Tag: nevin manimala

Radiat Oncol. 2025 Apr 15;20(1):53. doi: 10.1186/s13014-025-02630-x.

ABSTRACT

PURPOSE: Although partial breast irradiation (PBI) is accepted as an effective and cosmesis-preserving technique for low-risk early-stage breast cancer following standard lumpectomy, data supporting PBI following oncoplastic surgery are sparse. We report prospective data in efforts to determine whether PBI can be safely utilized after oncoplastic surgery.

METHODS: Patients with low-risk stage 0-1 breast cancer following successful lumpectomy with optional oncoplastic reconstruction were enrolled on a phase II trial. Patients were treated with a modified Florence regimen to 30 Gy in 5 fractions on the Varian Edge radiosurgery system using IMRT or VMAT. Presurgical MRI, post-operative seroma and surgical clips were used to assist target delineation. The effect of oncoplastic surgery on radiation dosimetry and Breast Cancer Treatment Outcome Scale scores were assessed using student’s t-test for continuous variables and chi-square for categorical variables.

RESULTS: From 2018 to 2022, 50 patients with 52 tumors were enrolled with 48% undergoing oncoplastic reconstruction. Although median PTV volumes were numerically larger in the oncoplastic group (266 cc vs. 223 cc), there were no statistically significant differences in PTV volumes, ratio of PTV to whole breast or mean heart or lung doses (p > 0.05). Mean baseline BCTOS aesthetic scores were 1.35 for standard lumpectomy vs. 2.52 for oncoplastic (p = 0.003). At long-term follow-up > 2 years, mean BCTOS aesthetic scores were 1.29 for standard lumpectomy vs. 1.35 for oncoplastic (p = 0.71). At a median follow-up of 46 months, there were no local recurrences.

CONCLUSIONS: When utilizing pre-treatment MRI, surgical clips and a relatively large PTV, PBI after oncoplastic surgery was safe and effective for appropriately selected patients. In combination with oncoplastic surgery, partial breast irradiation achieves excellent long-term cosmesis that improves over time.

PMID:40234874 | DOI:10.1186/s13014-025-02630-x

Chaos. 2025 Apr 1;35(4):043132. doi: 10.1063/5.0252938.

ABSTRACT

We use the minimum description length (MDL) principle, which is an information-theoretic criterion for model selection, to determine echo-state network readout subsets. We find that this method of MDL subset selection improves accuracy when forecasting the Lorenz, Rössler, and Thomas attractors. It also improves the performance benefit that occurs when higher-order terms are included in the readout layer. We provide an explanation for these improvements in terms of decreased linear dependence and improved consistency.

PMID:40233402 | DOI:10.1063/5.0252938

Chaos. 2025 Apr 1;35(4):043134. doi: 10.1063/5.0244816.

ABSTRACT

In this paper, we illustrate the innovative techniques to explore the dynamical properties of the hybrid complex systems by various parameters and demonstrate the clusters under the chaotic-condensation peculiarities to accentuate the different technological challenges in the modern world. The complex dynamic characteristics of the contemplated systems are explored with interferometry techniques, which play key roles in examining the consequences of intricate features to interpreting the dynamics of an assemblage that possesses the ability to traverse along dependable tracks of particles, and thus, the solutions within the framework of quantum perturbation for partially chaotic structures are explored with substantial peculiar outcomes in the expanding active matter systems. Correlation graphs with chaotic parameters illustrate the significance of coherent stochastic generation for quasi-granular systems at finite momenta that possess sufficient fractions of instability fluxes. The distribution of temperature profiles is demonstrated by employing specific techniques to account for the different asymmetries and distinct formulas that characterize the structure of the dynamical system using realistic interference methods. The analytical solution contained distinctive information about the response of chaotic and probabilistic droplets within the multiplicities throughout hot and cold particulates, which are triggered by an influenced time crossover phase that occurs continually under the emissions of various sources that proliferate. Our results indicate that the newly developed phase encompasses the partially coherent collection of active matter with the temperature, which probes the rapidity of its transformation, and such phases exhibit significant mutual relationships. The findings accentuate the significance of contemplating correlations and bestowing extraordinary farsightedness about the meticulous manifestation of complex systems. The current methods are unique in obtaining new forms of solutions that appear beneficial for researchers to further understand nonlinear dynamical problems. The acquired techniques are also applicable to examine the solutions of other types of chaotic systems with mathematical analysis through machine learning.

