Standard Measures Research Articles

AGEING, ORTHOSTATIC HYPOTENSION, AND MENTAL HEALTH: A CROSS-SECTIONAL STUDY IN NDOLA CITY OF ZAMBIA

<p><strong>Background:</strong> This study examines the relationship between ageing, standing blood pressure, and mental health in 770 adults from Ndola City, Zambia, focusing on orthostatic hypotension (OH). OH, characterized by a significant drop in blood pressure upon standing, is particularly prevalent among older adults and is associated with mental health disorders such as depression and stress. <strong>Methods:</strong> Using a cross-sectional design, participants were categorized by age, and standard blood pressure measurements were taken to assess OH. Mental health was evaluated using the Depression, Anxiety, and Stress Scale (DASS21) and the General Health Questionnaire (GHQ12). Statistical analyses, including Pearson chi-square tests, were employed to explore associations between age groups, the prevalence of OH, and mental health conditions. <strong>Results:</strong> Results indicated no significant association between age and the occurrence of OH (Pearson chi2(4) = 7.5702, Pr = 0.109). However, a significant relationship was found between age and depression (Pearson chi2(8) = 23.4265, Pr = 0.003), suggesting that older age correlates with higher depression levels. In contrast, anxiety did not show a significant association with age (Pearson chi2(4) = 4.5814, Pr = 0.333). Stress levels were significantly associated with age (Pearson chi2(8) = 37.1247, Pr = 0.000), as were distress levels (Pearson chi2(4) = 9.9089, Pr = 0.042). Conclusion: While age does not significantly impact the occurrence of OH, it is correlated with increased levels of depression and stress among older adults, highlighting the need for mental health interventions in this population.</p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0794/a.php" alt="Hit counter" /></p>

Cluster analysis of suicidal ideation and influencing factors among Spanish teachers

Suicidal ideation signals a higher suicide risk, particularly among teachers, affecting their well-being and impacting student development and academic success. This study, the first to use standardized measures with Spanish teachers, examines suicidal ideation among 1,251 educators from 107 schools. It analyzes suicidal thoughts and their associated risk and protective factors using a cross-sectional design. Results show an 18.86% prevalence of suicidal ideation, with 12.39% occurring in females. Anxiety and depression may act as risk factors, while emotional intelligence and resilience might serve as protective factors in identifying teachers with and without suicidal thoughts. The analyses identified four clusters based on suicidal ideation severity and psychological traits, indicating a need for enhanced targeted interventions. Main limitations include the cross-sectional design, reliance on self-reported data, and the lack of a broader perspective on sociocultural variables. Evidence highlights the need for tailored interventions to reduce teachers’ suicidal thoughts and improve their well-being.

Enhancing Bank Credit Card Transaction Fraud Detection with Machine Learning Techniques

Abstract: Because of the increasing prevalence and sophistication of credit card theft, standard detection measures frequently fail. This study investigates the use of several machine learning algorithms to improve fraud detection in bank credit card transactions. The research aims to develop enhanced fraud detection systems by employing an integrated strategy involving data preprocessing, the application of various classification algorithms, and performance evaluation. The study thoroughly examines algorithms such as Random Forest, Logistic Regression, and Neural Networks, focusing on their predictive capabilities and practical applications. The findings indicate that machine learning provides a robust framework for increasing the accuracy and efficiency of fraud detection systems, consequently assisting financial institutions in protecting customer transactions and strengthening security measures. Moreover, by prioritizing robust model selection and feature engineering, banks can significantly enhance their fraud detection performance. This research could greatly influence how financial institutions handle fraud, potentially reducing losses, improving operational efficiency, and securing transaction environments. The insights gained from this study are also valuable for informing broader financial security strategies and guiding future research in the field.

Loneliness Gets Under the Skin: A Scoping Review Exploring the Link Between Loneliness and Biological Measures of Inflammation.

