Circulation Journal
Online ISSN : 1347-4820
Print ISSN : 1346-9843
ISSN-L : 1346-9843
Rationale, Design, Feasibility, and Profile of the Japanese Circulation Society Chest Pain Registry　― Single-Center Pilot Study ―
Satoshi Yoshimura, Kanna Arimoto, Hirotoshi Nishikita, Yohei Fushimura, Yasuyuki Sumida, Hirokazu Yokoi, Chika Nishiyama, Takuya Taniguchi, Tetsuya Amano, Tomonori Itoh, Satomi Konno, Nogiku Niwamae, Masashi Sakuma, Kayoko Sato, Yasuhiro Satoh, Yoshio Tahara, Kenichi Tsujita, Yayoi Tetsuou Tsukada, Yasunori Ueda, Takeyuki Kiguchi, Kosuke Kiyohara, Tetsuhisa Kitamura, Taku Iwami , on behalf of the Education and Implementation for Cardiac Emergency Committee of the Japanese Circulation Society
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Keywords: Acute coronary syndrome, Acute myocardial infarction, Chest pain, Diagnosis, Emergency medicine
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Abstract

Background: Acute coronary syndrome (ACS) requires prompt diagnosis and treatment. Although “OPQRST” (Onset, Provocation, Quality, Region/Radiation, Symptoms, and Time) is commonly used, the evidence linking emergency department (ED) chest pain characteristics to ACS remains inconclusive. This study evaluated detailed symptoms in ED patients with and without ACS using a broad chest pain registry with symptom data.

Methods and Results: This single-center prospective study was conducted at Rakuwakai-Otowa Hospital in Kyoto, Japan, as a pilot study for a multicenter registry. We enrolled 420 consecutive adult patients presenting with chest pain at the ED from June 2022 to May 2023. Baseline characteristics (including symptoms) and outcomes were recorded. Of the 420 patients, 65 (15.5%) were diagnosed with ACS. Patients with and without ACS differed in the proportion with sudden onset (58.5% vs. 27.6%, respectively), radiation to the tooth (9.2% vs. 0.6%, respectively), and cold sweat (diaphoresis; 44.6% vs. 16.9%, respectively). In the overall population, positive likelihood ratios were 2.12 (95% confidence interval [CI] 1.63–2.76) for sudden onset, 16.38 (95% CI 3.38–79.41) for radiation to the tooth, and 2.64 (95% CI 1.85–3.77) for diaphoresis.

Conclusions: This study in a suburban area of Japan (one of the most super-aged societies) identified key chest pain characteristics in a broad chest pain cohort (i.e., sudden onset, radiation to the tooth, and diaphoresis) that may help with the rapid triage and diagnosis of ACS.

Acute coronary syndrome (ACS), which includes acute myocardial infarction (AMI) and unstable angina pectoris (UAP), is a critical cardiovascular condition requiring prompt diagnosis and treatment to reduce mortality.1–4 The incidence rate of AMI in Japan is reported to be in the range of 46.4–100.7 per 100,000 population for men and 9.6–35.7 per 100,000 population for women.1,5,6 Although the in-hospital mortality rate for AMI has decreased over the past 20 years due to advances in interventional and therapeutic techniques, there has been no improvement in recent years and the mortality rate remains high.7 Furthermore, it is has been suggested that ACS may result in death in approximately half of all cases before patients reach hospital.8

The traditional symptoms of ACS, summarized by the acronym “OPQRST” (Onset, Provocation, Quality, Region/Radiation, Symptoms [and/or Severity], and Time),9 guide clinicians in diagnosing ACS and encourage patients to seek emergency medical services (EMS). Previous studies suggest that symptoms such as radiation to the neck, jaw, and shoulders and cold sweat (diaphoresis) are specific indicators of ACS.10 However, robust evidence is lacking due to the limited number of studies including all patients with chest pain.10 Although some registry studies on ACS have been actively conducted worldwide,11–13 these studies have primarily targeted individuals diagnosed with ACS, rather than all patients with chest pain. Therefore, there are few studies on the performance of symptom-based diagnoses of ACS, highlighting the need for a registry that includes patients with chest pain and comprehensive information on the patient journey, from initial symptoms to diagnosis and clinical outcomes.

Thus, the aim of the present study was to clarify the characteristics of chest pain, its nature and details, in patients who visited the ED with chest symptoms and were diagnosed with ACS, using a broad chest pain registry with symptom data. In addition, this study serves as a feasibility study within the framework of an ongoing multicenter study (UMIN000053978), the goals of which are to: (1) develop a system for gathering and sharing medical data related to chest pain and ACS; (2) enhance emergency transportation networks; and (3) ensure access to EMS while formulating treatment guidelines for ACS. Consequently, this study has the potential to enhance emergency care systems and deepen our understanding of the symptoms of ACS in Japan as a “super-aged” society,14 across the world.

Methods

Study Design

The Education and Implementation for Cardiac Emergency Committee of the Japanese Circulation Society (JCS) initiated a cohort study called the Chest Pain Registry to systematically collect data on the characteristics of chest pain from June 1, 2022. The present study is a pilot study in a single center that was performed to check the feasibility of the subsequent multicenter study.

Study Setting

The present study is a single-center prospective study conducted at Rakuwakai-Otowa Hospital, a suburban general hospital with an emergency medical center in Kyoto. The hospital has over 400 beds in the general ward, including 32 beds for acute care and 12 beds in the intensive care unit. In 2022, the hospital recorded more than 22,000 visits (an average of 60 patients/day) and received over 7,000 emergency department (ED) patients via ambulance annually. Rakuwakai-Otowa Hospital is the only emergency medical center in the district, serving a population of 135,101 in the Yamashina district.15 Furthermore, Rakuwakai-Otowa Hospital rarely refuses patients even when there are no beds available, resulting in a high number of patients with chest pain seeking care at this facility.

ED System Overview

In Rakuwakai-Otowa Hospital, patients accessing outpatient services do so either by walking in or arriving via ambulance; all are routed through the ED before they are either discharged or admitted. Walk-in patients undergo triage by a nurse before being seen by a physician, whereas those arriving by ambulance receive immediate attention from an ED physician. In cases where ACS is suspected, a cardiologist is on standby 24/7 to consult and provide necessary examinations and treatments, including emergency cardiac catheterization, upon referral from the emergency medicine physician.

