Significant Implications For Healthcare Research Articles

Weighted vest intervention during whole-body circuit training improves serum resistin, insulin resistance, and cardiometabolic risk factors in normal-weight obese women

Background and objectivesObesity is a well-known cause of cardiovascular disease and metabolic disorders. Normal-weight obesity, where the body mass index(BMI) is within the normal range but the body fat percentage is high, also adversely impacts cardiovascular and metabolic health. This study explored the effects of whole-body circuit training using a weighted vest on serum resistin, insulin resistance, and cardiovascular disease risk factors in normal-weight obese women. MethodsThirty-six normal-weight obese women were divided into three groups: Weighted Vest Circuit Training(WVCT)(n = 12), Body Weight Circuit Training(BWCT)(n = 12), and a Control group(CON)(n = 12). Participants in the WVCT and BWCT groups engaged in whole-body circuit training three times per week for eight weeks. Serum resistin, cardiovascular disease risk factors, and insulin resistance were measured before and after the intervention. ResultsThe study revealed significant and impactful findings. There were substantial improvements in body composition(Skeletal Muscle Mass: +7.5 %, p = 0.042, d = 0.80), Serum Resistin(-38.2 %, p = 0.001, d = 0.85), insulin resistance(HOMA-IR: 27.1 %, p < 0.001, d = 0.88), and a reduction in IL-6 levels(-25.4 %, p = 0.082, d = 0.60) in the WVCT group compared to the BWCT and CON groups. The WVCT group outperformed the other groups, demonstrating greater effectiveness in reducing cardiovascular risk factors. ConclusionThese findings have significant implications for healthcare. Whole-body circuit training with weighted vests has effectively improved body composition, reduced serum resistin, and lowered insulin resistance, reducing cardiovascular disease risk factors in normal-weight obese women. These results could inform and enhance the treatment and management of obesity-related cardiovascular and metabolic disorders.

Enhancing diagnostic accuracy in symptom-based health checkers: a comprehensive machine learning approach with clinical vignettes and benchmarking.

The development of machine learning models for symptom-based health checkers is a rapidly evolving area with significant implications for healthcare. Accurate and efficient diagnostic tools can enhance patient outcomes and optimize healthcare resources. This study focuses on evaluating and optimizing machine learning models using a dataset of 10 diseases and 9,572 samples. The dataset was divided into training and testing sets to facilitate model training and evaluation. The following models were selected and optimized: Decision Tree, Random Forest, Naive Bayes, Logistic Regression and K-Nearest Neighbors. Evaluation metrics included accuracy, F1 scores, and 10-fold cross-validation. ROC-AUC and precision-recall curves were also utilized to assess model performance, particularly in scenarios with imbalanced datasets. Clinical vignettes were employed to gauge the real-world applicability of the models. The performance of the models was evaluated using accuracy, F1 scores, and 10-fold cross-validation. The use of ROC-AUC curves revealed that model performance improved with increasing complexity. Precision-recall curves were particularly useful in evaluating model sensitivity in imbalanced dataset scenarios. Clinical vignettes demonstrated the robustness of the models in providing accurate diagnoses. The study underscores the importance of comprehensive model evaluation techniques. The use of clinical vignette testing and analysis of ROC-AUC and precision-recall curves are crucial in ensuring the reliability and sensitivity of symptom-based health checkers. These techniques provide a more nuanced understanding of model performance and highlight areas for further improvement. This study highlights the significance of employing diverse evaluation metrics and methods to ensure the robustness and accuracy of machine learning models in symptom-based health checkers. The integration of clinical vignettes and the analysis of ROC-AUC and precision-recall curves are essential steps in developing reliable and sensitive diagnostic tools.

