Systemic light chain amyloidosis is a rare and debilitating disease, especially for which initially presented with digestive tract involvement. Myocardial amyloidosis is highly aggressive with generally poor prognosis and often resulted in missed diagnosis or misdiagnosis with routine examination tools. Multimodality imaging play an important role in diagnosing the amyloidosis effect on multiple organs. Chemoradiotherapy is the mainstay of treatment. This article presents a rare case of systemic light chain amyloidosis, initially with gastrointestinal symptoms, in a 68-year-old male. He was hospitalized with diarrhea for one year and a half, dysphagia for 4 months, but he had no dyspnea. The transthoracic echocardiogram revealed myocardial hypertrophy of the left ventricle, the hypertrophic heart muscle echoed like "ground glass". The left ventricular ejection fraction (LVEF) detected by Simpson method was 51% and global longitudinal strain (GLS) was -9.00%. But cardiac magnetic resonance showed the patient without gadolinium delayed enhancement. The urinary protein series quantification and the serum free light chain levels were all increased. While the ratio of free κ and free λ was decreased. Hence, the abdominal fat biopsy of the patient was amyloidosis by electronic and immunoelectron microscopy. Organs involved include heart, kidneys, gastrointestinal tract and nervous system, stage III of mayo 2012 model. The patient was treated with Dara-BCD chemotherapy. This case underscores the diagnostic complexity, emphasizing the need for early identification given the grim prognosis associated with systemic AL amyloidosis requiring clinical data, detailed imaging, and histopathological insights. After discharge, the patient became better and followed up in the outpatient. Systemic light chain amyloidosis can easily be missed diagnosis or misdiagnosis in its early stages, losing the opportunity for initiating earlier treatments to improve potential patient outcomes. Despite advancements in diagnostic biomarkers, this case highlights the potential for missed diagnosis with standard CMR imaging when gadolinium enhancement is negative. The utility of echocardiographic features such as reduced GLS and abnormal ECG findings emerges as critical in early identification of myocardial amyloidosis. The correct diagnosis of this case relied on the comprehensive utilization of multimodal imaging techniques including biopsy.

Background: Limited evidence exists regarding predictors of recurrence in patients with non-valvular atrial fibrillation (NVAF) following radiofrequency catheter ablation (RFCA). This study aimed to develop and validate a risk model for post-ablation recurrence in these patients. Methods: 242 patients were enrolled and randomly divided into a modeling group ( n = 169) and a validation group ( n = 73) according to 7:3. The echocardiographic parameters, laboratory values and clinical features were used to derive a predictive model. Univariate and multivariate logistic regression analyses were used to identify independent risk factors. Results: During the 1-year follow-up, 87(36.00%) patients experienced AF recurrence. The nomogram was established by five variables including left atrial volume index (OR1.055, 95% CI: 1.021–1.090, P = 0.001), right atrial volume index (OR1.040, 95% CI: 1.008–1.073, P = 0.014), systemic immune-inflammatory index(OR1.015, 95% CI: 1.001–1.030, P = 0.036), New York Heart Association classification (OR 2.861, 95% CI: 1.282–6.383, P = 0.010), and CHA₂DS₂-VASc score(OR1.417, 95% CI: 1.077–1.864, P = 0.013). The model was developed, an online Dynamic Nomogram ( https://cardiologyresearch.shinyapps.io/DynNomapp ) application via the platform, and subsequently validated. The calculator achieved a C-index of 0.837(95% Cl: 0.774–0.899) in the training cohort and 0.895 (95% Cl: 0.823–0.968) in the validation cohort. The calibration curve showed good consistency between the predictions and observations in the training and validation cohorts. Decision curve analysis and clinical impact curves indicated the clinical utility of the nomogram. Conclusion: We developed a nomogram based on LAVI, RAVI, SII, NYHA classification, CHA₂DS₂-VASc score to estimate the risk of AF recurrence after RFCA. The newly developed nomogram demonstrated good discrimination and accuracy, suggesting its potential utility in predicting AF recurrence. Given its performance, the model is a promising tool; however, it is still in its preliminary stages and requires further validation with larger, multi-center, prospective studies involving diverse populations to confirm its generalizability.

N/a Received: 01 December 2024 Accepted: 16 April 2025 Accepted Manuscript online: 22 April 2025 © . The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/). Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany