A novel scoring algorithm for chest pain can
effectively support the diagnosis of acute
coronary syndrome in prehospital settings:
a cross-sectional study

A novel scoring algorithm for chest pain can
effectively support the diagnosis of acute
coronary syndrome in prehospital settings:
a cross-sectional study

Acute coronary syndrome, Chest pain, Emergency medical technicians, Optimizing patient transport, Risk
assessment

Abstract
Background Early identification of acute coronary syndrome (ACS) in prehospital settings is crucial for optimal
patient outcomes. However, existing risk assessment tools require laboratory data, making them unsuitable for
prehospital use. Therefore, emergency medical technicians (EMTs) lack appropriate tools for prehospital ACS
assessment and must rely on individual diagnostic skills, despite the importance of reducing prehospital time.
To address this issue, a novel scoring system—Nagasaki Prehospital Chest Pain Assessment & Risk Determination
(N-CARD)—was developed using only prehospital information and validated for use by EMTs, with the aim of
improving patient outcomes and optimizing healthcare resource utilization.
Methods In total, 584 participants with chest pain or suspected cardiac etiology who underwent a prehospital
12-lead electrocardiogram (ECG) between April 2023 and March 2024 were analyzed. The prehospital diagnostic score
for ACS, N-CARD score, was developed using logistic regression based on the following variables: age, pain location,

pain type, pain duration, coronary risk factors, and 12-lead ECG findings. Modeling was performed separately for high-
risk and low-risk groups based on prior coronary artery disease (CAD) history. The model’s performance was internally

validated using bootstrap methods.
Results The N-CARD scoring system was developed separately for participants without (N=433) and with (N=151)
a history of CAD. The score ranged from −1 to 10 for those without a history of CAD and 0 to 32 for those with a
history of CAD. For participants without a history of CAD, scores≥6 suggested ACS (specificity>90%), whereas
scores≤3 suggested non-ACS (sensitivity>90%), with an optimism-corrected area under the curve (AUC) of 0.90.
For participants with a history of CAD, scores≥24 suggested ACS, whereas scores≤6 suggested non-ACS, with an
optimism-corrected AUC of 0.69.

Keita Iyama1*† , Shuntaro Sato2†, Ryohei Akashi3

, Kensho Baba4

, Koichi Hayakawa1,5, Satoshi Ikeda3

, Koji Maemura3

and Osamu Tasaki1

https://doi.org/10.1186/s12245-025-01019-7

2025

Peri Irawan

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