Study Population

We enrolled all consecutive patients aged ≥18 years presenting with a primary complaint of “chest pain” at the ED between June 1, 2022 and May 31, 2023. The term “chest pain” encompasses any type of chest pain and discomfort, including typical angina symptoms as well as other forms of chest pain and discomfort.1–3 In addition, we included all patients with a diagnosis of ACS (AMI and UAP), including those presenting with cardiac arrest, to ensure that ACS patients without chest pain were not missed during the study period. We excluded patients with onset of chest pain within the hospital and chest pain of obvious external origin (e.g., traumatic accident).

Data Collection and Quality Control

Figure 1 shows the study flow in the ED and hospital. In this study, as a principle, information was registered in the electronic data capture (EDC) system at the scene by ED nurses or emergency medical technicians. In emergency cases where registration was difficult, the information registered was based on prediagnosis medical records in the ED. Patient details were deidentified and registered in the EDC system. The principal investigator at the institution was responsible for monitoring the data and confirming any missing data; if there were missing data, nurses and paramedics in the ED were able to provide additional information as needed. All patients were evaluated for ACS by an emergency physician or cardiologist, with cases of ACS adjudicated by the cardiologist in charge. This assessment involved medical evaluation, such as an electrocardiogram (ECG), measurement of troponin levels, and coronary angiography. In the present study, the diagnostic flow for patients with chest pain followed international ACS and chest pain guidelines.1–3 The cardiologist recorded the diagnosis of ACS and input information into the EDC system. For patients who were not hospitalized, the diagnosis of ACS was based on ED medical records. Details for each of the variables collected in this study are provided in Supplementary Table 1. Brief descriptions of the data included in this study are provided below.

Figure 1.

Study flow and overview. The figure shows the process for confirming a diagnosis following a hospital visit. Clinical staff collect chest pain information at the emergency department (ED) and enter it into an electronic data capture (EDC) system, typically via a tablet device. After the initial evaluation, a cardiologist assesses each patient for acute coronary syndrome (ACS) and records the diagnosis in the EDC system. For patients with non-cardiac conditions or those not admitted, the diagnosis is based on ED records. ECG, electrocardiogram.

Details of the Data Collected Details of the data collected are provided in the Supplementary Methods. Brief descriptions of the collected data are given below.

Patient Characteristics Information collected included patient sex, age, height, weight, hospital arrival date, cardiovascular history, medication use, comorbidities, smoking status, and atrial fibrillation. For patients experiencing out-of-hospital cardiac arrest (OHCA), we also recorded whether bystander cardiopulmonary resuscitation had been provided, witness status, and initial documented rhythm.

EMS Data EMS records provided timestamps (call, scene arrival, departure, hospital arrival), vital signs (blood pressure, heart rate, respiratory rate, SpO2), and level of consciousness (Japanese Coma Scale).

Chest Pain Characteristics Symptoms were evaluated using the OPQRST method,1–3,9 and included onset time, the nature of the pain, radiation, exacerbating factors, and associated symptoms. “Sudden onset” was defined as pain peaking within 1 min.

Vital Signs on ED Arrival Recorded parameters included blood pressure, heart rate, respiratory rate, SpO2 (room air/oxygen), oxygen dosage, shock status, Killip classification, and Braunwald classification.1–3

Hospital Management Treatment data encompassed mechanical circulatory support, coronary angiography, thrombotic occlusion, stenosis, percutaneous coronary intervention, stent placement, culprit lesion, and reperfusion time.

Outcomes and Definitions Outcomes included ED and hospitalization diagnoses, along with 30-day survival. ACS included both AMI and UAP, following universal guidelines.1–3 A diagnosis of AMI required elevated troponin levels with ischemic symptoms, ECG changes, imaging evidence, or intracoronary thrombus according to the universal definition.1–3 Cardiologists determined ST-elevation myocardial infarction (STEMI) or non-ST segment elevation myocardial infarction (NSTEMI). Other diagnoses were categorized as cardiovascular or non-cardiovascular diseases.

Data Management and Quality Control The data underwent thorough verification before and after development of the EDC system. Categorical data clarification and comprehensive data cleaning were conducted using R. Key variables, including dates and vital signs, were checked for consistency. The final dataset was validated and corrected by April 10, 2024. Further details on data cleaning and quality control are provided in the Supplementary Methods.

Statistical Analysis

Demographics, comorbidities, EMS information, vital signs upon arrival, symptom details (OPQRST), and outcome were compared between non-ACS and ACS patients using the Mann-Whitney U test and Chi-squared test and/or Fisher’s exact test, as appropriate, with 2-tailed P<0.05 considered statistically significant. Although the present study is exploratory research aimed at generating hypotheses about which variables, particularly details of symptoms, such as OPQRST, may be useful for detecting ACS, Bonferroni correction was used for background characteristics and for comparisons of OPQRST between groups to address the issue of multiple testing.16 In addition, we performed a subgroup analysis based on age, dividing participants into younger (age <65 years) and older (age ≥65 years) groups, with the significance level set at 0.05. The cut-off age of 65 years was determined based on previous studies.17,18 We also compared symptoms of non-ACS and ACS patients according to type of hospital visit (walk-in or ambulance). In addition, we analyzed characteristics across 3 groups: non-ACS, STEMI, and NSTEMI/UAP.

For variables that differed significantly among groups, we calculated their diagnostic accuracy (i.e., sensitivity, specificity, positive predictive value [PPV], negative predictive value [NPV], positive likelihood ratio [LR+], and negative likelihood ratio [LR−] with 95% confidence intervals [CIs]) in a post hoc analysis. These analyses were repeated in ACS and non-ACS stratified according to age.

All statistical analyses were performed using R version 4.3.1 (2023-06-16).

Ethical Considerations

This JCS Chest Pain Registry, including a retrospective analysis, was approved by the ethics committees of Kyoto University (R-3319-2) and Rakuwakai-Otowa Hospital (01-21-00139). The requirement for informed consent was waived. Both this single-center study (UMIN000045934) and the upcoming multicenter study (UMIN000053978) have been registered with the University Hospital Medical Information Network (UMIN).

This manuscript was written based on the STROBE statement.19

Results

Figure 2 shows an overview of the study patients. In all, 12,247 non-trauma patients presented to the ED between June 1, 2022, and May 31, 2023. Of these, 460 patients aged ≥18 years had chest pain. After excluding 1 duplicate patient, 24 patients who were referred from another hospital or clinic, 9 patients referred from the cardiovascular outpatient department, and 6 patients who were OHCA, 420 adult patients were eligible for analysis in this study.