Smart Health Monitoring with Power-Aware IoT Using a Wireless Body Area Network

Smart health monitoring systems have become increasingly popular in recent years due to the growth of the Internet of Things (IoT) technology and its applications in healthcare. This project proposes an IoT-based smart health monitoring system that utilises an ESP32 Microcontroller, MAX30100 Pulse Oximeter Heart Rate Sensor Module, MLX90614 ESF Non-Contact Human Body Infrared Temperature Measurement Module, LCD 16*2, 3.7v 2000mAh Lithium Battery, TP4056 1A Li-Ion Lithium Battery charging Module, and some buttons. The system is designed to monitor the user's heart rate, blood oxygen level, and body temperature in real-time and display the readings on an LCD screen as well as an IoT web page. The project aims to provide an affordable, portable, and user-friendly smart health monitoring solution that can be used at home, in hospitals, or other healthcare settings. The project methodology involved a combination of hardware and software components, including circuit design and programming using the Arduino IDE. The system was tested and evaluated for its performance, accuracy, and usability using a sample population. The results showed that the system was effective in monitoring the user's vital signs and displaying the readings in real-time. The system was found to be accurate and reliable, with a high level of user satisfaction and ease of use. Overall, the IoT-based smart health monitoring system proposed in this project has significant implications for healthcare, particularly in terms of remote monitoring, telemedicine, and personalised healthcare. The system has the potential to improve patient outcomes, reduce healthcare costs, and increase access to healthcare services. The project also highlights the potential of IoT technology in healthcare and the need for further research and development in this area

Defining anthropometric thresholds (mid-arm circumference and calf circumference) in older adults residing in the community: a cross-sectional analysis using data from the population representative Longitudinal Aging Study in India (LASI DAD)

ObjectivesTo identify factors associated with malnutrition (undernutrition and overnutrition) and determine appropriate cut-off values for mid-arm circumference (MAC) and calf circumference (CC) among community-dwelling Indian older adults.DesignData from the first...

Automated solid phase DNA extraction on a lab-on-a-disc with two-degrees of freedom instrumentation

BackgroundLab-on-a-disc (LoaD) technology has emerged as a transformative approach for point-of-care diagnostics and high-throughput testing. The promise of integrating multiple laboratory functions onto a single integrated platform has significant implications for healthcare, especially in resource-limited settings. However, one of the primary challenges faced in the design and manufacture of LoaD devices is the integration of effective valving mechanisms. These valves are essential for fluid control and routing, but their intricacy often leads to complexities in design and increased vulnerability to failure. This emphasizes the need for improved designs and manufacturing processes without complex, integrated valving mechanisms. (96) ResultsWe describe a fully automated biological workflow and reagent actuation on a LoaD device without an integrated valving system. The Two Degrees-of-Freedom (2DoF) custom centrifuge alters the centre of rotation, facilitating fluid flow direction changes on the microfluidic platform through a custom programmed interface. A novel 360-degree fluid manipulation approach via secondary planetary gear motion enabled sequential assay reagent actuation without embedded valve triggering, with the addition of infinite incubation times and efficient use of platform realty. The simplified LoaD platform uses clever design, with intermediate flow chambers to avoid cross contamination between reagent steps. Notably, the optimized LoaD platform demonstrated a two-fold DNA yield at higher HEK-293 cell concentrations compared to commercially available spin-column kits. This significantly simplified LoaD platform successfully automated a common, complex workflow without inhibiting DNA purification. (129) SignificanceThis system exhibits the clever coupling of both 2DoF and centrifugal microfluidics to create an autonomous testing package capable of eradicating the need for complex valving systems to automate biological workflows on LoaDs. This automated system has outperformed commercially available DNA extraction kits for higher cell counts. The platform's elimination of valve requirements ensures unlimited sample incubation times and enhances reliability, making it a straightforward option for automated biological workflows, particularly in diagnostics. (73)

The impact of the COVID-19 pandemic on nasopharyngeal carcinoma patients – a national cancer centre experience