Research suggests that systemic inflammation may link loneliness to adverse health outcomes, yet there is a gap in comprehensively reviewing recent evidence on the relationship between loneliness and biological measures of inflammation in adults. This scoping review synthesizes current research to address the question: Is there a definitive link between loneliness and biological markers of inflammation in adults? Following the methods outlined by Arksey and O'Malley, we developed a protocol, defined our research question, and systematically searched PubMed, CINAHL, Embase, and Scopus for English-language studies conducted from 2018 to 2023 exploring the relationship between loneliness and biomarkers of inflammation in adults. Twelve studies meeting the inclusion criteria displayed heterogeneity in terms of sample characteristics, loneliness scales, and inflammatory biomarkers. The UCLA Loneliness Scale, in various forms, emerged as the predominant tool for measuring loneliness, while C-reactive protein and interleukin-6 were the most frequently evaluated inflammatory biomarkers. Notably, all 12 studies reported an association between loneliness and at least 1 biological marker of inflammation. Research consistently associates loneliness with poor health outcomes in aging adults, but the underlying mechanisms remain unclear. This scoping review suggests that inflammation may serve as a pathway linking loneliness to adverse health outcomes. However, the variability across studies highlights the need for standardized measurement methods and a consideration of both the duration and extent of loneliness. Enhancing our understanding of how loneliness affects systemic inflammation may help clarify why loneliness is associated with negative health outcomes.

Firm-level capabilities and response to a negative export shock: 2014 Russian embargo on the West

This paper investigates the resources and capabilities that determine firm-level adjustments after a sudden unexpected closure of a major export market. We focus on the effects of the 2014 Russian embargo on Western food exporters using the example of Estonian firms. The paper applies a novel multimethod approach consisting of Study I quantifying the embargo effect on the trade diversion of firms that had exported embargoed goods to Russia, and Study II conducting a multiple case study into three dairy exporters highly affected by the embargo. Study I employs a difference-in-difference model with matched exporters of embargoed goods as treatment. Study II builds on extensive document analysis that serves as input for interviews with the CEOs of the sample dairy firms. We find that pre-shock productivity is on average a good predictor of post-shock firm trade diversion (Study I), however, we specify that the key firm-level resources and capabilities necessary for successful post-shock adjustments might not be reflected in the standard quantitative productivity level measures (Study II). We conclude that key firm-level resources and capabilities for embargo-resilience are the quality of exporting experience, competitive product-market matching, absorptive capacity, and managerial vision and empowerment.

Field versus laboratory measurements of PFAS sorption by soils and sediments

Sorption by soils and sediments is an important process that influences the distribution, transport, and fate of per and polyfluoroalkyl substances (PFAS) in the environment. Many laboratory studies have been conducted to quantify magnitudes of PFAS sorption as a function of the properties of the PFAS, solutions, and porous media. A critical question is how representative are laboratory-measured sorption magnitudes for field applications. To address this question, log Koc data were compiled from the literature for a range of PFAS of different chain lengths and functional groups. The aggregated field-based data consisted of two types, in-situ measurements comprising paired soil/sediment and water samples and ex-situ measurements obtained from laboratory desorption experiments employing field-contaminated media. These two sets of field-based measurements were compared to a comprehensive data set of standard laboratory batch-type measurements. The compiled data sets represent an extremely wide range of soil and sediment properties. One important novel outcome is the observation that the enhanced sorption of short-chain PFAS observed in several prior laboratory studies is also observed for the field data. This differential enhanced sorption should be accounted for in site investigations and modeling studies. Another relevant outcome is the observation of consistency between measurements obtained with standard batch adsorption experiments and those from desorption studies employing either field-contaminated or artificially-contaminated media. The mean log Koc values determined for the in-situ measured field data were generally larger than the mean laboratory-determined values, particularly for the short-chain PFAS. Notably, however, values for subsets of the laboratory data representing measurements for lower aqueous concentrations or for soils with low organic-carbon contents (<1 %) compared well to the in-situ field data. Measurements compiled for anionic-polyfluoroalkyl, neutral, and cationic PFAS compared well to those for PFCAs and PFSAs. Overall, the results indicate that the laboratory measurements of PFAS sorption were generally representative of the field-derived magnitudes when compared on a consistent basis.

Predicting neonatal mortality prior to discharge from hospital in prenatally diagnosed left congenital diaphragmatic hernia.

