Systematic review of the Manchester Acute Coronary Scores.


The series of MACS scores are something developed in Manchester and led by our very own Prof. Rick Body. We;ve talked about them a lot on the blog, but for obvious reasons that does present a bit of a conflict of interest. This week we have a paper on MACS that has not been written by our team here in Virchester and which hopefully gives a more objective view of the performance of MACS and it’s variations.

Chest pain remains as one of the most common reasons for emergency department (ED) visits globally, particularly in the developed world. Early identification of patients with acute coronary syndrome (ACS) is crucial as it allows for timely intervention, potentially reducing morbidity and mortality. However, the challenge lies in distinguishing those with ACS from those with non-cardiac causes of chest pain. This is where decision aids, such as the Manchester Acute Coronary Syndrome (MACS) decision rules, play a pivotal role. These rules help clinicians stratify patients based on their risk of having ACS, thus aiding in decision-making regarding further diagnostic testing and management.

The original MACS rule, introduced by Rick Body and colleagues here, incorporated a combination of clinical variables and biomarkers to predict 30-day major adverse cardiac events (MACEs). Given the advancements in biomarkers and the need for more simplified models, two derivatives, the Troponin-only MACS (T-MACS) and the History and Electrocardiogram-only MACS (HE-MACS), were developed. T-MACS removed the need to test for any biomarkers that are not routinely used (the original MACS rule required testing for heart-type fatty acid binding protein). HE-MACS allows decisions to be made based only on a patient’s history and ECG, without the need for any blood tests. This systematic review and meta-analysis aimed to evaluate the diagnostic performance of these decision aids in detecting acute myocardial infarction (AMI) and predicting 30-day MACE. The paper is published in the EJEM. The abstract is below, but as always we recommend you read the full paper yourself and come to your own conclusions.


Background and importance: Multiple decision-aiding models are available to help physicians identify acute coronary syndrome (ACS) and accelerate the decision-making process in emergency departments (EDs).

Objective: This study evaluates the diagnostic performance of the Manchester Acute Coronary Syndrome (MACS) rule and its derivations, enhancing the evidence for their clinical use.

Design: Systematic review and meta-analysis.

Settings and participants: Medline, Embase, Scopus, and Web of Science were searched from inception until October 2023 for studies including adult ED patients with suspected cardiac chest pain and inconclusive findings requiring ACS risk-stratification.

Outcome measures and analysis: The predictive value of MACS, Troponin-only MACS (T-MACS), or History and Electrocardiogram-only MACS (HE-MACS) decision aids for diagnosing acute myocardial infarction (AMI) and 30-day major adverse cardiac outcomes (MACEs) among patients admitted to ED with chest pain suspected of ACS. Overall sensitivity and specificity were synthesized using the ‘Diagma’ package in STATA statistical software. Applicability and risk of bias assessment were performed using the QUADAS-2 tool.

Main results: For AMI detection, MACS has a sensitivity of 99% [confidence interval (CI): 97-100], specificity of 19% (CI: 10-32), and AUC of 0.816 (CI: 0.720-0.885). T-MACS shows a sensitivity of 98% (CI: 98-99), specificity of 35% (CI: 29-42), and AUC of 0.859 (CI: 0.824-0.887). HE-MACS exhibits a sensitivity of 99% (CI: 98-100), specificity of 9% (CI: 3-21), and AUC of 0.787 (CI: 0.647-0.882). For MACE detection, MACS demonstrates a sensitivity of 98% (CI: 94-100), specificity of 22% (CI: 10-42), and AUC of 0.804 (CI: 0.659-0.897). T-MACS displays a sensitivity of 96% (CI: 94-98), specificity of 36% (CI: 30-43), and AUC of 0.792 (CI: 0.748-0.830). HE-MACS maintains a sensitivity of 99% (CI: 97-99), specificity of 10% (CI 6-16), and AUC of 0.713 (CI: 0.625-0.787).

Conclusion: Of all the MACS models, T-MACS displayed the highest overall accuracy due to its high sensitivity and significantly superior specificity. T-MACS exhibits very good diagnostic performance in predicting both AMI and MACE. This makes it a highly promising tool for managing patients with acute chest pain.

Roshdi Dizaji S, Ahmadzadeh K, Zarei H, Miri R, Yousefifard M. Performance of Manchester Acute Coronary Syndromes decision rules in acute coronary syndrome: a systematic review and meta-analysis. Eur J Emerg Med. 2024 Jun 11. doi: 10.1097/MEJ.0000000000001147. Epub ahead of print. PMID: 38864570.

