Category: Statistics

Invest Radiol. 2025 Apr 25. doi: 10.1097/RLI.0000000000001198. Online ahead of print.

ABSTRACT

OBJECTIVES: In cardiac amyloidosis (CA) protein misfolding and consecutive storage into the extracellular myocardial compartment causes left ventricular hypertrophy and, in later stages of the disease, heart failure. The aim of this study was to compare extracellular volume (ECV) measurements obtained from photon-counting CT (PCCT) to the imaging reference cardiac magnetic resonance imaging (CMR) and to evaluate coronary artery disease (CAD) in a CA cohort.

MATERIALS AND METHODS: Thirty CA patients (mean age 77.5 +/- 7.9 years) underwent clinically indicated coronary CT angiography (CCTA) for the evaluation of CAD on a first-generation PCCT including a late-phase scan for assessment of ECV. ECV in PCCT was derived using 2 different techniques: (I) a single-energy (SE) technique, based on attenuation changes between the precontrast calcium scoring scan and delayed CCTA in the equilibrium phase (II) a dual-energy (DE) technique, based on iodine density maps from the delayed scan. Both methods were compared with CMR-derived ECV. Statistical analysis included repeated-measures analysis of variance (RM-ANOVA) with Bonferroni-adjusted pairwise comparisons. Correlations between methods were assessed using Pearson’s correlation coefficient, and agreement was evaluated using Bland-Altman analysis.

RESULTS: CMR exhibited the highest mean ECV value (42.93 ± 10.14), followed by the SE method (42.5 ± 9.1), while the DE method yielded the lowest ECV values (40.7 ± 9.2). When compared with CMR, ECV obtained via the DE method was significantly lower (MDiff = -2.24, P = 0.04). In contrast, no significant difference was observed between CMR and the SE method (MDiff = 0.43, P = 1.00). Differences between the DE and SE methods were significant (MDiff = -1.82, P < 0.001). Despite these differences, all 3 methods demonstrated excellent positive correlations. The strongest correlation was observed between the DE and SE methods (r = 0.98, P < 0.001), indicating high consistency in their measurements. Comparatively, the correlation between CMR and DE (r = 0.892, P < 0.001) was slightly stronger than that between CMR and SE methods (r = 0.882, P < 0.001). CAD was present in 29 (97.0%) CA patients with a mean Agatston score of 1086 ± 1398 (range 0-6848.5). Despite this high mean plaque burden and 14 (47.6%) patients presenting with atrial fibrillation, image quality was preserved in 29 (97.0%) patients with 17 (57.6%) of the patients having nonobstructive CAD.

CONCLUSIONS: Compared to the imaging reference standard CMR, ECV derived from the DE and SE methods via PCCT demonstrated excellent positive correlations with CMR. The DE method exhibited minor differences compared to CMR, which were clinically not relevant. CAD with an extensive burden of calcified plaque was highly prevalent in CA; however, 57.6% of patients presented with nonobstructive CAD. Therefore, PCCT is a valuable tool for imaging both the coronary arteries and myocardial structure in CA.

PMID:40279664 | DOI:10.1097/RLI.0000000000001198

Med Sci Sports Exerc. 2025 Apr 25. doi: 10.1249/MSS.0000000000003742. Online ahead of print.

ABSTRACT

PURPOSE: We aimed to develop and validate a risk-assessment tool for energy deficiency in young exercising women using disordered eating subscales and self-reported health-related information.

METHODS: We retrospectively analyzed 7 studies in competitive and recreationally active women [n = 202, age 21.7 ± 0.3 years, body mass index (BMI) 21.21 ± 0.14 kg/m2, (mean ± SEM)]. Participants completed the Health, Exercise and Nutrition Survey (HENS), the Three-Factor Eating Questionnaire (TFEQ), and the Eating Disorder Inventory-3 (EDI-3). Energy deficiency was defined as fasting serum total triiodothyronine (TT3) <73.2 ng/dL. A cut-off of TT3 < 80 ng/dL was also tested. Potential predictors of energy deficiency were: age of menarche, gynecological age, disordered eating, menstrual status, and bone health items (HENS); dietary cognitive restraint (TFEQ); and Perfectionism, Body Dissatisfaction, and Drive for Thinness (EDI-3). A model set (n = 152; 21.8 ± 0.3 years, 21.23 ± 0.16 kg/m2) was used to select predictors, identify interaction terms, and fit 500 random iterations of stepwise logistic regression. Predictors included in ≥450 models were used in a final model and tested on a validation set (n = 50; 21.6 ± 0.4 years, 21.15 ± 0.3 kg/m2).