To evaluate the association of standardized prenatal imaging parameters and immediate neonatal variables with mortality prior to discharge in infants with isolated left congenital diaphragmatic hernia (LCDH), and to compare the performance of ultrasound- and magnetic resonance imaging (MRI)-based severity grading for the prediction of neonatal mortality. This was a retrospective study of infants with prenatally diagnosed isolated LCDH referred to a single tertiary center between 2008 and 2020. Fetuses with right or bilateral congenital diaphragmatic hernia, additional major structural anomaly or known genetic condition, as well as cases that underwent fetal intervention or declined postnatal intervention, were excluded. Ultrasound and MRI images were reviewed retrospectively. Univariable and multivariable analyses were performed, incorporating prenatal and immediate neonatal factors to analyze the association with neonatal mortality prior to discharge, and a prediction calculator was generated. The performance of ultrasound and that of MRI for the prediction of neonatal mortality were compared. Of 253 pregnancies with fetal CDH, 104 met the inclusion criteria, of whom 77 (74%) neonates survived to discharge. Seventy-five fetuses underwent both prenatal ultrasound and MRI. On multivariable analysis, observed/expected (o/e) lung-to-head ratio and o/e total fetal lung volume were associated independently with neonatal death (adjusted odds ratio, 0.89 (95% CI, 0.83-0.95) and 0.90 (95% CI, 0.84-0.97), respectively), whereas liver position was not. There was no significant difference in predictive performance between using ultrasound and MRI together (area under the receiver-operating-characteristics curve (AUC), 0.85 (95% CI, 0.76-0.93)) compared with using ultrasound alone (AUC, 0.81 (95% CI, 0.72-0.90); P = 0.19). The addition of neonatal parameters (gestational age at birth and small-for-gestational age) did not improve model performance (AUC, 0.87 (95% CI, 0.80-0.95)) compared with the combined ultrasound and MRI model (P = 0.22). There was poor agreement between severity assessment on ultrasound and MRI (Cohen's κ, 0.19). Most discrepancies were seen among cases deemed to be non-severe on ultrasound and severe on MRI, and outcomes were more consistent with MRI-based prognostication. In fetuses with prenatally diagnosed isolated LCDH, mortality prediction using standardized ultrasound and MRI measurements performed reasonably well. In cases classified as non-severe on ultrasound, MRI is recommended, as it may provide more accurate prognostication and assist in the determination of candidacy for fetal intervention. © 2024 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

A refined TTC assay precisely detects cardiac injury and cellular viability in the infarcted mouse heart

Histological analysis with 2,3,5-triphenyltetrazolium chloride (TTC) staining is the most frequently used tool to detect myocardial ischemia/reperfusion injury. However, its practicality is often challenged by poor image quality in gross histology, leading to an equivocal infarct-boundary delineation and potentially compromised measurement accuracy. Here, we introduce several crucial refinements in staining protocol and sample processing, which enable TTC images to be analyzed with light microscopy. The refined protocol involves a two-step TTC staining process (perfusion and immersion) and subsequent Zamboni fixation to differentiate myocardial viability and necrosis, and use of Coomassie brilliant blue to label area-at-risk. After the duo-staining steps were completed, the heart sample was embedded and sliced transversally by a cryostat into a series of thin sections (50 µm) for microscopic analysis. The refined TTC (redTTC) assay yielded remarkably high-quality images with striking color intensity and sharply defined boundaries, permitting unambiguous and reliable delineation of the infarct and area-at-risk. In the same animals, the redTTC assay showed good agreement with the in-vivo gold standard measurements (LGE and MEMRI). Meanwhile, redTTC imaging allows tracking of viable cardiomyocytes at cellular resolution, and with this enhanced capability, we convincingly demonstrated the pro-survival action of stem cells based-therapy. Therefore, the redTTC assay represents a significant technical advance that permits precise detection of the true extent of cardiac injury and cardiomyocyte viability. This approach is cost-effective and may be adapted for use in diverse applications, making it highly appealing to many laboratories performing ischemia/reperfusion injury experiments.

