USage of chitosan for Femoral (USF) haemostasis after percutaneous procedures: a comparative open label study.

AIMS: To test the efficacy and safety of a chitosan pad for femoral haemostasis as an adjunct to manual compression. Haemostasis of the femoral artery after coronary angiography by manual compression is time consuming and uncomfortable for the patient. Closure devices are costly and do not reduce vascular complication rate. The HemCon(r) pad is used by the US army to control traumatic bleeding. It consists of chitosan, a positively charged carbohydrate that attracts the negatively charged blood cells and platelets and promotes clotting. METHODS AND RESULTS: Patients undergoing percutaneous coronary angiography were 1:1 randomised for manual compression with regular or HemCon(r) pad. All patients were catheterised with 6 Fr sheath and received 2500 u of heparin. Time to haemostasis, incidence of minor and major bleeding, haematoma size, post-procedural stay at the hospital and level of satisfaction were compared between the two groups. Seventy patients in the HemCon group and 66 patients in the regular pad groups were recruited. Activated clotting time (ACT) before manual compression was similar, 183.9 ± 43.4 and 178.3 ± 34.2 seconds in the HemCon(r) and regular pad groups respectively. Time to haemostasis was 5.6 ± 2.1 and 8.4 ± 3.5 minutes in the HemCon® and regular pad groups, respectively (p<0.001). Haematoma developed in 6% and 14.8% of patients in the HemCon(r) and regular pad group, respectively (p=0.14). CONCLUSIONS: The HemCon(r) pad significantly decreased time-to-haemostasis compared to the regular pad. The total incidence of haematoma tended to be lower in the HemCon(r) pad compared to the regular pad group.

Six- and twelve-month clinical outcomes after implantation of prokinetic BMS in patients with acute coronary syndrome.

AIMS: To evaluate the Prokinetic bare metal stent implanted in patients presenting with acute coronary syndrome (ACS). METHODS: We retrospectively studied ACS patients who underwent percutaneous coronary intervention (PCI) with a Prokinetic stent implantation. Excluded were patients presenting with cardiogenic shock, undergoing PCI to left main coronary artery (LM), or having implantation of additional stents other than Prokinetic. Six and 12 months clinical follow-up was obtained by phone. RESULTS: A total of 140 Prokinetic stents were implanted in 117 patients (age 64+/-13.0 years, 78% men). Thirty two percent of the patients had unstable angina, 36% had non ST-elevation myocardial infarction (NSTEMI) and 33% had ST-elevation myocardial infarction (STEMI). Forty two percent of lesions were categorized as B2 and 21% as C type. Procedural success was achieved in 99.1% of lesions. Clinical success was achieved in 97.4% of patients. Major adverse cardiac events (MACE) rate was 8.5% and 11.1% at 6 and 12 months follow-up, respectively. The incidence of cardiac death, MI and TLR was 2.6%, 3.4% and 2.6%, respectively at 6 months, and 4.3%, 4.3%, 2.6% respectively at 12 months. CONCLUSIONS: Clinical outcomes at 6 and 12 months after Prokinetic stent implantation are excellent and may be attributable to its unique combination of composition, design and coating.

Adaptive cardiac resynchronization therapy device based on spiking neurons architecture and reinforcement learning scheme.

Spiking neural network (NN) architecture that uses Hebbian learning and reinforcement-learning schemes for adapting the synaptic weights is implemented in silicon and performs dynamic optimization according to hemodynamic sensor for a cardiac resynchronization therapy (CRT) device. The spiking NN architecture dynamically changes the atrioventricular (AV) delay and interventricular (VV) interval parameters according to the information provided by the intracardiac electrograms (IEGMs) and hemodynamic sensors. The spiking NN coprocessor performs the adaptive part and is controlled by a deterministic algorithm master controller. The simulated cardiac output obtained with the adaptive CRT device is 30% higher than with a nonadaptive CRT device and is likely to provide improvement in the quality of life for patients with congestive heart failure. The spiking NN architecture shows synaptic plasticity acquired during the learning process. The synaptic plasticity is manifested by a dynamic learning rate parameter that correlates patterns of hemodynamic sensor with the system outputs, i.e., the optimal AV and VV pacing intervals.

Adaptive cardiac resynchronization therapy device: a simulation report.

We report the results of a simulation of an adaptive cardiac resynchronization therapy (CRT) device performing biventricular pacing in which the atrioventricular (AV) delay and interventricular (VV) interval parameters are changed dynamically in response to data provided by the simulated IEGMs and simulated hemodynamic sensors. A learning module, an artificial neural network, performs the adaptive part of the algorithm supervised by an algorithmic deterministic module, internally or externally from the implanted CRT or CRT-D. The simulated cardiac output obtained with the adaptive CRT device is considerably higher (30%) especially with higher heart rates than in the nonadaptive CRT mode and is likely to be translated into improvement in quality of life of patients with congestive heart failure.