Modeling Surgery: A New Way Toward Understanding Earth Climate Variability

A new modeling concept, referred to as Modeling Surgery, has been recently developed at University of Wisconsin-Madison. It is specifically designed to diagnose coupled feedbacks between different climate components as well as climatic teleconnections within a specific component through systematically modifying the coupling configurations and teleconnective pathways. It thus provides a powerful means for identifying the causes and mechanisms of low-frequency variability in the Earth's climate system. In this paper, we will give a short review of our recent progress in this new area.

Risk factors for acute kidney injury following coronary artery bypass graft surgery in a Chinese population and development of a prediction model

BACKGROUND Acute kidney injury(AKI)after coronary artery bypass graft(CABG)surgery is associated with significant morbidity and mortality.This retrospective study aimed to establish a risk score for postoperative AKI in a Chinese population.METHODS A total of 1138 patients undergoing CABG were collected from September 2018 to May 2020 and divided into a derivation and validation cohort.AKI was defined according to the Kidney Disease Improving Global Outcomes(KDIGO)criteria.Multivariable logistic regression analysis was used to determine the independent predictors of AKI,and the predictive ability of the model was determined using a receiver operating characteristic(ROC)curve.RESULTS The incidence of cardiac surgery–associated acute kidney injury(CSA-AKI)was 24.17%,and 0.53%of AKI patients required dialysis(AKI-D).Among the derivation cohort,multivariable logistic regression showed that age≥70 years,body mass index(BMI)≥25 kg/m2,estimated glomerular filtration rate(eGFR)≤60 mL/min per 1.73 m2,ejection fraction(EF)≤45%,use of statins,red blood cell transfusion,use of adrenaline,intra-aortic balloon pump(IABP)implantation,postoperative low cardiac output syndrome(LCOS)and reoperation for bleeding were independent predictors.The predictive model was scored from 0 to32 points with three risk categories.The AKI frequencies were as follows:0-8 points(15.9%),9-17 points(36.5%)and≥18 points(90.4%).The area under of the ROC curve was 0.730(95%CI:0.691-0.768)in the derivation cohort.The predictive index had good discrimination in the validation cohort,with an area under the curve of 0.735(95%CI:0.655-0.815).The model was well calibrated according to the Hosmer-Lemeshow test(P=0.372).CONCLUSION The performance of the prediction model was valid and accurate in predicting KDIGO-AKI after CABG surgery in Chinese patients,and could improve the early prognosis and clinical interventions.

A New Three-Dimensional(3D)Printing Prepress Algorithm for Simulation of Planned Surgery for Congenital Heart Disease

Background:Three-dimensional printing technology may become a key factor in transforming clinical practice and in significant improvement of treatment outcomes.The introduction of this technique into pediatric cardiac surgery will allow us to study features of the anatomy and spatial relations of a defect and to simulate the optimal surgical repair on a printed model in every individual case.Methods:We performed the prospective cohort study which included 29 children with congenital heart defects.The hearts and the great vessels were modeled and printed out.Measurements of the same cardiac areas were taken in the same planes and points at multislice computed tomography images(group 1)and on printed 3D models of the hearts(group 2).Pre-printing treatment of the multislice computed tomography data and 3D model preparation were performed according to a newly developed algorithm.Results:The measurements taken on the 3D-printed cardiac models and the tomographic images did not differ significantly,which allowed us to conclude that the models were highly accurate and informative.The new algorithm greatly simplifies and speeds up the preparation of a 3D model for printing,while maintaining high accuracy and level of detail.Conclusions:The 3D-printed models provide an accurate preoperative assessment of the anatomy of a defect in each case.The new algorithm has several important advantages over other available programs.They enable the development of customized preliminary plans for surgical repair of each specific complex congenital heart disease,predict possible issues,determine the optimal surgical tactics,and significantly improve surgical outcomes.

Cornea modelling

Background:Biomechanics introduces numerous technologies to support clinical practice in ophthalmology,with the goal of improving surgical outcomes and to develop new advanced technologies with minimum impact on clinical training.Unfortunately,a few misconceptions on the way that computational methods should be applied to living tissues contributes to a lack of confidence towards computer-based approaches.Methods:Corneal biomechanics relies on sound theories of mechanics,including concepts of equilibrium,geometrical measurements,and complex material behaviors.The peculiarities of biological tissues require the consideration of multi-physics,typical of the eye environment,and to adopt customized geometrical models constructed on the basis of advanced optical imaging and in-vivo testing.Results:Patient-specific models are able to predict the outcomes of refractive surgery and to exploit the results of in-vivo test to characterize the material properties of the corneal tissue.Conclusions:Corneal biomechanics can become an important support to clinical practice,provided that methods are based on the actual multi-physics and use customized geometrical and mechanical models.