Comparison of destructive and non-destructive fracture toughness measurements for Q235 steel butt-welded joint

As a critical component of a welded structure, the integrity of the welded joint significantly affects the safety and reliability of the structure in service. Therefore, it is essential to investigate the integrity of welded joints. However, given the harshness of standard measurements renders them unsuitable for application to small volume zones, welded structures or in-service structures. In this study, the fracture properties of a Q235 steel butt-welded joint was evaluated by boundary effect modelling (BEM) method and the ball indentation (BI) method. The results demonstrate that the fracture toughness distribution obtained by the two methods are consistent, with the highest fracture toughness in the weld metal, followed by the heat-affected zone and the base metal, and the lowest fracture toughness in the fusion zone, which is in agreement with the results of the metallographic testing. Furthermore, the relative errors of the zones obtained by the ball indentation method and the boundary effect modelling method ranging from 10.16 to 19.05%, which indicates safety margin ought to be considered for employing the BI method to determine fracture properties of in-service structures.

AVOTREX: A Global Dataset of Extinct Birds and Their Traits

ABSTRACTMotivationHuman activities have been reshaping the natural world for tens of thousands of years, leading to the extinction of hundreds of bird species. Past research has provided evidence of extinction selectivity towards certain groups of species, but trait information is lacking for the majority of clades, especially for prehistoric extinctions identified only through subfossil remains. This incomplete knowledge potentially obscures the structure of natural communities, undermining our ability to infer changes in biodiversity across space and time, including trends in functional and phylogenetic diversity. Biases in currently available trait data also limit our ability to identify drivers and processes of extinction. Here we present AVOTREX, an open‐access database of species traits for all birds known to have gone extinct in the last 130,000 years. This database provides detailed morphological information for 610 extinct species, along with a pipeline to build phylogenetic trees that include these extinct species.Main Types of Variables ContainedFor each extinct bird species, we provide information on the taxonomy, geographic location, and period of extinction. We also present data on island endemicity, flight ability, and body mass, as well as standard measurements of external (matching the AVONET database of extant birds) and skeletal morphology from museum specimens where available. To ensure comprehensive morphological data coverage, we estimate all missing morphological measurements using a data imputation technique based on machine learning. Finally, we provide an R package to graft all extinct species onto a global phylogeny of extant species (BirdTree).Spatial Location and GrainGlobal.Time Period and GrainAll known globally extinct bird species from 130,000 years ago up until 2024.Major Taxa and Level of MeasurementBirds (Class Aves), species level.Software FormatSpreadsheets (.csv) stored in Dryad.

Angiopoietin II in Critically Ill Septic Patients: A Post Hoc Analysis of the DRAK Study

Introduction: Angiopoietin II (Ang-II) plays a pivotal role in the development of microcirculatory dysfunction as it provokes endothelial barrier disruption in patients with sepsis or septic shock. In particular, those with acute kidney injury show high Ang-II concentrations. So far, it is unclear which covariates influence Ang-II concentration in the early phase of sepsis, especially if extracorporeal therapies also do. Methods: Ang-II concentrations were measured in 171 patients with sepsis after the first day of antibiotic treatment between 03/2013 and 01/2015. Ang-II was correlated with potential influencing factors (Spearman correlation). A multivariate model was established including the significant correlating parameters. The Mann–Whitney U test and the Kruskal–Wallis test were used to detect significant differences in Ang-II concentration. Results: The median Ang-II concentration was 8015 pg/mL (interquartile range (IQR): 5024–14,185). A total of forty patients were treated with kidney replacement therapy (KRT) and 20 were supported by venovenous extracorporeal membrane oxygenation (vv-ECMO). Sequential organ failure assessment (SOFA) score (r = 0.541), creatinine clearance (r = −0.467), urinary output (r = −0.289), interleukin (IL)-6 (r = 0.529), C-reactive protein (CRP) (r = 0.241), platelet count (r = −0.419), bilirubin (r = 0.565), lactate (r = 0.322), KRT (r = 0.451), and fluid balance (r = 0.373) significantly correlated with Ang-II concentration and were included in the multivariate model. There, creatinine clearance (p &lt; 0.01, b = −26.3, 95% confidence interval (CI) −41.8–−10.8), fluid balance (p = 0.002, b = 0.92, 95% CI 0.33–1.51), and CRP (p = 0.004, b = 127.6, 95% CI 41.6–213.7) were associated with Ang-II concentration. Furthermore, patients with KRT (median: 15,219 pg/mL, IQR: 10,548–20,270) had significantly (p &lt; 0.01) higher Ang-II concentrations than those with vv-ECMO support (median: 6412 pg/mL, IQR: 5246–10,257) or those without extracorporeal therapy (median: 7156 pg/mL, IQR: 4409–12,741). Conclusion: Increased CRP, positive fluid balance, and impaired kidney function were associated with higher Ang-II concentrations in critically ill patients in the early stage of sepsis in this post hoc analysis. In particular, patients with KRT had very high Ang-II concentrations, whereas the use of vv-ECMO was not related to higher Ang-II concentrations. The significance for clinical practice should be clarified by a prospective study with standardized measurements.