Figure 2.

Patient flow. The figure shows the categorization of adult patients (aged ≥18 years) with chest pain who were admitted to the emergency department (ED) without an out-of-hospital cardiac arrest (OHCA) between June 1, 2022 and May 31, 2023. Of the 12,247 non-trauma adult patients who presented at the ED, 460 patients experienced chest pain. Of these 460 patients, 24 were referred from other hospitals or clinics, and 9 were referred from cardiovascular outpatient departments. Six patients experienced OHCA and were excluded from the primary analysis. Of the remaining 420 patients, 65 (15.5%) were diagnosed with acute coronary syndrome (ACS) in the ED and further classified into ST-elevation myocardial infarction (STEMI; n=36), non-STEMI (NSTEMI; n=6), and unstable angina pectoris (UAP; n=23) groups.

The baseline characteristics of the 420 patients with chest pain are presented in Table 1. Of these 420 patients, 65 (15.5%) were diagnosed with ACS. The median age of patients was 75 years in the non-ACS group and 70 years in the ACS group. There were 185 (52.1%) and 47 (72.3%) men in the non-ACS and ACS groups, respectively. The median body mass index was 21.9 and 24.2 kg/m2 in the non-ACS and ACS groups, respectively. In the non-ACS and ACS groups, 55 (15.5%) and 20 (30.8%) patients, respectively, were current smokers 186 (52.4%) and 46 (70.8%) patients, respectively, had hypertension (Table 1).

Table 1.

Patient Characteristics and Status in the Emergency Department According to the Presence of ACS

  Non-ACS
(n=355)		 ACS
(n=65)		 P value Missing
(%)
Age (years) 75 [57–82] 70 [61–78] 0.116 0
Male sex 185 (52.1) 47 (72.3) 0.003 0
BMI (kg/m2) 21.9 [19.5–24.5] 24.2 [21.3–27.0] 0.001 5.2
Smoking status     0.001A 0.5
　Current smoker 55 (15.5) 20 (30.8)    
　Ex-smoker 106 (29.9) 23 (35.4)    
　Non-smoker 166 (46.8) 14 (21.5)    
　Unknown 27 (7.6) 7 (10.8)    
Past medical history of CVDsB       0
　Old MI 49 (13.8) 10 (15.4) 0.227  
　Coronary stenosis 10 (2.8) 10 (15.4) 0.045  
　Aortic dissection 6 (1.7) 0 (0) 0.291  
　Heart failure 45 (12.7) 5 (7.7) 0.254  
　Cerebral infarction 27 (7.6) 2 (3.1) 0.186  
　Cerebral hemorrhage 8 (2.3) 3 (4.6) 0.273  
　Subarachnoid hemorrhage 0 (0) 0 (0) N/A  
　None of the above 231 (65.1) 46 (70.8) 0.373  
Past medical history of coronary risk factors
　Diabetes 67 (18.9) 16 (24.6) 0.285 0
　　Unknown 0 (0) 0 (0)    
　Dyslipidemia 132 (37.2) 23 (35.4) 0.870 0.2
　　Unknown 1 (0.3) 0 (0)    
　Hypertension 186 (52.4) 46 (70.8) 0.006 0
　　Unknown 0 (0) 0 (0)    
　Atrial fibrillation 64 (18.0) 3 (4.6) 0.020 0
　　Unknown 2 (0.6) 0 (0.0)    
　Chronic kidney disease 38 (10.7) 8 (12.3) 0.687 0.5
　　Unknown 0 (0) 0 (0)    
　Dialysis 11 (3.1) 3 (4.6) 0.518 0.2
　　Unknown 1 (0.3) 0 (0)    
Vital signs on hospital arrival
　SBP (mmHg) 144.0 [127.0–168.0] 146.5 [135.0–166.8] 0.160 0
　DBP (mmHg) 83.0 [71.0–96.0] 89.0 [78.0–105.0] 0.030 0.2
　Heart rate (beats/min) 80.0 [71.0–92.0] 74.0 [68.0–86.0] 0.053 0.5
　Respiratory rate (/min) 18.0 [16.0–20.0] 19.0 [16.0–22.0] 0.086 0.5
　SpO2 on ambient air (%) 98.0 [97.0–99.0] 98.0 [97.0–99.0] 0.386 6.7
Means of attending hospital     0.006A 0
　Arrival by ambulance 148 (41.7) 39 (60.0)    
　Walk-in visit 207 (58.3) 26 (40.0)    
Coronary angiography 16 (4.5) 61 (93.8) <0.001 0

Unless indicated otherwise, data are given as the median [interquartile range] or n (%). AThe global test was performed using the Chi-squared test. BMultiple responses were possible. ACS, acute coronary syndrome; BMI, body mass index; CVDs, cardiovascular diseases; DBP, diastolic blood pressure; MI, myocardial infarction; N/A, not applicable; SBP, systolic blood pressure.

Details of chest pain (OPQRST) are provided in Table 2. Compared with the non-ACS group, a higher proportion of patients in the ACS group experienced sudden onset (98 [27.6%] vs. 38 [58.5%]), squeezing pain (149 [42.0%] vs. 34 [52.3%]), radiation to the tooth (2 [0.6%] vs. 6 [9.2%]), and cold sweat (diaphoresis; 60 [16.9%] vs. 29 [44.6%]). However, a higher proportion of patients in the non-ACS than ACS group reported pain worsening with positional changes (28 [7.9%] vs. 1 [1.5%]) and tenderness (44 [12.4%] vs. 2 [3.1%]). A similar proportion of patients in the non-ACS and ACS groups experienced oppressive pain (73 [20.6%] vs. 14 [21.5%], respectively).

Table 2.