RESULTS: The final model included BMI; number of menstrual cycles in the last 6 months, dietary cognitive restraint, and body dissatisfaction index. The FED-Q coefficient detected TT3 < 73.2 ng/dL with 84.2% sensitivity, 80.6% specificity, and 82% accuracy, and TT3 < 80 ng/dL with 85% sensitivity, 83.3% specificity, and 84% accuracy.

CONCLUSIONS: At present, the Female Energy Deficiency Questionnaire is the only questionnaire that is specifically designed as an indicator of energy deficiency in female athletes across a variety of sports.

PMID:40279653 | DOI:10.1249/MSS.0000000000003742

J Med Internet Res. 2025 Apr 25;27:e59085. doi: 10.2196/59085.

ABSTRACT

BACKGROUND: Motivational interviewing (MI) is frequently used to facilitate behavior change. The use of change talk during motivational interviews can predict subsequent behavior change. However, no studies have compared the information obtained from traditional face-to-face motivational interviews and computer-mediated motivational interviews or resulted in the same amount of behavior change.

OBJECTIVE: This study aimed to investigate if face-to-face motivational-type interviews (MTIs) and computer-mediated MTIs elicit the same amount of “change talk” and behavior change when young adults discuss their ambivalence about using marijuana.

METHODS: A total of 150 users, including frequent marijuana users, occasional marijuana users, and non-marijuana users, participated in the study. All participants reported being at least moderately ambivalent about their current level of marijuana use. Participants were randomly assigned to complete a brief MTI using either the standard face-to-face format or a computer-mediated format. Amrhein’s manual for assessing the presence of “change talk” and “sustain talk” was used to code the language produced by respondents in each interview format. A reduction in marijuana use was assessed at a 2-month follow-up.

RESULTS: The word count was significantly higher in face-to-face MTIs compared with computer-mediated MTIs (P<.001). After controlling for verbosity, face-to-face MTIs, and computer-mediated MTIs did not differ statistically in the overall amount of change talk (P=.47) and sustain talk (P=.05). Face-to-face MTIs elicited significantly more reasons for reducing future marijuana use (ie, change talk; P=.02) and readiness toward not using marijuana (ie, change talk; P=.009), even after controlling for verbosity. However, these differences were not statistically significant after using a conservative Bonferroni correction (P<.004). After controlling for marijuana use at Time 1, the relationship between the strength of commitment language at Time 1 and marijuana use at Time 2 was not statistically significant (semipartial correlation r=0.03, P=.57). The association between Time 1 change talk and Time 2 marijuana use depended on the type of motivational interview that participants experienced: face-to-face MTI versus computer-mediated MTI (B=0.45, P=.01). A negative binomial regression with a log link function was used to probe this relationship after controlling for 2 covariates: gender and Time 1 (baseline assessment) marijuana use. Among participants in the face-to-face MTI condition, Time 2 (follow-up) marijuana use decreased as the strength of Time 1 change talk increased, although this finding was not significant (B=-0.21, P=.08). However, among participants in the computer-mediated MTI condition, Time 2 marijuana use was not significantly related to the strength of Time 1 change talk (B=0.13, P=.16).

CONCLUSIONS: Computer-mediated MTIs and face-to-face MTIs elicit both change talk and sustain talk, which suggests that motivational interviews could potentially be adapted for delivery via text-based computer platforms. However, further research is needed to enhance the predictive validity of the type of language obtained via computer-delivered MI.

TRIAL REGISTRATION: ClinicalTrials.gov NCT06945471; https://clinicaltrials.gov/study/NCT06945471.

PMID:40279644 | DOI:10.2196/59085

Phys Rev Lett. 2025 Apr 11;134(14):140601. doi: 10.1103/PhysRevLett.134.140601.

