Prospective Validation of EDACS-ADP for 30-Day MACE in Patients with Chest Pain

By Kursat Kaan Kerimoglu, Burcu Tanay Demirdoven, Mehmet Karaman

Affiliations

1. Department of Emergency Medicine, Alsancak Nevvar-Salih Isgoren State Hospital, Izmir, Turkiye

doi: 10.29271/jcpsp.2026.08.977

ABSTRACT
Objective: To validate the Emergency Department Assessment of Chest Pain Score–Accelerated Diagnostic Pathway (EDACS-ADP) for predicting 30-day major adverse cardiac events (MACE) in patients with chest pain.
Study Design: An observational study.
Place and Duration of the Study: Department of Emergency, Alsancak Nevvar-Salih Isgoren State Hospital, Izmir, Turkiye, from July to November 2025.
Methodology: Adult patients with chest pain were prospectively evaluated using the EDACS-ADP. The predictive ability of EDACS-ADP for 30-day MACE was assessed by calculating sensitivity, specificity, positive predictive value, negative predictive value (NPV), likelihood ratios, and by receiver operating characteristic curve analysis with area under the curve estimation.
Results: Of the 1,389 screened patients, 773 completed the 30-day follow-up period. The mean age was 45.3 ± 16.1 years, and 55.1% were male. MACE occurred in 49 patients (6.3%), including 32 patients with myocardial infarction and three patients with cardiac death. Using the EDACS-ADP, 608 patients (78.7%) were classified as low-risk, accounting for 6 (12.2%) of all 30-day MACE events. In contrast, 165 patients (21.3%) were classified as at risk, accounting for 43 (87.8%) MACE events (p = 0.001). The diagnostic performance of EDACS-ADP was significantly superior to that of EDACS alone, with a sensitivity of 87.8% versus 34.7% and an NPV of 99.0% versus 95.3%. The relative risk of MACE for at-risk patients was 5.2, with an odds ratio of 35.3.
Conclusion: EDACS-ADP showed a high diagnostic accuracy and excellent NPV for detecting low-risk patients with chest pain in the emergency department, confirming its usefulness in secondary care settings in Turkiye.

Key Words: Chest pain, Emergency department, Acute coronary syndrome, Accelerated diagnostic pathway, Major adverse cardiac events, Risk stratification.

INTRODUCTION

Chest pain is a common indication for seeking care in emer- gency departments (EDs), requiring rapid assessment to exclude potentially serious conditions such as acute coronary syndrome (ACS).¹ Most presentations are non-life-threatening, with nearly half of patients eventually diagnosed with non-specific chest pain.¹ Although ACS accounts for only a small proportion of suspected cases, serious underlying diseases can occur.² Healthcare systems require rapid assessment and management to quickly identify critical conditions.³ Thus, emergency physicians rely on clinical tools to accurately identify low-risk patients among those presenting with ACS not requiring immediate hospitalisation and further diagnostic testing.⁴ Clinical decision pathways integrating structured risk scores, electrocardiography (ECG), and high-sensitivity cardiac troponin I (hs-cTnI) measurements safely stratify low-risk patients eligible for early discharge.⁵

Overcrowding in EDs is a major public health issue that poses a risk to patient safety,⁶ and demands effective implementation of clinical decision pathways.⁷ Available risk stratification systems for patients with undifferentiated chest pain mainly assess ACS likelihood to avoid unnecessary admissions.^8,9 However, the premature discharge of high-risk individuals may result in adverse outcomes and expose ED physicians to medicolegal risks, as chest pain and ACS remain among the most frequent causes of litigation in emergency medicine.¹⁰

Although most diagnostic and risk-stratification tools assess the probability of coronary artery disease (CAD), implementing an effective early rule-out strategy for ACS is critical to reducing ED overcrowding and improving patient outcomes.¹¹ The Emergency Department Assessment of Chest Pain Score (EDACS) is a reliable tool, allowing safe early discharge of low-risk patients more appropriately managed on an outpatient basis.¹² The EDACS-Accelerated Diagnostic Pathway (EDACS-ADP) further combines the EDACS score with ECG findings and serial hs-cTnI measurements to identify low-risk individuals having a high negative predictive value (NPV) for short-term major adverse cardiac events (MACE).¹³ Although EDACS-ADP achieves strong diagnostic performance and has been validated across diverse cohorts, local validation remains essential to account for differences in population characteristics, clinical workflows, and assay-specific hs-cTnI thresholds.¹⁴ 

This study aimed to prospectively validate the diagnostic accuracy of the EDACS-ADP in predicting 30-day MACE in adult patients with chest pain presenting to the ED of a secondary-level healthcare facility.

