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Background: Peripheral Nerve Stimulation (PNS) is an established therapy for chronic neuropathic pain of peripheral origin, typically following nerve injury. However, there is a paucity of Randomized Controlled Trials (RCTs) demonstrating the therapeutic benefits of PNS. The goals of the current study (COMFORT Study) are to document the safety and efficacy of the Nalu Neurostimulation in a PNS RCT, compared to conventional medical management (CMM). Methods/Design: This is a prospective, multicenter, RCT evaluating the treatment of neuropathic pain with PNS therapy. One of the following four regions will be targeted for treatment: low back, shoulder, knee or foot/ankle. Consented subjects will undergo a baseline evaluation, after which they are randomized 2:1 (PNS+CMM arm to CMM arm). Subjects randomized to PNS+CMM arm will undergo a trial implant period using best clinical practices. Subjects who pass the trial phase, by showing a ≥ 50% reduction in pain relative to baseline, will receive the permanent implant. All subjects receiving a permanent implant will be followed for a total of 36 months. At the 3-month primary end point, subjects in CMM arm will be given the option to crossover into PNS+CMM arm, beginning with a trial implant. The study duration is expected to be 5.5 years from first enrollment to last follow-up of last subject and subsequent study closure. Adverse events will be captured throughout the study. Discussion: The COMFORT study, described here, has the potential to demonstrate the efficacy and safety of the Nalu Neurostimulation System in the treatment of peripheral neuropathy. Results of this study will be the first Level-I evidence, out to 36 months, validating the use of this PNS system in the treatment of chronic pain. This study is designed to enroll the largest cohort, to date, of subjects comparing PNS+CMM vs CMM alone. Plain Language Summary: Peripheral nerve stimulation (PNS) has been used for decades to treat neuropathic pain of peripheral origin. This therapy typically involves the placement small (~1 mm diameter) cylindrical electrodes (leads) near the nerve(s) in question, which is then followed by the delivery mild electrical pulses to the target, thereby blocking the pain signal from reaching the central nervous system. Despite the clinical success of this approach, there are few randomized controlled trials (RCTs) demonstrating PNS efficacy in the treatment of peripheral neuralgia/neuropathy. This may be, in large part, due to a paucity of PNS devices that are small enough to deliver this therapy at multiple locations in the extremities and the torso. For example, most implantable pulse generators (IPGs) range in size from 14 to 40 cm3 in volume. The purpose of this RCT is to demonstrate the safety and efficacy of an externally powered micro-IPG (< 1.5 cm3 in volume), in the delivery of PNS to treat peripheral neuropathic pain. Active Arm subjects will receive therapy with the micro-IPG and continue to use conventional medical management (CMM); Control Arm subjects will be treated with CMM only. The primary endpoint is the responder rate at 3-months, in both arms, defined as the percentage of subjects with ≥ 50% pain reduction from baseline following implantation of the micro-IPG. Control Arm subjects will be given the option to crossover to the Active Arm at 3-months. Study subjects in both arms are followed out to 36 months. [ABSTRACT FROM AUTHOR]

Many decisions must be made before relevant uncertainties are revealed; hence robustness approaches to decision making are often considered. There are two major approaches to robustness in the literature: (i) maximizing the value of the worst outcome and (ii) minimizing the maximum ex post regret of the decision. While the first approach seeks the best worst‐case outcome, it may result in substantial opportunity losses relative to the ex post optimal decision; this is particularly critical in new product design decisions as it leaves the leading firm exposed to a late entrant who designs its products after uncertainties are resolved. The second approach seeks to minimize these ex post opportunity losses, but it may expose the decision maker to greater downside risk, that is, lower outcome in the worst case. Most studies have examined one of these approaches in isolation; in contrast, in this study, we explore the trade‐offs between protecting upside regret and downside risk with a focus on a product line design (PLD) problem, which relies greatly on conjoint analysis data. The PLD problem may suffer from significant uncertainty in the partworth utilities which define the attribute‐level consumer preferences on a product for different population segments. Our numerical experiments, based on a real conjoint data set, show that neither robustness approaches dominates the other and hence our proposed approach uses both. We construct a Min‐Value vs. Max‐Relative‐Regret efficient frontier to narrow down the PLD choice and propose a metric to quantify the trade‐offs and finalize the selection. [ABSTRACT FROM AUTHOR]

Agribusiness firms, with an eye toward increasing population and evolving weather patterns, are investing heavily into developing new varieties of staple crops that can provide higher yields and are robust to weather fluctuations. In this paper, we describe a multiyear effort at Dow Agrosciences (now Corteva) to manage its seed corn portfolio, which includes several hundred seeds and is valued at more than $1 billion. The effort had two mutually interacting parts: (1) developing a decision-analytic theory to estimate the production yield distributions for new seed varieties from discrete quantile judgments provided by plant biology experts and (2) developing an optimization protocol to determine Dow's annual production plan for the seed portfolio with the flexibility of backup production in South America, under production yield uncertainty. The first part, owned by the research and development (R&D) function, provides yield probability distributions as inputs to the optimization protocol of the second part, which the production function owns. The results of the optimization problem, which include information about the attractiveness of specific future varieties, are returned to R&D. Both parts incorporate contextual details specific to this industry. In this paper, we show the optimality of linear policies for both problems. Additionally, the linear policies have many attractive structural properties that continue to hold for the more complex instances of the problems. A major strength of the theory we developed is that it is implementable in a transparent fashion, providing managers with a user-friendly, real-time decision support tool. The implementation of the theory developed has led to significant monetary and managerial benefits at Dow. [ABSTRACT FROM AUTHOR]

