Clinical scores for risk stratification of chest pain patients in the emergency department: an updated systematic review

Liu, Nan; Ng, Janson Cheng Ji; Ting, Chu En; Sakamoto, Jeffrey Tadashi; Ho, Andrew Fu Wah; Koh, Zhi Xiong; Pek, Pin Pin; Lim, Swee Han; Ong, Marcus Eng Hock

doi:10.21037/jeccm.2018.01.10

Cited by 18 publications

(13 citation statements)

References 42 publications

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“…We therefore did not include studies on CDRs that are commonly used in EDs, such as the History, ECG, Age, Risk factors and initial Troponin (HEART),32 Global Registry of Acute Coronary Events33 and Thrombolysis in Myocardial Infarction34 scores as well as the more recent Manchester Acute Coronary Syndromes rule 35. For a comprehensive overview of chest pain rules recently validated in ED patients, we refer to the systematic review by Liu et al 36…”

Section: Discussionmentioning

confidence: 99%

Chest pain in general practice: a systematic review of prediction rules

et al. 2019

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ObjectiveTo identify and assess the performance of clinical decision rules (CDR) for chest pain in general practice.DesignSystematic review of diagnostic studies.Data sourcesMedline/Pubmed, Embase/Ovid, CINAHL/EBSCO and Google Scholar up to October 2018.Study selectionStudies that assessed CDRs for intermittent-type chest pain and for rule out of acute coronary syndrome (ACS) applicable in general practice, thus not relying on advanced laboratory, computer or diagnostic testing.Review methodsReviewers identified studies, extracted data and assessed the quality of the evidence (using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2)), independently and in duplicate.ResultsEight studies comprising five CDRs met the inclusion criteria. Three CDRs are designed for rule out of coronary disease in intermittent-type chest pain (Gencer rule, Marburg Heart Score, INTERCHEST), and two for rule out of ACS (Grijseels rule, Bruins Slot rule). Studies that examined the Marburg Heart Score had the highest methodological quality with consistent sensitivity (86%–91%), specificity (61%–81%) and positive (23%–35%) and negative (97%–98%) predictive values (PPV and NPV). The diagnostic performance of Gencer (PPV: 20%–34%, NPV: 95%–99%) and INTERCHEST (PPV: 35%–43%, NPV: 96%–98%) appear comparable, but requires further validation. The Marburg Heart Score was more sensitive in detecting coronary disease than the clinical judgement of the general practitioner. The performance of CDRs that focused on rule out of ACS were: Grijseels rule (sensitivity: 91%, specificity: 37%, PPV: 57%, NPV: 82%) and Bruins Slot (sensitivity: 97%, specificity: 10%, PPV: 23%, NPV: 92%). Compared with clinical judgement, the Bruins Slot rule appeared to be safer than clinical judgement alone, but the study was limited in sample size.ConclusionsIn general practice, there is currently no clinical decision aid that can safely rule out ACS. For intermittent chest pain, several rules exist, of which the Marburg Heart Score has been most extensively tested and appears to outperform clinical judgement alone.

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Section: Discussionmentioning

confidence: 99%

Chest pain in general practice: a systematic review of prediction rules

et al. 2019

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“…In a large retrospective study in this issue the HEART score performed equally good among Caucasian and different Asian ethnic groups. 1 However, in contrast with earlier studies 2 –5 the negative predictive value was lower (95% instead of 99 to 100%) with a higher incidence of major adverse cardiac events indicating that further studies are needed to determine the safety of discharging low risk patients solely based on the HEART score. Performing a O & 1 hour serial sampling of a high sensitivity cardiac troponin along the calculation of the HEART score may possibly result in more accurate detection of a low risk group of chest pain patients that safely can be discharged from the emergency department.…”

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confidence: 73%

Triage, diagnosis and management of acute chest pain syndromes, atypical and high-risk subtypes of acute coronary artery syndromes

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2018

European Heart Journal: Acute Cardiovascular Care

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“…These promising results motivated the use of HRV to develop objective and computerized risk stratification tools for chest pain patients [44,45]. In an updated review of clinical scores for chest pain, Liu et al [5] summarized several studies which aimed to develop alternative techniques for risk stratification.…”

Section: Discussionmentioning

confidence: 99%

“…Hence, early identification of chest pain patients who are at high-risk of developing adverse cardiac events has been a pressing issue to contend with in the ED. Several established clinical scores have been used for risk stratifying chest pain patients in the ED [4,5], including the History, ECG, Age, Risk factors and Troponin (HEART) [6], the Thrombolysis in Myocardial Infarction (TIMI) [7], and the Global Registry of Acute Coronary Events (GRACE) [8] scores. Of these scores, the HEART score is the most accurate and widely used [5,[9][10][11][12], with recent studies focusing on the development of risk score-based clinical pathways for rapid, yet safe discharge of low-risk patients [1,3,13,14].…”

Section: Introductionmentioning

confidence: 99%

“…In a recent review of clinical scores for ED patients with chest pain [5], heart rate variability (HRV) has demonstrated its capability in building predictive models for accurate risk stratification [15][16][17]. HRV is a widely adopted tool for evaluating changes in cardiac autonomic regulation, and has been shown to be strongly associated with the autonomic nervous system (ANS) [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

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Heart rate n-variability (HRnV) and its application to risk stratification of chest pain patients in the emergency department

Liu

Guo

Koh

et al. 2020

BMC Cardiovasc Disord

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Background: Chest pain is one of the most common complaints among patients presenting to the emergency department (ED). Causes of chest pain can be benign or life threatening, making accurate risk stratification a critical issue in the ED. In addition to the use of established clinical scores, prior studies have attempted to create predictive models with heart rate variability (HRV). In this study, we proposed heart rate n-variability (HRnV), an alternative representation of beat-to-beat variation in electrocardiogram (ECG), and investigated its association with major adverse cardiac events (MACE) in ED patients with chest pain. Methods: We conducted a retrospective analysis of data collected from the ED of a tertiary hospital in Singapore between September 2010 and July 2015. Patients > 20 years old who presented to the ED with chief complaint of chest pain were conveniently recruited. Five to six-minute single-lead ECGs, demographics, medical history, troponin, and other required variables were collected. We developed the HRnV-Calc software to calculate HRnV parameters. The primary outcome was 30-day MACE, which included all-cause death, acute myocardial infarction, and revascularization. Univariable and multivariable logistic regression analyses were conducted to investigate the association between individual risk factors and the outcome. Receiver operating characteristic (ROC) analysis was performed to compare the HRnV model (based on leave-one-out cross-validation) against other clinical scores in predicting 30-day MACE.

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Clinical scores for risk stratification of chest pain patients in the emergency department: an updated systematic review

Cited by 18 publications

References 42 publications

Chest pain in general practice: a systematic review of prediction rules

Chest pain in general practice: a systematic review of prediction rules

Triage, diagnosis and management of acute chest pain syndromes, atypical and high-risk subtypes of acute coronary artery syndromes

Heart rate n-variability (HRnV) and its application to risk stratification of chest pain patients in the emergency department

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