METHODOLOGY

This observational study was conducted at the Department of Emergency, Alsancak Nevvar-Salih Isgoren State Hospital, Izmir, Turkiye, from July to November 2025. Patients requiring advanced cardiac intervention or intensive coronary care are transferred to tertiary centres for definitive management.

The study was reported in accordance with the Standards for Reporting Diagnostic Accuracy Studies 2015 (STARD 2015) guidelines, and informed consent was obtained from the participants. Consecutive patients aged ≥18 years presenting to the ED with chest pain during the study period were prospectively enrolled if they underwent standardised evaluation with 12-lead ECG and hs-cTnI testing. Patients presenting with acute myocardial infarction (AMI), haemodynamic instability requiring urgent intervention, confirmed non-cardiac causes of chest pain, pregnancy, documented MACE or planned revascularisation within the preceding 30 days, and those who left the ED before completing the observation protocol, or had incomplete data, were excluded. MACE incidence and survival analyses were determined for patients discharged from the ED.

The EDACS-ADP was prospectively applied as the index test. The EDACS incorporates demographic variables (age and gender), cardiovascular risk factors (hypertension, hyperlipidaemia, diabetes mellitus, family history of premature CAD, and smoking history), and chest pain characteristics such as radiation, diaphoresis, or pain occurring with exertion. Each variable contributed a weighted point value, with a total score ranging from –10 to +34; higher scores indicate a greater likelihood of ACS.¹⁵

In accordance with the EDACS-ADP, all patients underwent a standard 12-lead ECG and serial hs-cTnI measurements at 0 and 2 hours using the VITROS 5600 Immunodiagnostic System (Ortho Clinical Diagnostics, Raritan, NJ, USA). Ischaemic ECG changes were defined as ST-segment depression or elevation of ≥1 mm in two or more contiguous leads, new or presumed new left bundle branch block, pathologic T-wave inversion in contiguous leads, or new Q waves consistent with myocardial infarction.

Patients were classified as low-risk if all of the following crite-ria were met: EDACS score <16, absence of new ischaemic ECG changes as defined above, and both 0- and 2-hour hs-cTnI values <11 ng/L. Patients not meeting these criteria were categorised as at risk, and management was determined at the discretion of the attending physician.

The primary outcome was the occurrence of 30-day MACE, consisting of a combination of AMI, cardiac-related death, and other confirmed cardiac adverse events necessitating medical intervention. These include tachyarrhythmia or bradyarrhythmia requiring treatment, ventricular fibrillation, aortic dissection or aneurysm, newly diagnosed or decompensated congestive heart failure, cardiopulmonary resuscitation, angiographically confirmed CAD, and any coronary revascularisation procedure. Unstable angina was excluded from the definition of MACE because it is often subjective and lacks consistent objective biochemical or imaging evidence of myocardial injury.

Outcome data were collected from the hospital’s electronic medical records and confirmed via a 30-day follow-up call. Information, including demographics, cardiovascular risk factors, CAD history, vital signs, symptom details, EDACS variables, ECG results, hs-cTnI levels, and follow-up out- comes, was documented on standardised case report forms. A history of CAD was delineated as a history of myocardial ischaemia, angiographically-confirmed coronary artery stenosis, imaging evidence of wall motion abnormalities, or ischaemic ECG changes consistent with prior infarction.

EDACS scores and ECG findings were independently evaluated by two investigators blinded to patient outcomes. On disagreement, a third reviewer made the final decision regarding the analysis. As part of the institutional protocol, emergency physicians typically order hs-cTnI tests for all patients with chest pain. The initial troponin measurement defined the 0-hour result, with a second sample collected 2 hours after ED admission, regardless of the first level.

