Population-based analysis of 4113 patients with acute cholecystitis: defining the optimal time-point for laparoscopic cholecystectomy

Objective: To compare clinical outcomes after laparoscopic cholecystectomy (LC) for acute cholecystitis performed at various time-points after hospital admission. Background: Symptomatic gallstones represent an important public health problem with LC the treatment of choice. LC is increasingly offered for acute cholecystitis, however, the optimal time-point for LC in this setting remains a matter of debate. Methods: Analysis was based on the prospective database of the Swiss Association of Laparoscopic and Thoracoscopic Surgery and included patients undergoing emergency LC for acute cholecystitis between 1995 and 2006, grouped according to the time-points of LC since hospital admission (admission day (d0), d1, d2, d3, d4/5, d ≥6). Linear and generalized linear regression models assessed the effect of timing of LC on intra- or postoperative complications, conversion and reoperation rates and length of postoperative hospital stay. Results: Of 4113 patients, 52.8% were female, median age was 59.8 years. Delaying LC resulted in significantly higher conversion rates (from 11.9% at d0 to 27.9% at d ≥6 days after admission, P < 0.001), surgical postoperative complications (5.7% to 13%, P < 0.001) and re-operation rates (0.9% to 3%, P = 0.007), with a significantly longer postoperative hospital stay (P < 0.001). Conclusions: Delaying LC for acute cholecystitis has no advantages, resulting in significantly increased conversion/re-operation rate, postoperative complications and longer postoperative hospital stay. This investigation—one of the largest in the literature—provides compelling evidence that acute cholecystitis merits surgery within 48 hours of hospital admission if impact on the patient and health care system is to be minimized.

Optimal Scheduling of Work-Content-Constrained Projects

The execution of a project requires resources that are generally scarce. Classical approaches to resource allocation assume that the usage of these resources by an individual project activity is constant during the execution of that activity; in practice, however, the project manager may vary resource usage over time within prescribed bounds. This variation gives rise to the project scheduling problem which consists in allocating the scarce resources to the project activities over time such that the project duration is minimized, the total number of resource units allocated equals the prescribed work content of each activity, and various work-content-related constraints are met. We formulate this problem for the first time as a mixed-integer linear program. Our computational results for a standard test set from the literature indicate that this model outperforms the state-of-the-art solution methods for this problem.

Dilution of non-reactive tracers in variably saturated sandy structures

Based on a dye tracer experiment in a sand tank we addressed the problem of local dispersion of conservative tracers in the unsaturated zone. The sand bedding was designed to have a defined spatial heterogeneity with a strong anisotropy. We estimated the parameters that characterize the local dispersion and dilution from concentration maps of a high spatial and temporal resolution obtained by image analysis. The plume spreading and mixing behavior was quantified on the basis of the coefficient of variation of the concentration and of the dilution index. The heterogeneous structure modified the flow pattern depending on water saturation. The shape of the tracer plumes revealed the structural signature of the sand bedding at low saturation only. In this case pronounced preferential flow was observed. At higher flow rates the structure remained hidden by a spatially almost homogeneous behavior of the plumes. In this context, we mainly discuss the mechanism of re-distributing a finite mass of inert solutes over a large volume, due to macro- and micro-heterogeneities of the structure. (C) 2001 Elsevier Science Ltd. AU rights reserved.

Numerical solution of optimal control problems with constant control delays

We investigate a class of optimal control problems that exhibit constant exogenously given delays in the control in the equation of motion of the differential states. Therefore, we formulate an exemplary optimal control problem with one stock and one control variable and review some analytic properties of an optimal solution. However, analytical considerations are quite limited in case of delayed optimal control problems. In order to overcome these limits, we reformulate the problem and apply direct numerical methods to calculate approximate solutions that give a better understanding of this class of optimization problems. In particular, we present two possibilities to reformulate the delayed optimal control problem into an instantaneous optimal control problem and show how these can be solved numerically with a stateof- the-art direct method by applying Bock’s direct multiple shooting algorithm. We further demonstrate the strength of our approach by two economic examples.

Twenty questions with noise: Bayes optimal policies for entropy loss

We consider the problem of twenty questions with noisy answers, in which we seek to find a target by repeatedly choosing a set, asking an oracle whether the target lies in this set, and obtaining an answer corrupted by noise. Starting with a prior distribution on the target's location, we seek to minimize the expected entropy of the posterior distribution. We formulate this problem as a dynamic program and show that any policy optimizing the one-step expected reduction in entropy is also optimal over the full horizon. Two such Bayes optimal policies are presented: one generalizes the probabilistic bisection policy due to Horstein and the other asks a deterministic set of questions. We study the structural properties of the latter, and illustrate its use in a computer vision application.

