Measuring Duchenne muscular dystrophy impact: development of a proxy-reported measure derived from PROMIS item banks

Background Person-reported outcomes measurement development for rare diseases has lagged behind that of more common diseases. In studies of caregivers of patients with rare diseases, one relies on proxy report to characterize this disability. It is important to measure the child’s disability accurately and comprehensively because it affects caregiver burden. We aimed to create a condition-specific caregiver proxy-report measure for Duchenne Muscular Dystrophy (DMD) in order to understand the impact of DMD on the caregiver. Drawing on relevant item banks from the Patient-Reported Outcome Measurement Information System (PROMIS), we sought to confirm their reliability and validity in the target sample of DMD caregivers. Methods This web-based study recruited DMD caregivers via Rare Patient Voice, patient-advocacy groups, and word of mouth. Recruitment was stratified by age of the caregiver’s child with DMD, which broadly represents stages of DMD progression: 2–7, 8–12, 13–17, and > 18. Telephone interviews with DMD parent-caregivers pretested possible measures for content validity. The web-based study utilized an algorithm to categorize respondents’ ambulatory status for tailored administration of PROMIS Parent-Proxy items as well as some new items developed based on caregiver interviews. Item response theory analyses were implemented. Results The study sample included 521 DMD caregivers representing equally the four age strata. The proxy-report measure included the following domains: fatigue impact, strength impact, cognitive function, upper extremity function, positive affect, negative affect, sleep-device symptoms, and mobility. The first five domains had strong psychometric characteristics (unidimensionality; acceptable model fit; strong standardized factor loadings; high marginal reliability). Negative Affect, covering anger, anxiety, depressive symptoms, and psychological stress, fit a bifactor model with good model fit, high marginal reliability, and strong factor loadings. The Sleep-device symptoms domain was not unidimensional, and the mobility domain did not have a simple structure due to residual correlations among items at opposite end of the mobility-disability continuum. These two domain scores were retained as clinimetric indices (i.e., uncalibrated scales), to achieve the overall goal of having a content-valid DMD-specific measure across all stages of disease severity. Conclusions The present study derived a DMD-specific proxy-report measure from PROMIS item banks and supplemental items that could potentially be utilized in caregiver research across all stages of the care recipient’s DMD. Future research will focus on assessing the responsiveness and validity of the measure over time and its comparison to DMD patient self-report.

Opportunistic maintenance strategy of a Heave Compensation System for expected performance degradation

In the marine industry, heave compensation systems are applied to marine equipment to compensate for the adverse effects of waves and the hydraulic system is usually used as the power system of heave compensation systems. This article introduces importance theory to the opportunistic maintenance (OM) strategy to provide guidance for the maintenance of heave compensation systems. The working principle of a semi-active heave compensation system and the specific working states of its hydraulic components are also first explained. Opportunistic maintenance is applied to the semi-active heave compensation system. Moreover, the joint integrated importance measure (JIIM) between different components at different moments is analyzed and used as the basis for the selection of components on which to perform PM, with the ultimate goal of delaying the degradation of the expected performance of the system. Finally, compared with conditional marginal reliability importance (CMRI)-based OM, the effectiveness of JIIM-based OM is verified by the Monte Carlo method.

MUPPscore: An R script for expected a posteriori scoring of multidimensional pairwise preference items

In this manual, we present a flexible and freely available tool for obtaining latent trait scores from multi-unidimensional pairwise preference (MUPP) tests: An R script named MUPPscore. The development of the MUPPscore script provides a solution to the issue that is the previously inconvenient estimation of forced choice item pairs. Instead of using the computationally-intensive multidimensional Bayes modal procedure, the MUPPscore script employs the expected a posterior (EAP) scoring procedure, which provides plausible latent trait score estimates and is also consistent with scoring algorithms used in existing software programs intended for single stimulus measures (e.g., GGUM2004, IRTPRO). The MUPPscore script also returns the empirical marginal reliability of EAP theta estimates and outputs a series of files that can be used to easily create and modify three-dimensional surface charts for plotting MUPP item response function (IRF) in Microsoft Excel.

Importance analysis in two kinds of redundant systems: k-out-of-n and consecutive k-out-of-n: F systems

The voting system is a kind of redundant system, and the k-out-of- n system and consecutive k-out-of- n system have been widely used in engineering practice. In this article, the marginal reliability importance and joint reliability importance in k-out-of- n: F systems and consecutive k-out-of- n: F systems are studied for some situations. Then, some properties and relevant remarks of the marginal reliability importance and joint reliability importance in two kinds of system models are analyzed for parameters p, k, and n. Finally, an oil pump transportation system is used to demonstrate the proposed method and illustrate the feasibility and practicality of the model.

