Cardiology

Impact of coronary risk scores on disposition decision in emergency patients with chest pain

a b s t r a c t

Background: Coronary risk scores (CRS) including History, Electrocardiogram, Age, Risk Factors, Troponin score and Emergency Department Assessment of Chest pain Score (EDACS) can help identify patients at low risk of Major adverse cardiac events. In the emergency department (ED), there are wide variations in hos- pital admission rates among patients with chest pain.

Objective: This study aimed to evaluate the impact of CRS on the disposition of patients with symptoms sugges- tive of acute coronary syndrome in the ED.

Methods: This retrospective cohort study included 3660 adult patients who presented to the ED with chest pain between January and July in 2019. Study inclusion criteria were age > 18 years and a primary position Interna- tional Statistical Classification of Diseases and Related Health Problems-10th revision coded diagnosis of angina pectoris (I20.0-I20.9) or chronic ischemic heart disease (I25.0-I25.9) by the treating ED physician. If the treating ED physician completed the electronic structured variables for CRS calculation to assist disposition planning, then the patient would be classified as the CRS group; otherwise, the patient was included in the control group.

Results: Among the 2676 patients, 746 were classified into the CRS group, whereas the other 1930 were classified into the control group. There was no significant difference in sex, age, initial vital signs, and ED length of stay be- tween the two groups. The coronary risk factors were similar between the two groups, except for a higher inci- dence of smokers in the CRS group (19.6% vs. 16.1%, p = 0.031). Compared with the control group, significantly more patients were discharged (70.1% vs. 64.6%) directly from the ED, while fewer patients who were hospital- ized (25.9% vs. 29.7%) or against-advise discharge (AAD) (2.6% vs. 4.0%) in the CRS group. Major adverse cardiac events and mortality at 60 days between the two groups were not significantly different.

Conclusions: A higher ED discharge rate of the group using CRS may indicate that ED physicians have more con-

fidence in discharging low-risk patients based on CRS.

(C) 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://

creativecommons.org/licenses/by-nc-nd/4.0/).

  1. Introduction

Heart disease is the leading cause of death globally in the past de- cade, and an increasing number of people experience cardiovascular diseases annually. In 2017, cardiovascular diseases account for approx- imately 17.8 million deaths worldwide, which amounted to an increase of 21.1% from 2007 [1]. Chest pain is the most common chief complaint of acute myocardial infarction (AMI), but there are also multiple non- cardiac causes that lead to the same complaint. Chest pain is the second most common complaint in the emergency department (ED). It ac- counts for approximately more than 5 million annual visits to the ED in the United States [2]. However, failure to accurately diagnose AMI

* Corresponding author at: Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital, 123 Ta-Pei Road, Niao-Sung, Kaohsiung 833, Taiwan.

E-mail address: [email protected] (C.-Y. Cheng).

may lead to delayed appropriate treatments, increased risk of mortality, and increased Medical costs [3,4].

The gold standard method for diagnosing coronary artery disease is cardiac catheterization [5]. The diagnosis of AMI cannot always be made based on initial presentation; therefore, additional testing in- cluding exercise treadmill testing, stress myocardial perfusion study, echocardiography, and Computed tomography coronary angiography may assist clinicians in making the diagnosis [6]. Failure to hospitalize ACS patients is related to the absence of typical features of cardiac is- chemia, normal electrocardiogram (ECG) results, emergency physician variables, and low ED volume [4,7]. Hence, a large proportion of pa- tients with chest pain are hospitalized, but almost 75% of the patients hospitalized with suspected ACS did not have chest pain [8]. Previous studies showed wide variation in the decision to hospitalize patients with chest pain, ranging from 38% to 81% in the lowest and highest quintiles [9]. Among physicians, there exists wide variability in chest

https://doi.org/10.1016/j.ajem.2021.04.029

0735-6757/(C) 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

pain observation unit utilization and admission. Physician risk toler- ance was correlated to decision making in ED patients with chest pain [10]. Use of risk stratification protocols has been reported to re- duce inpatient admissions for patients with chest pain as the primary chief complaint [11].

This study aimed to evaluate the impact of using coronary risk scores (CRS) on the disposition of patients with symptoms suggestive of acute coronary syndrome in the ED. We hypothesized that ED physicians would have more confidence in discharge low-risk patients based on CRS.

  1. Methods
    1. Study design

This single-center retrospective study was conducted at Kaohsiung Chang Gung Memorial Hospital, a 2692-bed acute-care medical center, and the largest tertiary care hospital in southern Taiwan. The study pe- riod was from January 2019 to July 2019. All patients were treated by 31 certified ED physicians. The study protocol was approved by the Ethics Committee of Chang Gung Memorial Hospital. Because of the retrospec- tive nature of the study, the need for informed consent from the subjects was waived.

