Articles

<b>Objective: </b>This study aims to investigate the relationship between the presence of chronic medical conditions and cessation among U.S. adults who use combustible tobacco. We hypothesized that having chronic medical conditions would be associated with a higher likelihood of successfully quitting combustible tobacco.<b> </b><b>Methods: </b>We utilized longitudinal data from the Population Assessment of Tobacco and Health (PATH) Study, using data from Waves 1 to 6. Only current daily smokers were included in our analysis. The independent variable was the number of chronic medical conditions, defined as zero, one, or two or more. The outcome was becoming a former smoker (quitting smoking). Using multivariate regression analyses, we assessed the association between the number of chronic conditions and tobacco cessation over the six waves. We controlled for potential confounding variables, including demographic factors and socioeconomic status.<b> </b><b>Results: </b>Our analysis revealed a significant association between the number of chronic medical conditions and the likelihood of quitting smoking. Specifically, individuals with two or more chronic conditions exhibited a greater probability of quitting smoking compared to those with no chronic conditions. The results remained significant after adjusting for potential confounders.<b> </b><b>Conclusions: </b>Multiple chronic medical conditions may act as a catalyst for smoking cessation among U.S. adults. This suggests that the presence of multimorbidity, defined as multiple chronic disease diagnoses, may serve as “teachable moments,” prompting significant health behavior changes. These findings highlight the potential for leveraging chronic disease management and healthcare interventions to promote tobacco cessation, particularly among individuals with multiple chronic conditions.

This paper investigates the constructability of angles multiples of 3 within the framework of Euclidean geometry. It makes a significant contribution by presenting the first geometric construction for all such angles, offering a rigorous solution to a longstanding geometric problem. The paper reaffirms the efficacy of Euclidean geometry in providing precise constructions and robust proofs for these angles, demonstrating the enduring strength of Euclidean principles from classical to modern times. The presented workflow goes beyond Euclidean geometry to examine non-Euclidean methods, particularly analytical approaches, revealing misconceptions that compromise the genetic and geometric rigor of Euclidean principles. The paper exposes incongruities when algebraic proofs related to angle constructability are applied to the Euclidean system, emphasizing the misalignment of fundamental geometric concepts. A notable result in the paper is the construction of a angle, introducing the “ angle chord” as a novel geometric property. This property challenges assumptions made by non-Euclidean methods and highlights the nuanced geometric properties crucial for rigorous constructions. The paper refutes the fallacy of relying solely on algebra for solutions to angles multiples of , emphasizing the necessity of embracing Euclidean geometry for geometric discoveries. The paper underscores the merits and resilience of Euclidean geometry, showcasing its independence and depth across historical and modern perspectives. The newly presented geometric construction not only resolves a longstanding question but also emphasizes the intrinsic strength and uniqueness of Euclidean principles in contrast to alternative methodologies.

<b>Background:</b> Multiple epiphyseal dysplasia (MED) a rare form of skeletal dysplasia with early-onset osteoarthritis affecting the hip and knee joints. There is paucity of evidence regarding the long term outcomes of arthroplasty in this patient cohort. This is the first study to describe the outcomes of bilateral arthroplasty of the hip and knee in patients with MED. <b>Methods:</b> A prospective study of patients with MED who underwent bilateral staged total hip arthroplasty (THA) and bilateral simultaneous total knee arthroplasty (TKA) between July 2013 to April 2014. Preoperative and postoperative clinical and radiographic assessment including functional outcomes namely Merle d’aubigne score, Harris hip score (HHS), Knee society score (KSS) and numeric rating scale (NRS) for pain were recorded in prospective database and evaluated. <b>Results:</b> 3 patients (female - 1 / male - 2) with MED who underwent bilateral lower limb arthroplasty of the hip and knee were reviewed periodically with an average followup of 7.31 years. Mean preoperative Merle d'Aubigné score (6.33 ± 0.58), HHS (31.83 ± 5.31) and KSS (28.67 ± 7.97) increased following bilateral lower limb arthroplasty with mean postoperative Merle d'Aubigné score (16.33 ± 0.58), HHS (84.33 ± 5.99) and KSS (86.33 ± 7.09) (<i>P</i><0.001). Mean NRS decreased from 7.33 ± 0.58 in the preoperative period to 0.67 ± 0.58 at the most recent followup (<i>P</i><0.001). One patient had heterotrophic ossification following<b> </b>THA. There were no revisions.<b> </b><b>Conclusions:</b> Bilateral lower limb arthroplasty of the hip and knee is a good treatment option to restore function and mobility in MED patients with advanced degenerative arthritis. Careful preoperative planning, meticulous surgical techniques, patient focussed postoperative rehabilitation with multidisciplinary team approach are vital to ensure good functional outcomes and implant survivorship.

In this study, the system identification of a multiple input multiple-output (MIMO) water tank has been investigated. The given experimental system is a first-order system. Its transfer function was evaluated and the time constant was predicted. Once the parameters of the transfer functions (delay, gain, and time constant) were determined for each step input. This model each of the step responses using MatLab’s Simulink. These simulated responses were then compared to the observed experimental responses.

Architectural frameworks for large-scale Electronic Health Record (EHR) data platforms are described. Existing EHR data platform architectures often leverage multiple cloud-based solutions blended with institutional infrastructures to manage and analyze clinical data at scale. Key design principles governing the scale of existing EHR data architecture include model design, governance structure, data access management, data security/policy/protection, data-information-language-based standardization, and analytics tool alignment, among others. The rapidly evolving technology landscape and the unprecedented volume of incident and retrospective clinical data being collected and generated within healthcare organizations have led to the emergent need for a dedicated architectural framework to support large-scale computing in the health informatics domain. The application areas of large-scale computing in health informatics include real-time predictive analytics, risk stratification, patient cohort analytics, development of predictive models for specific institutions or population groups, and many more. The use of EHR data for a multitude of decision-making processes in both clinical and non-clinical settings has prompted the establishment of policies prescribing the conditions of access and use of EHR data for non-employed individuals in the organization. Consequently, the demand for accessing, using, and managing EHR data at scale has impacted the over.