For clinical management, attending emergency physicians initially established a diagnosis based on cardiac biomarkers and ECG results during ED evaluation. If diagnostic uncertainty persisted, a cardiology consultation was sought, and the cardiologist's opinion established the final diagnosis.

After 30 days, outcome verification was performed by a researcher blinded to the index ED presentation. Follow-up data were obtained from hospital electronic medical documents and cross-checked using the National e-Nabiz Health Information System. If records of medical contact or event data were absent, the patient (or a family member) was contacted by telephone on two separate occasions to confirm survival status, any recurrent ED visits for chest pain, and the occurrence of diagnostic or therapeutic cardiac procedures during the follow-up period.

All analyses were performed using IBM SPSS Statistics (v.26.0; IBM Corp., Armonk, NY) and MedCalc Statistical Software (version 23.4.5; MedCalc Software Ltd., Ostend, Belgium). Normality of continuous variables was assessed using the Shapiro–Wilk test. For continuous variables, between-group differences were tested using either the independent samples t-test or the Mann–Whitney U test. Categorical variables were compared using the chi-squared or Fisher’s exact tests. The incidence of 30-day MACE was calculated for the entire cohort. Diagnostic performance for EDACS and EDACS-ADP classifications was assessed by determining sensitivity, specificity, positive predictive value (PPV), NPV, accuracy, miss rate, relative risk (RR), odds ratio (OR), and likelihood ratios (LR⁺ and LR⁻), along with 95% confidence intervals (CIs). For EDACS-ADP, diagnostic measures were derived from the low-risk and at-risk classification, whereas a literature-established cut-off score of ≥16 was used for EDACS. Receiver operating characteristic (ROC) curve analysis was conducted for both the EDACS and EDACS-ADP models, with the area under the curve (AUC) and 95% CIs calculated using the DeLong method. Comparative risk estimates, including RR and OR, were calculated to evaluate the differences in 30-day MACE between the low- and at-risk groups, as defined by the EDACS-ADP. Statistical significance was set at a two-tailed p-value of <0.05.

RESULTS

In total, 1,389 consecutive patients with chest pain were screened for eligibility. Overall, 577 patients satisfied the predefined exclusion criteria, which included lack of informed consent (n = 412), confirmed AMI (n = 92), non-cardiac chest pain (n = 37), missing hs-cTnI or ECG results (n = 17), discharge against medical advice (n = 14), haemodynamic instability (n = 3), and pre-existing documented MACE (n = 2). Thus, 812 patients were available for 30-day follow-up, of whom 39 were lost to follow-up. Consequently, 773 patients completed the follow-up and were included in the final analysis (Figure 1).

The mean age of the study population was 45.3±16.1 years, and 426 patients (55.1%) were male. Most patients were aged 40–49 years (n = 188, 24.3%). Hypertension (n = 70, 9.1%) and ischaemic heart disease (n = 68, 8.8%) were the most common comorbidities, with 53.9% of patients (n = 409) presenting at the ED during daytime shifts. Patient baseline characteristics are summarised in Table I.

Within the 30-day follow-up period, 49 patients (6.3%) developed MACE, whereas 724 (93.7%) remained event-free. Among those with MACE, 32 (65.3%) were diagnosed with AMI, 14 (28.6%) experienced clinically significant adverse events requiring medical intervention, and 3 (6.1%) experienced cardiac-related death. The mean age was significantly higher in the MACE group than in the non-MACE group (56.0 vs. 44.6 years; p <0.001).

Table I: Comparison of baseline characteristics between MACE and non-MACE patients.
 