    1. Study setting and population

The study inclusion criteria were (1) non-trauma patients who were

> 18 years old, (2) had visited the ED with a chief complaint of chest pain, and a primary position International Statistical Classification of Diseases and Related Health Problems-10th revision coded diagnosis of angina pectoris (I20.0-I20.9) or chronic ischemic heart disease (I25.0-I25.9). Patients with myocardial infarction (MI), cardiogenic shock, or cardiac arrest in the ED were excluded from our study.

Since January 2019, electronic structured data entry was imple- mented in the hospital’s medical system. The predictor variables for CRS calculations, including History, Electrocardiogram, Age, Risk Fac- tors, Troponin (HEART) and Emergency Department Assessment of Chest pain Score (EDACS) scores, were set as one of the electronic struc- tured data sheets. The CRS would be presented on the medical chart if the treating ED physician completed the electronic structured variables to assist disposition planning. Patients who had their CRS data pre- sented on the medical chart were included into the CRS group. The other patients were included into the control group, and the CRS data of the control group were calculated retrospectively. The electronic medical records of patients were retrospectively reviewed by four certi- fied ED physicians.

2.3

. Risk score calculation and outcome

Pulse rate

86 +- 21

86 +- 21

0.936

Body temperature

36.5 +- 1.0

36.5 +- 0.5

0.097

To facilitate patients visiting the ED with primary complaints of

Respiratory rate

18.7 +- 2.6

18.9 +- 2.1

0.074

adverse cardiac events (MACEs) and mortality within 60 days. MACEs were defined as the Composite outcome of MI, cardiac arrest, cardio- genic shock, and all-cause mortality.

2.4. Statistical analysis

Descriptive analyses of our independent variables are reported as percentages or mean +- standard deviation. Continuous variables were analyzed using Student’s t-test. Categorical variables are shown as ac- tual numbers or percentages and were compared using the Pearson’s chi-square test or the Fisher’s exact test. p < 0.05 was considered as sta- tistically significant. Statistical analyses were performed using SPSS Sta- tistics, version 24 (IBM Corp., Armonk, NY, USA).

  1. Results

During the study period, 2707 patients were included. We excluded 6 patients who died at the ED and 25 patients with incomplete medical records. Among 2676 patients, 1930 were classified into the control group and 746 in the CRS group. The distribution of the treating ED phy- sicians between the two groups was not significantly different. Baseline characteristics are shown in Table 1. There was no significant difference in sex, age, and initial vital signs at triage, including systolic blood pres- sure, diastolic blood pressure, pulse rate, body temperature, and respi- ratory rate between the two groups. The coronary risk factors were similar between the two groups, except for a higher incidence of smokers in the CRS group (19.6% vs. 16.1%, p = 0.031). There were no significant differences in the medical history of coronary artery disease, cerebrovascular disease, peripheral arterial occlusive disease, conges- tive heart failure, hypertension, hyperlipidemia, diabetes mellitus, obesity, and family history of coronary artery disease. The CRS group obtained a higher score in the EDACS (18.3 +- 5.8 vs. 17.6 +- 6.7, p = 0.014), while the HEART scores of the two groups showed border- line statistical significance (2.9 +- 1.2 vs. 2.8 +- 1.3, p = 0.050).

As shown in Table 2, there was no significant difference in ED LOS (800.5 +- 1068.2 vs. 739.6 +- 980.4 min, p = 0.158), MACE (3.5% vs.

3.8%, p = 0.686), and mortality (1.4% vs. 1.5%, p = 0.706) within 60

Table 1

Patient characteristics.

Characteristics Control n = 1930 Risk score n = 746 P-value

Sex (male %)

53.9%

55.5%

0.242

Age (mean +- SD) (years)

Vital signs at triage

62.1 +- 13.4

63.2 +- 12.9

0.078

(mean +- SD)

Systolic blood pressure

147 +- 33

147 +- 31

0.823

Diastolic blood pressure

83 +- 29

85 +- 43

0.127

chest pain, the HEART score was created in 2008, including parameters of history, electrocardiography, age, risk factors, and troponin [12]. EDACS includes parameters including age, male sex, age 18-50 years, known coronary artery disease (CAD) or >= 3 risk factors, diaphoresis, pain radiating to the arm or shoulder, pain occurring or worsening with inspiration, and pain reproduced by palpation [13]. Coronary ar- tery disease was defined as a previous episode of acute MI, coronary ar- tery bypass graft, or percutaneous intervention. Risk factors were defined as a family history of premature CAD, hyperlipidemia, diabetes, hypertension, and current smoker. Cardiac troponin I values were ob- tained using the High-sensitivity troponin I assay (Beckman -Access 10% CV 0.04 ng/mL) throughout the study period.