Characteristics of Chest Pain Assessed by OPQRST (Onset, Provocation, Quality, Region/Radiation, Symptoms, and Time) Among Patients With Chest Pain

  Non-ACS
(n=355)		 ACS
(n=65)		 P valueA Missing
(%)
Pattern of onset     <0.001B 3.6
　Sudden onset 98 (27.6) 38 (58.5)    
　Acute onset 90 (25.4) 12 (18.5)    
　Chronic onset 145 (40.8) 12 (18.5)    
　Unknown 9 (2.5) 1 (1.5)    
Provocation factorsC       0
　Worsening with breathing 30 (8.5) 2 (3.1) 0.212  
　Worsening with cough 5 (1.4) 0 (0) 0.733  
　Worsening with positional changes 28 (7.9) 1 (1.5) 0.112  
　Worsening with effort 18 (5.1) 4 (6.2) 0.954  
　None of above 273 (76.9) 57 (87.7) 0.051  
　Unknown 20 (5.6) 4 (6.2) 1.000  
Type of painC       0
　Oppressive 73 (20.6) 14 (21.5) 0.991  
　Sense of compression 57 (16.1) 11 (16.9) 1.000  
　Squeezing 149 (42.0) 34 (52.3) 0.159  
　Tightness 18 (5.1) 3 (4.6) 1.000  
　Heartburning 2 (0.6) 1 (1.5) 0.954  
　Prickling 10 (2.8) 2 (3.1) 1.000  
　Stabbing 9 (2.5) 4 (6.2) 0.246  
　Discomfort 57 (16.1) 7 (10.8) 0.367  
　None of the above 22 (6.2) 3 (4.6) 0.833  
　Unknown 6 (1.7) 2 (3.1) 0.796  
TendernessC 44 (12.4) 2 (3.1) 0.046 7.9
　Unknown 5 (1.4) 2 (3.1) 0.661  
Region/radiationC       4.0
　Tooth 2 (0.6) 6 (9.2) <0.001  
　Jaw 2 (0.6) 3 (4.6) 0.006  
　Neck 17 (4.8) 1 (1.5) 0.234  
　Right shoulder 5 (1.4) 3 (4.6) 0.082  
　Left shoulder 17 (4.8) 9 (13.8) 0.005  
　Precordial (middle) 194 (54.6) 39 (60.0) 0.504  
　Precordial (right) 36 (10.1) 7 (10.8) 0.878  
　Precordial (left) 118 (33.2) 32 (49.2) 0.013  
　Epigastric region 67 (18.9) 10 (15.4) 0.504  
　Right hypochondrium 4 (1.1)   0.390  
　Left hypochondrium 4 (1.1) 1 (1.5) 0.778  
　Others 5 (1.4) 4 (6.2) 0.015  
　None of the above 7 (2) 1 (1.5) 0.814  
Associated symptomsC       1.2
　Breathlessness 103 (29.0) 18 (27.7) 0.777  
　Back pain 50 (14.1) 12 (18.5) 0.386  
　Discomfort 29 (8.2) 9 (13.8) 0.153  
　Cold sweat 60 (16.9) 29 (44.6) <0.001  
　Vomiting 22 (6.2) 5 (7.7) 0.673  
　Nausea 38 (10.7) 5 (7.7) 0.442  
　Malaise 15 (4.2) 4 (6.2) 0.508  
　Syncope 1 (0.3) 2 (3.1) 0.015  
　None of the above 130 (37.1) 16 (24.6) 0.052  
　Unknown 5 (1.4) 0 (0.0) 0.332  
Recurring chest pain 106 (29.9) 27 (41.5) 0.086 0.2
　Unknown 12 (3.4) 4 (6.2) 0.471  
Duration of pain     0.191B 0
　<5 min 17 (4.8) 4 (6.2)    
　5–20 min 34 (9.6) 11 (16.9)    
　20 min-1 h 79 (22.3) 16 (24.6)    
　>1 h 221 (62.3) 32 (49.2)    
　Unknown 4 (1.1) 2 (3.1)    

AThe significance level was set at 0.0011 (0.05/45) after adjustment for multiple testing using the Bonferroni correction. BGlobal tests were performed using Fisher’s exact test. CMultiple responses were possible. ACS, acute coronary syndrome.

Table 3 shows analyses stratified by age. Sudden onset and cold sweat were frequently observed in ACS patients regardless of age group. However, these symptoms were more common in younger (<65 years) than older (≥65 years) patients. Among younger (<65 years) patients, sudden onset (70.8% vs. 36.1%; P=0.004) and cold sweat (64.0% vs. 18.8%; P<0.001) were significantly more frequent in the ACS than non-ACS group. Among older (≥65 years) patients, there were significant differences between ACS and non-ACS groups in sudden onset (52.5% vs. 24.3%, respectively; P=0.003) and cold sweat (32.5% vs. 16.0%, respectively; P=0.028). The symptoms of patients with and without ACS according to type of hospital visit (walk-in or ambulance) and ACS type (STEMI, NSTEMI, or UAP) are detailed in Supplementary Tables 2 and 3.

Table 3.

Characteristics of Chest Pain Assessed Using OPQRST (Onset, Provocation, Quality, Region/Radiation, Symptoms, and Time) Among Patients With Chest Pain Stratified by Age Group

