A deep learning framework for non-functional requirement classification

Analyzing, identifying, and classifying nonfunctional requirements from requirement documents is time-consuming and challenging. Machine learning-based approaches have been proposed to minimize analysts' efforts, labor, and stress. However, the traditional approach of supervised machine learning necessitates manual feature extraction, which is time-consuming. This study presents a novel deep-learning framework for NFR classification to overcome these limitations. The framework leverages a more profound architecture that naturally captures feature structures, possesses enhanced representational power, and efficiently captures a broader context than shallower structures. To evaluate the effectiveness of the proposed method, an experiment was conducted on two widely-used datasets, encompassing 914 NFR instances. Performance analysis was performed on the applied models, and the results were evaluated using various metrics. Notably, the DReqANN model outperforms the other models in classifying NFR, achieving precision between 81 and 99.8%, recall between 74 and 89%, and F1-score between 83 and 89%. These significant results highlight the exceptional efficacy of the proposed deep learning framework in addressing NFR classification tasks, showcasing its potential for advancing the field of NFR analysis and classification.

The Role of Artificial Intelligence of Things in Achieving Sustainable Development Goals: State of the Art

With the environmental and societal changes, the achievement of sustainable development goals (SDGs) and the realization of sustainability in general is now more important than ever. Through a bibliometric analysis and scientific mapping analysis, this study aims to explore and provide a review regarding the role of artificial intelligence (AI), the Internet of Things (IoT), and artificial intelligence of things (AIoT) in realizing sustainable development and achieving SDGs. AIoT can be defined as the combination of AI with IoT to create more efficient and data-driven interconnected, intelligent, and autonomous IoT systems and infrastructure that use AI methods and algorithms. The analysis involved 9182 documents from Scopus and Web of Science (WoS) from 1989 to 2022. Descriptive statistics of the related documents and the annual scientific production were explored. The most relevant and impactful authors, articles, outlets, affiliations, countries, and keywords were identified. The most popular topics and research directions throughout the years and the advancement of the field and the research focus were also examined. The study examines the results, discusses the main findings, presents open issues, and suggests new research directions. Based on the results of this study, AIoT emerged as an important contributor in ensuring sustainability and in achieving SDGs.

IN.PACT AV Access Randomized Trial of Drug-Coated Balloons for Dysfunctional Arteriovenous Fistulae: Clinical Outcomes through 36 Months

PURPOSE

To present the 36-month outcomes of the prospective randomized IN.PACT AV Access study of participants with obstructive de novo or restenotic native upper extremity arteriovenous dialysis fistula lesions treated with drug-coated balloon (DCBs) or standard percutaneous transluminal angioplasty (PTA) following successful high-pressure PTA.

MATERIALS AND METHODS

Participants at 29 international sites were randomized 1:1 to receive an IN.PACT AV DCB (n = 170) or undergo PTA (n = 160). The outcomes through 36 months included target lesion primary patency (TLPP) and access circuit primary patency (ACPP) (composites of clinically driven target lesion or access circuit revascularization and/or access circuit thrombosis), number of reinterventions, and serious adverse events involving the access circuit.

RESULTS

TLPP was 52.1% in the DCB group compared with 36.7% in the PTA group through 24 months and 43.1% in the DCB group compared with 28.6% in the PTA group through 36 months (both log-rank P < .001). ACPP was 39.4% in the DCB group compared with 25.3% in the PTA group through 24 months and 26.4% in the DCB group compared with 16.6% in the PTA group through 36 months (both log-rank P < .001). Cumulative incidence of access circuit thrombosis through 36 months was 8.2% in the DCB group compared with 18.3% in the PTA group (log-rank P = .040). Cumulative incidence of mortality through 36 months was 26.6% in the DCB group compared with 30.8% in the PTA group (log-rank P = .71).

CONCLUSIONS

This study demonstrated superior TLPP and ACPP with DCBs compared with PTA, with no difference in mortality through 3 years. Access circuit thrombosis was statistically significantly higher in the PTA group at 3 years.

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

INTRODUCTION

The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures.

METHODS

In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025.

FINDINGS

Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2-6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5-5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4-10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32-4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23-11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation.

INTERPRETATION

After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification.

FUNDING

UK Research and Innovation and National Institute for Health Research.