The primary effectiveness outcome was ED length of stay and ED disposition. ED LOS was defined as the time from ED arrival to ED discharge. ED disposition was classified as discharge, admission, trans- fer, or against advice discharge. The secondary outcomes were major

Coronary risk factors (%)

Coronary artery disease

38.8%

42.7%

0.062

Cerebrovascular disease

10.3%

8.3%

0.142

Peripheral arterial occlusive

4.7%

4.3%

0.682

disease

Congestive heart failure

13.5%

12.7%

0.478

Hypertension

58.3%

61.8%

0.094

Hyperlipidemia

23.9%

27.2%

0.073

Diabetes mellitus

30.7%

33.6%

0.148

Obesity

4.5%

3.9%

0.602

Smoking

16.1%

19.6%

0.031?

Family history of CAD

2.2%

1.8%

0.540

Coronary risk score HEART

2.8 +- 1.3

2.9 +- 1.2

0.050

EDACS

17.6 +- 6.7

18.3 +- 5.8

0.014?

SD: Standard deviation, NS: Not significant, CAD: coronary artery disease, HEART = His- tory, Electrocardiogram, Age, Risk Factors, Troponin score, EDACS = Emergency Depart- ment Assessment of Chest pain Score.

* p < 0.05.

Table 2

Outcomes.

Control n = 1930

Risk score n = 746

P-value

ED LOS (minutes)

739.6 +- 980.4

800.5 +- 1068.2

0.158

Disposition

<0.001?

Discharge

64.6%

70.1%

Admission

29.7%

25.9%

AAD

4.0%

2.6%

Transfer

1.7%

1.3%

Outcome in 60 days MACE

3.8%

3.5%

0.686

Mortality

1.5%

1.4%

0.706

ED LOS: emergency department length of stay, AAD: against advice discharge, MACE = major adverse cardiac events.

* p < 0.05.

days between the CRS and control groups, respectively. Compared with the control group, significantly more patients were discharged (70.1% vs. 64.6%) directly from the ED, while fewer patients who were hospital- ized (25.9% vs. 29.7%) or against-advise discharge (AAD) (2.6% vs. 4.0%) in the CRS group.

As shown in Table 3 and Fig. 1, the area under the Receiver operating characteristic curve analysis for patients with chest pain who were discharged directly from the ED was 0.70 (95% confidence interval [CI], 0.68-0.72) in the HEART score and 0.57 [95% CI, 0.56-0.60]) in the EDACS score. The best cutoff point for predicting patient discharge di- rectly from the ED was 4 (sensitivity, 84.4%; specificity, 46.9%; Youden’s index, 0.31) in the HEART score and 13 (sensitivity, 47.1%; specificity, 61.5%; Youden’s index, 0.13) in the EDACS score. The AUROC curve for CRS group patients with chest pain who were discharged from the ED directly was 0.70 (95% confidence interval [CI], 0.66-0.72) in the HEART score and 0.62 (95% CI, 0.59-0.67) in the EDACS score (Table 3 and Fig. 2). The best cutoff point was 4 (sensitivity, 83.2%; specificity, 42.6%; Youden’s index, 0.26) in the HEART score, and 14 (sensitivity 43.9%, specificity 79.2%, Youden’s index 0.23) in the EDACS score.

  1. Discussion

This single-center retrospective study showed that while using CRS for the disposition of patients with Suspected acute coronary syndrome, ED physicians tend to discharge a higher proportion of patients. Al- though the discharge rate was higher in the CRS group, the rates of MACE and mortality within 60 days were similar to those of the control group. This might indicate that ED physicians would have more confi- dence in discharging low-risk patients based on CRS.

Previous studies documented that physician risk tolerance was sig- nificantly associated with the decision to admit patients or order for ad- ditional tests. Self-reported physician risk-taking behavior was documented with higher computed tomography ordering rate in patients with abdominal pain [14], dizziness [15], pediatric Minor head injury [16], and suspicion of pulmonary embolism (PE) [17]. Al- though the CT ordering rate was altered due to different physician risk tolerance, there was no significant difference in the admission rate and the final diagnostic rate [14-16]. In addition, for defensive behavior

Fig. 1. Area under the receiver operating characteristic curves for various chest pain scores among all patients.

Image of Fig. 2

Image of Fig. 1Fig. 2. Area under the receiver operating characteristic (ROC) curves for various chest pain scores among coronary risk score (CRS) group patients.

such as “fear of missing PE,” increased CT pulmonary angiography or- dering rate was associated with decreased odds of a positive finding [17]. It is known that the ED is a place of high stress, high variables, and high emotions among patients and families. The defensive medicine practice was observed among ED physicians by more laboratory and image studies than medically indicated [17].