Purpose or objectiveThe COVID-19 pandemic has resulted in significant healthcare implications, with care for cancer patients compromised due to resource diversion towards battling the pandemic. We aim to investigate the impact of the peak wave of the pandemic in 2020 on the delivery of cancer care in Singapore, specifically via our nasopharyngeal carcinoma (NPC) treatment data. This study applies real world numbers to the impact of COVID-19 on cancer care delivery in Singapore. The choice of nasopharyngeal cancer allows a good direct estimate of common treatment measures such as time to biopsy, time to staging scans, time to treatment commencement, due to its clear protocol and algorithms for staging and treatment; thus serving as an excellent surrogate for the effectiveness and timeliness of the different aspects of cancer care delivery.Materials and methodsIn this retrospective study, we included all patients with newly diagnosed NPC from 1st January to 31st May from 2017 to 2020 at our centre. This time period was chosen as it coincided with the period in 2020 during the COVID-19 pandemic where there was the most strain on healthcare resources and the most restrictions on population movement within Singapore, which may impact on healthcare seeking behaviour. Narrowing down the time period to the first 5 months of the 4 respective years also allowed us to reduce the effect of annual seasonal variation in patient numbers seen as a result of holidays and festive periods such as the Lunar New Year and scheduled school holidays. Electronic medical records (EMR) were accessed. Only newly diagnosed NPC cases were included in our analysis. Patients with second synchronous primary malignancies or NPC disease recurrence were excluded. Data analysis was carried out using a combination of SPSS and Microsoft Excel.ResultsSignificantly, there was a reduction of 37–46.3% in newly diagnosed NPC cases during the peak of the COVID-19 pandemic from January to end May 2020 compared to the preceding three years. Despite the reduction in numbers of newly diagnosed NPC, there was no statistically significant differences in delay from biopsy to the first radiation oncology visit and from biopsy to the first day of treatment in 2020 compared to the preceding years. All the patients treated in our centre also received the standard NPC treatment for their disease stage as per international guidelines.ConclusionWe recommend a heightened awareness of the dangers of delaying cancer presentation and care in healthcare policies and resource allocation and at the same time, encourage patient’s confidence in their ability to seek care. With the resurgence of new COVID-19 variants and case numbers worldwide and in Singapore, this study focuses upon the need to be aware of the exigencies of other clinical groups in resource utilization. It would be instructive to compare this study with future long term follow up to investigate the trajectory of our cancer care delivery, as well as survival outcomes.

Frailty trajectory predicts subsequent cognitive decline: A 26-year population-based longitudinal cohort study.

Frailty refers to a decline in the physiological functioning of one or more organ systems. It remained unclear whether variations in the trajectory of frailty over time were associated with subsequent cognitive change. The aim of the current study was to investigate the association between frailty trajectories and subsequent cognitive decline based on the Health and Retirement Study (HRS). A total of 15,454 participants were included. The frailty trajectory was assessed using the Paulson-Lichtenberg Frailty Index, while the cognitive function was evaluated using the Langa-Weir Classification. Results showed that severe frailty was significantly associated with the subsequent decline in cognitive function (β [95% CI]=-0.21 [-0.40, -0.03], p=0.03). In the five identified frailty trajectories, participants with mild frailty (inverted U-shaped, β [95% CI]=-0.22 [-0.43, -0.02], p=0.04), mild frailty (U-shaped, β [95% CI]=-0.22 [-0.39, -0.06], p=0.01), and frailty (β [95% CI]=-0.34 [-0.62, -0.07], p=0.01) were all significantly associated with the subsequent cognition decline in the elderly. The current study suggested that monitoring and addressing frailty trajectories in older adults may be a critical approach in preventing or mitigating cognitive decline, which had significant implications for healthcare.

Hybrid Deep Learning Approach for Accurate Tumor Detection in Medical Imaging Data.

The automated extraction of critical information from electronic medical records, such as oncological medical events, has become increasingly important with the widespread use of electronic health records. However, extracting tumor-related medical events can be challenging due to their unique characteristics. To address this difficulty, we propose a novel approach that utilizes Generative Adversarial Networks (GANs) for data augmentation and pseudo-data generation algorithms to improve the model's transfer learning skills for various tumor-related medical events. Our approach involves a two-stage pre-processing and model training process, where the data is cleansed, normalized, and augmented using pseudo-data. We evaluate our approach using the i2b2/UTHealth 2010 dataset and observe promising results in extracting primary tumor site size, tumor size, and metastatic site information. The proposed method has significant implications for healthcare and medical research as it can extract vital information from electronic medical records for oncological medical events.

The role of obesity on urinary incontinence and anal incontinence in women: a review.

Obesity prevalence is increasing worldwide, with significant healthcare implications. We searched PubMed/MEDLINE, Embase and the Cochrane Library for articles registered until June 2020 to explore the relationship between obesity and urinary (UI) and anal incontinence (AI). Obesity is associated with low-grade, systemic inflammation and proinflammatory cytokine release, producing reactive oxygen species and oxidative stress. This alters collagen metabolism and, in combination with increased intra-abdominal pressure, contributes to the development of UI. Whereas in AI, stool consistency may be a factor. Weight loss can reduce UI and should be a management focus; however, the effect of weight loss on AI is less clear.

