The HEART score for early rule out of acute coronary syndromes in the emergency department: a systematic review and meta-analysis

Abstract

Aims:

The objective of this systematic review was to summarise the current evidence on the diagnostic accuracy of the HEART score for predicting major adverse cardiac events in patients presenting with undifferentiated chest pain to the emergency department.

Methods and results:

Two investigators independently searched Medline, Embase and Cochrane databases between 2008 and May 2016 identifying eligible studies providing diagnostic accuracy data on the HEART score for predicting major adverse cardiac events as the primary outcome. For the 12 studies meeting inclusion criteria, study characteristics and diagnostic accuracy measures were systematically extracted and study quality assessed using the QUADAS-2 tool. After quality assessment, nine studies including data from 11,217 patients were combined in the meta-analysis applying a generalised linear mixed model approach with random effects assumption (Stata 13.1). In total, 15.4% of patients (range 7.3–29.1%) developed major adverse cardiac events after a mean of 6 weeks’ follow-up. Among patients categorised as ‘low risk’ and suitable for early discharge (HEART score 0–3), the pooled incidence of ‘missed’ major adverse cardiac events was 1.6%. The pooled sensitivity and specificity of the HEART score for predicting major adverse cardiac events were 96.7% (95% confidence interval (CI) 94.0–98.2%) and 47.0% (95% CI 41.0–53.5%), respectively.

Conclusions:

Patients with a HEART score of 0–3 are at low risk of incident major adverse cardiac events. As 3.3% of patients with major adverse cardiac events are ‘missed’ by the HEART score, clinicians must ask whether this risk is acceptably low for clinical implementation.

Keywords

HEART score acute coronary syndromes diagnostic accuracy sensitivity and specificity emergency medicine clinical decision rules

Background

Chest pain is one of the most common reasons for emergency hospital admission.¹ Hospital and emergency department (ED) crowding is a growing problem and is associated with higher patient mortality.² This highlights the pressing need for diagnostic strategies that can rapidly ‘rule out’ acute coronary syndromes (ACSs) and avoid unnecessary hospital admission.

While it may be possible to achieve that within as little as one hour of arrival using high sensitivity cardiac troponin (hs-cTn) assays, such strategies still require two blood tests. Furthermore, high sensitivity assays are not available in all hospitals.³ The HEART score is a simple tool that can be used at the time of a patient’s first presentation to the ED. It was designed to identify a group of patients that can be immediately discharged from the ED following a single blood test (Table 1).⁴ Patients with a HEART score of 0–3 are considered ‘low risk’ and eligible for potential immediate discharge.⁴

Table 1.

The HEART score.⁴

HEART score
History	Highly suspicious	2
	Moderately suspicious	1
	Slightly suspicious	0
ECG	Significant ST-depression	2
	Non-specific repolarisation disturbance	1
	Normal	0
Age	⩾65 years	2
	>45–<65 years	1
	⩽45 years	0
Risk factors	⩾3 risk factors,^a or history of atherosclerotic disease^b	2
	1 or 2 risk factors	1
	No risk factors known	0
Troponin	⩾3× normal limit	2
	>1–<3× normal limit	1
	⩽ normal limit	0

Risk factors include: currently treated diabetes mellitus, current or recent smoker, diagnosed and/or treated hypertension, diagnosed hypercholesterolaemia, family history of coronary artery disease, obesity (body mass index >30).

History of atherosclerotic disease includes: coronary revascularisation, myocardial infarction, stroke, or peripheral arterial disease, irrespective of the risk factors for coronary artery disease.

We aimed systematically to appraise the available evidence to determine the diagnostic accuracy of the HEART score for predicting major adverse cardiac events (MACEs) in patients with suspected ACS in the ED.

Methods

Search strategy and eligibility criteria

This systematic review was performed in accordance with the PRISMA guidelines and Cochrane methodology for diagnostic test accuracy reviews.^5,6 We searched the Medline, Embase and Cochrane databases for the term ‘HEART score’ (in all fields) from 1 January 2008 to 15 May 2016. The time period for the publication was restricted to start in 2008, the year the HEART score was first derived and published.⁴ The reference lists of relevant publications were also hand searched.