MR-guided HDR prostate brachytherapy with teleoperated steerable needles

Conformity of tumour volumes and dose plans in prostate brachytherapy (BT) can be constrained by unwanted needle deflections, needle access restrictions and visualisation limitations. This work validates the feasibility of teleoperated robotic control of an active steerable needle using magnetic resonance (MR) for guidance. With this system, perturbations can be counteracted and critical structures can be circumvented to access currently inaccessible areas. The system comprises of (1) a novel steerable needle, (2) the minimally invasive robotics in an MR environment (MIRIAM) system, and (3) the daVinci Research Kit (dVRK). MR scans provide visual feedback to the operator controlling the dVRK. Needle steering is performed along curved trajectories to avoid the urethra towards targets (representing tumour tissue) in a prostate phantom with a targeting error of 1.2 ± 1.0 mm. This work shows the potential clinical applicability of active needle steering for prostate BT with a teleoperated robotic system in an MR environment.

Patient Reported Financial Distress and its Association with Quality of Life and Symptom Burden in Cancer Patients Reporting to a Public Facility in LMIC

PURPOSE/OBJECTIVE(S)

Financial distress (FD) associates with worse quality of life (QoL) and there is paucity of literature from low middle income setting (LMIC). We investigated the prevalence & impact of subjective FD on QoL & symptom burden in advanced cancer patients, reporting to a public facility.

MATERIALS/METHODS

Patients aged ≥18yrs with a diagnosis of cancer within 3months and without prior treatment were accrued. Subjective FD was assessed by EORTC QLQ-C30 and symptoms were assessed by ESAS-R at baseline and 3 months. Patients were classified as experiencing FD if they answered ≥2 on a Likert scale question (1-4 points) asking about FD and dichotomized as Grp 1: No FD and Grp 2: FD. Mean change in score was calculated by subtracting the baseline from the 3-month score for each subscale, minimal important difference (MID) was defined using an anchor of ≥ 10-point compared to baseline for Global Qol and compared between groups. We used Mann Whitney, independent sample t test and Fisher's exact test for determining the association between FD and QoL and symptom burden. A p-value < 0.05 was considered statistically significant.

RESULTS

Of the 100 patients participating in the study, 69% reported subjective financial distress at baseline, 10% had insurance coverage, 27% used distressed financing (borrowing :21%; sold off assets:6%) and debt accumulation was seen in 34% patients. Cost reduction strategies were adopted by 98% patients. Mean Global Health (GH), physical (PF), emotional function (EF) was significantly worse at all time-points in FD patients. Physical (pain, tiredness) and psychological symptom scores (anxiety, depression) were significantly higher at all time points for FD patients. Mean change score for subscales of QoL and symptom burden was not significantly different between groups from baseline to 3 months (Table1).MID for deterioration of Global Qol was Grp 1 vs 2; 21.1% vs 32.7%, p = 0.504.

CONCLUSION

Two-thirds of patients have FD at presentation and report worse quality of life and symptom burden at all time-points. Presence of FD is not associated with significant change in QoL scores or symptom burden over 3 months. Measures are warranted to screen and reduce FD.

Racial and Ethnic Disparities in Treatment of Critical Limb Ischemia: A National Perspective

Background Recent guidelines have emphasized the use of medical management, early diagnosis, and a multidisciplinary team to effectively treat patients with critical limb ischemia (CLI). Previous literature briefly highlighted the current racial disparities in its intervention. Herein, we analyze the trend over a 14-year time period to investigate whether the disparities gap in CLI management is closing. Methods and Results The National Inpatient Sample was queried between 2005 and 2018 for hospitalizations involving CLI. Nontraumatic amputations and revascularization were identified. Utilization trends of these procedures were compared between races (White, Black, Hispanic, Asian and Pacific Islander, Native American, and Other). Multivariable regression assessed differences in race regarding procedure usage. There were 6 904 562 admissions involving CLI in the 14-year study period. The rate of admissions in White patients who received any revascularization decreased by 0.23% (P<0.001) and decreased by 0.25% (P=0.025) for Asian and Pacific Islander patients. Among all patients, the annual rate of admission in White patients who received any amputation increased by 0.21% (P<0.001), increased by 0.19% (P=0.001) for Hispanic patients, and increased by 0.19% (P=0.012) for the Other race patients. Admissions involving Black, Hispanic, Asian and Pacific Islander, or Other race patients had higher odds of receiving any revascularization compared with White patients. All races had higher odds of receiving major amputation compared with White patients. Conclusions Our analysis highlights disparities in CLI treatment in our nationally representative sample. Non-White patients are more likely to receive invasive treatments, including major amputations and revascularization for CLI, compared with White patients.