Betrokken vertwijfeling: een intersectionele analyse van partnergeweld in de huisartsenpraktijk

Abstract Intimate Partner Violence (IPV) is a major societal problem with significant healthcare implications. The consequences of this kind of violence result in victims (and perpetrators) regularly needing healthcare. Various structural barriers can prevent victims from accessing services or result in inadequate responses to their needs. International research shows that general practitioners can play an important role in tackling IPV but that they also are confronted with various difficulties themselves. Drawing on seventeen in-depth interviews with general practitioners in Flanders, we discuss in this article the experiences of GPs who come across IPV in their health care practice. We use an intersectional approach to better understand the difficulties GPs face by looking at the complexity underlying these cases and by exploring GPs’ understanding of vulnerabilities of marginalised groups. A thematic data analysis was applied. Using a number of case studies, we found that GPs are confronted with various structural barriers that complicate the care of patients who are victims of IPV. This gives rise to alternative care strategies, which are based on a sentiment of ‘involved incertitude’.

Intracellular detection and communication of a wireless chip in cell

The rapid growth and development of technology has had significant implications for healthcare, personalized medicine, and our understanding of biology. In this work, we leverage the miniaturization of electronics to realize the first demonstration of wireless detection and communication of an electronic device inside a cell. This is a significant forward step towards a vision of non-invasive, intracellular wireless platforms for single-cell analyses. We demonstrate that a 25 upmu m wireless radio frequency identification (RFID) device can not only be taken up by a mammalian cell but can also be detected and specifically identified externally while located intracellularly. The S-parameters and power delivery efficiency of the electronic communication system is quantified before and after immersion in a biological environment; the results show distinct electrical responses for different RFID tags, allowing for classification of cells by examining the electrical output noninvasively. This versatile platform can be adapted for realization of a broad modality of sensors and actuators. This work precedes and facilitates the development of long-term intracellular real-time measurement systems for personalized medicine and furthering our understanding of intrinsic biological behaviors. It helps provide an advanced technique to better assess the long-term evolution of cellular physiology as a result of drug and disease stimuli in a way that is not feasible using current methods.

Inter-generational Effects of Technology: Why Millennial Physicians May Be Less at Risk for Burnout Than Baby Boomers.

Purpose of ReviewYounger generations of physicians are using technology more fluently than previous generations. This has significant implications for healthcare as these digital natives become a majority of the population’s patients, clinicians, and healthcare leaders.Recent FindingsHistorically, healthcare has been slow to adopt new technology. Many physicians have attributed burnout symptoms to technology-related causes like the EMR. This is partly due to policies and practices led by those who were less familiar and comfortable with using new technologies.SummaryYounger physicians will drive technological advancement and integration faster than previous generations, allowing technology to adapt more quickly to serve the needs of clinicians and patients. These changes will improve efficiency, allow more flexible working arrangements, and increase convenience for patients and physicians. The next generation of physicians will use technology to support their work and lifestyle preferences, making them more resilient to burnout than previous generations.

Distributed Biological Foundries for Global Health.

Historically, many industries such as manufacturing have undergone a trend away from centralized, large-scale production toward a more distributed form. Currently, this same trend is witnessed in biological manufacturing and bioprocessing, with the rise of biological foundries where one can synthesize, grow, isolate, and purify a broad range of biologics. The adoption of distributed practices for biological processing has significant implications for healthcare, diagnostics, and therapies. This essay discusses the many diverse factors that have facilitated this growth, ranging from the establishment of available biological components, or "parts," low-cost programmable hardware, and others. Currently existing examples of distributed biological foundries are also identified, separating the discussion into those that are accessible only by elite users and the more recent emerging foundries that are more accessible to the general population. Taking lessons from other fields, it is argued that this trend toward distributed biological manufacturing is inevitable, so adapting to this trend is important for the progress of creating new therapeutics, sensors, diagnostics, and reagents for biomedical applications.