  Age <65 years (n=137) Age ≥65 years (n=283)
Non-ACS
(n=112)		 ACS
(n=25)		 P valueA Non-ACS
(n=243)		 ACS
(n=40)		 P valueA
Pattern of onset     0.004B     0.003B
　Sudden onset 39 (36.1) 17 (70.8)   59 (24.3) 21 (52.5)  
　Acute onset 24 (22.2) 4 (16.7)   66 (27.2) 8 (20.0)  
　Chronic onset 44 (40.7) 2 (8.3)   101 (41.6) 10 (25.0)  
　Unknown 1 (0.9) 1 (4.2)   8 (3.3) 0 (0)  
　Missing 4 (3.6) 1 (4.0)   9 (3.7) 1 (2.5)  
Provocation factorsC
　Worsening with breathing 13 (11.6) 0 (0) 0.158 17 (7.0) 2 (5.0) 0.899
　Worsening with cough 0 (0) 0 (0) N/A 5 (2.1) 0 (0) 0.789
　Worsening with positional changes 13 (11.6) 1 (4.0) 0.441 15 (6.2) 0 (0) 0.217
　Worsening with effort 6 (5.4) 1 (4.0) 1.000 12 (4.9) 3 (7.5) 0.772
　None of the above 30 (26.8) 3 (12.0) 0.192 191 (78.6) 35 (87.5) 0.277
　Unknown 5 (4.5) 2 (8.0) 0.823 15 (6.2) 2 (5.0) 1.000
Type of painC
　Oppressive 17 (15.2) 4 (16.0) 1.000 56 (23.0) 10 (25.0) 0.945
　Sense of compression 19 (17.0) 1 (4.0) 0.178 38 (15.6) 10 (25.0) 0.217
　Squeezing 46 (41.1) 15 (60.0) 0.134 103 (42.4) 19 (47.5) 0.665
　Tightness 7 (6.2) 1 (4.0) 1.000 11 (4.5) 2 (5.0) 1.000
　Heartburning 0 (0) 1 (4.0) 0.409 2 (0.8) 0 (0) 1.000
　Prickling 4 (3.6) 0 (0) 0.763 6 (2.5) 2 (5.0) 0.704
　Stabbing 1 (0.9) 1 (4.0) 0.803 8 (3.3) 3 (7.5) 0.404
　Discomfort 17 (15.2) 2 (8.0) 0.536 40 (16.5) 5 (12.5) 0.688
　None of the above 12 (10.7) 1 (4.0) 0.510 10 (4.1) 2 (5.0) 1.000
　Unknown 0 (0.0) 2 (8.0) 0.036 6 (2.5) 0 (0) 0.680
Tenderness 12 (10.7) 1 (4.0) 0.510 32 (13.2) 1 (2.5) 0.093
　Unknown 0 (0) 2 (8.0) 0.036 0 (0) 2 (8.0) 0.036
Region/radiationC
　Tooth 0 (0.0) 3 (12.0) 0.003 2 (0.8) 3 (7.5) 0.020
　Jaw 1 (0.9) 1 (4.0) 0.803 1 (0.4) 2 (5.0) 0.073
　Neck 9 (8.0) 1 (4.0) 0.782 8 (3.3) 0 (0) 0.516
　Right shoulder 0 (0) 2 (8.0) 0.036 5 (2.1) 1 (2.5) 1.000
　Left shoulder 4 (3.6) 6 (24.0) 0.002 13 (5.3) 3 (7.5) 0.860
　Precordial (middle) 59 (52.7) 14 (56.0) 0.937 135 (55.6) 25 (62.5) 0.516
　Precordial (right) 8 (7.1) 1 (4.0) 0.899 28 (11.5) 6 (15.0) 1.000
　Precordial (left) 49 (43.8) 12 (48.0) 0.870 69 (28.4) 20 (50.0) 0.011
　Epigastric region 20 (17.9) 5 (20.0) 1.000 47 (19.3) 5 (12.5) 0.415
　Right hypochondrium 0 (0) 0 (0) N/A 4 (1.6) 0 (0) 0.925
　Left hypochondrium 2 (1.8) 1 (4.0) 1.000 2 (0.8) 0 (0) 1.000
　Others 2 (1.8) 2 (8.0) 0.312 3 (1.2) 2 (5.0) 0.304
　Unknown 2 (1.8) 0 (0) 1.000 5 (2.1) 1 (2.5) 1.000
Associated symptomsC
　Breathlessness 35 (31.2) 3 (12.0) 0.090 68 (28.0) 15 (37.5) 0.340
　Back pain 19 (17.0) 5 (20.0) 0.944 31 (12.8) 7 (17.5) 0.608
　Discomfort 8 (7.1) 3 (12.0) 0.688 21 (8.6) 6 (15.0) 0.351
　Cold sweat 21 (18.8) 16 (64.0) <0.001 39 (16.0) 13 (32.5) 0.028
　Vomiting 8 (7.1) 2 (8.0) 1.000 14 (5.8) 3 (7.5) 0.969
　Nausea 17 (15.2) 2 (8.0) 0.536 21 (8.6) 3 (7.5) 1.000
　Malaise 3 (2.7) 1 (4.0) 1.000 12 (4.9) 3 (7.5) 0.796
　Syncope 0 (0) 2 (8.0) 0.036 1 (0.4) 0 (0) 1.000
　None of the above 39 (34.8) 5 (20.0) 0.231 91 (37.4) 11 (27.5) 0.260
　Unknown 0 (0) 0 (0) N/A 5 (2.1) 0 (0) 0.778
Recurring chest pain 42 (37.5) 9 (36.0) 1.000 64 (26.3) 18 (45.0) 0.033
　Unknown 2 (1.8) 2 (8.0) 0.312 10 (4.1) 2 (5.0) 1.000
Duration of pain
　<5 min 11 (9.8) 1 (4.0) 0.265B 6 (2.5) 3 (7.5) 0.172B
　5–20 min 12 (10.7) 4 (16.0)   22 (9.1) 7 (17.5)  
　20 min-1 h 21 (18.8) 8 (32.0)   58 (23.9) 8 (20.0)  
　>1 h 67 (59.8) 11 (44.0)   154 (63.4) 21 (52.5)  
　Unknown 1 (0.9) 1 (4.0)   3 (1.2) 1 (2.5)  

Unless indicated otherwise, data are given as n (%). ASubgroup analyses were conducted without adjustment for multiplicity (significance level set at 0.05). BGlobal tests were performed using Fisher’s exact test. CMultiple responses were possible. ACS, acute coronary syndrome; N/A, not applicable.

Table 4 provides details of diagnoses. Of the non-ACS patients, 15 (4.2%) were diagnosed with acute aortic dissection, 96 (22.9%) were diagnosed with other cardiac causes, and 134 (31.9%) were diagnosed with pain of unknown origin. Of the 65 ACS patients, 36 (55.4%) were diagnosed with STEMI, 6 (9.2%) were diagnosed with NSTEMI, and 23 (35.4%) were diagnosed with UAP.

Table 4.

