A simple nomogram to help guide the diagnosis of cardiac amyloidosis in patients with heart failure with preserved ejection fraction.

BACKGROUND

Cardiac amyloidosis (CA) has been recognized as a more frequent cause of heart failure with preserved ejection fraction (HFpEF). However, missed and delayed diagnosis in CA by cardiologists are common. The study aimed to develop a simple nomogram to identify high risk of CA in HFpEF patients, warranting a further systematic diagnostic algorithm of CA.

METHODS

A total of 337 consecutively hospitalized HFpEF patients [ejection fraction (EF) ≥40%] with increased wall thickness (IWT; ≥12 mm) who underwent a complete diagnostic evaluation for suspected CA from April 2015 to September 2024 were retrospectively included. The diagnosis of transthyretin CA (ATTR-CA) was mainly established by 99mTc-pyrophosphate (99mTc-PYP) scintigraphy, whereas the diagnosis of immunoglobulin light chain CA (AL-CA) was predominantly confirmed by histological biopsy. Patients were randomly divided into training and validation cohorts at a ratio of 7:3. A simple nomogram was established to predict the risk of CA by multivariate logistic regression analysis in the training cohort (n=236) and then validated in the validation cohort (n=101).

RESULTS

A final diagnosis of CA was established in 152 patients, among whom 35 (23%) were identified as ATTR-CA and 117 (77%) as AL-CA, indicating that the prevalence of AL-CA was significantly higher than that of ATTR-CA in our cohort of Chinese HFpEF patients. More importantly, ATTR-CA and AL-CA exhibited comparable clinical and echocardiographic characteristics, thus we developed a simple and unified nomogram model incorporating the absence of hypertension, poor precordial R wave progression, relative wall thickness (RWT), early diastolic mitral peak flow velocity/late diastolic mitral peak flow velocity (E/A) ratio, and right ventricular (RV) wall thickening to identify high risk of CA in Chinese HFpEF patients. The area under the curve (AUC) for the training cohort was 0.881, and for the validation cohort was 0.854, indicating good discrimination. Meanwhile, the calibration curves comparing predicted frequency against observed frequency indicated excellent concordance. Decision curve analysis (DCA) further validated the utility of the nomogram in a clinical setting.

CONCLUSIONS

The nomogram model based on 5 easily assessable variables aids identifying increased risk of CA in Chinese HFpEF patients. It provides a practical approach and facilitates clinical decision-making by cardiologists for further systematic diagnostic algorithm of CA.