Variables	Characteristics	Overall (n = 773)	Non-MACE (n = 724)	MACE (n = 49)	p-values
Gender, n (%)	Male	426 (55.1)	394 (54.4)	32 (65.3)	0.138c
Age group, years, n (%)	18-29	153 (19.8)	146 (20.2)	7 (14.3)	0.317c
	30-39	140 (18.1)	135 (18.6)	5 (10.2)	0.138c
	40-49	188 (24.3)	184 (25.4)	4 (8.2)	0.005f
	50-59	145 (18.8)	136 (18.8)	9 (18.4)	0.942c
	60-69	80 (10.3)	68 (9.4)	12 (24.5)	<0.001c
	≥70	67 (8.7)	55 (7.6)	12 (24.5)	<0.001c
Comorbidities, n (%)	Hypertension	70 (9.1)	64 (8.8)	6 (12.2)	0.421c
	Ischaemic heart disease	68 (8.8)	58 (8.0)	10 (20.4)	0.003c
	Diabetes mellitus	28 (3.6)	24 (3.3)	4 (8.2)	0.095f
	COPD	17 (2.2)	17 (2.3)	0 (0.0)	0.618c
	Hyperlipidaemia	11 (1.4)	10 (1.4)	1 (2.0)	0.516f
	Congestive heart failure	5 (0.6)	3 (0.4)	2 (4.1)	0.035f
	Other	13 (1.7)	12 (1.7)	1 (2.0)	0.576f
ED shift distribution, n (%)	Morning shift (08:00–15:59)	409 (52.9)	381 (52.6)	28 (57.1)	0.540c
	Evening shift (16:00–23:59)	263 (34.0)	245 (33.8)	18 (36.7)	0.679c
	Night shift (24:00–07:59)	101 (13.1)	98 (13.5)	3 (6.1)	0.187f
Accelerated diagnostic protocol components, n (%)	Positive 0h/2h Troponin-I	42 (5.3)	29 (4.0)	13 (26.5)	<0.001c
	Abnormal initial ECG	54 (7.0)	38 (5.2)	16 (32.7)	<0.001c
Risk stratification, n (%)	EDACS low risk	687 (88.9)	655 (90.5)	32 (65.3)	<0.001c
	EDACS at-risk	86 (11.1)	69 (9.5)	17 (34.6)	-
	EDACS-ADP low risk	608 (78.7)	602 (83.1)	6 (12.2)	<0.001c
	EDACS-ADP at-risk	165 (21.3)	122 (16.9)	43 (87.8)	-
hs-cTnI levels	0h (ng/L), median (IQR)	1.5 (0.0-2.8)	1.5 (0.0-2.7)	2.0 (0.0-6.4)	0.017u
	2h (ng/L), median (IQR)	1.5 (0.0-3.7)	1.5 (0.0-3.5)	2.3 (0.0-8.2)	0.009u
Age, years, mean (SD)		45.3 (16.1)	44.6 (15.6)	56.0 (19.6)	<0.001t
Vital signs	SBP (mmHg), mean (SD)	139.5 (25.2)	139.2 (24.2)	144.1 (37.1)	0.365t
	DBP (mmHg), mean (SD)	82.4 (14.0)	82.5 (14.0)	81.4 (13.9)	0.593t
	HR (beats/minute), mean (SD)	85.8 (16.8)	85.8 (16.9)	85.2 (15.6)	0.815t
	O2 saturation (%), median (IQR)	98.0 (97.0-99.0)	98.0 (97.0-99.0)	98.0 (97.0-99.0)	0.481u
	Temperature (oC), mean (SD)	36.3 (0.3)	36.3 (0.3)	36.3 (0.4)	0.975t
EDACS score, median (IQR)		6 (2, 10)	6 (2, 10)	10 (5, 16)	<0.001u
ADP: Accelerated diagnostic protocol; COPD: Chronic obstructive pulmonary disease; ECG: Electrocardiogram; ED: Emergency department; DBP: Diastolic blood pressure; EDACS: Emergency department assessment of chest pain score; h: Hour, HR: Heart rate; hs-cTnI: High-sensitivity cardiac troponin-I; IQR: Interquartile range; MACE: Major adverse cardiac event; SBP: Systolic blood pressure; SD: Standard deviation. Values are expressed as n (%), mean (SD: standard deviation), or median (IQR: interquartile range). t Student's t-test for independent samples, f Fisher’s exact test, c Chi-squared test, u Mann–Whitney U test for independent samples.

 

Table II: Distribution of EDACS-ADP components in patients presenting with chest pain.

