Life expectancy of contemporary cardiac pacemakers is limited due to the use of an internal primary battery. Repeated device replacement interventions are necessary, which leads to an elevated risk for patients and an increase of health care costs. The aim of our study is to investigate the feasibility of powering an endocardial pacemaker by converting a minimal amount of the heart’s kinetic energy into electric energy.The intrinsic cardiac muscle activity makes it an ideal candidate as continuous source of energy for endocardial pacemakers. For this reason, we developed a prototype able to generate enough power to supply a pacing circuit under different orientations and heart rate. The prototype consists of a mass imbalance that drives an electromagnetic generator while oscillating. We developed a mathematical model to estimate the amount of energy harvested from inside a heart chamber. Finally, the implemented prototype was successfully tested during in-vitro and in-vivo experiments.Life expectancy of contemporary cardiac pacemakers is limited due to the use of an internal primary battery. Repeated device replacement interventions are necessary, which leads to an elevated risk for patients and an increase of health care costs. The aim of our study is to investigate the feasibility of powering an endocardial pacemaker by converting a minimal amount of the heart’s kinetic energy into electric energy. The intrinsic cardiac muscle activity makes it an ideal candidate as continuous source of energy for endocardial pacemakers. For this reason, we developed a prototype able to generate enough power to supply a pacing circuit under different orientations and heart rate. The prototype consists of a mass imbalance that drives an electromagnetic generator while oscillating. We developed a mathematical model to estimate the amount of energy harvested from inside a heart chamber. Finally, the implemented prototype was successfully tested during in-vitro and in-vivo experiments.

NorCPM1 (Bethke et al., 2021; https://doi.org/10.5194/gmd-14-7073-2021) is a CMIP6-type global climate model (GCM) designed for generating climate reanalyses and conducting seasonal-to-decadal climate predictions. It integrates the Norwegian Earth System Model version 1 (NorESM1) with CMIP6 external forcings and utilizes the ensemble Kalman filter (EnKF) data assimilation technique. NorESM1 features an isopycnic-coordinate ocean component that includes biogeochemistry. The EnKF (Evensen, 2003; https://doi.org/10.1007/s10236-003-0036-9) is one of the most advanced data assimilation methods, offering uncertainty quantification through Monte-Carlo ensembles. The forecast error covariances, which propagate information from observed to non-observed variables, are flow-dependent and evolve with the climate system's variability. NorCPM1 uses anomaly assimilation to prevent prediction drift caused by changes in model climatology. The atmospheric and land components have a horizontal resolution of 1.9° latitude and 2.5° longitude, with the atmosphere consisting of 26 hybrid sigma-pressure levels up to 3 hPa, indicating that the stratosphere is not fully resolved. The ocean and sea ice components have a horizontal resolution of about 1°. The ocean component includes 51 isopycnic vertical layers and a bulk mixed layer that represents two layers with dynamically changing thicknesses and densities. This dataset features a prediction-like pacemaker simulation using NorCPM1, which imposes the development and evolution of the cold and fresh anomaly in the subpolar gyre (SPG) region throughout the pacemaker period. The "pacemaking" is applied from initialization on October 15, 2014, through December 31, 2019. After this period, the pacemaker simulation continues without restoring or assimilation until December 31, 2024. The dataset includes 30 members. All ocean physical state variables in the SPG are constrained by assimilating (i) temperature and salinity anomalies from EN4 Objective Analysis (only data below the mixed layer with an observation weight greater than 0.8 are assimilated) and (ii) SST anomalies from OISSTV2. During each assimilation time step, observations update both observed and unobserved variables using the EnKF method, with forecast error covariances estimated from the ensemble members (Bethke et al., 2021). The climatology reference period is 1980-2010 for temperature and salinity, and 1982-2010 for SST. The pacemaker region is defined as [0-80°W, 30-60°N] with 5° linear transition zones to zero at the southern and northern boundaries.

These are peer-reviewed supplementary materials for the article 'Costs and outcomes of mobile cardiac outpatient telemetry monitoring post-transcatheter aortic valve replacement' published in the Journal of Comparative Effectiveness Research.Supplementary Table 1: CPT and ICD-10 CodesSupplementary Table 2: Propensity score adjusted revenue center costs for patients with MCOT monitoring versus non-MCOT monitoring post-TAVR procedureAim: To estimate the costs and outcomes of transcatheter aortic valve replacement (TAVR) recipients based on the use of mobile cardiac outpatient telemetry (MCOT) monitoring. Materials & methods: A retrospective database study was conducted to estimate costs, contribution margins (CMs), pacemaker insertions and other outcomes for patients undergoing TAVR procedures with MCOT monitoring postprocedure versus non-MCOT monitoring. Results: A total of 4164 patients were identified (283 MCOT monitoring and 3881 non-MCOT monitoring). The rate of pacemaker insertion following hospital discharge was higher in the MCOT cohort (6.6 MCOT vs 2.1% non-MCOT; p = 0.007). MCOT use was associated with lower costs and improved CMs of the index TAVR admission (costs: US$40,569 MCOT vs $43,289 non-MCOT; p = 0.003; CMs: US$7087 MCOT vs $5177 non-MCOT; p = 0.047) with no difference through the subsequent 60-day period following discharge. Conclusion: MCOT for ambulatory cardiac monitoring post-TAVR discharge is associated with higher rates of pacemaker insertion, at no overall greater costs.