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Updated: Jan 13, 2026
Murine Echocardiography of Left Atrium, Aorta, and Pulmonary Artery
Published on: February 20, 2017
Development and validation of an echocardiographic nomogram for identifying cardiac amyloidosis in patients with left
Shichu Liang1, Zhiyue Liu1, Fanfan Shi2
1Department of Cardiology, West China Hospital, Sichuan University, No.37 GuoXue Alley, Chengdu, 610041, China.
Insights
This study developed a highly accurate echocardiographic model to identify cardiac amyloidosis (CA) in patients with left ventricular hypertrophy (LVH). The nomogram aids in early CA detection and guides further diagnostic steps.
Area of Science:
- Cardiology
- Medical Imaging
- Diagnostic Tools
Background:
- Echocardiography is the primary non-invasive method for screening cardiac amyloidosis (CA).
- Cardiac amyloidosis-associated left ventricular hypertrophy (CA-LVH) requires effective identification strategies.
- Developing a predictive model using echocardiographic parameters is crucial for early diagnosis.
Purpose of the Study:
- To establish a cohort of CA-LVH within a hospital population.
- To develop an echocardiographic identification model for CA using readily available parameters.
- To improve the diagnostic accuracy of CA screening in patients with LVH.
Main Methods:
- Retrospective nested cohort study of clinical and echocardiographic data (2008-2023).
- Calculation of relative wall thickness (RWT) and asymmetric hypertrophy.
- Development of the AMYLI score and a nomogram model based on logistic regression analysis.
Main Results:
- A multivariable logistic regression identified key predictive factors for CA in LVH patients.
- These factors included LVID, LVEF, AMYLI score, asymmetric hypertrophy, granular sparkling, pericardial effusion, and valvular regurgitation.
- The constructed nomogram model demonstrated high accuracy (0.91-0.92) and sensitivity (0.90-0.91).
Conclusions:
- The developed nomogram shows significant predictive accuracy for CA in LVH.
- This tool can enhance CA screening using routine echocardiography.
- It strategically guides further diagnostic evaluations for suspected cardiac amyloidosis.
Background:
Echocardiography is the principal non-invasive imaging modality for screening cardiac amyloidosis (CA). This study aimed to establish a cohort of CA-associated left ventricular hypertrophy (CA-LVH) within a hospital-based population and to develop an echocardiographic identification model for CA using readily available echocardiographic parameters.
Methods:
This retrospective nested cohort study involved the collection of clinical and echocardiographic data from three hospitals affiliated with the West China Medical Center, Sichuan University, between January 1, 2008, and December 31, 2023. The relative wall thickness (RWT) was calculated as twice the left ventricular posterior wall thickness (LVPW) divided by the left ventricular internal diameter (LVID). Asymmetric hypertrophy was defined as a ratio of interventricular septal thickness (IVS) to LVPW greater than 1.3. The AMYLI score was computed as the product of RWT and E/e' ratio.
Results:
A total of 185 CA patients (183 AL-CA and 2 ATTR-CA) who underwent 309 echocardiography examinations from different time periods with 1,213 echocardiographic data points from in-hospital non-CA-LVH cases matched for age, gender, and body surface area were included. Multivariable logistic regression analysis identified a history of hypertension [odds ratio (OR): 0.04, 95% confidence interval (CI): 0.021-0.073], LVID [OR: 0.927, 95%CI: 0.878-0.977], left ventricular ejection fraction (LVEF) [OR: 0.95, 95%CI: 0.908-0.993], AMYLI score [OR: 1.088, 95%CI: 1.024-1.161], asymmetric hypertrophy [OR: 3.729, 95%CI: 1.884-7.441], granular sparkling [OR: 3.111, 95%CI: 1.355-7.431], small pericardial effusion [OR: 2.77, 95%CI: 1.563-4.937], mild aortic regurgitation [OR: 2.353, 95%CI: 1.278-4.361], mild mitral regurgitation [OR: 4.331, 95%CI: 2.347-8.141], and mild tricuspid regurgitation [OR: 3.837, 95%CI: 2.026-7.358] as independent predictive factors for CA in LVH patients. The predictive factors were used to construct a nomogram model, which demonstrated high accuracy (0.91-0.92), specificity (0.91-0.92), sensitivity (0.90-0.91), positive predictive value (0.73), negative predictive value (0.93-0.98), and Youden index (0.81-0.83).
Conclusion:
The developed nomogram displayed remarkable predictive accuracy, which has the potential to enhance CA screening via routine echocardiography and strategically guide subsequent diagnostic evaluations.