Benchmark problems for reactive transport modeling of the generation and attenuation of acid rock drainage

Acid rock drainage (ARD) is a problem of international relevance with substantial environmental and economic implications. Reactive transport modeling has proven a powerful tool for the process-based assessment of metal release and attenuation at ARD sites. Although a variety of models has been used to investigate ARD, a systematic model intercomparison has not been conducted to date. This contribution presents such a model intercomparison involving three synthetic benchmark problems designed to evaluate model results for the most relevant processes at ARD sites. The first benchmark (ARD-B1) focuses on the oxidation of sulfide minerals in an unsaturated tailing impoundment, affected by the ingress of atmospheric oxygen. ARD-B2 extends the first problem to include pH buffering by primary mineral dissolution and secondary mineral precipitation. The third problem (ARD-B3) in addition considers the kinetic and pH-dependent dissolution of silicate minerals under low pH conditions. The set of benchmarks was solved by four reactive transport codes, namely CrunchFlow, Flotran, HP1, and MIN3P. The results comparison focused on spatial profiles of dissolved concentrations, pH and pE, pore gas composition, and mineral assemblages. In addition, results of transient profiles for selected elements and cumulative mass loadings were considered in the intercomparison. Despite substantial differences in model formulations, very good agreement was obtained between the various codes. Residual deviations between the results are analyzed and discussed in terms of their implications for capturing system evolution and long-term mass loading predictions.

The inverse problem for Schwinger pair production

The production of electron–positron pairs in time-dependent electric fields (Schwinger mechanism) depends non-linearly on the applied field profile. Accordingly, the resulting momentum spectrum is extremely sensitive to small variations of the field parameters. Owing to this non-linear dependence it is so far unpredictable how to choose a field configuration such that a predetermined momentum distribution is generated. We show that quantum kinetic theory along with optimal control theory can be used to approximately solve this inverse problem for Schwinger pair production. We exemplify this by studying the superposition of a small number of harmonic components resulting in predetermined signatures in the asymptotic momentum spectrum. In the long run, our results could facilitate the observation of this yet unobserved pair production mechanism in quantum electrodynamics by providing suggestions for tailored field configurations.

Biomarker-guided personalised emergency medicine for all - hope for another hype?

Polymorbid patients, diverse diagnostic and therapeutic options, more complex hospital structures, financial incentives, benchmarking, as well as perceptional and societal changes put pressure on medical doctors, specifically if medical errors surface. This is particularly true for the emergency department setting, where patients face delayed or erroneous initial diagnostic or therapeutic measures and costly hospital stays due to sub-optimal triage. A "biomarker" is any laboratory tool with the potential better to detect and characterise diseases, to simplify complex clinical algorithms and to improve clinical problem solving in routine care. They must be embedded in clinical algorithms to complement and not replace basic medical skills. Unselected ordering of laboratory tests and shortcomings in test performance and interpretation contribute to diagnostic errors. Test results may be ambiguous with false positive or false negative results and generate unnecessary harm and costs. Laboratory tests should only be ordered, if results have clinical consequences. In studies, we must move beyond the observational reporting and meta-analysing of diagnostic accuracies for biomarkers. Instead, specific cut-off ranges should be proposed and intervention studies conducted to prove outcome relevant impacts on patient care. The focus of this review is to exemplify the appropriate use of selected laboratory tests in the emergency setting for which randomised-controlled intervention studies have proven clinical benefit. Herein, we focus on initial patient triage and allocation of treatment opportunities in patients with cardiorespiratory diseases in the emergency department. The following five biomarkers will be discussed: proadrenomedullin for prognostic triage assessment and site-of-care decisions, cardiac troponin for acute myocardial infarction, natriuretic peptides for acute heart failure, D-dimers for venous thromboembolism, C-reactive protein as a marker of inflammation, and procalcitonin for antibiotic stewardship in infections of the respiratory tract and sepsis. For these markers we provide an overview on physiopathology, historical evolution of evidence, strengths and limitations for a rational implementation into clinical algorithms. We critically discuss results from key intervention trials that led to their use in clinical routine and potential future indications. The rational for the use of all these biomarkers, first, tackle diagnostic ambiguity and consecutive defensive medicine, second, delayed and sub-optimal therapeutic decisions, and third, prognostic uncertainty with misguided triage and site-of-care decisions all contributing to the waste of our limited health care resources. A multifaceted approach for a more targeted management of medical patients from emergency admission to discharge including biomarkers, will translate into better resource use, shorter length of hospital stay, reduced overall costs, improved patients satisfaction and outcomes in terms of mortality and re-hospitalisation. Hopefully, the concepts outlined in this review will help the reader to improve their diagnostic skills and become more parsimonious laboratory test requesters.

Differentiating the Multipoint Expected Improvement for Optimal Batch Design

This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.