Assessing TDApp: An AI-based clinical decision support system for ADHD treatment recommendations
Por:
Baykova, E, Raya, I, Lombardía, C, Gonzalvo, B, Andreu, I, Losada, D, Falkenhain, T, Cunill R, Serrano, D, Rigau, D, Ramírez-Saco, D, López, B and Castells, X
Publicada:
22 ago 2025
Resumen:
Introduction Clinical practice guidelines (CPGs) have several limitations, namely: obsolescence, lack of personalization, and insufficient patient participation. These factors may contribute to suboptimal treatment recommendation compliance and poorer clinical outcomes. APPRAISE-RS is an adaptation of the GRADE heuristic designed to generate CPG-like treatment recommendations that are automated, updated, personalized, participatory, and explanatory using a symbolic AI approach. TDApp is a clinical decision support system (CDSS) that implements APPRAISE-RS for ADHD.Methods Two clinical trials were conducted. In both studies a total of 33 and 32 ADHD patients, respectively, requiring treatment initiation or a major treatment change were enrolled. TDApp recommendations were compared to those of selected CPGs (American Academy of Pediatrics, National Institute for Health and Care Excellence, Spanish Health System, Canadian ADHD Resource Alliance, and the Australasian ADHD Professionals Association) CPGs. The diversity of treatment recommendations was analyzed using Blau's index. Concordance between TDApp and CPGs recommendations was assessed by calculating the proportion of patients for whom TDApp recommended one drug that was also endorsed by CPGs. Dendrograms were plotted to compare the distance between treatment recommendations as calculated using the NbN nomenclature.Results The first study investigated eight methods that differed in how patient and clinician preferred outcomes were handled and the extent to which TDApp tailored the analysis of evidence. The method deemed most suitable was examined in the second study, which found that 50-75% of the patients received at least one favorable treatment recommendation. TDApp evaluated over 10 drugs, including recently marketed ones, with amphetamine derivatives emerging as the most frequently recommended interventions. TDApp generated 8-12 distinct treatment recommendations with a diversity index of 0.70-0.88, which was higher than those of CPGs. The proportion of patients for whom TDApp recommendations overlapped with at least one drug endorsed by CPGs ranged from 21.9% to 100%. Dendrogram analysis revealed that TDApp was positioned on one side of the tree, while CPGs clustered together on the opposite side.Conclusions TDApp is an advanced prototype of an CDSS offering automated, participatory, personalized, and explanatory treatment recommendations for ADHD. It represents a promising alternative to CPGs for aiding clinicians and patients in shared treatment decision-making.
Filiaciones:
Baykova, E:
Inst Hlth Care ICS IAS, Girona, Spain
Raya, I:
Univ Girona, Control Engn & Intelligent Syst eXiT, Girona, Spain
Lombardía, C:
Inst Hlth Care ICS IAS, Girona, Spain
Gonzalvo, B:
Inst Hlth Care ICS IAS, Girona, Spain
Andreu, I:
Inst Hlth Care ICS IAS, Girona, Spain
Losada, D:
Inst Hlth Care ICS IAS, Girona, Spain
Falkenhain, T:
Inst Hlth Care ICS IAS, Girona, Spain
Cunill R:
St Joan de Deu Numancia Hlth Pk, Barcelona, Spain
Serrano, D:
Inst Hlth Care ICS IAS, Girona, Spain
Rigau, D:
Ibero Amer Cochrane Ctr CCIb, Barcelona, Spain
Ramírez-Saco, D:
Dept Clin Pharmacol, Valll dHebron Barcelona Hosp Campus, Barcelona, Spain
López, B:
Univ Girona, Control Engn & Intelligent Syst eXiT, Girona, Spain
Castells, X:
Univ Girona, Dept Med Sci, TransLab Res Grp, Girona, Spain
Green Submitted, gold
|