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. 2025 Jun;19(6):e70060.
doi: 10.1111/crj.70060.

ECG Abnormalities and Biomarkers Enable Rapid Risk Stratification in Normotensive Patients With Acute Pulmonary Embolism

Siqi Jiao  1 , Ying Liu  2 , Haoming He  3 , Qing Li  1 , Zhe Wang  3 , Yinong Chen  1 , Longyang Zhu  1 , Shuwen Zheng  4 , Furong Yang  4 , Zhenguo Zhai  5   6   7 , Yihong Sun  8
Affiliations

ECG Abnormalities and Biomarkers Enable Rapid Risk Stratification in Normotensive Patients With Acute Pulmonary Embolism

Siqi Jiao et al. Clin Respir J. 2025 Jun.

Abstract

Background: The patients with suspected pulmonary embolism (PE) were usually screened using electrocardiogram (ECG) and blood panel of D-dimer, troponin, and blood gas analysis in the emergency.

Objectives: This study aimed to explore a rapid risk model to predict in-hospital adverse events for normotensive PE patients.

Methods: Patients with acute PE having normal blood pressure on appearance were retrospectively enrolled at China-Japan Friendship Hospital from January 2017 to February 2020. The in-hospital adverse events were defined as death and clinical deterioration during hospitalization. The risk model for in-hospital adverse events was generated by multivariate regression analysis. The discrimination ability of the model was compared with PESI, Bova, and FAST risk score, and evaluated by the receiver operating characteristic curve (ROC), net reclassification improvement (NRI), and integrated discrimination improvement index (IDI).

Results: Of the 213 patients, 35 (16.4%) experienced in-hospital adverse events,y including 15 deaths. The average age was 69 ± 19 years, and 118 (44.6%) were females. Multiple logistic regression analysis showed that independent risk factors associated with in-hospital adverse events were low QRS voltage in ECG (OR: 5.321; 95% CI: 1.608-7.310), positive age-adjusted D-dimer (OR: 2.061; 95% CI: 0.622-6.836), positive troponin (OR: 3.504; 95% CI: 1.744-8.259), and PaO2/FiO2 < 300 (OR: 3.268; 95% CI: 0.978-5.260). The ROC analysis showed that the AUC of the new model (0.847, 95% CI: 0.786-0.901) was better than the PESI score (0.628, 95% CI: 0.509-0.769), the Bova score (0.701, 95% CI: 0.594-0.808), and the FAST score (0.775 95% CI: 0.690-0.859).

Conclusion: ECG abnormalities and biomarkers on admission may provide a rapid and effective approach to identify patients with poor prognoses during hospitalization.

Keywords: acute pulmonary embolism; in‐hospital adverse events; low to moderate risk; prognosis.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Flow diagram of patient enrolment . ACS, acute coronary syndrome; CTEPH, chronic thromboembolic pulmonary hypertension; PE, pulmonary embolism.
FIGURE 2
FIGURE 2
Distribution of the proportion of the patients with high risk based on risk stratification. All the risk scores stratify patients as low risk and high risk. The risk scores are defined in Table S1.
FIGURE 3
FIGURE 3
Receiver operating characteristics (ROC) analysis of risk assessment strategies with regard to in‐hospital adverse outcomes. Model: a total point score for a given patient is obtained by summing the points: low QRS voltages in ECG (5 points), higher D‐D (per 2 mg/L) (1 points), positive troponin (3 points), and PaO2/FiO2 < 300 (3 points).
See this image and copyright information in PMC

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