PMID:40233401 | DOI:10.1063/5.0244816

Chaos. 2025 Apr 1;35(4):043128. doi: 10.1063/5.0250492.

ABSTRACT

Two dynamical indicators, the local dimension and the extremal index, used to quantify persistence in phase space have been developed and applied to different data across various disciplines. These are computed using the asymptotic limit of exceedances over a threshold, which turns to be a generalized Pareto distribution in many cases. However, the derivation of the asymptotic distribution requires mathematical properties, which are not present even in highly idealized dynamical systems and unlikely to be present in the real data. Here, we examine in detail the issues that arise when estimating these quantities for some known dynamical systems. We focus on how the geometry of an invariant set can affect the regularly varying properties of the invariant measure. We demonstrate that singular measures supported on sets of the non-integer dimension are typically not regularly varying and that the absence of regular variation makes the estimates resolution dependent. We show as well that the most common extremal index estimation method is not well defined for continuous time processes sampled at fixed time steps, which is an underlying assumption in its application to data.

PMID:40233400 | DOI:10.1063/5.0250492

Chaos. 2025 Apr 1;35(4):043131. doi: 10.1063/5.0249549.

ABSTRACT

This work explores the relationship between state space methods and Koopman operator-based methods for predicting the time evolution of nonlinear dynamical systems. We demonstrate that extended dynamic mode decomposition with dictionary learning (EDMD-DL), when combined with a state space projection, is equivalent to a neural network representation of the nonlinear discrete-time flow map on the state space. We highlight how this projection step introduces nonlinearity into the evolution equations, enabling significantly improved EDMD-DL predictions. With this projection, EDMD-DL leads to a nonlinear dynamical system on the state space, which can be represented in either discrete or continuous time. This system has a natural structure for neural networks, where the state is first expanded into a high-dimensional feature space followed by linear mapping that represents the discrete-time map or the vector field as a linear combination of these features. Inspired by these observations, we implement several variations of neural ordinary differential equations (ODEs) and EDMD-DL, developed by combining different aspects of their respective model structures and training procedures. We evaluate these methods using numerical experiments on chaotic dynamics in the Lorenz system and a nine-mode model of turbulent shear flow, showing comparable performance across methods in terms of short-time trajectory prediction, reconstruction of long-time statistics, and prediction of rare events. These results highlight the equivalence of the EDMD-DL implementation with a state space projection to a neural ODE representation of the dynamics. We also show that these methods provide comparable performance to a non-Markovian approach in terms of the prediction of extreme events.

PMID:40233399 | DOI:10.1063/5.0249549

J Am Acad Orthop Surg. 2025 Apr 10. doi: 10.5435/JAAOS-D-24-01041. Online ahead of print.

ABSTRACT

Workplace violence (WPV) is a pervasive issue in health care that has shown rising incidence in recent years. There are several risk factors related to the worker, occupational environment, and patient that predispose to WPV events and should be considered in risk mitigation strategies. WPV has been associated with negative effects on worker health and professional efficacy. Past work has shown that multifactorial intervention models are more effective at improving WPV prevention and response in health care. This review summarizes the statistical trends, risk factors, and negative effects of WPV in health care, as well as interventions to improve prevention and response.

PMID:40233398 | DOI:10.5435/JAAOS-D-24-01041

J Am Acad Orthop Surg. 2025 Apr 10. doi: 10.5435/JAAOS-D-24-01049. Online ahead of print.

ABSTRACT

INTRODUCTION: The steep rise in utilization of large language model chatbots, such as ChatGPT, has spilled into medicine in recent years. The newest version of ChatGPT, ChatGPT-4, has passed medical licensure examinations and, specifically in orthopaedics, has performed at the level of a postgraduate level three orthopaedic surgery resident on the Orthopaedic In-Service Training Examination question bank sets. The purpose of this study was to evaluate ChatGPT-4’s diagnostic and decision-making capacity in the clinical management of bone-related injuries of the foot and ankle.

METHODS: Eight bone-related foot and ankle orthopaedic cases were presented to ChatGPT-4 and subsequently evaluated by three fellowship-trained foot and ankle orthopaedic surgeons. Cases were scored using criteria on a Likert scale, graded from a total score of 5 (lowest) to 25 (highest) across five criteria. ChatGPT-4 was referred to as “Dr. GPT,” establishing a peer dynamic so that the role of an orthopaedic surgeon was emulated by the chatbot.