Clinical characteristics	Scores	Number of patients (n)	Percentage (%)
Age
18-45	+2	419	54.2
46-50	+4	83	10.7
51-55	+6	77	10.0
56-60	+8	59	7.6
61-65	+10	42	5.4
66-70	+12	34	4.4
71-75	+14	18	2.3
76-80	+16	20	2.6
81-85	+18	14	1.8
86+	+20	7	0.9
Male gender	+6	426	55.1
Aged 18-50 years and either Known CAD or ≥3 risk factors	+4	54	7.0
Symptoms and signs
Diaphoresis	+3	30	3.9
Pain radiates to the arm, shoulder, neck, or jaw	+5	69	8.9
Pain occurred or worsened with inspiration	-4	187	24.2
Pain is reproduced by palpation	-6	212	27.4
EDACS
Low risk	<16	687	88.9
At risk	≥16	86	11.1
Accelerated diagnostic protocol components
Abnormal initial ECG	-	54	7.0
0h/2h troponin positive	-	42	5.4
EDACS-ADP
Low risk	-	608	78.7
At risk	-	165	21.3

Table III: Predictive performance of the EDACS and its EDACS-ADP for predicting 30-day MACE.

Parameters	EDACS	EDACS-ADP
Sensitivity, [% (95% CI)]	34.7 (21.6–49.6)	87.7 (75.2–95.3)
Specificity, [% (95% CI)]	90.5 (88.0–92.5)	83.1 (80.2–85.8)
PPV, [% (95% CI)]	19.7 (13.6–27.7)	26.1 (22.5–29.9)
NPV, [% (95% CI)]	95.3 (93.3–96.1)	99.0 (97.9–99.5)
RR, (95% CI)	4.2 (3.2–5.6)	5.2 (4.3–6.3)
OR, (95% CI)	5.0 (2.7–9.2)	35.3 (14.7–84.9)
LR+ (95% CI)	3.6 (2.3–5.6)	5.2 (4.2–6.3)
LR– (95% CI)	0.7 (0.5–0.8)	0.1 (0.0–0.3)
AUC (95% CI)	0.665 (0.575–0.755)	0.855 (0.799–0.910)
ADP: Accelerated diagnostic protocol; AUC: Area under the ROC curve; CI: Confidence interval; EDACS: Emergency department assessment of chest pain score; LR+: Positive likelihood ratio; LR–: Negative likelihood ratio; ROC: Receiver operating characteristic; RR: Relative risk; OR: Odds ratio; PPV: Positive predictive value; NPV: Negative predictive value.

Figure 1: Flow diagram of research cohort formation.

Figure 2: ROC curves for the EDACS score and the EDACS-ADP in predicting 30-day MACE.

The gender distribution was similar between groups (p = 0.138). The prevalence of ischaemic heart disease was also higher in patients experiencing MACE (n = 10, 20.4% vs. n = 58, 8.0%; p = 0.003). The median EDACS scores were higher in patients who developed MACE than in those without MACE (10 vs. 6; p <0.001). Similarly, abnormal ECG findings (n = 16, 32.7% vs. n = 38, 5.2%) and elevated 0/2 hour hs-cTnI levels (n = 13, 26.5% vs. n = 29, 4.0%) were significantly more prevalent in the MACE group (p <0.001, for all; Table I).

When the EDACS and EDACS-ADP components were examined, most patients were aged 18-45 years (419, 54.2%). Among symptoms contributing positively to the EDACS score, pain radiating to the arm, shoulder, neck, or jaw was observed in 69 patients (8.9%), while diaphoresis was present in 30 patients (3.9%). In contrast, negative symptom components included pain reproduced by palpation in 212 patients (27.4%) and pain worsened with inspiration in 187 patients (24.2%). The category of patients aged 18–50 years with either known CAD or three or more cardiovascular risk factors was identified in 54 patients (7.0%). The distribution of EDACS and EDACS-ADP components is summarised in Table II.

Based on the EDACS classification, 687 patients (88.9%) were categorised as low-risk, accounting for 32 of the 30-day MACE events (65.3%). In contrast, 86 patients (11.1%) were classified as at risk, and 17 MACE events (34.6%) occurred in this group within 30 days, representing a significantly higher incidence compared with the low-risk group (p <0.001). When the EDACS-ADP was applied, 608 patients (78.7%) were classified as low-risk, among whom 6 of the 30-day MACE events (12.2%) were observed. A total of 165 patients (21.3%) were classified as at-risk, and this group accounted for 43 of the 30-day MACE events (87.8%), which was significantly higher than that observed in the low-risk group (p <0.001, Table I).

