Consensus on the assessment of systemic sclerosis-associated primary heart involvement: World Scleroderma Foundation/Heart Failure Association guidance on screening, diagnosis, and follow-up assessment

INTRODUCTION: Heart involvement is a common problem in systemic sclerosis. Recently, a definition of systemic sclerosis primary heart involvement had been proposed. Our aim was to establish consensus guidance on the screening, diagnosis and follow-up of systemic sclerosis primary heart involvement patients. METHODS: A systematic literature review was performed to investigate the tests used to evaluate heart involvement in systemic sclerosis. The extracted data were categorized into relevant domains (conventional radiology, electrocardiography, echocardiography, cardiac magnetic resonance imaging, laboratory, and others) and presented to experts and one patient research partner, who discussed the data and added their opinion. This led to the formulation of overarching principles and guidance statements, then reviewed and voted on for agreement. Consensus was attained when the mean agreement was ⩾7/10 and of ⩾70% of voters. RESULTS: Among 2650 publications, 168 met eligibility criteria; the data extracted were discussed over three meetings. Seven overarching principles and 10 guidance points were created, revised and voted on. The consensus highlighted the importance of patient counseling, differential diagnosis and multidisciplinary team management, as well as defining screening and diagnostic approaches. The initial core evaluation should integrate history, physical examination, rest electrocardiography, trans-thoracic echocardiography and standard serum cardiac biomarkers. Further investigations should be individually tailored and decided through a multidisciplinary management. The overall mean agreement was 9.1/10, with mean 93% of experts voting above 7/10. CONCLUSION: This consensus-based guidance on screening, diagnosis and follow-up of systemic sclerosis primary heart involvement provides a foundation for standard of care and future feasibility studies that are ongoing to support its application in clinical practice

Power-Law Inter-Spike Interval Distributions Infer a Conditional Maximization of Entropy in Cortical Neurons

The brain is considered to use a relatively small amount of energy for its efficient information processing. Under a severe restriction on the energy consumption, the maximization of mutual information (MMI), which is adequate for designing artificial processing machines, may not suit for the brain. The MMI attempts to send information as accurate as possible and this usually requires a sufficient energy supply for establishing clearly discretized communication bands. Here, we derive an alternative hypothesis for neural code from the neuronal activities recorded juxtacellularly in the sensorimotor cortex of behaving rats. Our hypothesis states that in vivo cortical neurons maximize the entropy of neuronal firing under two constraints, one limiting the energy consumption (as assumed previously) and one restricting the uncertainty in output spike sequences at given firing rate. Thus, the conditional maximization of firing-rate entropy (CMFE) solves a tradeoff between the energy cost and noise in neuronal response. In short, the CMFE sends a rich variety of information through broader communication bands (i.e., widely distributed firing rates) at the cost of accuracy. We demonstrate that the CMFE is reflected in the long-tailed, typically power law, distributions of inter-spike intervals obtained for the majority of recorded neurons. In other words, the power-law tails are more consistent with the CMFE rather than the MMI. Thus, we propose the mathematical principle by which cortical neurons may represent information about synaptic input into their output spike trains