ECG Abnormalities and Biomarkers Enable Rapid Risk Stratification in Normotensive Patients With Acute Pulmonary Embolism
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 f...
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| Format: | Article |
| Language: | English |
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Wiley
2025-06-01
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| Series: | The Clinical Respiratory Journal |
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| Online Access: | https://doi.org/10.1111/crj.70060 |
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| author | Siqi Jiao Ying Liu Haoming He Qing Li Zhe Wang Yinong Chen Longyang Zhu Shuwen Zheng Furong Yang Zhenguo Zhai Yihong Sun |
| author_facet | Siqi Jiao Ying Liu Haoming He Qing Li Zhe Wang Yinong Chen Longyang Zhu Shuwen Zheng Furong Yang Zhenguo Zhai Yihong Sun |
| author_sort | Siqi Jiao |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9325e89c9bbf4c8fac514f168740584b |
| institution | Kabale University |
| issn | 1752-6981 1752-699X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Clinical Respiratory Journal |
| spelling | doaj-art-9325e89c9bbf4c8fac514f168740584b2025-08-20T03:26:33ZengWileyThe Clinical Respiratory Journal1752-69811752-699X2025-06-01196n/an/a10.1111/crj.70060ECG Abnormalities and Biomarkers Enable Rapid Risk Stratification in Normotensive Patients With Acute Pulmonary EmbolismSiqi Jiao0Ying Liu1Haoming He2Qing Li3Zhe Wang4Yinong Chen5Longyang Zhu6Shuwen Zheng7Furong Yang8Zhenguo Zhai9Yihong Sun10Peking University Health Science Center China‐Japan Friendship Hospital Beijing ChinaBeijing Ditan Hospital Capital Medical University Beijing ChinaDepartment of Cardiology, China‐Japan Friendship Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing ChinaPeking University Health Science Center China‐Japan Friendship Hospital Beijing ChinaDepartment of Cardiology, China‐Japan Friendship Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing ChinaPeking University Health Science Center China‐Japan Friendship Hospital Beijing ChinaPeking University Health Science Center China‐Japan Friendship Hospital Beijing ChinaSchool of Traditional Chinese Medicine Beijing University of Chinese Medicine Beijing ChinaSchool of Traditional Chinese Medicine Beijing University of Chinese Medicine Beijing ChinaDepartment of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine China‐Japan Friendship Hospital Beijing ChinaDepartment of Cardiology, Beijing Anzhen Hospital Capital Medical University, Beijing Institute of Heart Lung and Blood Vessel Diseases Beijing ChinaABSTRACT 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.https://doi.org/10.1111/crj.70060acute pulmonary embolismin‐hospital adverse eventslow to moderate riskprognosis |
| spellingShingle | Siqi Jiao Ying Liu Haoming He Qing Li Zhe Wang Yinong Chen Longyang Zhu Shuwen Zheng Furong Yang Zhenguo Zhai Yihong Sun ECG Abnormalities and Biomarkers Enable Rapid Risk Stratification in Normotensive Patients With Acute Pulmonary Embolism The Clinical Respiratory Journal acute pulmonary embolism in‐hospital adverse events low to moderate risk prognosis |
| title | ECG Abnormalities and Biomarkers Enable Rapid Risk Stratification in Normotensive Patients With Acute Pulmonary Embolism |
| title_full | ECG Abnormalities and Biomarkers Enable Rapid Risk Stratification in Normotensive Patients With Acute Pulmonary Embolism |
| title_fullStr | ECG Abnormalities and Biomarkers Enable Rapid Risk Stratification in Normotensive Patients With Acute Pulmonary Embolism |
| title_full_unstemmed | ECG Abnormalities and Biomarkers Enable Rapid Risk Stratification in Normotensive Patients With Acute Pulmonary Embolism |
| title_short | ECG Abnormalities and Biomarkers Enable Rapid Risk Stratification in Normotensive Patients With Acute Pulmonary Embolism |
| title_sort | ecg abnormalities and biomarkers enable rapid risk stratification in normotensive patients with acute pulmonary embolism |
| topic | acute pulmonary embolism in‐hospital adverse events low to moderate risk prognosis |
| url | https://doi.org/10.1111/crj.70060 |
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