Assessment of Kidney Function Discrepancies in Pediatric CAKUT Patients Using Bedside Schwartz Equation and Renal Scintigraphy

Background and Objectives: This research explores the correlation between estimated glomerular filtration rates (eGFR) obtained using the bedside Schwartz equation, and renal scintigraphy in children with congenital kidney and urinary tract abnormalities (CAKUT). The objective is to enhance understanding and management of renal health in this demographic by analyzing kidney size-function relationships. Methods: A retrospective observational analysis was performed on 94 pediatric CAKUT patients at the “Louis Turcanu” Emergency Hospital for Children, Timisoara. Kidney function data, extracted from medical records, were evaluated using the Schwartz equation, renal scintigraphy, and the gold standard iohexol clearance. Ethical approval was secured for the study, which employed descriptive and inferential statistical methods, including t-tests and correlation coefficients, to compare eGFR values. Results: Significant variances were found in eGFRs across different body surface area (BSA) percentiles. For instance, the eGFR for the right kidney in the 25th–50th BSA percentile (102.02 ± 41.52 mL/min/BSA) was notably higher than that of the left (35.60 ± 26.05 mL/min/BSA; p = 0.01). The overall sample reflected a higher eGFR in the right kidney (76.03 ± 40.91 mL/min/BSA) compared to the left (57.46 ± 35.91 mL/min/BSA; p = 0.02). Additionally, a strong positive Pearson correlation (r = 0.80, p = 0.02) was found between scintigraphy and ultrasound measures in the 50th–75th percentiles for left renal percentiles, demonstrating consistent patterns across different evaluations of kidney function. Conclusions: This comparison indicates a complex relationship between eGFR values and kidney size, suggesting potential inaccuracies in standard bedside eGFR measurements for pediatric CAKUT patients. The findings underscore the necessity for accurate diagnostic tools specifically designed for pediatric applications and advocate for the integration of multiple diagnostic techniques to improve clinical management.

Online unsupervised performance-based cognitive testing: A feasible and reliable approach to scalable cognitive phenotyping of Parkinson's patients

IntroductionA better understanding of the heterogeneity in the cognitive and mood symptoms of Parkinson's disease will require research conducted in large samples of patients. Fully online and remote research assessments present interesting opportunities for scaling up research but the feasibility and reliability of remote and fully unsupervised performance-based cognitive testing in individuals with Parkinson's disease is unknown. This study aims to establish the feasibility and reliability of this testing modality in Parkinson's patients. MethodsSixty-seven Parkinson's patients and 36 older adults completed two sessions of an at-home, online battery of five cognitive tasks and three self-report questionnaires. Feasibility was established by examining completion rates and data quality. Test-retest reliability was evaluated using the Intraclass Correlation Coefficient (ICC (2,1)). ResultsOverall completion rates and data quality were high with few participant exclusions across tasks. With regards to test-retest reliability, intraclass correlation coefficients were quite variable across measures extracted from a task as well as across tasks, but at least one standard measure from each task achieved moderate to good reliability levels. Self-report questionnaires achieved a higher test-retest reliability than cognitive tasks. Feasibility and reliability were similar between Parkinson's patients and older adults. ConclusionThese results demonstrate that remote and unsupervised testing is a feasible and reliable method of measuring cognition and mood in Parkinson's patients that achieves levels of test-retest reliability that are comparable to those reported for standard in-person testing.

What impact does urinary and anal incontinence have on a woman’s quality of life?