Complex multigestational anomalies

The increase in multiple gestation pregnancies has resulted in significant health care implications for both mother and child. Our ability to diagnose and intervene on an at-risk multi-gestation pregnancy has dramatically improved. It is important for the pediatric surgeon to be equipped with a basic fund of knowledge concerning these pregnancies. An understanding of amnionicity and chorionicity will equip the practitioner with the ability to identify which pregnancies are at risk for specific complications. This article highlights multi-gestation pregnancies that are monochorionic (single shared placenta) and can be complicated by twin-twin transfusion syndrome (TTTS), twin reversed arterial perfusion (TRAP) sequence, twin anemia polycythemia sequence (TAPS), or selective fetal intrauterine growth restriction (sIUGR). The risk of fetal demise is significant in these pregnancies. Understanding recommended surveillance and warning signs can alert surgeons to developing complications. Specialized fetal care centers possess the ability to intervene on these pregnancies in utero.

Living with Hereditary Haemorrhagic Telangiectasia: stigma, coping with unpredictable symptoms, and self-advocacy

Objective: Hereditary Haemorrhagic Telangiectasia (HHT) is a genetic condition causing frequent nose bleeds, skin lesions (telangiectasia) and arteriovenous malformations. Approximately, 50% of people experience life-threatening HHT symptoms including haemorrhages in the brain, lungs and liver. This study aimed to gain a qualitative understanding of the psychosocial impact of HHT over time. Design: Using a phenomenological framework, a rigorous narrative analysis was performed on 20 semi-structured interviews with individuals with HHT aged 20s–60s. Main outcome measures: Qualitative themes explaining life experiences prior to and following a clinical diagnosis of HHT. Results: Narratives highlighted four psychosocial themes: (i) the psychological impact of visible symptoms was significant and related to experiences of social stigma, (ii) individuals struggled to identify triggers of symptoms in order to reduce unpredictability, (iii) an illness identity was rejected by minimising HHT when talking about the present self, and by positive reframing as ‘lucky’ and (iv) self-advocacy was necessitated due to lack of expert coordinated care. Conclusion: HHT has a demanding impact on social, physical and psychological well-being. These findings have significant implications for health care, as narratives about interactions with health professionals often used the terms ‘frustrating’ and ‘not being heard’.

The global challenge of ageing population – Part I: Definitions, epidemiology and physiological changes

Background &amp; Objectives Over the past 50 years, epidemiological data from the World Health Organisation has demonstrated a trend towards population ageing throughout the world. While this is widely recognised in the developed world, the phenomenon has been largely overlooked in the developing world, despite the fact that the rate of ageing in developing countries far outstrips that of developed countries. This global trend towards an increasingly older society has significant implications for healthcare. This article aims to review the definitions of ageing, its epidemiological characteristics and physiological changes associated with ageing. Methods A narrative review of the literature was undertaken using Medline, CINAHL and the Cochrane Database, supplemented by manual searches of the literature, and guided by the reference lists of relevant papers identified in the electronic search. No restriction was placed on the type of paper to be included in the study. Results The initial electronic search of the three databases included 239 papers, of which 60 were found to be relevant and included in this review. These articles discussed the epidemiology and definition of ageing, the physiology of ageing and its impact on health and illness, and the implications for health services. The overall findings of the studies implicate the clear differences in the physiology of older people, which do create specific challenges for health service provision. Conclusion Population ageing is a significant global phenomenon, affecting both developed and developing regions of the world. More work is needed, particularly in the developing world, to better understand the impact of ageing on our population.

Automatic seizure detection by modified line length and Mahalanobis distance function

Abstract Automatic seizure detection with high accuracy and in linear time has profound implications on therapeutic intervention mechanisms. In this work taking into account 12 popular seizure detection algorithms we have shown that line length is one feature that is extractable in linear time from EEG signals and capable of automatic seizure onset detection with highest accuracy among linear time extractable features. Also line length is less prone to give false positives. The detection accuracy has been ascertained by ROC curve analysis on Freiburg Seizure Prediction Project data containing intracranial EEG recordings of 87 seizures from 21 patients with sufficient interictal signals. Next, we have modified the classical line length feature extraction algorithm to improve its accuracy without any additional computational burden. Finally, we have applied both classical line length (LL) and modified line length (MLL) on all focal channels and detected seizures on multidimensional focal channel signals by Mahalanobis distance function (MDF). Both detected 73 out of 87 seizures. Area under the ROC curve (AUC), detection delay and false positive for LL and MLL are 0.951, 11.903 s, 0.201/h and 0.954, 11.698 s, 0.198/h respectively. Since LL has already been incorporated into an FDA approved commercially available closed loop intervention system, even this minute improvement may have significant healthcare implications.