What Kind of Study is This?

This study is a systematic review and meta-analysis adhering to the PRISMA-DTA guidelines. It involved a comprehensive literature search across multiple databases, including Medline, Embase, Scopus, and Web of Science, to identify studies that assessed the diagnostic accuracy of the MACS, T-MACS, and HE-MACS decision rules. The included studies focused on adult patients presenting to the ED with suspected cardiac chest pain requiring ACS risk stratification. The outcomes of interest were the occurrence of AMI and 30-day MACE, with the sensitivity and specificity of each decision aid being key metrics of performance.

Tell Me About the Patients

The studies included in this meta-analysis enrolled a diverse cohort of adult patients presenting to the ED with acute chest pain. The inclusion criteria ensured that only those patients for whom the attending clinicians had considered an evaluation for ACS were included. Exclusion criteria were rigorous, omitting studies that involved non-cardiac or traumatic chest pain, pediatric populations, or those with modifications to the original MACS models. The patients represented a wide range of demographics, including different ages, genders, and ethnic backgrounds, enhancing the generalisability of the findings.

What Were the Measured Outcomes in This Study?

The primary outcomes measured in this study were:

  • Acute Myocardial Infarction (AMI): This included both ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI).
  • 30-Day Major Adverse Cardiac Events (MACE): This encompassed AMI, all-cause or ischemic mortality, and planned or emergent revascularisation within 30 days of the initial ED presentation.

The diagnostic performance indicators for each decision rule (MACS, T-MACS, HE-MACS) included sensitivity, specificity, area under the receiver operating characteristic curve (AUC), positive likelihood ratio (PLR), and negative likelihood ratio (NLR).

What Are the Main Results?

The meta-analysis synthesised data from 17 studies, providing a comprehensive evaluation of the MACS decision rules. Here are the key results:

  • For AMI Detection:
  • MACS: Sensitivity of 99% (CI: 97–100), specificity of 19% (CI: 10–32), AUC of 0.816 (CI: 0.720–0.885).
  • T-MACS: Sensitivity of 98% (CI: 98–99), specificity of 35% (CI: 29–42), AUC of 0.859 (CI: 0.824–0.887).
  • HE-MACS: Sensitivity of 99% (CI: 98–100), specificity of 9% (CI: 3–21), AUC of 0.787 (CI: 0.647–0.882).
  • For 30-Day MACE Prediction:
  • MACS: Sensitivity of 98% (CI: 94–100), specificity of 22% (CI: 10–42), AUC of 0.804 (CI: 0.659–0.897).
  • T-MACS: Sensitivity of 96% (CI: 94–98), specificity of 36% (CI: 30–43), AUC of 0.792 (CI: 0.748–0.830).
  • HE-MACS: Sensitivity of 99% (CI: 97–99), specificity of 10% (CI 6–16), AUC of 0.713 (CI: 0.625–0.787).

Main Takeaways:

  • T-MACS emerged as the most accurate model in these comparisons due to its high sensitivity and significantly better specificity compared to the other models.
  • HE-MACS had the highest sensitivity but the lowest specificity, limiting its practical utility in ruling out non-cardiac chest pain.
  • All models demonstrated high diagnostic accuracy, making them valuable tools in the ED setting for managing patients with acute chest pain.

Critically Appraise the Methodology and Findings

The methodology of this systematic review and meta-analysis looks robust, and follows established guidelines and employing rigorous search and selection criteria. However, several limitations should be noted:

  • Population Diversity: While the multicentre nature of the included studies enhances generalisability, differences in healthcare systems and patient populations across countries might affect the applicability of the findings across different health economies.
  • Study Designs and Quality: The included studies varied in design, with some being prospective cohorts and others retrospective analyses. The quality assessment revealed that some studies had a potential risk of bias, particularly regarding patient selection and the timing of outcome adjudication. To some extent this is inevitable in review articles (as by their very definition they use work that was designed and delivered by others), but it’s a good reminder that any review article/meta-analysis is only as good as the studies that are included.
  • Specificity vs Sensitivity: The high sensitivity but low specificity of the MACS and HE-MACS models suggests that while these tools are excellent for ruling out AMI and MACE, they may lead to a higher number of false positives, potentially increasing the burden on healthcare resources if used unwisely. As we have said on St Emlyn’s many times with regard to diagnostic studies, the test performance is one thing, but how the test is used by clinicians is equally important (and harder to define and control).
  • Publication Bias: No significant publication bias was detected for MACS and T-MACS, but there was a possibility of bias for HE-MACS in AMI detection due to the limited number of studies available.