Retrospective and prospective cohort studies, as well as randomised controlled trials investigating patients with possible ACSs in the ED, were eligible. In order to be considered for inclusion, studies needed to evaluate the HEART score at the time of arrival, and to report the prevalence of acute myocardial infarction (AMI) and the incidence of MACEs as outcomes. We excluded conference abstracts not allowing for sufficient assessment of the methodological approach. Likewise, publications in languages other than English, Dutch and German were excluded.

Index test and outcome measures

The HEART score is defined as a composite score ranging from 0 to 10 points. Each of the five acronym domains (history, electrocardiogram (ECG), age, risk factors and troponin) is scored with 0 to 2 points according to the original definition (Table 1).

The primary outcome of MACEs was defined as a composite of prevalent or incident AMI, percutaneous coronary intervention, coronary artery bypass graft surgery and all-cause death. Studies only reporting the prevalence of AMI were also considered for the initial analyses. The third universal definition of AMI, consistent with a rise and/or fall of a cardiac biomarker with minimally one result above the 99th percentile upper reference limit in the context of a patient presenting with cardiac ischaemia (ECG changes or imaging evidence),⁷ was considered the optimal reference standard.

Patients with a HEART score of 0–3 points are considered at low risk of developing MACEs and therefore constitute a patient group eligible for potential immediate discharge. The remaining patients with a score between 4 and 10 points were considered at high risk of developing MACEs.^4,8,9

Data extraction

All results of the complete search on all databases were screened based on title and abstract for potential eligibility by two authors (PvdB and RB). Both authors then independently undertook a full-text review, after which eligible studies were short-listed for data extraction. Discrepancies between investigators were solved by discussion. Trial authors were contacted for missing data and clarifications whenever necessary. We extracted and collated all data required for a diagnostic accuracy assessment including 2×2 tables for the HEART scores 0–3 and 4–10 with respective MACEs and/or AMI rates, prevalence of MACEs and/or AMI, proportion of low-risk patients with HEART score of 0–3 and the percentage of missed MACEs and/or AMI.

The quality of eligible primary diagnostic accuracy cohort studies was assessed with a modified version of the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies – version 2) tool to suit the purpose of this systematic review.¹⁰ The modified QUADAS-2 tool is provided in the Supplementary Appendix.

Statistical analysis

Studies deemed to have an acceptable risk of bias were included for further meta-analysis. The analysis was conducted using STATA Statistical Software IC package, version 13.1 (StataCorp LP, College Station, TX, USA) applying MIDAS and METANDI commands utilising a generalised linear mixed model approach with random effects assumption to generate pooled estimates of diagnostic accuracy. Between-study heterogeneity was assessed with the Cochrane Q chi-square test and the I² statistics. With diagnostic test accuracy studies heterogeneity is to be expected, therefore requiring a random effects model approach by default.¹¹ We generated a summary receiver operating characteristic (ROC) curve, which allowed calculation of the area under the curve (AUC) as a global measure of diagnostic test performance as well as a visual evaluation of heterogeneity and any potential threshold effect.¹² To determine the potential effects of publication bias a Deeks funnel plot was obtained, with P<0.10 for the slope coefficient considered to indicate significant asymmetry and therefore a high likelihood of publication bias.¹³

Results

Our literature search identified 218 articles of which 18 were considered potentially eligible for inclusion based on title and abstract screening. After independent review 12 studies met the inclusion criteria for this review providing the necessary data allowing for computation of diagnostic accuracy measures.^8,9,14–23 General study characteristics are summarised in Table 2. A more detailed summary of inclusion and exclusion criteria, precise definitions of outcomes, the exact definitions utilised for the calculation of the HEART score, as well as the cardiac troponin assays used and the timing of troponin testing, is provided in the Supplementary Appendix. Test characteristics for each individual study including 2×2 tables, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), as well as the proportion of patients identified as low risk (HEART score 0–3) are presented in Table 3.

Table 2.

Characteristics of included studies.