Reliability and Importance Measures for Combined m-Consecutive-k-Out-of-n: F and Consecutive-kb-Out-of-n: F Systems with Non-Homogeneous Markov-Dependent Components

A Combined [Formula: see text]-Consecutive-[Formula: see text]-out-of-[Formula: see text] and Consecutive-[Formula: see text]-out-of-[Formula: see text]: F System consists of [Formula: see text] components ordered in a line such that the system fails iff there exist at least [Formula: see text] consecutive failed components, or at least [Formula: see text] nonoverlapping runs of [Formula: see text] consecutive failed components, where [Formula: see text]. This system was been introduced by Mohan et al. [P. Mohan, M. Agrawal and K. Sen, Combined [Formula: see text]-consecutive-[Formula: see text]-out-of-[Formula: see text]: F and consecutive-[Formula: see text]-out-of-[Formula: see text]: F systems, IEEE Trans. Reliab. 58 (2009) 328–337] where they propose an algorithm to evaluate system reliability by using the (GERT) technique, in the independent case. In this paper, we propose a new formula of the reliability of this system for nonhomogeneous Markov-dependent components. For a Combined [Formula: see text]-Consecutive-[Formula: see text]-out-of-[Formula: see text] and Consecutive-[Formula: see text]-out-of-[Formula: see text]: F System with nonhomogeneous Markov-dependent components, we derive closed-form formulas for the marginal reliability importance measure of a single component, and the joint reliability importance measure of two or more than two components using probability generating function (pgf) and conditional pgf methods.

Unrestricted Bridging Resolution

In contrast to identity anaphors, which indicate coreference between a noun phrase and its antecedent, bridging anaphors link to their antecedent(s) via lexico-semantic, frame, or encyclopedic relations. Bridging resolution involves recognizing bridging anaphors and finding links to antecedents. In contrast to most prior work, we tackle both problems. Our work also follows a more wide-ranging definition of bridging than most previous work and does not impose any restrictions on the type of bridging anaphora or relations between anaphor and antecedent. We create a corpus (ISNotes) annotated for information status (IS), bridging being one of the IS subcategories. The annotations reach high reliability for all categories and marginal reliability for the bridging subcategory. We use a two-stage statistical global inference method for bridging resolution. Given all mentions in a document, the first stage, bridging anaphora recognition, recognizes bridging anaphors as a subtask of learning fine-grained IS. We use a cascading collective classification method where (i) collective classification allows us to investigate relations among several mentions and autocorrelation among IS classes and (ii) cascaded classification allows us to tackle class imbalance, important for minority classes such as bridging. We show that our method outperforms current methods both for IS recognition overall as well as for bridging, specifically. The second stage, bridging antecedent selection, finds the antecedents for all predicted bridging anaphors. We investigate the phenomenon of semantically or syntactically related bridging anaphors that share the same antecedent, a phenomenon we call sibling anaphors. We show that taking sibling anaphors into account in a joint inference model improves antecedent selection performance. In addition, we develop semantic and salience features for antecedent selection and suggest a novel method to build the candidate antecedent list for an anaphor, using the discourse scope of the anaphor. Our model outperforms previous work significantly.

A linear m-consecutive-k-out-of-n system with sparse d of non-homogeneous Markov-dependent components

Consider non-homogeneous Markov-dependent components in an m-consecutive- k-out-of- n:F (G) system with sparse [Formula: see text], which consists of [Formula: see text] linearly ordered components. Two failed components are consecutive with sparse [Formula: see text] if and if there are at most [Formula: see text] working components between the two failed components, and the m-consecutive- k-out-of- n:F system with sparse [Formula: see text] fails if and if there exist at least [Formula: see text] non-overlapping runs of [Formula: see text] consecutive failed components with sparse [Formula: see text] for [Formula: see text]. We use conditional probability generating function method to derive uniform closed-form formulas for system reliability, marginal reliability importance measure, and joint reliability importance measure for such the F system and the corresponding G system. We present numerical examples to demonstrate the use of the formulas. Along with the work in this article, we summarize the work on consecutive- k systems of Markov-dependent components in terms of system reliability, marginal reliability importance, and joint reliability importance.

ON CONDITIONAL MARGINAL AND CONDITIONAL JOINT RELIABILITY IMPORTANCE

The reliability importance of one or more components when another component is assumed to be working/non-working is measured by Conditional Marginal Reliability Importance (CMRI) and Conditional Joint Reliability Importance (CJRI) respectively. We consider two systems viz the series-in-parallel and series-parallel. The expressions for CMRI and CJRI are derived for both the systems when the components are independent but not identically distributed. It is shown that the sign of the joint importance of three components and Conditional Joint Importance (CJI) can be determined using Schur-convexity (concavity) of the reliability function. The difference in the reliability functions of two coherent systems with n ≥ 3 statistically independent and with dependent components is derived. It is shown to be measured by their covariance, the JRI and the CJRIs. CMRIs and CJRIs of a phased type electronic system and a bridge structure are worked out.

EFFICIENT COMPUTATION OF NETWORK RELIABILITY IMPORTANCE ON K-TERMINAL RELIABILITY

This paper proposes an algorithm to compute marginal reliability importance for network systems with k-terminal reliability efficiently. Marginal reliability importance is an appropriate quantitative measure on a system component against system reliability and it contributes to design of reliable systems. Computing marginal reliability importance in network systems is time-consuming due to its NP-hardness. This paper extends the algorithm proposed in our last study to deal with k-terminal reliability and incorporates an extended factoring theorem to improve the algorithm. Numerical experiments compare the proposed algorithm with a traditional method to reveal efficiency of the algorithm. The algorithm helps to construct efficient algorithm to reliable network design problems.