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Assessing the validity of a psychometric test is fundamental to ensure a reliable interpretation of its outcomes. Few attempts have been made recently to complement classical approaches (e.g., factor models) with a novel technique based on network analysis. The objective of the current study is to carry out a network-based validation of the Eating Disorder Inventory 3 (EDI-3), a questionnaire designed for the assessment of eating disorders. Exploiting a reliable, open source sample of 1206 patients diagnosed with an eating disorder, we set up a robust validation process encompassing detection and handling of redundant EDI-3 items, estimation of the cross-sample psychometric network, resampling bootstrap procedure and computation of the median network of the replica samples. We then employed a community detection algorithm to identify the topological clusters, evaluated their coherence with the EDI-3 subscales and replicated the full validation analysis on the subpopulations corresponding to patients diagnosed with either anorexia nervosa or bulimia nervosa. Results of the network-based analysis, and particularly the topological community structures, provided support for almost all the composite scores of the EDI-3 and for 2 single subscales: Bulimia and Maturity Fear. A moderate instability of some dimensions led to the identification of a few multidimensional items that should be better located in the intersection of multiple psychological scales. We also found that, besides symptoms typically attributed to eating disorders, such as drive for thinness, also non-specific symptoms like low self-esteem and interoceptive deficits play a central role in both the cross-sample and the diagnosis-specific networks. Our work adds insights into the complex and multidimensional structure of EDI-3 by providing support to its network-based validity on both mixed and diagnosis-specific samples. Moreover, we replicated previous results that reinforce the transdiagnostic theory of eating disorders., (© 2023. The Author(s).)

Background: Network science represents a powerful and increasingly promising method for studying complex real-world problems. In the last decade, it has been applied to psychometric data in the attempt to explain psychopathologies as complex systems of causally interconnected symptoms. One category of mental disorders, relevant for their severity, incidence and multifaceted structure, is that of eating disorders (EDs), serious disturbances that negatively affect a person's eating behavior., Aims: We aimed to review the corpus of psychometric network analysis methods by scrutinizing a large sample of network-based studies that exploit psychometric data related to EDs. A particular focus is given to the description of the methodologies for network estimation, network description and network stability analysis providing also a review of the statistical software packages currently used to carry out each phase of the network estimation and analysis workflow. Moreover, we try to highlight aspects with potential clinical impact such as core symptoms, influences of external factors, comorbidities, and related changes in network structure and connectivity across both time and subpopulations., Methods: A systematic search was conducted (February 2022) on three different literature databases to identify 57 relevant research articles. The exclusion criteria comprehended studies not based on psychometric data, studies not using network analysis, studies with different aims or not focused on ED, and review articles., Results: Almost all the selected 57 papers employed the same analytical procedures implemented in a collection of R packages specifically designed for psychometric network analysis and are mostly based on cross-sectional data retrieved from structured psychometric questionnaires, with just few exemptions of panel data. Most of them used the same techniques for all phases of their analysis. In particular, a pervasive use of the Gaussian Graphical Model with LASSO regularization was registered for in network estimation step. Among the clinically relevant results, we can include the fact that all papers found strong symptom interconnections between specific and nonspecific ED symptoms, suggesting that both types should therefore be addressed by clinical treatment., Conclusions: We here presented the largest and most comprehensive review to date about psychometric network analysis methods. Although these methods still need solid validation in the clinical setting, they have already been able to show many strengths and important results, as well as great potentials and perspectives, which have been analyzed here to provide suggestions on their use and their possible improvement., Competing Interests: The authors have declared that no competing interests exist.

Tacrolimus (FK-506) is a calcium-calcineurin inhibitor, successfully used in transplant recipients. We report the successful use of tacrolimus as a single immunosuppressant in a patient who had developed myasthenia gravis (MG) during interferon alpha treatment. In this case, the coexistence of hepatitis C and type 2 diabetes mellitus contraindicated the use of both steroids and azathioprine, and cyclosporine A, although effective, had induced renal failure. Tacrolimus proved to be effective in the treatment of MG, was not significantly hepatotoxic, and was less nephrotoxic than cyclosporine., (Copyright 2002 John Wiley & Sons, Inc.)