Study	Year	Country	Study design	Number of sites	Study period
Backus et al. ⁸	2010	Netherlands	Retrospective cohort study	4	1 Jan–31 Mar 2006
Fesmire et al. ¹⁴	2012	USA	Retrospective cohort study	1	13-month period
Backus et al. ⁹	2013	Netherlands	Prospective cohort study	10	Oct 2008–Nov 2009
Six et al. ¹⁵	2013	9 Asia-Pacific countries	Retrospective cohort study	14	Nov 2007–Dec 2010
Melki and Jernberg ¹⁶	2013	Sweden	Retrospective cohort study	1	1 Jan–12 Feb 2009
Marcoon et al. ¹⁷	2013	USA	Retrospective cohort study	1	1999–2009
Visser et al. ¹⁸	2014	Netherlands	Prospective cohort study	1	1 Dec 2012–31 Jul 2013
Leite et al. ¹⁹	2015	Portugal	Retrospective cohort study	1	23–29 Jan 2012 and 23–29 Jul 2012
Carlton et al. ²⁰	2015	UK	Retrospective cohort study	1	Jul 2012–Aug 2013
Bodapati et al. ²¹	2016	Australia	Retrospective cohort study	1	1 Jan 2013–16 May 2013
Sun et al. ²²	2016	USA	Retrospective cohort study	8	1 Jun 1999–Aug 2001
Santi et al. ²³	2016	Italy	Retrospective cohort study	1	1 Jan–30 Jun 2014

Table 3.

Diagnostic and predictive indices of the HEART score for predicting major adverse cardiac events or acute myocardial infarction (95% confidence intervals in parentheses).

Study	Outcome	N	Sensitivity	Specificity	NPV	PPV	Proportion low risk^a	Outcome prevalence	Missed outcome^a
Backus 2010	MACE within 6 weeks	880	98.1% (94.6–99.6)	41.6% (37.9–45.2)	99.0% (97.1–99.8)	26.9% (23.3–30.7)	32.5%	18.0%	1.0%
Fesmire 2012	MACE within 30 days	2148	92.4% (88.9–95.1)	48.5% (47.2–51.8)	97.4% (96.2–98.3)	23.9% (21.5–26.4)	43.3%	14.7%	2.6%
Backus 2013	MACE within 6 weeks	2388	96.3% (94.0–97.9)	43.2% (41.0–45.4)	98.3% (97.2–99.0)	25.8% (23.6–28.1)	36.4%	17.0%	1.7%
Six 2013	MACE within 30 days	2906	96.3% (93.8–97.9)	31.8% (30.0–33.7)	98.3% (97.2–99.0)	17.3% (15.7–19.0)	28.2%	12.9%	1.7%
Melki 2013	MACE within 3 months	410	96.7% (82.8–99.9)	64.7% (59.7–69.6)	99.6% (97.8–100)	17.8% (12.3–24.5)	60.2%	7.3%	0.4%
Marcoon 2013	MACE within 30 days	8252	75.5% (72.0–78.7)	67.5% (66.5–68.6)	96.9% (96.4–97.4)	16.8% (15.5–18.2)	64.1%	8.0%	3.1%
Visser 2014	MACE within 6 weeks	255	93.3% (84.1–97.8)	44.4% (37.1–52.0)	94.1% (86.8–98.1)	41.2% (33.7–49.0)	33.3%	29.4%	5.9%
Leite 2015	MACE within 6 weeks	174	90.9% (70.8–98.9)	63.2% (55.0–70.8)	98.0% (92.8–99.8)	26.3% (16.9–37.7)	56.3%	12.6%	2.0%
Bodapati 2016	MACE within 30 days	678	98.6% (95.0–99.8)	43.5% (39.2–47.8)	99.2% (97.0–99.9)	31.6% (27.3–36.2)	34.7%	20.9%	0.9%
Sun 2016	MACE within 30 days	8255	85.8% (82.5–88.7)	51.2% (50.1–52.3)	98.2% (97.8–98.6)	10.3% (9.4–11.3)	48.9%	6.2%	1.8%
Santi 2016	MACE within 30 days	1378	100% (98.2–100)	43.7% (40.8–46.6)	100% (99.3–100)	23.8% (21.0–26.8)	37.2%	15.0%	0.0%
Carlton 2015 (hs-cTnT)	(non)-fatal AMI within 30 days	959	93.7% (85.5–99.9)	33.9% (33.1–34.2)	98.3% (96.2–99.4)	11.3% (10.3–11.8)	31.6%	8.2%	1.7%
Carlton 2015 (hs-cTnI)	(non)-fatal AMI within 30 days	867	97.0% (88.7–99.5)	34.7% (34.0–34.9)	99.3% (97.3–99.9)	10.9% (10.0–11.2)	35.2%	7.6%	0.7%