Should We Change Practice Based on This Study?

This is not a question for me, as we already use it, but others may well be interested in using scoring systems to stratify chest pain patients. This study certainly supports our current practice given the high diagnostic accuracy and practical benefits of the T-MACS model. Thus there is a strong case for its integration into clinical practice for managing patients with suspected ACS in the ED. T-MACS offers a balanced approach with excellent sensitivity and reasonable specificity, making it a valuable tool for both ruling out and ruling in patients. However, the implementation should be tailored to individual ED settings, considering local resources, training needs, and patient demographics. There is also the question of other scores out there and how they are used in practice. Whilst a number of other scores have been tested against the MACS family, they are not really presented here and that’s an area for future study.


In this study, the Manchester Acute Coronary Syndromes (MACS) decision rules, particularly the T-MACS model, demonstrated high diagnostic accuracy for detecting AMI and predicting 30-day MACE among patients presenting to the ED with suspected cardiac chest pain. The systematic review and meta-analysis provide robust evidence supporting the clinical utility of these decision aids, highlighting T-MACS as the most promising tool due to its superior specificity and excellent sensitivity. While further research may be warranted to explore long-term outcomes and applicability in different healthcare settings, the findings support our use of T-MACS in routine clinical practice here in Virchester. This study, and the studies incorporated within it also remind us that external validation, via studies that attempt to reproduce or test derived scores in real practice are an essential part of the scientific method.

As always read the full paper yourself, especially as this study is positive about work we have done in Virchester. That means you should be even more skeptical than usual about what we say!


References and further reading

  1. Body R, Carley S, McDowell G, et al. The Manchester Acute Coronary Syndromes (MACS) decision rule: validation with a new automated assay for heart-type fatty acid binding protein. Emerg Med J. 2014;31(12):1013-1018.
  2. Rick Body, “The MACS Rule: Immediate ‘rule in’ and ‘rule out’ for suspected cardiac chest pain,” in St.Emlyn’s, April 30, 2014,
  3. Body R, Burrows G, Carley S, et al. The Manchester Acute Coronary Syndromes (MACS) decision rule for suspected cardiac chest pain: derivation and external validation. Heart. 2014;100(17):1462-1468.
  4. Body R, Carlton E, Sperrin M, et al. Troponin-only Manchester Acute Coronary Syndromes (T-MACS) decision aid: single biomarker re-derivation and external validation in three cohorts. Emerg Med J. 2017;34(6):349-356.
  5. Charlie Reynard, “Risk scores for cardiac chest pain: the first head-to-head comparison!,” in St.Emlyn’s, December 8, 2019,
  6. Rick Body, “The MACS rule: a new user-friendly version,” in St.Emlyn’s, January 28, 2015,
  7. Carlton E, Body R, Greaves K. External validation of the Manchester Acute Coronary Syndromes (MACS) and Troponin-only Manchester Acute Coronary Syndromes (T-MACS) decision aids. Heart. 2016;102(20):1589-1594.
  8. Greenslade JH, Cullen L, Parsonage W, et al. Validation of the Manchester Acute Coronary Syndromes decision rule. Clin Biochem. 2015;48(4-5):265-268.
  9. Body R, Cook G, Burrows G, et al. Can the Manchester Acute Coronary Syndromes (MACS) decision rule identify low-risk patients with chest pain for early discharge? Heart. 2017;103(23):1820-1828.
  10. Carlton EW, Khattab A, Greaves K. Identifying patients suitable for discharge after a single-presentation high-sensitivity troponin result: a comparison of five established risk scores and two high-sensitivity assays. Ann Emerg Med. 2015;66(6):635-645.
  11. Carlton E, Body R, Greaves K. Comparison of the HEART, TIMI, and GRACE scores in predicting major adverse cardiac outcomes in patients with chest pain. Am J Emerg Med. 2016;34(8):1352-1359.

Cite this article as: Simon Carley, "Systematic review of the Manchester Acute Coronary Scores.," in St.Emlyn's, July 3, 2024,

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