hospital mortality assessment for today’s critically ill patients. Crit Care Med 2006; 34: 1297–1310.
19. Abu-Assi E, Ferreira-González I, Ribera A, Marsal JR, Cascant P, Heras M, et al. Do GRACE (Global Registry of Acute Coronary Events) risk scores still maintain their performance for predicting mortality in the era of contemporary management of acute coronary syndromes? Am Heart J 2010; 160: 826–834.e1–e3.
20. Meune C, Drexler B, Haaf P, Reichlin T, Reiter M, Meissner J, et al. The GRACE score’s performance in predicting in-hospital and 1-year outcome in the era of high-sensitivity cardiac troponin assays and B-type natriuretic peptide. Heart 2011; 97: 1479–1483.
21. Eggers KM, Kempf T, Venge P, Wallentin L, Wollert KC, Lindahl B. Improving long-term risk prediction in patients with acute chest pain: The Global Registry of Acute Coronary Events (GRACE) risk score is enhanced by selected nonnecrosis biomarkers. Am Heart J 2010; 160: 88–94.
22. Yan AT, Yan RT, Tan M, Casanova A, Labinaz M, Sridhar K, et al. Risk scores for risk stratification in acute coronary syndromes: Useful but simpler is not necessarily better. Eur Heart J 2007; 28: 1072–1078.
23. Page MJ, Moher D, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. PRISMA 2020 explanation and elaboration: Updated guidance and exemplars for reporting systematic reviews. BMJ 2021; 372: n160.
24. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. J Clin Epidemiol 2009; 62: e1–e34.
25. Sterne JAC, Savović J, Page MJ, Elbers RG, Blencowe NS, Boutron I, et al. RoB 2: A revised tool for assessing risk of bias in randomised trials. BMJ 2019; 366: l4898.
26. Atkins D, Eccles M, Flottorp S, Guyatt GH, Henry D, Hill S, et al. Systems for grading the quality of evidence and the strength of recommendations I: Critical appraisal of existing approaches. BMC Health Serv Res 2004; 4: 38.
27. Guyatt GH, Oxman AD, Schünemann HJ, Tugwell P, Knottnerus A. GRADE guidelines: A new series of articles in the Journal of Clinical Epidemiology. J Clin Epidemiol 2011; 64: 380–382.
28. Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al., editors. Cochrane Handbook for Systematic Reviews of Interventions, version 6.5 (updated August 2024). Cochrane, 2024. www.training.cochrane.org/handbook.
29. Huedo-Medina TB, Sánchez-Meca J, Marín-Martínez F, Botella J. Assessing heterogeneity in meta-analysis: Q statistic or I² index? Psychol Methods 2006; 11: 193–206.
30. Chew DP, Hyun K, Morton E, Horsfall M, Hillis GS, Chow CK, et al. Objective risk assessment vs standard care for acute coronary syndromes: A randomized clinical trial. JAMA Cardiol 2021; 6: 304–313.
31. Gale CP, Stocken DD, Aktaa S, Reynolds C, Gilberts R, Brieger D, et al. Effectiveness of GRACE risk score in patients admitted to hospital with non-ST elevation acute coronary syndrome (UKGRIS): Parallel group cluster randomised controlled trial. BMJ 2023; 381: e073843.
32. Fujii T, Suzuki T, Torii S, Murakami T, Nakano M, Nakazawa G, et al. Diagnostic accuracy of Global Registry of Acute Coronary Events (GRACE) risk score in ST-elevation myocardial infarction for in-hospital and 360-day mortality in Japanese patients. Circ J 2014; 78: 2950–2954, doi:10.1253/circj.CJ-14-0808.
33. Kikuchi M, Tahara Y, Yamaguchi J, Nakashima T, Nomura O, Tanaka A, et al. Executive summary: Acute coronary syndrome in the Japan Resuscitation Council Guidelines for Resuscitation 2020. Circ J 2023; 87: 866–878, doi:10.1253/circj.CJ-23-0096.
34. Mehta SR, Granger CB, Boden WE, Steg PG, Bassand JP, Faxon DP, et al. Early versus delayed invasive intervention in acute coronary syndromes. N Engl J Med 2009; 360: 2165–2175.
35. Kofoed KF, Kelbæk H, Hansen PR, Torp-Pedersen C, Høfsten D, Kløvgaard L, et al. Early versus standard care invasive examination and treatment of patients with non-ST-segment elevation acute coronary syndrome. Circulation 2018; 138: 2741–2750, doi:10.1161/CIRCULATIONAHA.118.037152.
36. Ozaki Y, Tobe A, Onuma Y, Shirai S, Kimura K, Amano T, et al. CVIT expert consensus document on primary percutaneous coronary intervention (PCI) for acute coronary syndromes (ACS) in 2024. Cardiovasc Interv Ther 2024; 39: 335–375, doi:10.1007/s12928-024-01036-y.

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