The Case: A Missed Diagnosis of Cardiac Amyloidosis in Rheumatoid Arthritis A 55-year-old woman with a long-standing history of rheumatoid arthritis (RA), managed with methotrexate and intermittent corticosteroids, presented to the emergency department with progressive shortness of breath, leg swelling, and fatigue over the past month. On examination, she showed signs of heart failure: elevated jugular venous pressure, pulmonary crackles, and peripheral edema. Her electrocardiogram (ECG) revealed low voltage, and an echocardiogram showed thickened ventricular walls with a preserved ejection fraction. These findings led the initial team to diagnose hypertrophic cardiomyopathy, a common cause of heart failure with preserved ejection fraction (HFpEF). Standard heart failure treatments were initiated, but her symptoms persisted and worsened. How I Discovered It When I took over her care, I noticed something unusual: her heart failure was refractory to typical treatments, and she casually mentioned that her joint pain had recently worsened despite her RA medications. This prompted me to reconsider the diagnosis, as RA can occasionally cause extra-articular complications, including rare cardiac issues. I suspected cardiac amyloidosis—a condition where abnormal protein deposits build up in the heart—though it’s an uncommon manifestation of RA. To investigate further, I ordered a cardiac magnetic resonance imaging (MRI) scan. To enhance my analysis, I used a cutting-edge AI algorithm designed to detect patterns of amyloid deposition in cardiac imaging, which can be subtle and easily overlooked. The AI tool highlighted areas suggestive of amyloidosis, prompting me to pursue definitive testing. An endomyocardial biopsy confirmed AL (light-chain) amyloidosis, likely linked to her underlying RA, rather than hypertrophic cardiomyopathy. How I Treated It With the correct diagnosis established, I collaborated with a multidisciplinary team of cardiologists, rheumatologists, and hematologists. We shifted her treatment from standard heart failure management to a regimen targeting AL amyloidosis. This included chemotherapy to address the plasma cell dyscrasia producing the amyloid proteins, alongside supportive care for her heart failure. Over time, her shortness of breath and edema improved, and her condition stabilized, markedly enhancing her quality of life. Why This Case Is Important This case stands out for several critical reasons: Rare and Overlooked Complication: Cardiac amyloidosis is a rare manifestation of RA, often missed because its symptoms—heart failure, fatigue, and edema—mimic more common conditions like hypertrophic cardiomyopathy. Misdiagnosis can lead to inappropriate treatments, such as beta-blockers or calcium channel blockers, which may worsen amyloidosis outcomes. Identifying the true cause was essential to halt disease progression. Intersection of Cardiology and Rheumatology: This case exemplifies how autoimmune diseases like RA can affect the heart in unexpected ways. Clinicians must remain alert to these overlaps, especially when standard treatments fail, as subtle rheumatological clues (e.g., worsening joint pain) can point to the underlying issue. Life-Saving Diagnosis: Cardiac amyloidosis carries a poor prognosis if untreated, but early detection and targeted therapy can significantly improve survival and quality of life. This case underscores the value of persistence and advanced diagnostics in challenging presentations. Connection to Recent Findings in Medicine and AI This case ties directly into recent advancements in medicine and AI, enhancing both its discovery and broader implications: AI in Cardiac Imaging: AI algorithms are revolutionizing cardiac diagnostics by analyzing imaging data—such as MRI and echocardiography—to detect subtle abnormalities. In this case, the AI tool identified amyloid deposition patterns that might have been missed manually, aligning with recent developments where AI distinguishes between cardiomyopathies with high accuracy. This technology is increasingly vital for diagnosing rare conditions early. Predictive Analytics in Autoimmune Diseases: Recent research leverages AI to predict cardiac complications in autoimmune diseases like RA or systemic lupus erythematosus (SLE). By analyzing clinical, genetic, and imaging data, AI models can identify patients at risk for conditions like amyloidosis or myocarditis, enabling proactive monitoring and intervention. This case could have benefited from such predictive tools earlier in her disease course. Multimodal Data Integration: AI’s ability to synthesize diverse data—patient history, lab results, and imaging—mirrors its growing role in precision medicine. Here, an AI system could have flagged the combination of RA, worsening joint symptoms, and cardiac findings as suspicious for amyloidosis, accelerating the diagnostic process. Conclusion This fascinating case of cardiac amyloidosis in a patient with RA, initially mistaken for hypertrophic cardiomyopathy, highlights the critical need to consider rare cardiac complications in autoimmune diseases. My discovery stemmed from linking her refractory heart failure with worsening RA symptoms, confirmed through AI-assisted cardiac MRI analysis and biopsy. Treatment shifted to target the amyloidosis, yielding significant improvement. Its importance lies in avoiding misdiagnosis, improving outcomes, and showcasing the power of integrating cardiology and rheumatology. Recent advancements in AI-driven diagnostics and predictive analytics further amplify its relevance, demonstrating how technology can uncover hidden patterns and enhance patient care in complex medical scenarios.
