Role of Factor VII in Correcting Dilutional Coagulopathy and Reducing Re-operations for Bleeding Following Non-traumatic Major Gastrointestinal and Abdominal Surgery

Objective The objective of this study is to evaluate the effectiveness of rfVIIa in reducing blood product requirements and re-operation for postoperative bleeding after major abdominal surgery. Background Hemorrhage is a significant complication after major gastrointestinal and abdominal surgery. Clinically significant bleeding can lead to shock, transfusion of blood products, and re-operation. Recent reports suggest that activated rfVIIa may be effective in correcting coagulopathy and decreasing the need for re-operation. Methods This study was a retrospective review over a 4-year period of 17 consecutive bleeding postoperative patients who received rfVIIa to control hemorrhage and avoid re-operation. Outcome measures were blood and clotting factor transfusions, deaths, thromboembolic complications, and number of re-operations for bleeding. Results Seventeen patients with postoperative hemorrhage following major abdominal gastrointestinal surgery (nine pancreas, four sarcoma, two gastric, one carcinoid, and one fistula) were treated with rfVIIa. In these 17 patients, rfVIIa was administered for 18 episodes of bleeding (dose 2,400-9,600 mcg, 29.8-100.8 mcg/kg). Transfusion requirement of pRBC and FFP were each significantly less than pre-rfVIIa. Out of the 18 episodes, bleeding was controlled in 17 (94%) without surgery, and only one patient returned to the operating room for hemorrhage. There were no deaths and two thrombotic complications. Coagulopathy was corrected by rfVIIa from 1.37 to 0.96 (p<0.0001). Conclusion Use of rfVIIa in resuscitation for hemorrhage after non-traumatic major abdominal and gastrointestinal surgery can correct dilutional coagulopathy, reducing blood product requirements and need for re-operation

Changing patterns in diagnostic strategies and the treatment of blunt injury to solid abdominal organs

Background: In recent years there has been increasing interest shown in the nonoperative management (NOM) of blunt traumatic injury. The growing use of NOM for blunt abdominal organ injury has been made possible because of the progress made in the quality and availability of the multidetector computed tomography (MDCT) scan and the development of minimally invasive intervention options such as angioembolization. Aim: The purpose of this review is to describe the changes that have been made over the past decades in the management of blunt trauma to the liver, spleen and kidney. Results: The management of blunt abdominal injury has changed considerably. Focused assessment with sonography for trauma (FAST) examination has replaced diagnostic peritoneal lavage as diagnostic modality in the primary survey. MDCT scanning with intravenous contrast is now the gold standard diagnostic modality in hemodynamically stable patients with intra-abdominal fluid detected with FAST. One of the current discussions in the l erature is whether a whole body MDCT survey should be implemented in the primary survey. Conclusions The progress in imaging techniques has contributed to NOM being currently the treatment of choice for hemodynamically stable patients. Angioembolization can be used as an adjunct to NOM and has increased the succe

Hilbert space methods for reduced-rank Gaussian process regression

This paper proposes a novel scheme for reduced-rank Gaussian process regression. The method is based on an approximate series expansion of the covariance function in terms of an eigenfunction expansion of the Laplace operator in a compact subset of Rd. On this approximate eigenbasis, the eigenvalues of the covariance function can be expressed as simple functions of the spectral density of the Gaussian process, which allows the GP inference to be solved under a computational cost scaling as O(nm2) (initial) and O(m3) (hyperparameter learning) with m basis functions and n data points. Furthermore, the basis functions are independent of the parameters of the covariance function, which allows for very fast hyperparameter learning. The approach also allows for rigorous error analysis with Hilbert space theory, and we show that the approximation becomes exact when the size of the compact subset and the number of eigenfunctions go to infinity. We also show that the convergence rate of the truncation error is independent of the input dimensionality provided that the differentiability order of the covariance function increases appropriately, and for the squared exponential covariance function it is always bounded by ∼ 1 / m regardless of the input dimensionality. The expansion generalizes to Hilbert spaces with an inner product which is defined as an integral over a specified input density. The method is compared to previously proposed methods theoretically and through empirical tests with simulated and real data.Peer reviewe