Prevalence of night eating syndrome among inbound call centre employees in Kuala Lumpur, Malaysia

Background: Night eating syndrome (NES) is described as a disordered eating pattern relative to sleep, where consumption of food occurs in the evening and night. Numerous studies had been conducted in various populations but studies on (NES) among call centre employees are limited. Aim: This study aimed to determine the prevalence of NES and its determinants among selected inbound call centre employees in Kuala Lumpur, Malaysia. Methods: In this cross-sectional study, a total of 217 inbound call centre employees were recruited through random sampling. A self-administered socio-demographic and work-related questionnaire was used to collect data on the background of the respondents. Information on NES and well-being was obtained by using the Night Eating Questionnaire (NEQ) and World Health Organisation-Five Well-Being Index (WHO-5) respectively. Data on dietary intakes, smoking habits, alcohol intakes and life stress were acquired using a Simple Lifestyle Indicator Questionnaire (SLIQ) while eating behaviour of the respondents was studied using the Three-Factor Eating Questionnaire (TFEQ-18). Results: The mean age of the respondents was 24.1 ± 6.0 years. The prevalence of NES was 12.0% (95% CI = 8.12-17.24). The binary logistic regression identified that NES is significantly associated with adequate exercise (AOR = 4.250, p = 0.012) and emotional eating (AOR = 6.510, p = 0.014). Conclusion: This study showed that the prevalence of NES was high in the call centre and repeated nocturnal eating can have multiple adverse health effects. Therefore, promoting healthy eating habits are crucial to reduce the impacts of NES.

Health Disparities in Peripheral Artery Disease: A Scientific Statement From the American Heart Association

Peripheral artery disease (PAD) affects 200 million individuals worldwide. In the United States, certain demographic groups experience a disproportionately higher prevalence and clinical effect of PAD. The social and clinical effect of PAD includes higher rates of individual disability, depression, minor and major limb amputation along with cardiovascular and cerebrovascular events. The reasons behind the inequitable burden of PAD and inequitable delivery of care are both multifactorial and complex in nature, including systemic and structural inequity that exists within our society. Herein, we present an overview statement of the myriad variables that contribute to PAD disparities and conclude with a summary of potential novel solutions.

A Bibliometric Analysis of the Evolution of State-of-the-Art Blockchain Technology (BCT) in the Agrifood Sector from 2014 to 2022

In recent years, BCT has garnered significant attention from researchers worldwide. The technology in question is a distributed database system characterised by its decentralised nature and lack of reliability. BCT has been widely adopted by numerous governments and scholars across various sectors for a number of years. Blockchain technology also involves highly innovative and advanced concepts. Given the increasing interest among scholars in the academic community regarding the agrifood supply chain, the objective of this study was to investigate BCT and its potential for application in the fields of food and agriculture. This research paper presents a bibliometric analysis of articles on the utilisation of BCT in the fields of food and agriculture. This study discusses scholarly articles that have been published in esteemed academic journals and conferences. Through our bibliometric analysis, we aimed to discern the recurring trends and themes within the research on BCT in relation to agrifood systems. Furthermore, this study examines a diverse array of research domains, prominent scholarly publications, leading publishing platforms, prominent funding institutions, and the prospective trajectory of future research. This study also presents the prominent patterns and themes within this field through an analysis of the most influential scholarly articles, authors, countries, and keywords found in the existing literature. Hence, this research employed various analytical techniques, including analyzing the co-occurrence of author keywords, bibliographic coupling analysis, network view map analysis, and co-citation analysis. This study holds promise as a valuable learning resource for aspiring researchers seeking to acquire compelling and pertinent information about research outcomes from studies on the utilisation of BCT in the field of smart agriculture.

Contextualizing the BEST-CLI Trial Results in Clinical Practice

Background

Chronic limb-threatening ischemia (CLTI) is associated with poor long-term outcomes. Although prompt revascularization is recommended, the optimal revascularization strategy remains uncertain. The BEST-CLI trial compared endovascular and open surgical revascularization for CLTI, but the generalizability of this study to the clinical population with CLTI has not been evaluated.

Methods

We included Medicare beneficiaries aged 65-85 years with CLTI who underwent revascularization and would be eligible for enrollment in BEST-CLI between 2016 and 2019. The primary exposure was type of revascularization (endovascular vs autologous graft [cohort 1] vs nonautologous graft [cohort 2]), and the primary outcome was a composite of major adverse limb events (MALE) and death. MALE included above-ankle amputation and major intervention, which was defined as new bypass of index limb, thrombectomy, or thrombolysis.