N: number of patients; NPV: negative predictive value; PPV: positive predictive value; MACEs: major adverse cardiac events; AMI: acute myocardial infarction; hs-cTnT: high-sensitivity cardiac troponin T; hs-cTnI: high-sensitivity cardiac troponin I.

In patients with HEART score of 0–3.

After quality assessment, two further studies were excluded from the final meta-analysis.^17,22 The exclusion of those two studies was based on a significant deviation from the original HEART score definition in combination with a vaguely defined reference standard allocated using relatively old troponin assays as a result of early study periods. Both authors, based on the QUADAS-2 assessment, agreed that both studies were at significant risk of allocating intermediate risk patients wrongly to the low-risk group. A summary of the quality assessment of all 12 initially eligible studies with the QUADAS-2 tool is shown in Figure 1. The methodological quality assessment of included studies identified that most had important limitations. A detailed assessment of each individual study is available in the Supplementary Appendix. The major methodological limitations identified in various degrees included deviating from the original HEART score definition, frequent unblinded determination of the HEART score or patient outcome, the use of outdated definitions and insufficient or lacking information on the timing of reference standard troponin testing, contributing to potential verification bias. The study by Carlton et al. was excluded from the meta-analysis as this study did not provide data about the incidence of MACEs.²⁰ This yielded a total of nine studies for meta-analysis (Figure 2).

These nine studies included data from 11,217 patients. The pooled prevalence of MACEs was 15.4% (95% confidence interval (CI) 14.8–16.1%, range 7.3–29.1%) at a mean follow-up time of 6 weeks. Across the various studies 4101 (36.6%, range 28.2–60.1%) had a HEART score of 0–3 and would therefore have been potentially suitable for immediate discharge. In this low-risk group a combined total of 1.6% (95% CI 1.2–2.0%, range 0.9–5.9%) of the patients would have had a missed MACE. We found no evidence of publication bias (P=0.58; see Supplementary Appendix).

The pooled sensitivity estimate of the HEART score for predicting MACEs in the nine studies included was 96.7% (95% CI 94.0–98.2%) as summarised in Figure 3. The pooled specificity for the HEART score was 47.0% (95% CI 41.0–53.5%). The positive likelihood ratio (LR+) and negative likelihood ratio (LR–) were 1.82 (95% CI 1.62–2.06) and 0.07 (95% CI 0.04–0.13), respectively. Depending on the prevalence of MACEs in the various study cohorts the NPV was fairly constant between 97.4% and 100%, while the PPV was more variable between 17.3% and 41.2%.

On summary ROC curve analysis, the AUC of the HEART score was 0.81 (95% CI 0.77–0.84), as shown in Figure 4. While overall heterogeneity was relatively high, 12% was estimated to be attributed to a threshold effect with a low between-study variation of 14% for sensitivity and 5% for specificity. This was visually confirmed by inspection of the summary ROC curve.

Sensitivity analysis

In a sensitivity analysis pooling all studies eligible for the review, irrespective of the quality assessment, data from 27,724 patients were combined. The sensitivity of the HEART score for predicting MACEs varied across individual studies from 75.5% to 100%. In comparison to the primary analysis, the pooled sensitivity was lower at 95.1% (95% CI 90.5–97.5%) with a very high degree of heterogeneity (I²=96.09%, 95% CI 94.74–97.45%). The pooled specificity was slightly higher at 49.3% (95% CI 42.9–55.8%). The likelihood ratios were respectively calculated at LR+ of 1.88 (95% CI 1.68–2.10) and LR– of 0.10 (95% CI 0.05–0.18). The area under the summary ROC curve was lower, at 0.75 (95% CI 0.71–0.78) with a more scattered appearance representing higher between-study variability. A Forest plot, summary ROC curve and Deeks funnel plot for the sensitivity analysis are provided in the Supplementary Appendix.