The impact of pelvic floor dysfunction is often far-reaching, and can have a devastating impact on women’s lives. In the past 50 years, the concept of quality of life (QOL) has been increasingly used, but despite acceptance that relevant data are an important metric, there is little mention of it within the available pelvic-health-related grey literature. Therefore, this literature review looks at the published evidence to evaluate the impact that urinary incontinence (UI) and anal incontinence (AI) have on a woman’s QOL. A systematic search was conducted that involved MEDLINE, CINAHL, AMED, Google Scholar, pertinent grey literature and a hand-search of reference lists in relevant papers published in the English language between 2012 and 2022. The inclusion criteria were limited to two elements of pelvic health, i.e. UI and AI, because these are common, definable symptoms, and articles tend to focus on condition-specific, health-related QOL. The literature search was also limited to “titles only” because of the high-volume return rate when “abstract and title” was employed. Among the 418 papers initially identified, five met the eligibility criteria: three were specific to UI; and two focused on AI as a result of obstetric anal sphincter injuries and its impact on QOL. The literature review identified three themes: QOL is negatively affected by UI and AI; UI and AI have a negative impact across the different domains of QoL; and finally, there are geographical variations in UI and AI. It also offered some insight into the risk factors for and the prevalence of UI and AI that was in keeping with current literature. Continence is considered to be among the most basic of needs. These findings support the perception that UI and AI are both prevalent, and have a myriad of far-reaching consequences that negatively impact QOL. The results of this literature review demonstrate that there is a clear need for QOL measures in pelvic health research. However, there is also a need for standardized outcome measures to allow for a greater depth of synthesis, and where possible, meta-analysis. Future research needs to ensure that geographical and ethnicity data are considered and accurately reported in order to gain deeper insights and address known health inequalities. In line with current thinking, health professionals and women themselves should be made aware of the prevalence of and known risk factors for UI and AI so that they can focus on prevention and early recognition to optimize lifelong pelvic health.

Use of passively collected actigraphy data to detect individual depressive symptoms in a clinical subpopulation and a general population.

The presentation of major depressive disorder (MDD) can vary widely due to its heterogeneity, including inter- and intraindividual symptom variability, making MDD difficult to diagnose with standard measures in clinical settings. Prior work has demonstrated that passively collected actigraphy can be used to detect MDD at a disorder level; however, given the heterogeneous nature of MDD, comprising multiple distinct symptoms, it is important to measure the degree to which various MDD symptoms may be captured by such passive data. The current study investigated whether individual depressive symptoms could be detected from passively collected actigraphy data in a (a) clinical subpopulation (i.e., moderate depressive symptoms or greater) and (b) general population. Using data from the National Health and Nutrition Examination Survey, a large nationally representative sample (N = 8,378), we employed a convolutional neural network to determine which depressive symptoms in each population could be detected by wrist-worn, minute-level actigraphy data. Findings indicated a small-moderate correspondence between the predictions and observed outcomes for mood, psychomotor, and suicide items (area under the receiver operating characteristic curve [AUCs] = 0.58-0.61); a moderate-large correspondence for anhedonia (AUC = 0.64); and a large correspondence for fatigue (AUC = 0.74) in the clinical subpopulation (n = 766); and a small-moderate correspondence for sleep, appetite, psychomotor, and suicide items (AUCs = 0.56-0.60) in the general population (n = 8,378). Thus, individual depressive symptoms can be detected in individuals who likely meet the criteria for MDD, suggesting that wrist-worn actigraphy may be suitable for passively assessing these symptoms, providing important clinical implications for the diagnosis and treatment of MDD. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Narrative Review: Telemedicine Quality after the COVID-19 Public Health Emergency: Time to Reevaluate?