ABSTRACT

Gaussian boson sampling is a promising method for experimental demonstrations of quantum advantage because it is easier to implement than other comparable schemes. While most of the properties of Gaussian boson sampling are understood to the same degree as for these other schemes, we understand relatively little about the statistical properties of its output distribution. The most relevant statistical property, from the perspective of demonstrating quantum advantage, is the “anticoncentration” of the output distribution as measured by its second moment. The degree of anticoncentration features in arguments for the complexity-theoretic hardness of Gaussian boson sampling. In this Letter, we develop a graph-theoretic framework for analyzing the moments of the Gaussian boson sampling distribution. Using this framework, we show that Gaussian boson sampling undergoes a transition in anticoncentration as a function of the number of modes that are initially squeezed compared to the number of photons measured at the end of the circuit. When the number of initially squeezed modes scales sufficiently slowly with the number of photons, there is a lack of anticoncentration. However, if the number of initially squeezed modes scales quickly enough, the output probabilities anticoncentrate weakly.

PMID:40279623 | DOI:10.1103/PhysRevLett.134.140601

Phys Rev Lett. 2025 Apr 11;134(14):147401. doi: 10.1103/PhysRevLett.134.147401.

ABSTRACT

Geometrically frustrated assemblies where building blocks misfit have been shown to generate intriguing phenomena from self-limited growth, fiber formation, to structural complexity. We introduce a graph theory formulation of geometrically frustrated assemblies, capturing frustrated interactions through the concept of incompatible flows, providing a direct link between structural connectivity and frustration. This theory offers a minimal yet comprehensive framework for the fundamental statistical mechanics of frustrated assemblies, and connects it to tensor gauge theory formulations of amorphous solids. Through numerical simulations, the theory reveals new characteristics of frustrated assemblies, including two distinct percolation transitions for structure and incompatible flows, a crossover between cumulative and noncumulative frustration controlled by disorder, and a divergent length scale in their response.

PMID:40279594 | DOI:10.1103/PhysRevLett.134.147401

Phys Rev Lett. 2025 Apr 11;134(14):148001. doi: 10.1103/PhysRevLett.134.148001.

ABSTRACT

Accurate and efficient theoretical techniques for describing ionic fluids are highly desirable for many applications across the physical, biological, and materials sciences. With a rigorous statistical mechanical foundation, classical density functional theory (cDFT) is an appealing approach, but the competition between strong Coulombic interactions and steric repulsion limits the accuracy of current approximate functionals. Here, we extend a recently presented machine learning (ML) approach [Sammüller et al., Proc. Natl. Acad. Sci. U.S.A., 120, e2312484120 (2023)PNASA60027-842410.1073/pnas.2312484120] designed for systems with short-ranged interactions to ionic fluids. By adopting ideas from local molecular field theory, the framework we present amounts to using neural networks to learn the local relationship between the one-body direct correlation functions and inhomogeneous density profiles for a “mimic” short-ranged system, with effects of long-ranged interactions accounted for in a mean-field, yet well-controlled, manner. By comparing to results from molecular simulations, we show that our approach accurately describes the structure and thermodynamics of prototypical models for electrolyte solutions and ionic liquids, including size-asymmetric and multivalent systems. The framework we present acts as an important step toward extending ML approaches for cDFT to systems with accurate interatomic potentials.

PMID:40279585 | DOI:10.1103/PhysRevLett.134.148001

Phys Rev Lett. 2025 Apr 11;134(14):140404. doi: 10.1103/PhysRevLett.134.140404.

ABSTRACT

The eigenstate thermalization hypothesis (ETH) has been established as the general framework to understand quantum statistical mechanics. Only recently has the attention been paid to so-called full ETH, which accounts for higher-order correlations among matrix elements, and that can be rationalized theoretically using the language of free probability. In this work, we perform the first numerical investigation of the full ETH in physical many-body systems with local interactions by testing the decomposition of higher-order correlators into thermal free cumulants for local operators. We perform exact diagonalization on two classes of local nonintegrable (chaotic) quantum many-body systems: spin chain Hamiltonians and Floquet brickwork unitary circuits. We show that the dynamics of four-time correlation functions are encoded in fourth-order free cumulants, as predicted by ETH. Their dependence on frequency encodes the physical properties of local many-body systems and distinguishes them from structureless, rotationally invariant ensembles of random matrices.

