A second-generation artificial intelligence-based therapeutic regimen improves diuretic resistance in heart failure: Results of a feasibility open-labeled clinical trial

A second-generation artificial intelligence-based therapeutic regimen improves diuretic resistance in heart failure: Results of a feasibility open-labeled clinical trial

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 ef...

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Bibliographic Details
Published in:Biomedicine & pharmacotherapy Vol. 161; p. 114334
Main Authors: Gelman, Ram, Hurvitz, Noa, Nesserat, Rima, Kolben, Yotam, Nachman, Dean, Jamil, Khurram, Agus, Samuel, Asleh, Rabea, Amir, Offer, Berg, Marc, Ilan, Yaron
Format: Journal Article
Language:English
Published: France Elsevier Masson SAS 01-05-2023
Elsevier
Subjects:
Artificial Intelligence
Congestive heart failure
Diuretic resistance
Diuretics - therapeutic use
Feasibility Studies
Heart Failure
Humans
Peptide Fragments - therapeutic use
Prospective Studies
CHF
NYHA
Diuretic resistance
KCCQ
HFpER
AI
Congestive heart failure
SMW
NT-ProBNP
HFrEF
Artificial intelligence
HFmrEF
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Summary: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. 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. 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. 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.
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ISSN:0753-3322
1950-6007
DOI:10.1016/j.biopha.2023.114334