Lateral thoracotomy for epicardial pacemaker placement in patients with congenital heart disease.

OBJECTIVES: Our institution adopted a lateral thoracotomy approach to epicaridal pacemaker implantation with the objective of avoiding epicardial scar tissue and to achieve adequate lead pacing and sensing. We sought to assess the short-term outcomes of this approach. METHODS: A single-centre review was conducted in paediatric patients and adults with congenital heart disease or inherited arrhythmia syndromes who underwent a lateral thoracotomy for epicardial pacemaker placement from August 2010 to January 2016. Patient histories were recorded along with outcomes including complications, lead and generator performance. RESULTS: Twenty-one operations were performed in 20 patients (median age 17 years, range 3 months-49 years), including 19 pacemakers and 2 implantable-cardioverter defibrillators (ICDs). Prior epicardial pacemakers had been placed in 11 (55%) patients, including 3 with multiple pacemakers. Most patients had undergone at least 1 prior cardiac operation, with a mean of 3.2 (range 0-7) prior cardiac operations. Through our lateral thoracotomy approach, 17 of the 19 attempted atrial leads (89%) and 20 of the 20 attempted ventricular leads (100%) were successfully implanted with acceptable pacing thresholds. Complications included 1 (5%) bleeding, 2 (10%) pacemaker pocket revisions and 1 late death at 6 months unrelated to the pacemaker. There were no lead failures at a mean follow-up period of 27.5 months (range of 0.7-56.1 months). CONCLUSIONS: The lateral thoracotomy is a useful approach for epicardial pacemaker implantation in patients with congenital heart disease or inherited arrhythmia syndromes including those with multiple prior operations.

Demographic inferences using short-read genomic data in an approximate Bayesian computation framework: in silico evaluation of power, biases and proof of concept in Atlantic walrus.

Approximate Bayesian computation (ABC) is a powerful tool for model-based inference of demographic histories from large genetic data sets. For most organisms, its implementation has been hampered by the lack of sufficient genetic data. Genotyping-by-sequencing (GBS) provides cheap genome-scale data to fill this gap, but its potential has not fully been exploited. Here, we explored power, precision and biases of a coalescent-based ABC approach where GBS data were modelled with either a population mutation parameter (θ) or a fixed site (FS) approach, allowing single or several segregating sites per locus. With simulated data ranging from 500 to 50 000 loci, a variety of demographic models could be reliably inferred across a range of timescales and migration scenarios. Posterior estimates were informative with 1000 loci for migration and split time in simple population divergence models. In more complex models, posterior distributions were wide and almost reverted to the uninformative prior even with 50 000 loci. ABC parameter estimates, however, were generally more accurate than an alternative composite-likelihood method. Bottleneck scenarios proved particularly difficult, and only recent bottlenecks without recovery could be reliably detected and dated. Notably, minor-allele-frequency filters - usual practice for GBS data - negatively affected nearly all estimates. With this in mind, we used a combination of FS and θ approaches on empirical GBS data generated from the Atlantic walrus (Odobenus rosmarus rosmarus), collectively providing support for a population split before the last glacial maximum followed by asymmetrical migration and a high Arctic bottleneck. Overall, this study evaluates the potential and limitations of GBS data in an ABC-coalescence framework and proposes a best-practice approach.