Details of the Diagnosis in Overall and in Patients With and Without ACS Separately

  Overall
(n=420)		 Non-ACS
(n=355)		 ACS
(n=65)		 Missing
(%)A
Diagnosis       0.23
　Cardiovascular disease
　　STEMI 36 (8.6) N/A 36 (55.4)  
　　NSTEMI 6 (1.4) N/A 6 (9.2)  
　　UAP 23 (5.5) N/A 23 (35.4)  
　　Acute aortic dissection 15 (3.6) 15 (4.2) N/A  
　　Aortic aneurysm 0 (0) 0 (0) N/A  
　　Acute pulmonary embolism 0 (0) 0 (0) N/A  
　　Pericarditis 1 (0.2) 1 (0.3) N/A  
　　Fulminant myocarditis 0 (0) 0 (0) N/A  
　　Takotsubo cardiomyopathy 2 (0.5) 2 (0.6) N/A  
　　Other cardiac diseases 96 (22.9) 96 (27) N/A  
　Non-cardiovascular disease
　　Respiratory disease 19 (4.5) 19 (5.4) N/A  
　　Gastrointestinal disease 33 (7.9) 33 (9.3) N/A  
　　Renal disease 2 (0.5) 2 (0.6) N/A  
　　Collagen disease 0 (0) 0 (0) N/A  
　　Hematological disease 1 (0.2) 1 (0.3) N/A  
　　Infectious disease 2 (0.5) 2 (0.6) N/A  
　　Endocrine disease 2 (0.5) 2 (0.6) N/A  
　　Neurological disease 2 (0.5) 2 (0.6) N/A  
　　Psychiatric disease 14 (3.3) 14 (3.9) N/A  
　　Others 31 (7.4) 31 (8.7) N/A  
　　Unknown 134 (31.9) 134 (37.7) N/A  

ATransferred to another hospital. ACS, acute coronary syndrome; N/A, not applicable; NSTEMI, non-ST segment elevation myocardial infarction; STEMI, ST-elevation myocardial infarction; UAP, unstable angina pectoris.

The LRs for specific chest pain characteristics were analyzed to evaluate their diagnostic accuracy for ACS (Table 5). For the overall population, sudden onset of chest pain had a positive LR+ of 2.12 (95% CI 1.62–2.76) and a negative LR− of 0.57 (95% CI 0.43–0.77). Radiation to the tooth had the highest point estimate of LR+ (16.38; 95% CI 3.38–79.41) and an LR− of 0.91 (95% CI 0.84–0.99). Cold sweat (diaphoresis) was associated had an LR+ of 2.64 (95% CI 1.85–3.77) and an LR− of 0.67 (95% CI 0.53–0.83). Diagnostic values varied across age subgroups (Table 3); specifically, the LR+ for radiation to the left shoulder was 6.72 (95% CI 2.05–22.06) among younger (<65 years) patients, compared with 1.40 (95% CI 0.42–4.70) in older (≥65 years) patients. To clarify the results, post hoc analysis of the LR results are shown in Figure 3. Based on a previous report,20 we defined the diagnostic threshold as LR+ ≥2.0 with a 95% CI that does not include 1.0 and LR− ≤0.5 with a 95% CI that does not include 1.0. In the overall population, symptoms with a higher LR+ included sudden onset (LR+ 2.12; 95% CI 1.62–2.76), radiation to the tooth (LR+ 16.38; 95% CI 3.38–79.41), and cold sweat (LR+ 2.64; 95% CI 1.85–3.77). Notably, there were no symptoms with a low LR− in the overall population. In the younger (<65 years) age group, left shoulder pain (LR+ 6.72; 95% CI 2.05–22.06) and cold sweat (LR+ 3.41; 95% CI 2.10–5.54) had a higher LR+ than the other characteristics, whereas sudden onset had a low LR− (0.49; 95% CI 0.27–0.88). In the older (≥65 years) age group, sudden onset (LR+ 2.16; 95% CI 1.49–3.13), radiation to the tooth (LR+ 9.11; 95% CI 1.57–52.84), and cold sweat (LR+ 2.03; 95% CI 1.19–3.44) had a higher LR+ than the other characteristics. However, there were no pain characteristics with a low LR− that met our definition.

Table 5.

Diagnostic Accuracy for Acute Coronary Syndrome Based on Chest Pain Characteristics

  Sensitivity Specificity PPV NPV LR+ LR−
Overall cohort (n=420)
　Sudden onset 0.58 (0.46–0.71) 0.72 (0.67–0.77) 0.28 (0.21–0.36) 0.90 (0.86–0.94) 2.12 (1.62–2.76) 0.57 (0.43–0.77)
　Radiation to tooth 0.09 (0.03–0.19) 0.99 (0.98–1.00) 0.75 (0.35–0.97) 0.86 (0.82–0.89) 16.38 (3.38–79.41) 0.91 (0.84–0.99)
　Radiation to right shoulder 0.05 (0.01–0.13) 0.99 (0.97–1.00) 0.38 (0.09–0.76) 0.85 (0.81–0.88) 3.28 (0.8–13.38) 0.97 (0.92–1.02)
　Radiation to left shoulder 0.14 (0.07–0.25) 0.95 (0.92–0.97) 0.35 (0.17–0.56) 0.86 (0.82–0.89) 2.89 (1.35–6.2) 0.90 (0.82–1.00)
　Left precordial pain 0.49 (0.37–0.62) 0.67 (0.62–0.72) 0.21 (0.15–0.29) 0.88 (0.83–0.91) 1.48 (1.11–1.97) 0.76 (0.59–0.98)
　Cold sweat (diaphoresis) 0.45 (0.32–0.57) 0.83 (0.79–0.87) 0.33 (0.23–0.43) 0.89 (0.85–0.92) 2.64 (1.85–3.77) 0.67 (0.53–0.83)
　Syncope 0.03 (0.00–0.11) 1.00 (0.98–1.00) 0.67 (0.09–0.99) 0.85 (0.81–0.88) 10.92 (1.01–118.71) 0.97 (0.93–1.02)
　Recurring chest pain 0.42 (0.29–0.54) 0.70 (0.65–0.75) 0.20 (0.14–0.28) 0.87 (0.82–0.90) 1.39 (1.00–1.93) 0.83 (0.67–1.03)
Age <65 years (n=137)
　Sudden onset 0.68 (0.46–0.85) 0.65 (0.56–0.74) 0.30 (0.19–0.44) 0.90 (0.81–0.96) 1.95 (1.35–2.83) 0.49 (0.27–0.88)
　Radiation to tooth 0.12 (0.03–0.31) 1.00 (0.97–1.00) 1.00 (0.29–1.00) 0.84 (0.76–0.89) N/A 0.88 (0.76–1.02)
　Radiation to right shoulder 0.08 (0.01–0.26) 1.00 (0.97–1.00) 1.00 (0.16–1.00) 0.83 (0.76–0.89) N/A 0.92 (0.82–1.03)
　Radiation to left shoulder 0.24 (0.09–0.45) 0.96 (0.91–0.99) 0.60 (0.26–0.88) 0.85 (0.78–0.91) 6.72 (2.05–22.06) 0.79 (0.63–0.99)
　Left precordial pain 0.48 (0.28–0.69) 0.56 (0.47–0.66) 0.20 (0.11–0.32) 0.83 (0.73–0.91) 1.10 (0.69–1.74) 0.92 (0.61–1.39)
　Cold sweat (diaphoresis) 0.64 (0.43–0.82) 0.81 (0.73–0.88) 0.43 (0.27–0.61) 0.91 (0.84–0.96) 3.41 (2.10–5.54) 0.44 (0.26–0.75)
　Syncope 0.08 (0.01–0.26) 1.00 (0.97–1.00) 1.00 (0.16–1) 0.83 (0.76–0.89) N/A 0.92 (0.82–1.03)
　Recurring chest pain 0.36 (0.18–0.57) 0.63 (0.53–0.71) 0.18 (0.08–0.31) 0.81 (0.72–0.89) 0.96 (0.54–1.71) 1.02 (0.74–1.42)
Age ≥65 years (n=283)
　Sudden onset 0.53 (0.36–0.68) 0.76 (0.70–0.81) 0.26 (0.17–0.37) 0.91 (0.86–0.94) 2.16 (1.49–3.13) 0.63 (0.45–0.88)
　Radiation to tooth 0.08 (0.02–0.20) 0.99 (0.97–1.00) 0.60 (0.15–0.95) 0.87 (0.82–0.90) 9.11 (1.57–52.84) 0.93 (0.85–1.02)
　Radiation to right shoulder 0.03 (0–0.13) 0.98 (0.95–0.99) 0.17 (0–0.64) 0.86 (0.81–0.9) 1.22 (0.15–10.13) 1.00 (0.94–1.05)
　Radiation to left shoulder 0.08 (0.02–0.20) 0.95 (0.91–0.97) 0.19 (0.04–0.46) 0.86 (0.81–0.90) 1.40 (0.42–4.70) 0.98 (0.89–1.07)
　Left precordial pain 0.50 (0.34–0.66) 0.72 (0.65–0.77) 0.22 (0.14–0.33) 0.90 (0.85–0.94) 1.76 (1.22–2.55) 0.70 (0.51–0.96)
　Cold sweat (diaphoresis) 0.33 (0.19–0.49) 0.84 (0.79–0.88) 0.25 (0.14–0.39) 0.88 (0.83–0.92) 2.03 (1.19–3.44) 0.80 (0.64–1.00)
　Syncope 0.00 (0.00–0.09) 1.00 (0.98–1.00) 0.00 (0.00–0.98) 0.86 (0.81–0.90) N/A 1.00 (1.00–1.01)
　Recurring chest pain 0.45 (0.29–0.62) 0.74 (0.68–0.79) 0.22 (0.14–0.32) 0.89 (0.84–0.93) 1.71 (1.14–2.55) 0.75 (0.56–1.00)