Results

A total of 66,153 patients were included in this study (10,125 autologous grafts; 7867 nonautologous grafts; 48,161 endovascular). Compared with those enrolled in BEST-CLI cohort 1, patients in this study were older (mean age, 73.5 ± 5.7 vs 69.9 ± 9.9 years), more likely to be female (38.3% [22,340/58,286] vs 28.5% [408/1434]), and presented with more comorbidities. Endovascular operators for the study population vs BEST-CLI cohort 1 were less likely to be surgeons (55.9% [26,924/48,148] vs 73.0% [520/708]) and more likely to be cardiologists (25.5% [5900/48,148] vs 14.5% [103/78]). When assessing long-term outcomes, the crude risk of death or MALE in this cohort was higher with surgery (56.6% autologous grafts vs 42.6% BEST-CLI cohort 1 at a median of follow-up 2.7 years; 51.6% nonautologous grafts vs 42.8% BEST-CLI cohort 2 at a median follow-up of 1.6 years) but similar with the endovascular cohort (58.7% Medicare vs 57.4% cohort 1 at 2.7 years; 47.0% Medicare vs 47.7% cohort 2 at 1.6 years). Of those who received endovascular treatment, the risk of incident major intervention was less than half in this cohort compared with the trial cohort (10.0% Medicare vs 23.5% cohort 1 at 2.7 years; 8.6% Medicare vs 25.6% cohort 2 at 1.6 years), although technical endovascular failures were not captured.

Conclusions

These results suggest that the findings of the BEST-CLI trial may not be applicable to the entirety of the Medicare population of patients with CLTI undergoing revascularization.

A blockchain-based evaluation approach to analyse customer satisfaction using AI techniques

Due to technological advancements and consumer demands, online shopping creates new features and adapts to new standards. A robust customer satisfaction prediction model concerning trust and privacy platforms can encourage an organization to make better decisions about its service and quality. This study presented an approach to predict consumer satisfaction using the blockchain-based framework combining the Multi-Dimensional Naive Bayes-K Nearest Neighbor (MDNB-KNN) and the Multi-Objective Logistic Particle Swarm Optimization Algorithm (MOL-PSOA). A regression model is employed to quantify the impact of various production factors on customer satisfaction. The proposed method yields better levels of measurement for customer satisfaction (98%), accuracy (95%), necessary time (60%), precision (95%), and recall (95%) compared to existing studies. Measuring consumer satisfaction with a trustworthy platform facilitates to development of the conceptual and practical distinctions influencing customers' purchasing decisions.

National Trends in Complications of Vascular Access for Hemodialysis and Analysis of Racial Disparities Among Patients With End-Stage Renal Disease in the Inpatient Setting

Introduction

The aim of this study is to assess the trends in access-related complications, as well as the impact of race on these complications, among admitted patients with end-stage kidney disease (ESKD) receiving hemodialysis.

Methods

A retrospective cohort study between 2005 and 2018 was performed using the National Inpatient Sample (NIS). Hospitalizations involving ESKD and hemodialysis were identified. There were 9,246,553 total admissions involving ESKD and hemodialysis, of which 1,167,886 (12.6%) had complications. Trends in complications were assessed and compared among races.

Results

There was a decreasing trend in rates of mechanical (trend: -0.05% per year; P < 0.001), inflammatory or infectious (-0.48%; P < 0.001), and other (-0.19%; P < 0.001) complications from 2005 to 2018. Non-White patients had a greater magnitude in the decrease in trends in rates of complications compared to White patients (-0.69% per year vs. -0.57%; P < 0.001). Compared to the White patients, Black patients (odds ratio [OR]: 1.26; P < 0.001) and those of the other races (OR: 1.11; P < 0.001) had higher odds of complications. These differences were also statistically significant among lower socioeconomic classes (75 percentile vs. 0-25 percentile: P = 0.009) and within southern states (vs. Northeast: P < 0.001).

Conclusion

Although there was an overall decrease in the trends of dialysis-associated complications requiring hospitalization among ESKD patients receiving hemodialysis, non-White patients have higher odds of complications compared to White patients. The findings in this study emphasize the need for more equitable care for hemodialysis patients.

The Neurovasculome: Key Roles in Brain Health and Cognitive Impairment: A Scientific Statement From the American Heart Association/American Stroke Association

BACKGROUND

Preservation of brain health has emerged as a leading public health priority for the aging world population. Advances in neurovascular biology have revealed an intricate relationship among brain cells, meninges, and the hematic and lymphatic vasculature (the neurovasculome) that is highly relevant to the maintenance of cognitive function. In this scientific statement, a multidisciplinary team of experts examines these advances, assesses their relevance to brain health and disease, identifies knowledge gaps, and provides future directions.