RESULTS: The average score across all criteria for each case was 4.53 of 5, noting an overall average sum score of 22.7 of 25 for all cases. The pathology with the highest score was the second metatarsal stress fracture (24.3), whereas the case with the lowest score was hallux rigidus (21.3). Kendall correlation analysis of interrater reliability showed variable correlation among surgeons, without statistical significance.

CONCLUSION: ChatGPT-4 effectively diagnosed and provided appropriate treatment options for simple bone-related foot and ankle cases. Importantly, ChatGPT did not fabricate treatment options (ie, hallucination phenomenon), which has been previously well-documented in the literature, notably receiving its second-highest overall average score in this criterion. ChatGPT struggled to provide comprehensive information beyond standard treatment options. Overall, ChatGPT has the potential to serve as a widely accessible resource for patients and nonorthopaedic clinicians, although limitations may exist in the delivery of comprehensive information.

PMID:40233367 | DOI:10.5435/JAAOS-D-24-01049

JMIR Res Protoc. 2025 Apr 15;14:e63269. doi: 10.2196/63269.

ABSTRACT

BACKGROUND: Cognitive impairments are a key aspect of schizophrenia spectrum disorders (SSDs), significantly affecting clinical and functional outcomes. The COVID-19 pandemic has heightened concerns about mental health services and cognitive stimulation opportunities. Despite evidence-based interventions like action-based cognitive remediation (ABCR) and metacognitive training (MCT), a research-to-practice gap exists in their application across mental health settings.

OBJECTIVE: The iCogCA study aims to address this gap by implementing digital ABCR and MCT through a national Canadian collaborative effort using digital psychological interventions to enhance cognitive health in SSDs.

METHODS: The study involves 5 Canadian sites, with mental health care practitioners trained digitally through the E-Cog platform, which was developed by our research group. Over 2.5 years, participants with SSDs will undergo pre- and postintervention assessments for clinical symptoms, cognition, and functioning. Each site will run groups annually for both ABCR and MCT, totaling ~390 participants. A nonrandomized concurrent controlled design will assess effectiveness design, in which one intervention (eg, ABCR) acts as the active control for the other (eg, MCT) and vice versa, comparing cognitive and clinical outcomes between the interventions using generalized linear mixed effect modeling. Implementation strategy evaluation will consider the digital platform’s efficacy for mental health care practitioners’ training, contextual factors influencing implementation, and sustainability, using descriptive statistics for quantitative data and thematic analysis for qualitative data.

RESULTS: A pilot pragmatic trial has been conducted previously at the Montreal site, evaluating 3 early implementation outcomes: acceptability, feasibility, and engagement. Patient and therapist acceptability was deemed as high and feasible (21/28, 75% of recruited service users completed therapy, rated feasible by therapists). Technology did not appear to significantly impede program participation. Therapist-rated levels of engagement were also satisfactory. In the ongoing study, recruitment is underway (114 participants recruited as of winter 2024), and intervention groups have been conducted at all sites, with therapists receiving training via the E-Cog learning platform (32 enrolled as of winter 2024).

CONCLUSIONS: At least 3 significant innovations will stem from this project. First, this national effort represents a catalyst for the use of digital technologies to increase the adoption of evidence-based interventions and will provide important results on the effectiveness of digitally delivered ABCR and MCT. Second, the results of the implementation component of this study will generate the expertise needed to inform the implementation of similar initiatives. Third, the proposed study will introduce and validate our platform to train and supervise mental health care practitioners to deliver these interventions, which will then be made accessible to the broader mental health community.

TRIAL REGISTRATION: ClinicalTrials.gov NCT05661448; https://clinicaltrials.gov/study/NCT05661448.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/63269.

PMID:40233365 | DOI:10.2196/63269

JMIR Form Res. 2025 Apr 15;9:e68093. doi: 10.2196/68093.

ABSTRACT

BACKGROUND: Emerging digital health research poses roadblocks to the inclusion of historically marginalized populations in research. Exclusion of underresourced communities in digital health research is a result of multiple factors (eg, limited technology access, decreased digital literacy, language barriers, and historical mistrust of research and research institutions). Alternative methods of access and engagement may aid in achieving long-term sustainability of diversified participation in digital health research, ensuring that developed technologies and research outcomes are effective and equitable.

OBJECTIVE: This study aims to (1) characterize socioeconomic and demographic differences in individuals who enrolled and engaged with different remote, digital, and traditional recruitment methods in a digital health pregnancy study and (2) determine whether social media outreach is an efficient way of recruiting and retaining specific underrepresented populations (URPs) in digital health research.