Values in parentheses are 95% confidence intervals. LR−, negative likelihood ratio; N/A, not applicable; LR+, positive likelihood ratio; NPV, negative predictive value; PPV, positive predictive value.

Figure 3.

Diagnostic value of symptoms for chest pain: likelihood ratios (LR+ and LR−) by age group. Likelihood ratios for diagnosing chest pain are presented for all participants, as well as those aged <65 and ≥65 years separately. Sudden onset, tooth pain, and cold sweat had LR+ values ≥2.0, with cold sweat significant in both age groups. Left shoulder pain was relevant only for those aged <65 years. For LR− ≤0.5, sudden onset applies to those aged <65 years, but not to the overall or age ≥65 years groups. Although syncope had a high LR+, its 95% confidence interval (CI) was wide due to a few positive cases, so it was excluded from the figure.

Discussion

Summary

We successfully conducted a single-center prospective observational registry collecting detailed data on chest pain characteristics for consecutive adult patients presenting with chest pain to the ED as a pilot study of the Japanese Circulation Society Chest Pain Registry. We evaluated differences in the characteristics and details of chest pain (i.e., OPQRST) between non-ACS and ACS patients. Of the chest pain characteristics evaluated, sudden onset, radiation to the tooth, and cold sweat were associated with a greater chance of ACS. These characteristics of chest pain may be useful for the rapid triage of patients with ACS and patient’s advocation.

Evidence Gaps and Clinical Implications

Although a comprehensive review of chest pain and ACS symptoms was reported in 2015,10 according to assessments by systematic reviews of diagnostic accuracy studies,21,22 only a few studies have provided evidence regarding the diagnostic accuracy of symptom details because most studies only included ACS patients (i.e., did not include non-ACS patients with chest pain). In addition, evidence of the diagnostic accuracy of symptoms is lacking for the Japanese population and/or the super-aged population. To the best of our knowledge, no chest pain cohort like ours has been reported in Japan, which is one of the most super-aged societies in the world. This study makes it possible to comprehensively evaluate the diagnostic accuracy of the details of chest pain in the Japanese population.

Our findings highlight the diagnostic potential of specific chest pain characteristics, such as sudden onset, radiation to the tooth, and cold sweat (diaphoresis), in ruling in ACS in the ED. These symptoms reflect the underlying pathophysiology of ACS, where ischemia rapidly induces intense pain and autonomic responses.2 Atypical radiation patterns, such as tooth pain, may arise from cardiac-referred pain manifesting in uncommon regions.1,2 Incorporating these symptoms into ED triage protocols could enhance the identification of high-risk patients, enabling timely interventions and improving outcomes. Moreover, such symptom-based approaches may assist EMS personnel in the prehospital setting to detect ACS effectively. Although the present study does not aim to rule out ACS due to the low sensitivity and LR− values, guideline-recommended algorithms that incorporate high-sensitivity troponin and ECGs remain essential. Nonetheless, the symptoms identified can contribute to improved diagnostic accuracy, particularly in settings where there is a lack of cardiology specialists. Subgroup analysis demonstrated that the diagnostic utility of these symptoms may differ by age, because there were no symptoms with a low LR− in either the older population or the overall cohort. This highlights the importance of age-specific considerations when interpreting diagnostic findings.

These results also underscore the importance of public education and patient advocacy. With approximately 50% of AMI patients dying in the prehospital setting8 and 80% of ACS patients experiencing chest pain,23 early recognition of symptoms and prompt action are critical. Public health initiatives, such as Japan’s 2019 Cerebrovascular and Cardiovascular Disease Control Act24 and the JCS STOP MI Campaign,25 emphasize public awareness and education to reduce delays and improve outcomes. Building on these findings, this registry will serve as a foundation for future multicenter studies addressing key clinical and public health concerns, such as gender disparities, etiological patterns in vasospastic angina, and regional variations in symptom presentation.