METHODS

Authors with relevant expertise were selected in accordance with the American Heart Association conflict-of-interest management policy. They were assigned topics pertaining to their areas of expertise, reviewed the literature, and summarized the available data.

RESULTS

The neurovasculome, composed of extracranial, intracranial, and meningeal vessels, as well as lymphatics and associated cells, subserves critical homeostatic functions vital for brain health. These include delivering O2 and nutrients through blood flow and regulating immune trafficking, as well as clearing pathogenic proteins through perivascular spaces and dural lymphatics. Single-cell omics technologies have unveiled an unprecedented molecular heterogeneity in the cellular components of the neurovasculome and have identified novel reciprocal interactions with brain cells. The evidence suggests a previously unappreciated diversity of the pathogenic mechanisms by which disruption of the neurovasculome contributes to cognitive dysfunction in neurovascular and neurodegenerative diseases, providing new opportunities for the prevention, recognition, and treatment of these conditions.

CONCLUSIONS

These advances shed new light on the symbiotic relationship between the brain and its vessels and promise to provide new diagnostic and therapeutic approaches for brain disorders associated with cognitive dysfunction.

A bibliometric review of grid parity, energy transition and electricity cost research for sustainable development

As the topic of sustainable development continues to prominence in global affairs, the case for renewable energy has never been stronger. To be regarded as a perfect alternative to conventional (non-renewable) energy sources in many climes, renewable energy, such as solar and wind, shows promise when considering concepts like grid parity. A significant number of studies have been devoted to understanding the concept. However, only a few studies have committed themselves to analysing the research activity carried out on it. This paper will present a bibliometric and empirical review of worldwide grid parity, energy transition, and electricity cost research. To situate the progress in this research area, a detailed search of Scopus was used to identify and situate research development in the field from 1965 until 2021. Using the data extracted from Scopus and VOSviewer for analysis, we explore different aspects of the publications, such as the volume, growth rate, and coverage of published documents, the most influential research papers and journals in this research area, and the most studied research themes in recent years. We also discuss Governmental policies in developed and developing economies that have accelerated the attainment of Grid parity in certain countries. Also, an empirical review of top-down, bottom-up, and artificial neural network approaches to evaluating grid parity was conducted. The study revealed a steady increase in the research articles focused on grid parity, energy transition, and electricity cost research from 2006. The geographic distribution of the publications shows that most of the publications on the subject originated from the USA, Germany, China, United Kingdom, and Spain, raking in 42.2% of the publications. Also, the top 7 authors with the highest document count from Scopus are from Finland, which coincidentally is one of the countries making significant progress in Grid parity attainment. Of the total document count from Scopus, only 0.02% are papers published from African Countries. Could this reluctance to publish research findings on energy transition be one of the reasons for the slow progression of sustainable energy for all in Africa? Therefore, it is imperative now more than ever for more research focusing on the attainment of grid parity, energy transition, and electricity costs for developing countries to be brought to the fore. This article provides a review of state-of-the-art research on the attainment of grid parity and energy transition with a focus on the Levelized Cost of Electricity (LCOE) models of renewable energy sources.

Impact of Mobile Received Signal Strength (RSS) on Roaming and Non-roaming Mobile Subscribers

Mobile phones have transitioned from voice-centric devices to smart devices supporting functionalities like high-definition video and games, web browsers, radio reception, and video conferencing. Mobile phones are used in telemedicine, health monitoring applications, navigation tools, and gaming devices, among other applications. Given the above, Mobile broadband connectivity affects mobile access to the internet and voice communications. This paper assesses the impact of the Reference Signal Received Power (RSRP) and broadband connectivity around Covenant University. LTE, GSM, and HSPA mobile signal measurement campaigns were conducted around Covenant University in Ota, Ogun state, Nigeria. To investigate the best optimized mobile network for mobile subscribers on roaming services and subscriber's high performance and data rates. After the experiment, exploratory data analysis was used to visualize the best mobile network; GSM proved as stable than LTE and HSPA.

Cochlear nerve dysplasia in unilateral severe to profound congenital sensorineural hearing loss - Prevalence in Australian children and the impact of socioeconomic disadvantage on its management

INTRODUCTION

Congenital unilateral sensorineural hearing loss (cuSNHL) carries potentially significant social, educational, and developmental consequences. Early diagnosis enables investigation, and consideration of options for management and early intervention, helping to mitigate the effects of hearing loss. Cochlear nerve dysplasia (CND) is a prominent cause of cuSNHL and may affect candidacy for cochlear implantation. Socioeconomic disadvantage may impact on a patient's family's capacity to participate in necessary intervention and follow-up.