Similarly, wide variability in chest pain observation unit utilization and admission exists among physicians. Pine’s study found that ED phy- sicians with higher risk aversion were linked to a higher admission rate and greater use of cardiac markers [10]. Furthermore, one retrospective study reported that more experienced ED physicians tended to admit patients with chest pain who really experienced MACE, whereas young ED physicians were more likely to admit low-risk patients [18]. Application of the HEART Pathway was reported to reduce the one-

Table 3

Area under the receiver operating characteristic curve analysis for patients with chest pain discharge directly from the ED.

Patient

Risk score

AUROC (95% CI)

Best cut-off point

Sensitivity (%) (95% CI)

Specificity (%) (95% CI)

Youden’s index

All

HEART

0.70 (0.68-0.72)

4

84.4 (82.6-86.0)

46.9 (43.7-50.2)

0.31

EDACS

0.57 (0.56-0.60)

13

47.1 (44.7-49.4)

61.5 (58.3-64.7)

0.13

CRS group

HEART

0.70 (0.66-0.72)

4

83.2 (80.0-86.1)

42.6 (35.0-50.4)

0.26

EDACS

0.62 (0.59-0.67)

14

43.9 (39.8-48.0)

79.2 (72.4-85.1)

0.23

ED = emergency department, CRS = coronary risk scores, CI = confidence interval, HEART = History, Electrocardiogram, Age, Risk Factors, Troponin score, EDACS = Emergency Depart- ment Assessment of Chest pain Score.

year hospitalization rate by 7%, without a difference in the rates of death or MI at one-year follow-up (11.6% versus 12.4%) [19]. Mahler et al. also found that HEART pathway implementation was associated with a de- crease in the hospitalization rate by 6% at 30 days and very low death and MI rates among low-risk patients (1.1% versus 1.3%; adjusted odds ratio, 0.88; 95% CI, 0.58-1.33) [20]. Variation in ED practice was considered a quarry for improving healthcare quality, ED crowding, safety, efficiency, and costs. Establishing Diagnostic protocols for dispo- sition planning in patients with chest pain is likely to result in signifi- cantly fewer patients receiving unnecessary admission and substantial savings. Our study demonstrated that ED physicians tend to discharge a higher proportion of patients based on CRS calculation, which might support the above conclusion.

Several Risk stratification scores were developed and compared for better utility in ED settings. Using the HEART score to identify patients with chest pain, low-risk patients were at low probability (1.6%) of de- veloping MACEs at a mean of 6 weeks’ follow-up [21]. EDACS was re- ported to be sensitive for MACE was 88.2% at 30 days’ follow-up [22]. Mark et al. reported that both HEART and EDACS predicted a low risk of 60-day MACE with improved accuracy using a troponin I cutoff below the 99th percentile [23]. Stopyra et al. concluded that a HEART score of <=3 combined with the European Society of Cardiology 3-h path- way seems to be the most reliable clinical risk score with a 99.7% nega- tive predictive value (NPV), compared with an EDACS score of <16 (99.2% NPV) and the Global Registry of Acute coronary events score of <=108 (99% NPV) [24]. Shin et al. also demonstrated that the HEART score appeared to be more predictive of MACEs than EDACS and GRACE in patients with chest pain or angina equivalents [25]. Another multicenter study reported that the EDACS identified 10% more patients as low risk, with a nearly similar NPV as that of HEART [26]. In our study, the best cutoff point for predicting patient dis- charge directly from the ED was 4 in the HEART score and 13 in the EDACS score. In the CRS group, the best cutoff point was 4 in the HEART score and 14 in the EDACS score. Importantly, there was no sig- nificant difference in MACEs and mortality within 60 days between the control and CRS groups.

There were several limitations to our study. First, though up to 95% of the study patients had at least one follow-up at the outpatient department of the same hospital, there are 5% of the patients that lost follow-up or were managed at other hospitals thereafter, of whom the important outcomes such as mortality or MACEs could be lost. Second, we did not perform troponin test and ECG for all discharged patients during follow-up assessment. However, for the possibility of underestimating the incidence of MACEs, we carefully reviewed all rel- evant medical records if patients revisited our hospital during the follow-up period. Finally, this study was conducted in a single Tertiary medical center, which might limit the sample size and ethnic differ- ences. Further large-scale, multi-center studies should be conducted to improve the validity of the results.

In conclusion, the higher ED discharge rate of the group using CRS may indicate that ED physicians have more confidence in discharge low-risk patients based on CRS.

Funding

This research did not receive any specific grant from funding agen- cies in the public, commercial, or not-for-profit sectors.

IRB: The Institutional Review Board of Chang Cheng Memorial Hos- pital approved this study (IRB No.: 202002184B0).

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and analyzed during the current study are avail- able from the corresponding author on reasonable request.

Declaration of Competing Interest

The authors declare that they have no competing interests.

Acknowledgments

We appreciate the support provided for statistics at the Biostatistics Center of Kaohsiung Chang Gung Memorial Hospital.

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