Comparison With Previous Studies

The incidence of ACS in the present study was similar to the estimated incidence in a previous study,10 which reported that 13% (95% CI 11–16%) of patients with chest pain had ACS. Although sudden onset, radiation to the tooth, and cold sweat (palpitation) were related to the diagnosis of ACS in this study, there are some disparities compared with previous studies. First, a study from the US reported that sudden (abrupt) onset was not useful for the diagnosis of ACS, with an LR+ of 1.1 (95% CI: 1.0–1.2).26 This difference may be due to the definition of “suddenness”, which we defined as “pain reaching its peak within 1 min” but was defined as “pain occurred within 1 h” in the US study.26 Second, radiation to the neck/jaw was demonstrated as key to the diagnosis of ACS in previous studies,26,27 but did not differ between the non-ACS and ACS group in our study. In addition, radiation to the tooth was a significant factor to rule-in ACS in our study, but not in previous studies,9,26,27 which may indicate that “radiation to the tooth” was included in “radiation to the neck/jaw” in the other studies. Cold sweat (diaphoresis), which is specified in current guidelines,1–3 had a relatively high LR+ compared with other features in our study, and this is compatible with previous studies.26

As noted, our findings should be interpreted carefully because the ED patients in our study were older than in previous studies. For example, previous studies have reported a mean (±SD) age of 60.0±14.9 years26 and a median age of 59 years (interquartile range [IQR] 48–73 years).28 In contrast, the median age in the present study was 75 years (IQR 57–82 years). This reflects the fact that Japan is a “super-aged” society, with approximately 29% of the population aged ≥65 years or older in 2020 and an old-age dependency ratio of 49% in the same year.14

In addition to age, cultural or regional differences may influence symptom presentation and patient communication. A previous study from the US reported that older rural women struggled to recognize MI symptoms, resulting in delays in seeking emergency care.29 Symptom misinterpretation, privacy concerns, and perceived ambulance delays were identified as major barriers to timely treatment.29 In addition, a study in Japan30 found that prehospital symptom interpretation significantly affected in-hospital outcomes for ACS patients, likely due to onset-to-balloon time rather than door-to-balloon time. These findings underscore the importance of the chest pain registry to collect detailed data on symptom recognition and healthcare-seeking behavior across regions to support the development of targeted education and intervention.

Study Limitations

Despite the strengths of our study, there are several limitations. First, the study was conducted in a single center, which may limit the generalizability of the findings to other settings with different patient populations and healthcare systems. To address this, a multicenter study (UMIN000053978) covering 8 institutions in Japan has been initiated, and its results are awaited. Second, although we performed rigorous data cleaning and validation processes, there may be the potential for information bias. For example, details regarding symptoms were primarily collected in the EDC system before diagnosis, but when this was difficult due to emergency cases (e.g., cardiogenic shock), the details were collected after diagnosis, which may have led to observation bias. To minimize the bias, in such cases we collected symptom details based on medical records, which were made before diagnosis as far as possible. Third, although we accounted for multiple testing by applying Bonferroni correction, this approach may have led to a more conservative interpretation of the results, potentially overlooking other significant predictors of ACS. Conversely, in the subgroup analysis by age, setting the significance level at 0.05 raises the possibility of α error inflation. Although these statistical considerations regarding significance may complicate the interpretation of the results, we have presented diagnostic accuracy along with 95% CIs. From a clinical perspective, we believe that referencing these values would be preferable. Fourth, in this feasibility study, we could not determine whether ECG and troponin measurements were performed for all patients with chest pain. However, our clinical practice in the ED adheres to the diagnostic flowcharts outlined in the American Heart Association chest pain guidelines2 and the JCS guidelines.1 These guidelines emphasize the critical role of diagnostic tools, such as ECG and troponin, in differential diagnosis. To address this limitation, in the on-going multicenter study (UMIN000053978), based on the present feasibility study, we are collecting comprehensive data, including information on whether ECG and troponin measurements were performed, as well as the actual ECG findings and troponin values. Finally, because the present study was conducted in an ED, its applicability to prehospital settings is unclear. However, it could guide future research in prehospital care.

Conclusions

We conducted a single-center prospective cohort study as a pilot study of the JCS Chest Pain Registry including all consecutive adult patients with chest pain. Among the types of chest pain, sudden onset, radiation to the tooth, and cold sweat were associated with a greater chance of ACS. To improve outcomes and reduce sudden cardiac death, the JCS is working to encourage early visits to medical institutions or calls for an ambulance based on symptoms during the onset phase of ACS. Following the success of this pilot study, a multicenter chest pain registry has been started to strengthen these initiatives based on evidence.

Acknowledgments

The authors extend their gratitude to all the members who participated in the JCS Chest Pain Registry for their contribution. During the preparation of this manuscript, the authors used ChatGPT-4 (OpenAI, San Francisco, CA, USA) and Grammarly (Grammarly Inc., San Francisco, CA, USA) to help with translation and language editing. The authors used images in Figure 1, Figure 3, and the Central Figure obtained from Adobe Stock (https://stock.adobe.com/jp/) under the Standard License, and from Irasutoya (https://www.irasutoya.com), a Japanese free illustration website, under the terms of its free license.

Sources of Funding

Funding was provided by the Education and Implementation for Cardiac Emergency Committee of the Japanese Circulation Society.

Disclosures

S.Y., T.A., T. Itoh, S.K., C.N., N.N., M.S., K.S., Y. Satoh, T.T., Y.T., K.T., Y.T.T., Y.U., and T. Iwami are members of the Education and Implementation for Cardiac Emergency Committee of the Japanese Circulation Society, and the research is conducted with the budget of this committee. K.T., T.A., and Y.T. are members of Circulation Journal’s Editorial Team. There are no other financial or academic conflicts of interest.

IRB Information

The study protocol complies with the ethical guidelines of the 1975 Declaration of Helsinki and was approved by the ethics committees of Kyoto University (R-3319-2) and Rakuwakai-Otowa Hospital (01-21-00139).

Supplementary Files

Please find supplementary file(s);

https://doi.org/10.1253/circj.CJ-24-0832

References
 
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