Respondent driven sampling of wheelchair users: A lack of traction?

Internationally, wheelchair users are an emerging demographic phenomenon, due to their increased prevalence and rapidly increasing life-span. While having significant healthcare implications, basic robust epidemiological information about wheelchair users is often lacking due, in part, to this population's 'hidden' nature. Increasingly popular in epidemiological research, Respondent Driven Sampling (RDS) provides a mechanism for generating unbiased population-based estimates for hard-to-reach populations, overcoming biases inherent within other sampling methods. This paper reports the first published study to employ RDS amongst wheelchair users. Between October 2015 and January 2016, a short, successfully piloted, internet-based national survey was initiated. Twenty seeds from diverse organisations were invited to complete the survey then circulate it to peers within their networks following a well-defined protocol. A predetermined reminder protocol was triggered when seeds or their peers failed to respond. All participants were entered into a draw for an iPad. Overall, 19 people participated (nine women); 12 initial seeds, followed by seven second-wave participants arising from four seeds . Completion time for the survey ranged between 7 and 36 minutes. Despite repeated reminders, no further people were recruited. While New Zealand wheelchair user numbers are unknown, an estimated 14% of people have physical impairments that limited mobility. The 19 respondents generated from adopting the RDS methodology here thus represents a negligible fraction of wheelchair users in New Zealand, and an insufficient number to ensure equilibrium required for unbiased analyses. While successful in other hard-to-reach populations, applying RDS methodology to wheelchair users requires further consideration. Formative research exploring areas of network characteristics, acceptability of RDS, appropriate incentive options, and seed selection amongst wheelchair users is needed.

Delirium: The 21st century health care challenge for bedside clinicians

Delirium is a leading cause of preventable injury in hospitalized patients. Early recognition and intervention for delirium are critical to prevent morbidity and mortality, especially in the older population. Older patients are at increased risk for delirium owing to a combination of age-related changes and environmental factors. Health care providers, including nurses and physicians, often miss delirium symptoms and diagnosis in patients. Without early recognition and treatment, delirium can have significant life-changing consequences in our most vulnerable patients. This acute change in cognition can continue throughout the hospital course and may require additional rehabilitation or placement, delaying transition to home. As the baby boomers age, the older population is expected to increase, with significant implications for health care. With this in mind, the health care team, including frontline caregivers, need to be well informed about delirium. This article will expand readers’ knowledge and familiarity with delirium with the purpose of improving their practice and care of the older patient. It will also address the impact of delirium and discuss tools that can help to improve recognition. The most recent advances and current treatment methods to integrate into daily patient care are also discussed. This article places heavy emphasis on identification and prevention of delirium as these are the most important aspect of understanding delirium. Thus, treatment and management are both discussed after prevention since the primary focus of delirium is understanding and preventing this devastating syndrome in our hospitalized patients.

The imperative to prevent diabetes complications: a broadening spectrum and an increasing burden despite improved outcomes.

Diabetes mellitus and its complications are common; the complications are, of themselves, a major reason to manage diabetes. Recent data from Australia and similar developed health care systems overseas indicate that morbidity and mortality outcomes relating to diabetes complications are improving. However, these benefits are offset by increasing numbers of people diagnosed with diabetes, resulting in an increased disease burden with significant health care implications. Thus the imperative to prevent diabetes and diabetes complications has never been greater. Furthermore, the recognised spectrum of diabetes complications is broadening, especially complications relating to lipid levels, insulin resistance and the metabolic syndrome. Clinicians now need to be aware of both traditional complications (eg, nephropathy and cardiovascular disease) and non-traditional complications (eg, polycystic ovary syndrome, non-alcoholic fatty liver disease, some cancers and eating disorders). Complications outcomes could be further improved by decreasing the evidence-treatment gap - for example, by increasing personalisation of care in managing diabetes complications.