Key result
HATS model predicts significant coronary disease in prehospital chest pain with an AUC of 0.81.
Observational (n=409)
No
Effect estimate: AUC 0.81
The HATS score is a simple, proof-of-concept prehospital clinical prediction model that uses age, sex, typical chest pain, and family history to identify patients at risk of significant coronary lesions.
May aid prehospital triage of undifferentiated chest pain; hypothesis-generating and requires prospective validation.
Background: Undifferentiated chest pain is one of the most common reasons for emergency medical service (EMS) activation, yet its aetiological spectrum remains poorly characterised in the prehospital setting. Furthermore, no clinical prediction model has been specifically developed to identify patients at risk of significant coronary lesions using only information available before hospital arrival. This study aimed to describe the aetiologies of undifferentiated prehospital chest pain and develop a proof-of-concept clinical prediction model. Methods: We conducted a retrospective, single-centre study including 409 consecutive patients managed by the Orléans Mobile Intensive Care Unit (MICU) for undifferentiated chest pain between January and June 2024. Predictors of clinically significant coronary artery disease identified during in-hospital coronary assessment and management were evaluated using multivariable logistic regression. Model performance was assessed by discrimination and calibration, and internally validated using 1000 bootstrap resamples. Results: Cardiological aetiologies accounted for 19% of cases, including 53 patients (13%) meeting the primary outcome of clinically significant coronary artery disease. Four independent predictors were identified: age (OR 6.7–8.9 according to category), male sex (OR 2.2), typical chest pain (OR 6.6), and a positive family history of cardiovascular disease (OR 3.4). These variables were combined to develop the HATS (History, Age, Typical chest pain, Sex) model. The model demonstrated good discrimination (AUC 0.81), and satisfactory internal calibration (Hosmer–Lemeshow p = 0.88), with limited optimism after bootstrap validation. Conclusions: This study characterises the aetiological spectrum of undifferentiated prehospital chest pain and proposes HATS as an exploratory proof-of-concept prediction model. Prospective multicentre external validation and subsequent assessment of clinical utility are required before any consideration of clinical implementation.
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Laporal et al. (2026) conducted an observational in Undifferentiated prehospital chest pain (n=409). HATS prediction model (History, Age, Typical chest pain, Sex) was evaluated on Clinically significant coronary artery disease identified during in-hospital coronary assessment and management (AUC 0.81). The HATS clinical prediction model, incorporating history, age, typical chest pain, and sex, demonstrated good discrimination (AUC 0.81) for identifying significant coronary lesions in patients with undifferentiated prehospital chest pain.
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