Sensitivity analysis with the HEART score at a lower ⩽2 points cut-off

Five studies provided data for a potential lower 2 points or less cut-off for the HEART score including 6397 patients.^{14–16,18,21} The pooled sensitivity of the HEART score for predicting MACEs at the lower 2 points or less cut-off was higher at 99.4% (95% CI 96.8–99.9%) at the cost of a lower pooled specificity of 22.0% (95% CI 14.2–32.5%). The likelihood ratios were respectively a LR+ of 1.28 (95% CI 1.13–1.44) and a LR– of 0.03 (95% CI 0.00–0.18).

HEART score with high-sensitivity troponin assays

Three studies evaluated the HEART score with hs-cTn assays, only two of which reported data for MACEs at 30 days (which rendered a separate meta-analysis inappropriate). The prospective study of Visser et al. used the Roche Elecsys hs-cTnT assay, reporting a sensitivity of 93.3% (95% CI 84.1–97.8%) for MACEs at 6 weeks.¹⁸ Conversely, Santi et al. using the same troponin assay in a recent retrospective study reported 100% sensitivity (95% CI 98.2–100%) for MACEs within 30 days.²³ Carlton et al. evaluated HEART with two hs-cTn assays, although the primary outcome was non-fatal AMI within 30 days rather than MACEs.²⁰ In that study, the cut-off value used for the Roche Elecsys hs-cTnT assay deviated from the original HEART score definition (requiring a rise to three times the 99th percentile in order to score 2 points). The sensitivity of the HEART score with hs-cTnT (93.7%, 95% CI 85.5–99.9%) was found to be lower than with the Abbott Architect hs-cTnI assay (97.0%, 95% CI 88.7–99.5%).²⁰ All remaining studies reported the usage of various (contemporary) troponin assays only, with five studies not specifying the assay used.

Discussion

Our findings demonstrate that the HEART score could be used to identify patients with a suspected diagnosis of ACS who are at low probability (1.6%) of developing MACEs and who could potentially be discharged immediately from the ED. However, this risk may not be acceptable to clinicians. Indeed, only 40% of emergency physicians would be willing to discharge a patient from the ED if the probability of MACEs exceeds 1%.²⁴ Furthermore, the post-test probability of MACEs is heavily dependent on prevalence. Sensitivity may therefore be a superior measure of diagnostic accuracy, particularly on a meta-analysis of cohorts with varying prevalence. We found that the HEART score has a sensitivity of 96.7%. In our sensitivity analysis (which included two studies with lower methodological quality), the pooled sensitivity was lower still, at 95.1%. In an additional sensitivity analysis of five studies at a lower 2 points or less cut-off for the HEART score, suggested by the study of Six et al.,¹⁵ suggested the pooled sensitivity of 99.4% was raised to what is considered an acceptable risk of missing a MACE in the low-risk group. However, this increase in sensitivity comes with a drastically decreased pooled specificity of only 22.0%.

Our main analysis, although excluding two studies with significant concerns, has been limited by the overall quality of the remaining studies included. The retrospective nature and unclear reporting of certain key methodological aspects means that there is an uncertain degree of verification and selection bias. It is also important to note the wide range of troponin assays that have been used in studies evaluating the HEART score. This should be considered when interpreting the results and highlights the need for further research with improved standardisation of the troponin assays used with the HEART score. It is also important to note that the primary outcome (MACEs), which is widely used in diagnostic research in this field, is a composite. While it was not feasible or practical to run separate analyses for each individual component of this composite outcome, it is important to recognise that prevalent and incident AMI, death and revascularisation have different clinical significance.²⁵

The specificity of the HEART score may appear low (45%). However, it is important to recognise that patients with a HEART score greater than 3 should not be considered to have ACS ‘ruled in’. Rather, these patients would be expected to undergo further investigation with serial troponin testing in accordance with routine clinical protocols. In doing so, the lack of specificity ought not to increase resource utilisation, although this can only be robustly evaluated in the context of a randomised controlled trial.

An obvious advantage of the HEART score is its simplicity. It can be a paper-based score and is easy to calculate without the use of a computer. With the name of the score representing an acronym for the variables included in the score it is easy to remember, although recalling the different definitions of each category might still be challenging.

