ABSTRACT
Objective: Refractory type 1a endoleak after endovascular aneurysm repair (EVAR) can pose a significant challenge to surgeons and interventional radiologists. Continuous sac expansion results in aneurysm rupture and mortality. In such circumstances, an external infrarenal aortic wrap could serve as an essential and alternative solution. Methods: We assessed the application of an infrarenal aortic neck wrap for the treatment of refractory type 1a endoleak in n=6 consecutive patients along with the introduction of a novel assessment technique in order to assure their intraoperative success with no radiation exposure and contrast use. Results: The median sac expansion was 8.5 mm (interquartile range [IQR], 5-20 mm). The median neck diameter and length of the aortic neck were 23 mm (IQR, 18-25 mm) and 21 mm (IQR, 18-25 mm), respectively. The median length of follow-up post wrap is 24 months (IQR, 14-34 months). There was no associated mortality or morbidity and requirement for any further interventions. Conclusion: The study demonstrates that aortic wrapping for the treatment of refractory type 1a endoleak for any given neck diameter and length is safe, effective, and long lasting. The suggested novel intraoperative assessment technique contributes to the safety of the procedure by diminishing the need for intraoperative radiation exposure, contrast, and shorter operative time.
ABSTRACT
OBJECTIVES: The study evaluates the plausibility and applicability of prediction, pattern recognition and modelling of complications post-endovascular aneurysm repair (EVAR) by artificial intelligence for more accurate surveillance in practice. METHODS: A single-centre prospective data collection on (n = 250) EVAR cases with n = 26 preoperative attributes (factors) on endpoint of endoleak (types I-VI), occlusion, migration and mortality over a 13-year period was conducted. In addition to the traditional statistical analysis, data was subjected to machine learning algorithm through artificial neural network. The predictive accuracy (specificity and -1 sensitivity) on each endpoint is presented with percentage and receiver operative curve. The pattern recognition and model classification were conducted using discriminate analysis, decision tree, logistic regression, naive Bayes and support vector machines, and the best fit model was deployed for pattern recognition and modelling. RESULTS: The accuracy of the training, validation and predictive ability of artificial neural network in detection of endoleak type I was 95, 96 and 94%, type II (94, 83, 90 and 82%) and type III was 96, 94 and 96%, respectively. Endpoints are associated with increase in weights through predictive modeling that were not detected through statistical analytics. The overall accuracy of the model was >86%. CONCLUSION: The study highlights the applicability, accuracy and reliability of artificial intelligence in the detection of adverse outcomes post-EVAR for an accurate surveillance stratification.
Subject(s)
Aortic Aneurysm, Abdominal/surgery , Artificial Intelligence , Blood Vessel Prosthesis Implantation/adverse effects , Endovascular Procedures/adverse effects , Pattern Recognition, Automated , Postoperative Complications/diagnosis , Aged , Aged, 80 and over , Aortic Aneurysm, Abdominal/diagnostic imaging , Aortic Aneurysm, Abdominal/mortality , Blood Vessel Prosthesis , Blood Vessel Prosthesis Implantation/instrumentation , Blood Vessel Prosthesis Implantation/mortality , Decision Trees , Endoleak/diagnosis , Endoleak/etiology , Endoleak/mortality , Endovascular Procedures/instrumentation , Endovascular Procedures/mortality , Female , Foreign-Body Migration/diagnosis , Foreign-Body Migration/etiology , Foreign-Body Migration/mortality , Graft Occlusion, Vascular/diagnosis , Graft Occlusion, Vascular/etiology , Graft Occlusion, Vascular/mortality , Humans , Male , Middle Aged , Postoperative Complications/etiology , Postoperative Complications/mortality , Prospective Studies , Risk Assessment , Risk Factors , Support Vector Machine , Time Factors , Treatment OutcomeABSTRACT
Vascular injury initiates a cascade of phenotype-altering molecular events. Transcription factor function in this process, particularly that of negative regulators, is poorly understood. We demonstrate here that the forced expression of the injury-inducible GLI-Krüppel zinc finger protein Yin Yang-1 (YY1) inhibits neointima formation in human, rabbit and rat blood vessels. YY1 inhibits p21(WAF1/Cip1) transcription, prevents assembly of a p21(WAF1/Cip1)-cdk4-cyclin D1 complex, and blocks downstream pRb(Ser249/Thr252) phosphorylation and expression of PCNA and TK-1. Conversely, suppression of endogenous YY1 elevates levels of p21(WAF1/Cip1), PCNA, pRb(Ser249/Thr252) and TK-1, and increases intimal thickening. YY1 binds Sp1 and prevents its occupancy of a distinct element in the p21(WAF1/Cip1) promoter without YY1 itself binding the promoter. Additionally, YY1 induces ubiquitination and proteasome-dependent degradation of p53, decreasing p53 immunoreactivity in the artery wall. These findings define a new role for YY1 as both an inducer of p53 instability in smooth muscle cells, and an indirect repressor of p21(WAF1/Cip1) transcription, p21(WAF1/Cip1)-cdk4-cyclin D1 assembly and intimal thickening.