OBJECTIVE: This narrative review explores concerns and potential solutions for improving the quality of synchronous telemedicine visits for high utilizers like primary care, particularly after the COVID-19 pandemic. METHODS: A literature review identified studies published within the past 10 years focusing on telemedicine quality, primary care, and related aspects like liability, virtual exams, and patient safety. RESULTS: Despite the surge in popularity of telemedicine visits, concerns regarding their quality linger. These concerns encompass various aspects of the patient experience, administrative processes, and potential safety risks. Limitations in physical exam capabilities and the lack of readily available vital signs during telemedicine visits raise concerns about the accuracy of diagnoses. This is particularly true for situations requiring a more comprehensive physical assessment. Incomplete documentation due to abbreviated patient histories, missing physical exam findings, and the reliance on generic templates pose liability risks. This lack of thorough information makes it challenging to accurately capture the patient's condition and raises concerns about the quality of care provided. Patients themselves have expressed concerns about accuracy of a virtual visit, thus raising questions about the effectiveness of telemedicine in building rapport and ensuring clear communication. From an administrative standpoint, fears of misdiagnosis due to the limitations of virtual exams, inconsistencies in insurance coverage for telemedicine services, and unclear reimbursement standards for thorough visits continue to pose challenges. These uncertainties create ambiguity and make it difficult for healthcare providers to fully embrace telemedicine as a viable option. Finally, although mirroring in-person visit protocols for patient safety is considered crucial, many organizations currently lack standardized measures to ensure safety throughout the entire telemedicine journey. This includes potential risks during scheduling, appointment execution, and post-visit follow-up, highlighting the need for more robust safety protocols specifically designed for the telemedicine setting. Addressing these concerns is essential for ensuring the quality and sustainability of telemedicine integration. CONCLUSION: While telemedicine offers significant benefits, improving quality is essential for its sustainable integration into primary care. Standardizing protocols, educating clinicians and patients, implementing comprehensive physical exam procedures, and ensuring patient safety throughout the visit are key areas for improvement. Continuous monitoring and data analysis are crucial for identifying and addressing weaknesses and ensuring quality telemedicine care.

Association of Body Mass Index (BMI) with Diet, Physical Activity, and Lifestyle among Undergraduate Dental Students in a Private Dental College in Bangladesh

Background: Obesity can lead to severe health problems and elevate the risk of diseases such as hypertension, dyslipidemia and diabetes due to metabolic changes. Undergraduate dental students often struggle to maintain a healthy lifestyle and eating habits due to academic pressures. BMI, a standard obesity measure, is simple to calculate and assess nutritional status, helping to identify and prevent obesity-related diseases in at-risk individuals. Method: A cross-sectional study was performed among 253 students of Sapporo Dental College, a private dental college in Uttara, Dhaka, Bangladesh, to reveal the prevalence of overweight and obesity according to BMI and its association with dietary habits, physical activities, and lifestyles among them. Data was collected using a self-written, anonymous, semi-structured questionnaire using the convenient sampling technique between July 2023 and September 2023. Result: Among the 253 participants, females (n = 190, 75.10%) are more than males (n = 63, 25%). The prevalence of normal weight, underweight, overweight, and obesity among the participants was 132 (37.93%), 31 (8.91%), 56 (16.09%), and 129 (37.07%), respectively, based on BMI. 84% of obese students were taken 1 meal from outside per day (p values &lt; 0.05). 52% obese students did not engage in any form of physical activity on a weekly basis (p value 0.03). 55.5% obese students slept for &lt; 6 hours every night (p-value 0.04). Conclusion: Early modifications of lifestyle improve health. Annual screenings help to prevent obesity. Fitness and diet programs can reduce dental students' chronic disease risk. Study participants are future physicians. Thus, dental students should be physically active and aware of their eating and sleep habits to reduce obesity, which might influence patients' outlooks. Update Dent. Coll. j: 2024; 14(2):15-20

Effects of Multimodal Analgesia Combined with Comfort Management on Pain and Stress Indexes in Patients with Orthopedic Trauma after Intervention: A Retrospective Study.