PMID:40279584 | DOI:10.1103/PhysRevLett.134.140404

Phys Rev Lett. 2025 Apr 11;134(14):147203. doi: 10.1103/PhysRevLett.134.147203.

ABSTRACT

The Wigner-Smith time delay of flux conserving systems is a real quantity that measures how long an excitation resides in an interaction region. The complex generalization of time delay to non-Hermitian systems is still under development, in particular, its statistical properties in the short-wavelength limit of complex chaotic scattering systems has not been investigated. From the experimentally measured multiport scattering (S) matrices of one-dimensional graphs, a two-dimensional billiard, and a three-dimensional cavity, we calculate the complex Wigner-Smith (τ_{WS}), as well as each individual reflection (τ_{xx}) and transmission (τ_{xy}) time delay. The complex reflection time-delay differences (τ_{δR}) between each port are calculated, and the transmission time-delay differences (τ_{δT}) are introduced for systems exhibiting nonreciprocal scattering. Large time delays are associated with scattering singularities such as coherent perfect absorption, reflectionless scattering, slow light, and unidirectional invisibility. We demonstrate that the large-delay tails of the distributions of the real and imaginary parts of each time-delay quantity are superuniversal, independent of experimental parameters: wave propagation dimension D, number of scattering channels M, Dyson symmetry class β, and uniform attenuation η. The tails determine the abundance of the singularities in generic scattering systems, and the superuniversality is in direct contrast with the well-established time-delay statistics of unitary scattering systems, where the tail of the τ_{WS} distribution depends explicitly on the values of M and β. We relate the distribution statistics to the topological properties of the corresponding singularities. Although the results presented here are based on classical microwave experiments, they are applicable to any non-Hermitian wave-chaotic scattering system in the short-wavelength limit, such as optical or acoustic resonators.

PMID:40279582 | DOI:10.1103/PhysRevLett.134.147203

J Med Internet Res. 2025 Apr 25;27:e67114. doi: 10.2196/67114.

ABSTRACT

BACKGROUND: Recent years have seen an immense surge in the creation and use of chatbots as social and mental health companions. Aiming to provide empathic responses in support of the delivery of personalized support, these tools are often presented as offering immense potential. However, it is also essential that we understand the risks of their deployment, including their potential adverse impacts on the mental health of users, including those most at risk.

OBJECTIVE: The study aims to assess the ethical and pragmatic clinical implications of using chatbots that claim to aid mental health. While several studies within human-computer interaction and related fields have examined users’ perceptions of such systems, few studies have engaged mental health professionals in critical analysis of their conduct as mental health support tools. This paper comprises, in turn, an effort to assess the ethical and pragmatic clinical implications of using chatbots that claim to aid mental health.

METHODS: This study included 8 interdisciplinary mental health professional participants (from psychology and psychotherapy to social care and crisis volunteer workers) in a mixed methods and hands-on analysis of 2 popular mental health-related chatbots’ data handling, interface design, and responses. This analysis was carried out through profession-specific tasks with each chatbot, eliciting participants’ perceptions through both the Trust in Automation scale and semistructured interviews. Through thematic analysis and a 2-tailed, paired t test, these chatbots’ implications for mental health support were thus evaluated.

RESULTS: Qualitative analysis revealed emphatic initial impressions among mental health professionals of chatbot responses likely to produce harm, exhibiting a generic mode of care, and risking user dependence and manipulation given the central role of trust in the therapeutic relationship. Trust scores from the Trust in Automation scale, while exhibiting no statistically significant differences between the chatbots (t₆=-0.76; P=.48), indicated medium to low trust scores for each chatbot. The findings of this work highlight that the design and development of artificial intelligence (AI)-driven mental health-related solutions must be undertaken with utmost caution. The mental health professionals in this study collectively resist these chatbots and make clear that AI-driven chatbots used for mental health by at-risk users invite several potential and specific harms.

CONCLUSIONS: Through this work, we contributed insights into the mental health professional perspective on the design of chatbots used for mental health and underscore the necessity of ongoing critical assessment and iterative refinement to maximize the benefits and minimize the risks associated with integrating AI into mental health support.

PMID:40279575 | DOI:10.2196/67114