The EDACS score showed sensitivity, specificity, PPV, and NPV of 34.7 %, 90.5%, 19.8%, and 95.3%, respectively. Conversely, the EDACS-ADP demonstrated significantly better performance, with a sensitivity of 87.8%, specificity of 83.2%, PPV of 26.1%, and NPV of 99.0% (Table III). The EDACS-ADP had a miss rate of 12.2%, corresponding to six false-negative cases among 49 total events. The RR of MACE in the at-risk group compared with the low-risk group was 5.2, whereas the OR was 35.3. LR+ and LR– were 5.2 and 0.1, respectively, indicating a strong ability to rule out MACE (Table III).

A separate analysis was also performed for hard outcomes, defined as AMI or cardiac-related death. Overall, hard out- comes occurred in 35 patients (4.5%), representing most of the MACE events. Among these patients, 33 (94.3%) were classified as at-risk and 2 (5.7%) as low-risk by the EDACS-ADP (p <0.001). For hard outcomes, the EDACS-ADP demonstrated a sensitivity of 94.3%, specificity of 82.1%, and NPV of 99.7%.

Comparative ROC analysis showed a significant difference between the two models. The EDACS had an AUC of 0.665 (95% CI, 0.575–0.755; p <0.001), indicating a limited ability to discriminate when used alone, whereas EDACS-ADP achieved a much higher AUC of 0.855 (95% CI, 0.799–0.910; p <0.001; Figure 2).

DISCUSSION

The EDACS-ADP demonstrated high sensitivity and excellent NPV for predicting 30-day MACE, with a significant impro-vement in the overall diagnostic performance compared with the EDACS score. In Turkiye, studies have primarily involved tertiary care hospitals. This work represents an important prospective validation of the EDACS-ADP in a secondary care setting without dedicated cardiac care units, facilitating the safe identification and discharge of patients with low-risk chest pain and shortening of ED stays.

In this cohort, the 30-day MACE incidence (6.3%) was at the lower end of rates reported in recent studies of ED chest pain populations, which typically ranged from 10.2% to 31.4%.^15-21 This low incidence reflects both population- specific and system-level differences between this study setting and those reported in tertiary cardiac centres. Several contextual factors, including the younger study population, secondary care environment without on-site cardiac intervention facilities, deliberate exclusion of unstable angina from the composite MACE outcome, and assay-specific differences in troponin measurement thresholds, may explain these findings. Collectively, these factors may have expanded the low-risk patient pool while maintaining adequate event detection. Consequently, the overall MACE rate was lower without compromising the safety performance of EDACS-ADP.

In subgroup comparisons, patients experiencing MACE were notably older, and the gender distribution did not significantly differ between groups. Similarly, previous studies have also observed that older patients are more likely to experience MACE.^14,15,19 In contrast,  the results of this study showed a significantly higher male ratio in the MACE group, although other studies consistent with this study, found no gender-related differences.^16,18 Overall, age appears to be a consistent factor in adverse cardiac outcomes, whereas gender differences may vary according to population demographics, referral patterns, and healthcare settings. Addi- tionally, in the present study, the mean EDACS score, abnormal ECG findings, and elevated hs-cTnI levels were significantly higher in patients exhibiting MACE. Higher values of these predictors in the MACE group have also been reported,¹⁸ supporting the results of the current work. These findings underscore the importance of combining clinical scoring, ECG analysis, and serial hs-cTnI testing within the EDACS-ADP to improve early risk stratification.

The EDACS algorithm classified 88.9% of patients as low-risk; however, when ADP components were included, this percentage decreased to 78.7%. Conversely, previous studies have reported ADP integration halved the proportion of low-risk patients identified,^19,20,22 although only 30.6% low-risk patients were identified by Yoo et al.¹⁵ The younger mean age of the present cohort (45.3 vs. 49.6–62.7 years in prior studies) likely contributed to this difference, as lower age-related points and fewer comorbidities within the EDACS variables resulted in lower total scores and, consequently, a higher low-risk yield.

