Comprehensive Summary
This study by Gelman et al. examines the application of second-generation artificial intelligence (AI) systems to reduce diuretic resistance in peatients with congestive heart failure (CHF). Over a 10-week period, ten diuretic-resistant CHF patients from Hadassah-Hebrew University Medical Center participated in the study, and an individualized treatment plan in terms of dosing and times of medical administration was prepared for use with a mobile app called Altus Care. The research coordinators conducted weekly checkups regarding response to therapy through the KCCQ score, SMW, NTproBNP levels, and renal function. Using the second-generation AI system reduced the number of emergency room (ER) admissions and hospitalizations. The dose was reduced in seven patients, the KCCQ score improved in 9 patients, and NT-proBNP levels decreased in 7 patients. Within ten weeks, all evaluable patients demonstrated clinical improvement.
Outcomes and Implications
Diuretic resistance is a big problem with CHF patients; in fact, over one in three patients develop this condition. Interventions that can improve response to diuretics can result in fewer hospitalizations, improve symptoms, and possibly improve survival. Limitations of the study are the small and non-randomized sample size from one medical center. Nonetheless, the second-generation AI system was able to improve diuretic effects on CHF patients within a short duration, although a timeline for a long-term solution is still to be determined. A larger study with positive outcomes is needed to be more confident in the implementation of second-generation AI systems for CHF patients.