HEART FAILURE
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Heart failure (HF) is the most critical and costly public health crisis — the leading cause of death and the largest healthcare costs in the US and EU.
Heart Failure in the US
HF hospital admissions: 1.2–1.6M per year — 600k–800k for ADHF
30-day rehospitalization rate: 24%
Hospital length of stay: 3–5 days
Direct costs of rehospitalization: $13,000–$18,000 per readmission
Direct healthcare costs: $40B in 2025 — ≈ $50B in 2030
Pulmonary artery catheters (PACs) are the standard of care in complex acute HF patients and cardiac ICU patients.
However, PACs are avoided by clinicians due to complexity, risks, and misinterpretation — resulting in suboptimal treatment decisions and patient outcomes.
Patients
Significant risks
Pain & discomfort
No mobility, bed bound
Prolonged hospital stay
Physicians
PAC inaccuracies
Misinterpretation
Mistreatment
Complications
So, they avoid using PACs
Payers
Delayed discharge
Rehospitalization
Inefficiencies
Increased costs
Without PAC
Clinicians rely on indirect, less accurate methods resulting in delayed and suboptimal treatment decisions
Existing PACs are bulky, highly invasive catheters that require a complex insertion procedure and deliver hemodynamic data with limited reliability.
Indirect methods (e.g. physical exams, lung/heart sounds, lab tests, medical imaging) provide delayed data with limited accuracy.
Permanent electronic cardiac implants carry risks, long-term complications and high costs — their use is limited to specific chronic HF patients (e.g. CardioMEMS, Fire1)
Non-invasive wearable devices are not suitable for guiding clinical treatment decisions — they’re only suited for general health and fitness tracking.
Misinterpretation of the massive amounts of complex medical data and delayed recognition of deterioration often lead to suboptimal or even harmful treatment decisions.
Conclusion
A safer, more reliable AI-guided PAC would lead to better patient outcomes and savings.
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