METHODS

Infants with severe-profound cuSNHL referred to a large Australian quaternary pediatric center between October 2004 and December 2020 were retrospectively included. Audiometric and clinical data, and the presence of hearing loss risk factors were obtained from a prospectively collated database. In Australia MRI scans are provided free-of-charge to citizens and residents. MRI scans were reviewed to determine the status of the nerves within the internal acoustic meatus (IAM grade) along with attendance rates. Travel distance to the hospital was also calculated. Reasons for non-attendance at MRI were obtained from patient medical records and correspondence. Socioeconomic, educational, and occupational indices, and travel distances were obtained using patient residential postcodes with reference to Australian Bureau of Statistics data.

RESULTS

A total of 98 patients were reviewed, 64.3% (n = 63) of whom underwent MRI. The median age at diagnosis was 40 days (IQR 27). The prevalence of CND was 75% (n = 47). Importantly, there was no significant difference in the degree of hearing loss between IAM grades (F(4,57) = 1.029, p = 0.405). Socioeconomic indices were significantly lower in patients not attending MRI investigations compared with patients who did attend. Travel distance was not significantly different between the two groups.

CONCLUSION

CND is a prominent cause of cuSNHL in Australian infants. MRI at a young age allows parent education regarding management options and timely intervention where indicated. Socioeconomic disadvantage significantly impacts on participation in further routine assessment of cuSNHL, potentially limiting management options for these children long term.

Sentiment analysis of COVID-19 tweets from selected hashtags in Nigeria using VADER and Text Blob analyser

Background

Information is essential for growth; without it, little can be accomplished. Data gathering has seen significant changes throughout the previous few centuries because of the certain transitory medium. The look and style of information transference are affected by the employment of new and emerging technologies, some of which are efficient, others are reliable, and many more are quick and effective, but a few were disappointing for various reasons.

Aims

This study aims at using TextBlob and VADER analyser with historical tweets, to analyse emotional responses to the coronavirus pandemic (COVID-19). It shows us how much of a sociological, environmental, and economic impact it has in Nigeria, among other things. This study would be a tremendous step forward for students, researchers, and scholars who want to advance in fields like data science, machine learning, and deep learning.

Methodology

The hashtag ‘COVID-19' was used to collect 1,048,575 tweets from Twitter. The tweets were pre-processed with a Twitter tokenizer, while TextBlob and Valence Aware Dictionary for Sentiment Reasoning (VADER) were used for text mining and sentiment analysis, respectively. Topic modelling was done with Latent Dirichlet Allocation and visualized with Multidimensional scaling.

Results

The result of the VADER sentiment returned 39.8%, 31.3%, and 28.9%, positive, neutral, and negative sentiment, respectively, while the result of the TextBlob sentiment returned 46.0%, 36.7%, and 17.3%, neutral, positive, and negative sentiment, respectively.

Conclusion

With all of this, information from social media may be used to help organizations, governments, and nations around the world make smart and effective decisions about how to restrict and limit the negative effects of COVID-19. Also, know the opinion and challenges of people, then deal with the problem of misinformation. It is concluded that with popular belief a significant number of the populace regards COVID-19 as a virus that has come to stay, some believe it will eventually be conquered.

IN.PACT AV access randomized trial: Japan cohort outcomes through 12 months

PURPOSE

There is a lack of adjudicated and prospectively randomized published outcomes on the use of drug-coated balloons (DCB) to treat dysfunctional arteriovenous fistula in Asian patients. This post hoc subgroup analysis of 112 Japanese participants from the global IN.PACT AV Access trial reports outcomes through 12 months.

MATERIALS AND METHODS

Participants were treated with DCB (n = 58) or standard non-coated percutaneous transluminal angioplasty (PTA) balloons (n = 54). Outcomes included target lesion primary patency (TLPP), access circuit primary patency, and safety.

RESULTS

Through 6 months, TLPP was 86.0% (49/57) in the DCB group and 49.1% (26/53) in the PTA group (p < 0.001). Through 12 months, TLPP was 67.3% (37/55) in the DCB group and 43.4% (23/53) in the PTA group (p = 0.013).

CONCLUSION

In this post hoc analysis of Japanese participants from the IN.PACT AV Access trial, participants treated with DCB had higher TLPP through 6 and 12 months compared with PTA.