Because troponin results are expressed as multiples of the 99th percentile, the HEART score was designed to be used with any commercially available troponin assay. Our findings suggest varying diagnostic performance when a high sensitivity assay is used. Indeed, diagnostic sensitivity is actually lower in two studies that evaluated the HEART score with hs-cTnT (Roche Elecsys).^18,20 On the contrary, one retrospective study reported a very high sensitivity with the same assay.²³ Although the lack of direct comparisons between assays precludes the drawing of definitive conclusions, this does suggest the need for more work to validate the HEART score prospectively with hs-cTn assays.

Other diagnostic strategies to rule out ACS following a single blood test have also been described. For example, the computer-based Manchester acute coronary syndromes (MACS) rule. The MACS rule was shown effectively to rule out MACEs within 30 days with high sensitivity (97.8% and 100%) in two external observational studies, identifying around 20% of patients as ‘very low risk’ and therefore eligible for immediate discharge.^26,27 Similar to the HEART score, the MACS rule could be used not only to rule out ACS following a single blood test but also to risk stratify remaining patients, facilitating triage to the appropriate level of care. None of the studies included contained sufficient data to enable direct comparison of MACS and HEART but this is an important objective for future work.

With hs-cTn assays, it may also be possible to ‘rule out’ AMI in patients with initial hs-cTn concentrations below the limit of detection (LoD) of the assay. While a definitive rule out of AMI based on a single hs-cTnT at the LoD alone was found to be inappropriate in a meta-analysis,²⁸ a single hs-cTnI measurement combined with a non-ischaemic ECG has been reported to reach comparable diagnostic accuracy to our findings for the HEART score, providing a potentially very simplistic rule out strategy.²⁹ Given the increasing amount of data to back this strategy, the findings of our meta-analysis may mean that clinical implementation of the HEART score is less likely at institutions where hs-cTn assays are in use.

Finally, by adding in serial sampling it may be possible to improve diagnostic accuracy. For example, the HEART pathway uses the HEART score alongside troponin testing at 0 and 3 hours. The addition of the 3-hour sample has previously been shown to reduce the incidence of MACEs in ‘low-risk’ patients from 1.8% to 0.0%.³⁰ While the requirement for serial troponin testing is a disadvantage, other diagnostic protocols incorporating clinical risk stratification and serial troponin testing over 2–3 hours have shown similar promise. For example, the ADAPT-ADP and EDACS-ADP equally showing 0.0% missed MACEs within 30 days.³¹ Another observational study recently confirmed the potential of the one-hour rule in and rule out algorithm when combined with a non-ischaemic ECG and patient history, showing 0.5% missed MACEs within 30 days when including unstable angina and 0.0% missed MACEs without unstable angina.³² Whether the HEART score can provide additional value if used alongside the one-hour rule in and rule out algorithm with hs-cTn should be a focus for future work.³

Conclusion

Patients presenting with undifferentiated chest pain to the ED obtaining a HEART score of 0–3 at initial assessment are at low risk of incident MACEs. As 3.3% of patients with MACEs are ‘missed’ by the HEART score, clinicians must ask whether this risk is acceptably low for clinical implementation, and should be carefully guided by local circumstances influencing diagnostic performance. Future work should focus on robust comparison with alternative strategies.

Supplemental Material

Supplementary_Appendix_-_HEART_score_sys_rv_28052016 – Supplemental material for The HEART score for early rule out of acute coronary syndromes in the emergency department: a systematic review and meta-analysis

Supplemental material, Supplementary_Appendix_-_HEART_score_sys_rv_28052016 for The HEART score for early rule out of acute coronary syndromes in the emergency department: a systematic review and meta-analysis by MPatricia Van Den Berg and Richard Body in European Heart Journal: Acute Cardiovascular Care

Footnotes

Conflict of interest

Richard Body has previously undertaken research involving donation of reagents without charge by Roche, Abbott, Alere, Siemens and Randox. Richard Body has accepted the provision of economy class travel and accommodation to present findings unrelated to this work at two Roche-sponsored conferences and at a scientific session sponsored by Randox.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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