We have located links that may give you full text access.
Update of a model to predict outcomes after endovascular aneurysm repair.
Annals of Vascular Surgery 2021 April 8
OBJECTIVES: Risk assessment models must be continuously validated and updated to ensure that predictions remain valid. Here, the Endovascular Aneurysm Repair Risk Assessment Model, developed in 2008, is updated and improved.
METHODS: We used prospectively collected data from Australian patients who underwent elective endovascular aneurysm repair between 2009 and 2013 (n=695). Data were provided by treating surgeons and the National Death Index. Key outcomes were early and mid-term survival, early complications (endoleak, operative, and graft-related) and late complications (endoleak and graft-related). Multinomial logistic regression determined which preoperative variables best predicted each outcome. Area under Receiver Operating Characteristic curve (AUROC), model p-value and internal validation statistics were used to select the best model.
RESULTS: Ten preoperative variables were included in the modelling for 10 key outcomes. The most valid outcomes with AUROC>0.7 were 1- and 3-year survival, 30 and 90-day mortality, early and late endoleak (types I, III and IV) and type II endoleak (with an increase in sac size ≥5mm). The ten preoperative variables that contributed to outcome models were self-reported fitness, American Society of Anesthesiologists physical status score, history of stroke/transient ischaemic attack, age, aneurysm angle, infrarenal neck length, white cell count, respiratory assessment, diabetes and statin therapy. Fitness alone statistically significantly predicted 30 and 90-day deaths better than any other preoperative variable; achieving high AUROCs (0.78 and 0.80), and high odds ratios (12.8 [95% CI: 1.5-110.4] and 18.1 [95% CI: 2.2-149]).
CONCLUSIONS: An updated interactive predictive model of outcomes after endovascular aneurysm repair has been created. Many of the variables used in the 2008 model continued to be significant, however, new variables including fitness and respiratory assessment, improved the model. The new model uses variables routinely collected preoperatively, and hence can better support surgeon-patient discussions prior to operation. Informing patients of potential risks or likely outcomes following elective surgery can assist with preoperative shared decision-making.
METHODS: We used prospectively collected data from Australian patients who underwent elective endovascular aneurysm repair between 2009 and 2013 (n=695). Data were provided by treating surgeons and the National Death Index. Key outcomes were early and mid-term survival, early complications (endoleak, operative, and graft-related) and late complications (endoleak and graft-related). Multinomial logistic regression determined which preoperative variables best predicted each outcome. Area under Receiver Operating Characteristic curve (AUROC), model p-value and internal validation statistics were used to select the best model.
RESULTS: Ten preoperative variables were included in the modelling for 10 key outcomes. The most valid outcomes with AUROC>0.7 were 1- and 3-year survival, 30 and 90-day mortality, early and late endoleak (types I, III and IV) and type II endoleak (with an increase in sac size ≥5mm). The ten preoperative variables that contributed to outcome models were self-reported fitness, American Society of Anesthesiologists physical status score, history of stroke/transient ischaemic attack, age, aneurysm angle, infrarenal neck length, white cell count, respiratory assessment, diabetes and statin therapy. Fitness alone statistically significantly predicted 30 and 90-day deaths better than any other preoperative variable; achieving high AUROCs (0.78 and 0.80), and high odds ratios (12.8 [95% CI: 1.5-110.4] and 18.1 [95% CI: 2.2-149]).
CONCLUSIONS: An updated interactive predictive model of outcomes after endovascular aneurysm repair has been created. Many of the variables used in the 2008 model continued to be significant, however, new variables including fitness and respiratory assessment, improved the model. The new model uses variables routinely collected preoperatively, and hence can better support surgeon-patient discussions prior to operation. Informing patients of potential risks or likely outcomes following elective surgery can assist with preoperative shared decision-making.
Full text links
Trending Papers
A Personalized Approach to the Management of Congestion in Acute Heart Failure.Heart International 2023
Potential Mechanisms of the Protective Effects of the Cardiometabolic Drugs Type-2 Sodium-Glucose Transporter Inhibitors and Glucagon-like Peptide-1 Receptor Agonists in Heart Failure.International Journal of Molecular Sciences 2024 Februrary 21
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app