This study aims to assess the impact of combining multimodal analgesia with comfort care on pain levels, stress, negative emotions, and quality of life in individuals recovering from traumatic fractures. This retrospective study analyzed clinical data from traumatic fracture patients who underwent emergency operations at our hospital between June 2022 and February 2024. Patients were divided into two groups based on their postoperative pain management: the control group, which received standard measures, and the exposure group, which received a combination of multimodal analgesia and comfort-based care. We compared these groups for pain intensity (baseline and activity Visual Analog Scale (VAS) scores), serum stress biomarkers (norepinephrine, adrenaline, cortisol), emotional distress (self-rating depression scale (SDS), and the self-rating anxiety scale (SAS)), and overall quality of life (Comprehensive Quality of Life Assessment Questionnaire (GQOLI-74) score). Overall, this study evaluated differences in postoperative complications between the two pain management approaches. In this study, we included 101 participants, 41 in the exposed group and 60 in the control group. Before the intervention, baseline characteristics were similar between the two groups (p > 0.05). However, one week after the intervention, the resting and active VAS scores were significantly reduced in the exposed group than in the control group (p < 0.05). Furthermore, one week after the intervention, the exposed group had lower levels of serum sodium, epinephrine, cortisol, stress, and anxiety, as well as higher physical and mental health scores on the GQOLI-74 scale. During the intervention period, there was no significant difference in postoperative complications between the two groups (p > 0.05). Combining multi-mode analgesia with comfort management for patients with traumatic fractures significantly reduces postoperative pain and stress levels. Additionally, this approach can effectively enhance patients' negative emotions and improve their quality of life. This approach holds significant promise for practical use in clinical settings.

Pulmonary Emphysema Disease Classification Model Using Deep Structured Techniques

Emphysema is normally employed in the sense of morphology, and thus, imaging the modalities has a significant part in detecting the disorder. Most importantly, the High-Resolution Computed Tomography (HRCT) is a trustworthy component for illustrating the emphysema pathology. Hence, the pulmonary emphysema diagnosis at the starting stage is very important and can secure the life of a human. When there is a failure in the technique, there is a possibility of the death that displays the importance of effective diagnosis. The endotracheal intubation’s delay is prevented by implementing distinct mechanisms that result in various requirements. The presented work develops a deep learning-aided pulmonary emphysema disease classification model that is implemented to defeat the above difficulties. At first, the images are accumulated from a standard dataset. Then, the collected images are provided to the phase of segmentation. Here, the newly developed Adaptive Trans-Residual Dense UNet (ATRDUNet) is employed to perform the segmentation process. Also, the recommended ATRDUNet model helps to locate the disease in the appropriate location. Moreover, the performance of the segmentation process is enriched to fine-tune the parameter using the Fitness Revised Position of Wild Horse Optimizer (FRP-WHO). While optimizing the parameters effectively, it tends to handle the complex issues to strengthen the model accurately. The segmented results from the ATRDUNet are passed to Vision Transformer-based Residual DenseNet with LSTM layer (ViTrans-RDLSTM) for getting the final classified outcome. To this end, the analysis of the suggested model is correlated to find the effectiveness of the recommended model. However, these results are examined with the help of standard performance measures. Also, the experimentation is carried out using the standard “Automatic emphysema detection using weakly labeled HRCT lung images” dataset to attain better outcomes in the developed model. The findings of the recommended approach show 95% in terms of accuracy. Also, the statistical analysis of the developed model shows 23.9%, 12.3%, 15.2%, and 13.0% better performance than BWO, CO, HBA, and WHO in terms of mean analysis to show enriched performance.

A 3D Statistical Shape Model of the Right Ventricular Outflow Tract in Pulmonary Valve Replacement Patients Post-Surgical Repair.

Assessment of the right ventricular outflow tract and pulmonary arteries (RVOT) for percutaneous pulmonary valve implantation (PPVI) uses discrete measurements (diameters and lengths) from medical images. This multi-centre study identified the 3D RVOT shape features prevalent in patients late after surgical repair of congenital heart disease (CHD). A 3D RVOT statistical shape model (SSM) was computed from 81 retrospectively selected CHD patients (14.7 ± 6.8 years) who required pulmonary valve replacement late after surgical repair. A principal component analysis identified prevalent shape features (modes) within the population which were compared with standard geometric measurements (diameter, length and surface area) and between sub-groups of diagnosis, RVOT type and dysfunction. Shape mode 1 and 2 represented RVOT size and curvature and tapering and length, respectively. Shape modes 3-5 related to branch pulmonary artery calibre, conical vs. bulbous RVOTs and RVOT curvature, respectively. Tetralogy of Fallot, transannular patch type and regurgitant RVOTs were larger and straighter while conduit and stenotic types were longer and more cylindrical than other subgroups. This SSM analysed the main 3D shape features present in a population of RVOTs, exploiting the wide 3D anatomical information provided by routine imaging. This morphological information may have implications for PPVI patient selection and device design.