共 4 条
A second-generation artificial intelligence-based therapeutic regimen improves diuretic resistance in heart failure: Results of a feasibility open-labeled clinical trial
被引:13
|作者:
Gelman, Ram
[1
,2
]
Hurvitz, Noa
[1
,2
]
Nesserat, Rima
[1
,2
]
Kolben, Yotam
[1
,2
]
Nachman, Dean
[2
,3
]
Jamil, Khurram
[4
]
Agus, Samuel
[4
]
Asleh, Rabea
[2
,3
]
Amir, Offer
[2
,3
]
Berg, Marc
[4
]
Ilan, Yaron
[1
,2
,5
]
机构:
[1] Hebrew Univ Jerusalem, Hadassah Med Ctr, Dept Med, Jerusalem, Israel
[2] Hebrew Univ Jerusalem, Fac Med, Jerusalem, Israel
[3] Hebrew Univ Jerusalem, Hadassah Med Ctr, Dept Cardiol, Jerusalem, Israel
[4] Stanford Univ, Oberon Sci & Area 9 Innovat, Palo Alto, CA USA
[5] Hebrew Univ Jerusalem, Fac Med, Hadassah Med Ctr, Dept Med, POB 1200, Jerusalem, Israel
关键词:
Congestive heart failure;
Diuretic resistance;
Artificial intelligence;
RATE-VARIABILITY;
DRUG-RESISTANCE;
IMMUNE-SYSTEM;
PLATFORM;
CHRONOBIOLOGY;
CHRONOTHERAPY;
MICROTUBULES;
DYNAMICS;
D O I:
10.1016/j.biopha.2023.114334
中图分类号:
R-3 [医学研究方法];
R3 [基础医学];
学科分类号:
1001 ;
摘要:
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 CareTM 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.
引用
收藏
页数:6
相关论文