A novel, non-invasive AI-based telemonitoring system for heart failure: detection of undiagnosed hyperthyroidism in an asymptomatic patient - Allan Böhm; Julia Lucka; Amitai Segev; Marta Kollarova; Stefan Toth; Nikola Jajcay; Branislav Bezak (European Journal of Case Reports in Internal Medicine)
Background: Untreated thyroid disorders may precipitate heart failure (HF) decompensation. Assessment of cardiac filling pressures may aid in the early detection and prevention of clinical decompensation. Therapy guided by monitoring of cardiac filling pressures has been shown to improve quality of life and survival and reduce hospitalizations of individuals with HF. We have developed a non-invasive method to assess left ventricular filling pressures (LVFP) by analysing the photoplethysmography signal with Seeling HeartCore technology (Seerlinq, Bratislava, Slovakia). Case description: A 99-year-old female visited the clinic for a routine cardiac check-up. Laboratory investigations showed elevated NTproBNP and moderately elevated high sensitive troponin T. HeartCore algorithm indicated elevated LVFP. As part of the evaluation of worsening of sub-clinical HF, extended laboratory tests revealed low thyroid-stimulating hormone with high free thyroxine levels indicating increased thyroid function. The endocrinologist diagnosed hyperthyroidism with multinodular goitre and prescribed thiamazole. To prevent progression to clinical HF decompensation, the dose of furosemide was increased. At 4 months, during scheduled cardiac follow-up, the patient was clinically doing well, without any signs or symptoms of HF. Discussion: Remote monitoring devices that track pressures in the pulmonary artery require invasive implantation and are associated to potential complications. The high cost of these devices presents a significant barrier to widespread use. SEERLINQ is a novel system for remote haemodynamic monitoring based on non-invasive assessment of LVFP, presenting a promising alternative to current invasive methods. Conclusion: This case underscores the potential benefits of this technology in the early recognition of pre-clinical deterioration and its implementation for remote home monitoring in patients with HF.