New Insight in Loss of Gut Barrier during Major Non-Abdominal Surgery

PG - e3954 AB - BACKGROUND: Gut barrier loss has been implicated as a critical event in the occurrence of postoperative complications. We aimed to study the development of gut barrier loss in patients undergoing major non-abdominal surgery. METHODOLOGY/PRINCIPAL FINDINGS: Twenty consecutive children undergoing spinal fusion surgery were included. This kind of surgery is characterized by long operation time, significant blood loss, prolonged systemic hypotension, without directly leading to compromise of the intestines by intestinal manipulation or use of extracorporeal circulation. Blood was collected preoperatively, every two hours during surgery and 2, 4, 15 and 24 hours postoperatively. Gut mucosal barrier was assessed by plasma markers for enterocyte damage (I-FABP, I-BABP) and urinary presence of tight junction protein claudin-3. Intestinal mucosal perfusion was measured by gastric tonometry (P(r)CO2, P(r-a)CO2-gap). Plasma concentration of I-FABP, I-BABP and urinary expression of claudin-3 increased rapidly and significantly after the onset of surgery in most children. Postoperatively, all markers decreased promptly towards baseline values together with normalisation of MAP. Plasma levels of I-FABP, I-BABP were significantly negatively correlated with MAP at (1/2) hour before blood sampling (-0.726 (p<0.001), -0.483 (P<0.001), respectively). Furthermore, circulating I-FABP correlated with gastric mucosal P(r)CO2, P(r-a)CO2-gap measured at the same time points (0.553 (p = 0.040), 0.585 (p = 0.028), respectively). CONCLUSIONS/SIGNIFICANCE: This study shows the development of gut barrier loss in children undergoing major non-abdominal surgery, which is related to preceding hypotension and mesenterial hypoperfusion. These data shed new light on the potential role of peroperative circulatory perturbation and intestinal barrier los

Valuation of swing contracts by least-squares Monte Carlo simulation

Summary Natural gas and electricity are commonly traded through swing contracts that enable the buyer to exploit changes in market price or market demand by varying the quantity they receive from the producer (seller). The producer is assured of selling a minimum quantity at a fixed price, but must be able to meet the variable demand from the buyer. The flexibility of such contracts enables both parties to mitigate the risks and exploit the opportunities that arise from uncertainty in production, demand, price, and so on. But how valuable are they? Traditional net present value (NPV), based on expected values, cannot value this flexibility, and the traditional options/valuation techniques could not model the complexity of the terms of such contracts. Taking gas contracts as an example, this paper seeks to (a) raise awareness of how flexibility creates value for both parties and (b) show how least-squares Monte Carlo (LSM) simulation can be used to quantify its value in dollar terms, from the perspective of both producer and buyer. Because the value of flexibility arises from the ability it gives to respond to fluctuations (e.g., in commodity prices), a useful model of swing contracts needs to reflect the nature of these fluctuations.Bart J.A. Willigers, Steve Begg & Reidar Bratvol

Appraising unconventional resources: how many wells to drill and where to place them?

Appraisal programs undertaken by exploration and production (E&P) companies are designed to resolve subsurface uncertainties that contribute to uncertainty in the economic potential of undeveloped fields. Value-of-information (VOI) assessments allow E&P players to quantify the economic value of their proposed appraisal programs before carrying them out. This study proposes a VOI methodology that is tuned to the nature of the subsurface uncertainties in unconventional plays and is capable of assessing a wide range of appraisal strategies (defined as the number and configuration of wells). It addresses two main problems. The first is how to characterize the uncertainty (in a play) that an appraisal program is intended to reduce or resolve. The second is how to cast that characterization of the uncertainty in a VOI context so that the merits of various appraisal programs can be evaluated. This paper characterizes the subsurface uncertainty that arises because of inadequate sampling of natural geologic variability. In this work, three quantities are assumed to be uncertain: the mean and standard deviation (SD) (variability) of the expected ultimate recovery (EUR) of the population of wells to be drilled, should development go ahead, and the range of the variogram that describes the spatial correlation of EUR as a function of the distance between wells. The optimal appraisal program would presumably depend on the true values of these quantities. The methodology is illustrated by application to a typical unconventional play. The VOI of an appraisal program can be optimized in terms of the number of the appraisal wells to be drilled and the placement of those wells. This VOI increases as the placement of the set of wells is changed from being clustered in the central part of the appraised area to approaching uniform distribution across the area. To obtain the optimal well placement, the incremental learning from changing the well locations should be balanced against the incremental costs that are required to increase the spacing of the appraisal wells. The study results demonstrate how the VOI of each incremental appraisal well decreases with the number of appraisal wells and how an optimal number of appraisal wells can be determined.Bart J.A. Willigers, Steve Begg, and Reidar Bratvol

