RESUMEN
OBJECTIVES: We evaluated the feasibility of optimising coronary perfusion pressure (CPP) during cardiopulmonary resuscitation (CPR) with a closed-loop, machine-controlled CPR system (MC-CPR) that sends real-time haemodynamic feedback to a set of machine learning and control algorithms which determine compression/decompression characteristics over time. BACKGROUND: American Heart Association CPR guidelines (AHA-CPR) and standard mechanical devices employ a "one-size-fits-all" approach to CPR that fails to adjust compressions over time or individualise therapy, thus leading to deterioration of CPR effectiveness as duration exceeds 15-20 âmin. METHODS: CPR was administered for 30 âmin in a validated porcine model of cardiac arrest. Intubated anaesthetised pigs were randomly assigned to receive MC-CPR (6), mechanical CPR conducted according to AHA-CPR (6), or human-controlled CPR (HC-CPR) (10). MC-CPR directly controlled the CPR piston's amplitude of compression and decompression to maximise CPP over time. In HC-CPR a physician controlled the piston amplitudes to maximise CPP without any algorithmic feedback, while AHA-CPR had one compression depth without adaptation. RESULTS: MC-CPR significantly improved CPP throughout the 30-min resuscitation period compared to both AHA-CPR and HC-CPR. CPP and carotid blood flow (CBF) remained stable or improved with MC-CPR but deteriorated with AHA-CPR. HC-CPR showed initial but transient improvement that dissipated over time. CONCLUSION: Machine learning implemented in a closed-loop system successfully controlled CPR for 30 âmin in our preclinical model. MC-CPR significantly improved CPP and CBF compared to AHA-CPR and ameliorated the temporal haemodynamic deterioration that occurs with standard approaches.
RESUMEN
Chronic venous insufficiency affects over 2 million patients in the US alone, with severe cases involving thousands of patients with chronic leg ulcers and potential amputation. Current treatment options are limited, with surgical repair of vein valves being the most effective but challenging solution. A transcatheter vein valve made from a biologically-engineered matrix possessing the ability to regenerate has the potential to provide both valve function and long-term hemocompatibility and durability because the matrix becomes endothelialized and populated with host tissue cells. We have developed a novel tissue-engineered transcatheter vein valve (TEVV) on a Nitinol stent and demonstrated function and durability in vitro. Tissue was grown from fibroblasts in fibrin gel so as to embed the stent, with a tubular extension of the engineered tissue from one end of the stent that was stitched along opposite sides and everted into the stent to form a bileaflet valve. Following decellularization, to create an "off-the-shelf" TEVV comprised of the resulting collagenous matrix, it was tested in a pulse duplicator to evaluate hydrodynamic properties for a range of flow rates. The TEVV was shown to have forward pressure drops in the range of 2-4â¯mmHg, low closing volume, and nil regurgitation. Further hydrodynamic tests were performed after crimping and then again after 1 million cycle durability testing, showing no degradation of valve performance or any visual damage to the matrix. The TEVV held over 600â¯mmHg backpressure after the durability testing, ensuring the valve would withstand pressure spikes well outside of the normal in vivo range. Catheter-based delivery into the ovine iliac vein demonstrated TEVV closing 2 weeks p.o. and endothelialization without thrombosis 8 weeks p.o.