The 30-day MACE rate among patients categorised as low-risk by the EDACS-ADP was 1.0%, consistent with international validation studies reporting rates ranging 0.85% to 1.3%.^15,20 Conversely, Saribas et al. observed a nearly fourfold higher rate in their low-risk cohort.¹⁶ This discrepancy may be due to methodological differences, as the present study did not use a high-sensitivity troponin assay and, in some cases, relied on a single troponin measurement, which may have led to the misclassification of higher-risk individuals. These results collectively confirm that early discharge decisions guided by the EDACS-ADP are safe, thereby reinforcing its reliability in real-world secondary care ED environments.

Evaluation of the EDACS-ADP diagnostic performance revealed that adding ADP components significantly inc-reased sensitivity compared with the EDACS score, with an NPV of 99%.  The high LR⁺ and low LR⁻ values reinforced its strong rule-out ability. The separate hard outcome analysis also strengthened the clinical interpretation of the findings, showing that the EDACS-ADP classified most patients with AMI or cardiac-related death as at-risk and maintained a very high NPV for these clinically objective outcomes. Multiple validation studies have consistently reported similar results, with high sensitivity and NPV and low LR⁻ after incorporating ADP components.^16,19-25 Bozdereli-Berikol et al. reported lower sensitivity despite a similarly high NPV, possibly owing to fewer positive events caused by the early exclusion of high-risk cases during triage.¹⁸ The EDACS-ADP is a reliable tool for early risk assessment and safe discharge planning.

ROC curve analysis supported the reliability of the EDACS-ADP tool, revealing the limited discriminative ability of the EDACS score. However, performance significantly improved to an excellent AUC range when ADP was added. Similar improvements in AUC have been described,^16,24, whereas others have observed only moderate discriminative ability due to population or methodological differences.¹⁸ Thus, the EDACS should be used in combination with ECG findings and serial hs-cTnI testing for better diagnostic accuracy. Overall, the EDACS-ADP is a practical and effective cardiac rule-out pathway, especially suitable for secondary EDs. When incorporated into standard cardiac care algorithms, it may help reduce overcrowding and unnecessary observation times and optimise resource use.

The main strengths of this study are its prospective design, high follow-up rate, and the use of standardised hs-cTnI testing within a well-defined accelerated protocol. Nonetheless, some limitations should be acknowledged. First, this study was conducted at a single secondary care centre without an on-site cardiology unit, and the cohort was relatively young; therefore, the findings may not be directly generalisable to older chest pain populations or to tertiary and specialised EDs. Second, the small number of MACE may have affected the accuracy of the subgroup analyses. Third, the 30-day follow-up captured only short-term outcomes, making it impossible to conclude mid- or long-term prognoses. Fourth, the inclusion of only patients presenting with chest pain may have excluded those with atypical or non-chest pain presentations of ACS, potentially underestimating the event rates. Fifth, the relatively high number of patients excluded due to the absence of informed consent should be acknowledged as a further limitation, as this may have introduced selection bias and affected the representativeness of the study cohort. Finally, the study did not account for potentially fatal non-ACS causes of chest pain, and some results depended on a single hs-cTnI assay and an institutional cut-off value, which could affect external applicability.
 

CONCLUSION

This study offers a preliminary prospective validation of the EDACS-ADP conducted in a secondary-care Turkish ED. This pathway exhibited outstanding rule-out performance and accurately identified low-risk patients with chest pain, there-by supporting safe and early discharge decisions. Given its simplicity and strong predictive value, the EDACS-ADP is a practical and cost-efficient tool for optimising patient flow and minimising unnecessary hospital admissions in resource-constrained ED settings.

ETHICAL APPROVAL:
The study was approved by the Ethics Committee of Health Sciences Research of Izmir University of Economics, Izmir, Turkiye (Approval No. E-97429853-050.04-102516; dated: 11 July 2025).

COMPETING INTEREST:
The authors declared no conflict of interest.

PATIENTS’ CONSENT:
Written informed consent was obtained from all the participants.

AUTHORS’ CONTRIBUTIONS:
KKK: Conception and design of the study, data collection, analysis and interpretation, drafting, and critical revision of the manuscript for important intellectual content.

BTD: Data collection, data analysis, and interpretation of the results.
MK: Data collection, patient management, contribution to data analysis, and interpretation.
All authors approved the final version of the manuscript to be published.

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