Combining geostatistics with Bayesian updating to continually optimize drilling strategy in shale gas plays

We present a new methodology for improving the economic returns of shale gas plays. The development of an economically efficient drilling programme in such plays is a challenging task, requiring a large number of wells. Even after a relatively large number of wells have been drilled, the average well production and the variation of well performance (economics) remains highly uncertain. The ability to delineate a shale play with the fewest number of wells and to focus drilling in the most productive areas is an important driver of commercial success. The importance of probabilistic modelling in managing uncertainty in shale gas plays has been explicitly emphasised in a number of studies. The objective of this study is to develop a practical valuation methodology that addresses these complexities and is dynamic, in the sense that the optimal drilling strategy can be continually updated as we learn the outcome of each well drilled. Maximizing the returns from a shale gas play is essentially a problem of choosing well locations and numbers to optimize production volumes & rates. Drilling policies have to take account of a large number of already-drilled locations, possible new drilling locations, spatial dependencies between performance at those different (possible) well locations and the extent of uncertainty as to whether or not a well will be economic. These factors cause typical valuation methodologies to be impractical due to the "curse of dimensionality??. In this study an unconventional play is divided into cells. In each cell a fixed number of wells can be drilled. The chance of success (of a well having an NPV greater than zero) in any given cell is itself considered to be an uncertain variable. An initial probability distribution for the chance of success of each cell is derived from analogous plays plus any available information about the specific play. The methodology proceeds as follows. First, as each new well (or group of new wells) is drilled, the outcome is used in combination with the prior probability distribution (using Bayes Theorem) to create an updated probability distribution for the chance of success of the relevant grid cell. Thus, our initial estimate can be continuously updated as we get more and more actual outcomes. Second, the influence of the new chance of success on the surrounding cells, due to spatial correlation, is updated using indicator kriging, a geostatistical technique. The methodology proposed in this study informs the development of drilling policies for shale gas opportunities by using a probabilistic model that accounts for the uncertainty in the chance of success and its spatial dependency. The use of cells to represent a set of wells simplifies the analysis and greatly reduces the computing requirements. The methodology has been applied to a well set from the Barnett Shale, Texas, United States of America.B.J.A. Willigers, S. Begg, R. B. Bratvol

Personalization of CM Injection Protocols in Coronary Computed Tomographic Angiography (People CT Trial)

Aim. To evaluate the performance of three contrast media (CM) injection protocols for cardiac computed tomography angiography (CCTA) based on body weight (BW), lean BW (LBW), and cardiac output (CO). Materials and methods. A total of 327 consecutive patients referred for CCTA were randomized into one of the three CM injection protocols, where CM injection was based on either BW (112 patients), LBW (108 patients), or CO (107 patients). LBW and CO were calculated via formulas. All scans were ECG-gated and performed on a third-generation dual-source CT with 70–120 kV (automated tube voltage selection) and 100 kVqual.ref/330 mAsqual.ref. CM injection protocols were also adapted to scan time and tube voltage. The primary outcome was the proportion of patients with optimal intravascular attenuation (325–500 HU). Secondary outcomes were mean and standard deviation of intravascular attenuation values (HU), contrast-to-noise ratio (CNR), and subjective image quality with a 4-point Likert scale (1 = poor/2 = sufficient/3 = good/4 = excellent). The t-test for independent samples was used for pairwise comparisons between groups, and a chi-square test (χ2) was used to compare categorical variables between groups. All p values were 2-sided, and a p<0.05 was considered statistically significant. Results. Mean overall HU and CNR were 423 ± 60HU/14 ± 3 (BW), 404 ± 62HU/14 ± 3 (LBW), and 413 ± 63HU/14 ± 3 (CO) with a significant difference between groups BW and LBW (p=0.024). The proportion of patients with optimal intravascular attenuation (325–500 HU) was 83.9%, 84.3%, and 86.9% for groups BW, LBW, and CO, respectively, and between-group differences were small and nonsignificant. Mean CNR was diagnostic (≥10) in all groups. The proportion of scans with good-excellent image quality was 94.6%, 86.1%, and 90.7% in the BW, LBW, and CO groups, respectively. The difference between proportions was significant between the BW and LBW groups. Conclusion. Personalization of CM injection protocols based on BW, LBW, and CO, and scan time and tube voltage in CCTA resulted in low variation between patients in terms of intravascular attenuation and a high proportion of scans with an optimal intravascular attenuation. The results suggest that personalized CM injection protocols based on LBW or CO have no additional benefit when compared with CM injection protocols based on BW