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Algorithms of Electrocardiographic Changes for Quantitative and Localization Analysis of Thrombus Burden in Patients
Fan Wang1, Lan Wang2, ChunXi Yan3
1Department of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 200072 Shanghai, China.
Insights
New CHARIS algorithms can assess pulmonary thromboembolism (PTE) clot burden using electrocardiogram (ECG) findings. These models offer quantitative and localization analysis, aiding in early identification of severe PTE cases.
Area of Science:
- Cardiology
- Pulmonary Medicine
- Medical Imaging
Background:
- Electrocardiogram (ECG) abnormalities correlate with pulmonary thromboembolism (PTE) severity.
- Previous studies have not thoroughly investigated the use of ECG findings alone for evaluating PTE clot burden in Chinese patients.
- This study aimed to develop novel ECG-based models for quantitative and localization analysis of clot burden in acute PTE.
Purpose of the Study:
- To establish and validate novel risk prediction models using ECG signs for quantitative and localization analysis of clot burden in acute PTE patients.
- To assess the utility of ECG findings in identifying patients with heavy thrombus burdens prior to imaging diagnosis.
Main Methods:
- A retrospective cohort study of 341 acute PTE patients from three centers (2015-2019).
- Analysis of 12-lead ECGs at admission and computed tomography pulmonary angiography (CTPA) features to determine the Qanadli score.
- Development and validation of the CHARIS I and CHARIS II risk prediction models using derivation and external validation cohorts.
Main Results:
- The CHARIS I model quantitatively assessed the Qanadli score with moderate discrimination (c-index 0.720 in derivation, 0.663 in validation).
- The CHARIS II model predicted trunk obstruction probability with similar discrimination (c-index 0.753 in derivation, 0.741 in validation).
- Calibration curves and decision curve analysis confirmed the accuracy and clinical utility of both CHARIS algorithms.
Conclusions:
- The CHARIS algorithms provide quantitative and localization insights into clot burden in acute PTE patients.
- These ECG-based models can identify patients with heavy thrombus burdens before imaging confirmation.
- The CHARIS algorithms demonstrate potential for early risk stratification in acute PTE.
Background:
Various electrocardiographic (ECG) abnormalities are associated with the severity of pulmonary thromboembolism (PTE). The utility of evaluating the clot burden of PTE based on ECG findings alone has yet to be thoroughly investigated in Chinese patients. The aim of this study was therefore to use ECG signs to establish novel models for quantitative and localization analysis of clot burden in patients with acute PTE.
Methods:
Acute PTE patients from three centers were enrolled between 2015 and 2019 in a retrospective cohort study (NCT03802929). We analyzed the 12-lead ECGs at admission and studied computed tomography pulmonary angiography (CTPA) features to obtain the Qanadli score of clot burden and location of thrombus. Novel risk prediction models were developed and validated using derivation and external validation cohorts, respectively.
Results:
A total of 341 acute PTE patients were screened, of whom 246 (72.1%) were from Shanghai Tenth People's Hospital, 71 (20.8%) were from Shanghai Pulmonary Hospital and 24 (7.0%) were from Qidong People's Hospital. In the derivation cohort, predictors included in the final models were congestive heart failure, chronic obstructive pulmonary disease, hypertension, coronary heart disease, atrial fibrillation and ECG abnormalities. The CHARIS (COPD/CHF/CHD, HTN, Atrial arrhythmias/AF, RBBB/RAD, Inverted T wave and S1Q3T3/ Sinus tachycardia) I model was established for quantitatively assessing Qanadli score. It had moderate discrimination in both the derivation cohort (concordance index (c-index) of 0.720, 95% CI 0.655-0.780) and the validation cohort (c-index of 0.663, 95% CI 0.559-0.757). The CHARIS II model was used to predict the probability of trunk obstruction. It showed similar discrimination in the derivation cohort (c-index of 0.753, 95% CI 0.691-0.811) and in the validation cohort (c-index of 0.741, 95% CI 0.641-0.827). Calibration curves and Hosmer-Lemeshow test confirmed the accuracy of the risk prediction equations in the external validation dataset. Decision curve analysis showed the CHARIS I and CHARIS II algorithms had positive net benefits in both the derivation and validation cohorts.
Conclusions:
From quantitative and localization perspectives, the CHARIS algorithms can identify acute PTE patients with heavy thrombus burdens prior to imaging diagnosis.
Clinical Trial Registration:
NCT03802929, https://www.clinicaltrials.gov/study/NCT03802929.
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