A novel nomogram to predict the risk of anastomotic leakage in patients after oesophagectomy

Background: Anastomotic leakage is a dangerous postoperative complication of oesophageal surgery. The present study aimed to develop a simple and practical scoring system to predict the risk of anastomotic leakage after oesophageal resection. Methods: A consecutive series of 330 patients who underwent oesophageal cancer surgery from January 2016 to January 2018 at the Shanghai Chest Hospital were included to develop a prediction model. Anastomotic leakage was evaluated using oesophagography, computed tomography, or flexible endoscopy. Least absolute shrinkage and selection operator regression based on a generalized linear model was used to select variables for the anastomotic leakage risk model while avoiding overfitting. Multivariable logistic regression analysis was applied to build forest plots and a prediction model. The concordance index or the area under the curve was used to judge the discrimination, and calibration plots verified the consistency. Internal validation of the model was conducted, and the clinical usefulness and threshold screening of the model were evaluated by decision curve analysis. Results: The factors included in the predictive nomogram included Sex, diabetes history, anastomotic type, reconstruction route, smoking history, CRP level and presence of cardiac arrhythmia. The model displayed a discrimination performance with a concordance index of 0.690 (95% confidence interval: 0.620-0.760) and good calibration. A concordance index value of 0.664 was maintained during the internal validation. The calibration curve showed good agreement between the actual observations and the predicted results. Conclusion: The present prediction model, which requires only seven variables and includes Sex, diabetes history, anastomotic type, reconstruction route, smoking history, CRP level and presence of cardiac arrhythmia, may be useful for predicting anastomotic leakage in patients after oesophagectomy.

Higher-Ranked Annotation Polymorphic Dependency Analysis

The precision of a static analysis can be improved by increasing the context-sensitivity of the analysis. In a type-based formulation of static analysis for functional languages this can be achieved by, e.g., introducing let-polyvariance or subtyping. In this paper we go one step further by defining a higher-ranked polyvariant type system so that even properties of lambda-bound identifiers can be generalized over. We do this for dependency analysis, a generic analysis that can be instantiated to a range of different analyses that in this way all can profit.We prove that our analysis is sound with respect to a call-by-name semantics and that it satisfies a so-called noninterference property. We provide a type reconstruction algorithm that we have proven to be terminating, and sound and complete with respect to its declarative specification. Our principled description can serve as a blueprint for making other analyses higher-ranked.

Hydrostatic equilibrium preservation in MHD numerical simulation with stratified atmospheres

Context. Many astrophysical processes involving plasma flows are produced in the context of a gravitationally stratified atmosphere in hydrostatic equilibrium, in which strong gradients can exist with gas properties that vary in small regions by several orders of magnitude. The standard Godunov-type schemes with polynomial reconstruction used to numerically solve these problems fail to preserve the hydrostatic equilibrium owing to the appearance of spurious fluxes generated by the numerical unbalance between gravitational forces and pressure gradients. Aims. The aim of this work is to present local hydrostatic reconstruction techniques that can be implemented in existing codes with Godunov-type methods to obtain well-balanced schemes that numerically satisfy the hydrostatic equilibrium for various conditions. Methods. The proposed numerical scheme is based on the Godunov method with second order MUSCL-type reconstruction, as is extensively used in astrophysical applications. The difference between the scheme and the standard formulations is only given by calculating the pressure and density Riemann states on each intercell face and by computing the gravitational source term on each cell. Results. The local hydrostatic reconstruction scheme is implemented in the FLASH code to verify the well-balanced property for hydrostatic equilibrium with constant or linearly variable temperature and constant or variable gravity. In addition, the behavior of the scheme for hydrostatic equilibrium with arbitrary temperature distributions is also analyzed together with the ability to propagate low-amplitude waves and to capture shock waves. Conclusions. The scheme is demonstrated to be robust and relatively simple to implement in existing codes. This approach produces good results in hydrostatic equilibrium preservation, satisfying the well-balanced property for the preset conditions and strongly reducing the spurious fluxes for extreme configurations.

Error estimates for higher-order finite volume schemes for convection–diffusion problems

It is still an open problem to provea priorierror estimates for finite volume schemes of higher order MUSCL type, including limiters, on unstructured meshes, which show some improvement compared to first order schemes. In this paper we use these higher order schemes for the discretization of convection dominated elliptic problems in a convex bounded domainΩin ℝ2and we can prove such kind of ana priorierror estimate. In the part of the estimate, which refers to the discretization of the convective term, we gainh1/2. Although the original problem is linear, the numerical problem becomes nonlinear, due to MUSCL type reconstruction/limiter technique.