Why the study?
Over one-third of congestive heart failure patients develop diuretic resistance, prompting investigation into whether algorithm-controlled therapeutic regimens introducing regimen variability can improve diuretic resistance.
Does an AI-based personalized diuretic regimen improve outcomes in CHF patients with diuretic resistance?
Does an AI-based personalized diuretic regimen improve outcomes in CHF patients with diuretic resistance?
Answers are grounded in this paper and cite their sources.
An AI-guided personalized diuretic regimen may improve symptoms and biomarkers in diuretic-resistant.
INTRODUCTION: Diuretics are a mainstay therapy for congestive heart failure (CHF); however, over one-third of patients develop diuretic resistance. Second-generation artificial intelligence (AI) systems introduce variability into treatment regimens to overcome the compensatory mechanisms underlying the loss of effectiveness of diuretics. This open-labeled, proof-of-concept clinical trial sought to investigate the ability to improve diuretic resistance by implementing algorithm-controlled therapeutic regimens. METHODS: Ten CHF patients with diuretic resistance were enrolled in an open-labeled trial where the Altus Care™ app managed diuretics' dosage and administration times. The app provides a personalized therapeutic regimen creating variability in dosages and administration times within pre-defined ranges. Response to therapy was measured by the Kansas City Cardiomyopathy Questionnaire (KCCQ) score, 6-minute walk test (SMW), N-terminal pro-brain natriuretic peptide (NT-proBNP) levels, and renal function. RESULTS: The second-generation, AI-based, personalized regimen alleviated diuretic resistance. All evaluable patients demonstrated clinical improvement within ten weeks of intervention. A dose reduction (based on a three-week average before and last three weeks of intervention) was achieved in 7/10 patients (70 %, p = 0.042). The KCCQ score improved in 9/10 (90 %, p = 0.002), the SMW improved in 9/9 (100 %, p = 0.006), NT-proBNP was decreased in 7/10 (70 %, p = 0.02), and serum creatinine was decreased in 6/10 (60 %, p = 0.05). The intervention was associated with reduced number of emergency room visits and the number of CHF-associated hospitalizations. SUMMARY: The results support that the randomization of diuretic regimens guided by a second-generation personalized AI algorithm improves the response to diuretic therapy. Prospective controlled studies are needed to confirm these findings.
No takes yet. Share an insight, caveat, or question.
Gelman et al. (2023) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: