LOLATAO—An Artificial-Intelligence-Based Virtual Assistant for Clinical Follow-Up of Patients with Non-Valvular Atrial Fibrillation (AF) Undergoing Oral Anticoagulant Therapy (OAT): A Feasibility Study
Year: 2025
Type: article
Abstract: Background: The aim of this study was to evaluate, for the first time, the feasibility of implementing LOLA, a speech-AI-driven conversational assistant, in monitoring and managing OAT for patients with non-valvular atrial fibrillation (AF). Methods: In 2023, we conducted a pilot prospective observational study of patients with non-valvular atrial fibrillation (AF) and TAO. All patients received a first-contact call from LOLATAO and then monthly calls following a protocol predefined by haematologists. At the end of the study, a satisfaction questionnaire was carried out. Results: Of the fifty patients, the mean age was 75 years, and 33% were women. One-third of the patients (n = 16) were receiving antivitamin K treatment, and two-thirds (33) DOACs. A total of 579 calls were made with a median follow-up of 278 days. LOLATAO had high rates of acceptability (85%), adherence (90%), and satisfaction (>95%). A total of 42% of the patients reported at least one missed dose within the last month, and 18% reported having a scheduled intervention requiring bridging therapy. In patients with AVKs, 94% (n = 15) reported being unaware of their TRT at least once, and 75% (n = 12) of patients reported having a TRT < 65%. Those patients in whom the TRT was <65% were switched to DOACs. LOLATAO saved a total of 10 h per month for haematologists during follow-up. Conclusions: This study suggests that LOLATAO can be a helpful tool in the management of chronic follow-up of patients with AF and undergoing OAT, reducing the burden of care and with high rates of acceptance and satisfaction by patients.
Source: Journal of Clinical Medicine
DOI: 10.3390/jcm14093023
Authors: Amparo Santamaria, Cristina Antón Maldonado, Beatriz Sánchez-Quiñones, Nataly Ibarra Vega, Pedro Gónzalez, Rafael Carrasco
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W4409888605
