The pacing site has been shown to influence functional improvement with cardiac resynchronization therapy. We evaluated the effects of the pacing site on left ventricular (LV) function in an animal model. Equilibrium radionuclide angiography was acquired in sinus rhythm (NSR) and with ventricular pacing, from three pacing sites in seven normal and eight infarcted dogs. QRS duration, electrical activation pattern, wall motion, LV ejection fraction (EF), synchrony of ventricular contraction, and mean arterial pressure (MAP), were related to the pacing site and infarct size, during each of 120 episodes. Little changed during pacing in normals. In infarcted dogs, LV wall motion, and synchrony worsened, LVEF and MAP often fell. These changes related to altered activation patterns which were influenced by the pacing site but were not related to infarct size. Hemodynamic and functional LV changes after infarction were found to vary with the pacing site and associated conduction and synchrony.

Background

The pacing site has been shown to influence functional improvement with cardiac resynchronization therapy. We evaluated the effects of the pacing site on left ventricular (LV) function in an animal model.

Methods and results

Equilibrium radionuclide angiography was acquired in sinus rhythm (NSR) and with ventricular pacing, from three pacing sites in seven normal and eight infarcted dogs. QRS duration, electrical activation pattern, wall motion, LV ejection fraction (EF), synchrony of ventricular contraction, and mean arterial pressure (MAP), were related to the pacing site and infarct size, during each of 120 episodes. Little changed during pacing in normals. In infarcted dogs, LV wall motion, and synchrony worsened, LVEF and MAP often fell. These changes related to altered activation patterns which were influenced by the pacing site but were not related to infarct size.

Conclusions

Hemodynamic and functional LV changes after infarction were found to vary with the pacing site and associated conduction and synchrony.

Objective

Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers.

Materials and methods

The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics.

Results

Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access.

Conclusions

The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19.