MobileNet-SVM: A Lightweight Deep Transfer Learning Model to Diagnose BCH Scans for IoMT-Based Imaging Sensors

Many individuals worldwide pass away as a result of inadequate procedures for prompt illness identification and subsequent treatment. A valuable life can be saved or at least extended with the early identification of serious illnesses, such as various cancers and other life-threatening conditions. The development of the Internet of Medical Things (IoMT) has made it possible for healthcare technology to offer the general public efficient medical services and make a significant contribution to patients' recoveries. By using IoMT to diagnose and examine BreakHis v1 400× breast cancer histology (BCH) scans, disorders may be quickly identified and appropriate treatment can be given to a patient. Imaging equipment having the capability of auto-analyzing acquired pictures can be used to achieve this. However, the majority of deep learning (DL)-based image classification approaches are of a large number of parameters and unsuitable for application in IoMT-centered imaging sensors. The goal of this study is to create a lightweight deep transfer learning (DTL) model suited for BCH scan examination and has a good level of accuracy. In this study, a lightweight DTL-based model "MobileNet-SVM", which is the hybridization of MobileNet and Support Vector Machine (SVM), for auto-classifying BreakHis v1 400× BCH images is presented. When tested against a real dataset of BreakHis v1 400× BCH images, the suggested technique achieved a training accuracy of 100% on the training dataset. It also obtained an accuracy of 91% and an F1-score of 91.35 on the test dataset. Considering how complicated BCH scans are, the findings are encouraging. The MobileNet-SVM model is ideal for IoMT imaging equipment in addition to having a high degree of precision. According to the simulation findings, the suggested model requires a small computation speed and time.

User and Professional Aspects for Sustainable Computing Based on the Internet of Things in Europe

The commonly accepted definition of sustainability considers the availability of relevant resources to make an activity feasible and durable while also recognizing users' support as an essential part of the social side of sustainability. IoT represents a disruption in the general scenario of computing for both users and professionals. The real expansion and integration of applications based on IoT depend on our capacity of exploring the necessary skills and professional profiles that are essential for the implementation of IoT projects, but also on the perception of relevant aspects for users, e.g., privacy, legal, IPR, and security issues. Our participation in several EU-funded projects with a focus on this area has enabled the collection of information on both sides of IoT sustainability through surveys but also by collecting data from a variety of sources. Thanks to these varied and complementary sources of information, this article will explore the user and professional aspects of the sustainability of the Internet of Things in practice.

Understanding the Impact of Obesity on Ageing in the Radiance of DNA Metabolism

Ageing is a multi-factorial phenomenon which is considered as a major risk factor for the development of neurodegeneration, osteoporosis, cardiovascular disease, dementia, cancer, and other chronic diseases. Phenotypically, ageing is related with a combination of molecular, cellular, and physiological levels like genomic and epi-genomic alterations, loss of proteostasis, deregulation of cellular and subcellular function and mitochondrial dysfunction. Though, no single molecular mechanism accounts for the functional decline of different organ systems in older humans but accumulation of DNA damage or mutations is a dominant theory which contributes largely to the development of ageing and age-related diseases. However, mechanistic, and hierarchical order of these features of ageing has not been clarified yet. Scientific community now focus on the effect of obesity on accelerated ageing process. Obesity is a complex chronic disease that affects multiple organs and tissues. It can not only lead to various health conditions such as diabetes, cancer, and cardiovascular disease but also can decrease life expectancy which shows similar phenotype of ageing. Higher loads of DNA damage were also observed in the genome of obese people. Thus, inability of DNA damage repair may contribute to both ageing and obesity apart from cancer predisposition. The present review emphasizes on the involvement of molecular phenomenon of DNA metabolism in development of obesity and how it accelerates ageing in mammals.

Machine learning-based IoT system for COVID-19 epidemics

The planet earth has been facing COVID-19 epidemic as a challenge in recent time. It is predictable that the world will be fighting the pandemic by taking precautions steps before an operative vaccine is found. The IoT produces huge data volumes, whether private or public, through the invention of IoT devices in the form of smart devices with an improved rate of IoT data generation. A lot of devices interact with each other in the IoT ecosystem through the cloud or servers. Various techniques have been presented in recent time, using data mining approach have proven help detect possible cases of coronaviruses. Therefore, this study uses machine learning technique (ABC and SVM) to predict COVID-19 for IoT data system. The system used two machine learning techniques which are Artificial Bee Colony algorithm with Support Vector Machine classifier on a San Francisco COVID-19 dataset. The system was evaluated using confusion matrix and had a 95% accuracy, 95% sensitivity, 95% specificity, 97% precision, 96% F1 score, 89% Matthews correlation coefficient for ABC-L-SVM and 97% accuracy, 95% sensitivity, 100% specificity, 100% precision, 97% F1 score, 93.1% Matthews correlation coefficient for ABC-Q-SVM. In conclusion, the system shows that the process of dimensionality reduction utilizing ABC feature extraction techniques can boost the classification production for SVM. It was observed that fetching relevant information from IoT systems before classification is relatively beneficial.