In this paper, Saurabh Bansal and Genaro J. Gutierrez develop a data-driven approach to aggregate point forecasts provided by multiple experts into probability distributions while accounting for expert heterogeneity. They consider the commonly encountered business problem of estimating probability distributions when historical data for the underlying uncertainty are not available or relevant. In such situations, firms typically ask a panel of experts to provide their forecasts. The authors develop a new approach to use the experts' prior judgments to characterize their biases and the consistency of their judgments and use this information to aggregate their forward-looking judgments to obtain probability distributions. This approach quantifies the heterogeneity in expert judgments and incorporates this information into the aggregation protocol. It also establishes that bias and consistency in expert judgments are complements and not substitutes, and therefore, choosing an expert with less bias is not necessarily better than choosing an expert with a stronger bias. In this paper, we develop a new characterization of multiple-point forecasts provided by experts and use it in an optimization framework to deduce actionable signals, including the mean, standard deviation, or a combination of the two for underlying probability distributions. This framework consists of three steps: (1) calibrate experts' point forecasts using historical data to determine which quantile they provide, on average, when asked for forecasts, (2) quantify the precision in the experts' forecasts around their average quantile, and (3) use this calibration information in an optimization framework to deduce the signals of interest. We also show that precision and accuracy in expert judgments are complementary in terms of their informativeness. We also discuss implementation of the development and the realized benefits at a large government project in the agribusiness domain. [ABSTRACT FROM AUTHOR]

In this paper, we address the flowpath design issue of automated guided vehicle systems (AGVSs). In particular we concentrate on the design of unidirectional flowpaths (i.e. vehicles are restricted to travel only in one direction along a given segment of the flowpath). We have developed five different heuristics for the design of unidirectional AGVSs. We have also developed simulated annealing algorithms for the above problem. Our extensive computational results indicate that a composite heuristic (i.e. one that combines the most successful of our five heuristics) yields solutions of comparable quality in a fraction of the time required by simulated annealing. For large-size flowpath design problems, we advocate the usage of composite heuristics over simulated annealing, and in particular for the cases in which inaccurate estimates for the input data in our design problem exist. [ABSTRACT FROM AUTHOR]

This case presentation demonstrates radiographic evidence of lesions created following cooled radiofrequency (cRF) neurotomy of the knee. A 67-year-old man presented with chronic left knee osteoarthritis, pain, and disability. After a failed trial of conservative treatments, the patient underwent diagnostic genicular nerve blocks and subsequent cRF neurotomy of the left knee. Shortly after cRF, magnetic resonance imaging (MRI) of the left knee was performed. On MRI, lesions created by cRF ablation were identified. The images presented in this case offer a visual explanation for the success of cRF in the treatment of knee osteoarthritis.Level Of Evidence: V. [ABSTRACT FROM AUTHOR]

The article discusses the development of an approach to non-monetary benefits to conclude the mean and standard deviation of probability distribution. Information about the application of expert deduce for quantiles, is highlighted. Also emphasized is the extended set of technical details of the approach.

We analyze the dynamic strategic interactions between a manufacturer and a retailer in a decentralized distribution channel used to launch an innovative durable product (IDP). The underlying retail demand for the IDP is influenced by word-of-mouth from past adopters and follows a Bass-type diffusion process. The word-of-mouth influence creates a trade-off between immediate and future sales and profits, resulting in a multi-period dynamic supply chain coordination problem. Our analysis shows that while in some environments, the manufacturer is better off with a far-sighted retailer, there are also environments in which the manufacturer is better off with a myopic retailer. We characterize equilibrium dynamic pricing strategies and the resulting sales and profit trajectories. We demonstrate that revenue-sharing contracts can coordinate the IDP's supply chain with both far-sighted and myopic retailers throughout the entire planning horizon and arbitrarily allocate the channel profit. [ABSTRACT FROM AUTHOR]

This paper establishes a critically important positive role for operations management practices and financial hedging. We show that operations management decisions and financial hedging are intertwined, and we advance a framework that can identify their combined effects on investors' wealth. We show that: (a) firms (publicly traded corporations) will optimally hold adequate riskless working capital (e.g., cash) to minimize the cost of obtaining non-financial inputs, and the magnitude of this cash holding depends on operating details, and (b) operations management and financial hedging can lower firms' cash requirements, and boost productivity, defined as the wealth created in the firm per dollar of invested capital. Productivity-enhancing practices-by 'freeing up' some of the firm's cash-can maximize the investors' wealth. We show that these results obtain because firms' contracts with many of the providers of non-financial inputs are not traded, and because investors can invest not just in public corporations but also in businesses 'outside the markets' (e.g., proprietorships, partnerships, and private equity). [ABSTRACT FROM AUTHOR]