Heart failure remains a serious issue in healthcare services in\nIndonesia. Data from the Asian-HF Registry shows Indonesia ranks second\nwith the highest number of heart failure cases in Asia after China. The\none-year mortality rate for patients reaches 34.1 per cent, while around\n30 per cent of patients must return to hospital for treatment due to\nworsening conditions after being discharged. One factor triggering the\nhigh readmission rate is the presence of residual pulmonary congestion,\nor fluid accumulation in the lungs, which goes undetected before\npatients leave the hospital. This condition is often missed during\nexaminations using a conventional stethoscope. Meanwhile, methods such\nas Lung Ultrasound and NT-proBNP blood biomarker tests require special\nequipment, higher costs, and medical personnel with specific\ncompetencies.<\/p>\n
Addressing these challenges, Dr Rony M. Santoso, a Cardiovascular\nInterventional Consultant and Vascular Medicine Consultant at Primaya\nHospital Tangerang, developed the Novel Auscultation Device of\nArtificial Intelligence for Heart Failure (NAVI-HF). This artificial\nintelligence-based innovation is part of his doctoral dissertation\nresearch at the Faculty of Medicine, University of Indonesia. NAVI-HF is\ndesigned as a device to assist doctors in detecting signs of pulmonary\ncongestion through a more practical, rapid, and objective analysis of\nchest cavity sounds. Unlike a regular stethoscope, this device records\nchest sounds from five examination points for approximately one minute.\nThe recording is then analysed using an AI algorithm to identify whether\nthe patient still has signs of pulmonary congestion that could\npotentially cause worsening heart failure after hospital discharge.<\/p>\n
Research results on 246 acute heart failure patients showed NAVI-HF\nhas promising diagnostic performance. Compared to Lung Ultrasound as the\nreference standard, the device recorded an accuracy rate of 86 per cent,\nsensitivity of 91 per cent, and specificity of 82 per cent.\nAdditionally, a follow-up study conducted over six months found that\npatients with a positive NAVI-HF result had a 1.6 times higher risk of\nbeing readmitted due to heart failure compared to patients with a\nnegative result. According to Dr Rony, this innovation is not intended\nto replace the role of doctors but rather to serve as a supporting tool\nin identifying high-risk patients so that treatment can be administered\nmore quickly.<\/p>\n
\"One of the biggest challenges in managing heart failure is ensuring\nthe patient\u2019s condition is truly stable before leaving the hospital. We\ndeveloped NAVI-HF to help doctors identify patients who are still at\nrisk of deterioration through a simple, portable, AI-supported tool.\nThis way, patients who require closer monitoring can be recognised\nearlier so that therapy can be adjusted before complications occur,\" he\nexplained. He added that the development of NAVI-HF also opens\nopportunities for implementing home-based monitoring and telemedicine\nservices in the future. \"We hope this innovation can support earlier\ndetection, assist doctors in clinical decision-making, and\nsimultaneously reduce the risk of readmission due to heart failure,\" he\nadded. The development of NAVI-HF represents an example of the use of\nartificial intelligence technology in the medical world. The presence of\nthis technology is expected to help healthcare workers produce faster,\nmore objective, and more targeted diagnoses without replacing the role\nof doctors, while improving the quality of life for heart failure\npatients and reducing the burden on healthcare services in\nIndonesia.<\/p>", "url": "https:\/\/jawawa.id\/newsitem\/doctor-develops-ai-based-tool-for-early-detection-of-heart-failure-risk-1784429419", "image": "" }, "sponsor": "Okusi Associates", "sponsor_url": "https:\/\/okusiassociates.com" }