METHODS: The Better Understanding the Metamorphosis of Pregnancy (BUMP) study was used as a case example. This is a prospective, observational, cohort study using digital health technology to increase understanding of pregnancy among 524 women, aged 18-40 years, in the United States. The study used different recruitment strategies: patient portal for genetic testing results, paid/unpaid social media ads, and a community health organization providing care to pregnant women (Moses/Weitzman Health System).

RESULTS: Social media as a recruitment tool to engage URPs in a digital health study was overall effective, with a 23.6% (140/594) enrollment rate of those completing study interest forms across 25 weeks. Community-based partnerships were less successful, however, resulting in 53.3% (57/107) engagement with recruitment material and only 8.8% (5/57) ultimately enrolling in the study. Paid social media ads provided access to and enrollment of a diverse potential participant pool of race- or ethnicity-based URPs in comparison to other digital recruitment channels. Of those that engaged with study materials, paid recruitment had the highest percentage of non-White (non-Hispanic) respondents (85/321, 26.5%), in comparison to unpaid ads (Facebook and Reddit; 37/167, 22.2%). Of the enrolled participants, paid ads also had the highest percentage of non-White (non-Hispanic) participants (14/70, 20%), compared to unpaid ads (8/52, 15.4%) and genetic testing service subscribers (72/384, 18.8%). Recruitment completed via paid ads (Instagram) had the highest study retention rate (52/70, 74.3%) across outreach methods, whereas recruitment via community-based partnerships had the lowest (2/5, 40%). Retention of non-White (non-Hispanic) participants was low across recruitment methods: paid (8/52, 15.4%), unpaid (3/35, 14.3%), and genetic testing service subscribers (50/281, 17.8%).

CONCLUSIONS: Social media recruitment (paid/unpaid) provides access to URPs and facilitates sustained retention similar to other methods, but with varying strengths and weaknesses. URPs showed lower retention rates than their White counterparts across outreach methods. Community-based recruitment showed lower engagement, enrollment, and retention. These findings highlight social media’s potential for URP engagement and enrollment, illuminate potential roadblocks of traditional methods, and underscore the need for tailored research to improve URP enrollment and retention.

PMID:40233355 | DOI:10.2196/68093

J Am Acad Orthop Surg. 2025 Apr 10. doi: 10.5435/JAAOS-D-23-00543. Online ahead of print.

ABSTRACT

INTRODUCTION: Spondylolysis, a defect in the pars interarticularis, can be symptomatic or asymptomatic with an estimated prevalence of 4% by age 6 years and 6% by adulthood. This study’s goal was to determine the prevalence of lumbar spondylolysis found on CT scans in children and to characterize patient-specific risk factors.

METHODS: Abdominopelvic CT scans done (2017 to 2020) in patients up to age 18 years were reviewed. The radiology report was retrospectively reviewed for a spondylolysis, and a radiologist rereviewed the CT scan. Patient demographics and indications for CT scan were included. Firth bias-reduced logistic regression was used to model spondylolysis with each demographic variable as a predictor.

RESULTS: One thousand nine hundred thirty-one CT reports and imaging were reviewed; abdominal pain (41.91%) and trauma (29.46%) were the most common reasons for CT scan. Spondylolysis was found in 42 patients (2.18%) per the radiology report and in 71 patients (3.68%) on radiologist overread. Median age was 13 years (interquartile range, 10 to 16 years). Age groups had the following prevalence: 0 to 6 years (0.41%); 7 to 10 years (1.58%); 11 to 13 years (3.59%); 14 to 18 years (5.1%). Increased prevalence was found in ages 14 to 18 years that was statistically significant (odds ratio 1; P = 0.0004). L5 was the most common level; most defects were bilateral. White patients had a higher rate of spondylolysis (5.06%) than Black patients (2.05%). Black patients were less likely to have a spondylolysis with an OR of 0.4 (0.22 to 0.69; P = 0.0007).

DISCUSSION: This study demonstrated a lower prevalence of lumbar spondylolysis (3.68%) in children compared with the previous literature. Increasing prevalence with age suggests that spondylolysis develops over time, likely because of repetitive stress. Future studies should characterize these age-related and race-related differences for better understanding.

LEVEL OF EVIDENCE: Level IV, retrospective.

PMID:40233349 | DOI:10.5435/JAAOS-D-23-00543