Stent-assisted balloon-induced intimal disruption and relamination in complicated chronic residual type B aortic dissection after frozen elephant trunk treatment.

CASE REPORT: a 77-year-old man presented to our Emergency Department for worsening dyspnea. A chest CT scan showed a type A aortic dissection with a dilatation of the ascending and descending aorta. After evaluating the case with cardiac surgeons, it was decided to perform an aortic arch replacement through the frozen elephant trunk technique. Three months after cardiac surgery, a TC scan showed a residual 58 mm dissecting aneurysm of the descending thoracic aorta and a collapse of the true lumen so we decided to perform an endovascular treatment of the thoracoabdominal aorta according to the STABILISE technique. Due to the impossibility of cannulating the left renal artery (originating from the false lumen), a partial dilation of the dissecting stent was performed at the origin of the renal arteries, maintaining the communication between true and false lumen at the level of the aortic bifurcation. DISCUSSION: the STABILISE technique can be applied safely and effectively even in selected cases of residual chronic aortic dissection, constituting a safe and effective alternative to open thoracoabdominal surgery. CONCLUSIONS: the presence of a proximal artificial neck without proximal tears in the aortic arch can be a great advantage for subsequent endovascular interventions. It is therefore desirable to design a common surgical strategy within an aortic team to achieve a more favorable preoperative anatomy. KEY WORDS: Chronic dissection, Frozen elephant trunk, STABILISE.

Use of hidden Markov capture-recapture models to estimate abundance in the presence of uncertainty: Application to the estimation of prevalence of hybrids in animal populations.

Estimating the relative abundance (prevalence) of different population segments is a key step in addressing fundamental research questions in ecology, evolution, and conservation. The raw percentage of individuals in the sample (naive prevalence) is generally used for this purpose, but it is likely to be subject to two main sources of bias. First, the detectability of individuals is ignored; second, classification errors may occur due to some inherent limits of the diagnostic methods. We developed a hidden Markov (also known as multievent) capture-recapture model to estimate prevalence in free-ranging populations accounting for imperfect detectability and uncertainty in individual's classification. We carried out a simulation study to compare naive and model-based estimates of prevalence and assess the performance of our model under different sampling scenarios. We then illustrate our method with a real-world case study of estimating the prevalence of wolf (Canis lupus) and dog (Canis lupus familiaris) hybrids in a wolf population in northern Italy. We showed that the prevalence of hybrids could be estimated while accounting for both detectability and classification uncertainty. Model-based prevalence consistently had better performance than naive prevalence in the presence of differential detectability and assignment probability and was unbiased for sampling scenarios with high detectability. We also showed that ignoring detectability and uncertainty in the wolf case study would lead to underestimating the prevalence of hybrids. Our results underline the importance of a model-based approach to obtain unbiased estimates of prevalence of different population segments. Our model can be adapted to any taxa, and it can be used to estimate absolute abundance and prevalence in a variety of cases involving imperfect detection and uncertainty in classification of individuals (e.g., sex ratio, proportion of breeders, and prevalence of infected individuals).