An Overview of Telehealth in the Management of Cardiovascular Disease: A Scientific Statement From the American Heart Association

Telehealth enables the remote delivery of health care through telecommunication technologies and has substantially affected the evolving medical landscape. The COVID-19 pandemic accelerated the utilization of telehealth as health care professionals were forced to limit face-to-face in-person visits. It has been shown that information delivery, diagnosis, disease monitoring, and follow-up care can be conducted remotely, resulting in considerable changes specific to cardiovascular disease management. Despite increasing telehealth utilization, several factors such as technological infrastructure, reimbursement, and limited patient digital literacy can hinder the adoption of remote care. This scientific statement reviews definitions pertinent to telehealth discussions, summarizes the effect of telehealth utilization on cardiovascular and peripheral vascular disease care, and identifies obstacles to the adoption of telehealth that need to be addressed to improve health care accessibility and equity.

Machine learning for optimizing daily COVID-19 vaccine dissemination to combat the pandemic

Introduction

Vaccines are the most important instrument for bringing the pandemic to a close and saving lives and helping to reduce the risks of infection. It is important that everyone has equal access to immunizations that are both safe and effective. There is no one who is safe until everyone gets vaccinated. COVID-19 vaccinations are a game-changer in the fight against diseases. In addition to examining attitudes toward these vaccines in Africa, Asia, Oceania, Europe, North America, and South America, the purpose of this paper is to predict the acceptability of COVID-19 vaccines and study their predictors.

Materials and methods

Kaggle datasets are used to estimate the prediction outcomes of the daily COVID-19 vaccination to prevent a pandemic. The Kaggle data sets are classified into training and testing datasets. The training dataset is comprised of COVID-19 daily data from the 13th of December 2020 to the 13th of June 2021, while the testing dataset is comprised of COVID-19 daily data from the 14th of June 2021 to the 14th of October 2021. For the prediction of daily COVID-19 vaccination, four well-known machine learning algorithms were described and used in this study: CUBIST, Gaussian Process (GAUSS), Elastic Net (ENET), Spikes, and Slab (SPIKES).

Results

Among the models considered in this paper, CUBIST has the best prediction accuracy in terms of Mean Absolute Scaled Error (MASE) of 9.7368 for Asia, 2.8901 for America, 13.2169 for Oceania, and 3.9510 for South America respectively.

Conclusion

This research shows that machine learning can be of great benefit for optimizing daily immunization of citizens across the globe. And if used properly, it can help decision makers and health administrators to comprehend immunization rates and create strategies to enhance them.

Investigating factors for using insurance apps by customers: a study of a developing country

With the fast development of insurtech, many researchers are doing research in understanding customer behavior regarding the adoption of insurance applications. However, there is a lack of research on the subject in developing countries such as Vietnam. The primary purpose of this article is to develop a predictive model for the intention to use the insurance application of individual customers in Vietnam. In this research, the quantitative research method is conducted based on survey data collected in Ho Chi Minh City. Data are tested using various methods, such as Cronbach’s Alpha, EFA, Pearson correlation test, and multiple linear regression. From the analysis results, some factors positively influencing the intention to use insurance applications are identified, including Trust, Ease of Use, and Usefulness. However, the impact of Risk on Usefulness is not confirmed based on the sample data. From the analysis results, some managerial implications are made to improve the intention to use insurance applications of customers in Vietnam.

Bindarit encapsulated nanoparticles prevent venous neointimal hyperplasia and restenosis in a murine angioplasty model

Monocyte and macrophage recruitment occur to the injured vessel wall after percutaneous transluminal angioplasty (PTA) of stenotic arteriovenous fistulas (AVF) through increased expression of MCP-1 leading to venous neointimal hyperplasia (VNH) and venous stenosis (VS). We hypothesized that adventitial delivery of Bindarit, an oral selective inhibitor of MCP-1, -2, and -3 encapsulated in poly lactic-co-glycolic acid (PLGA) nanoparticles embedded in a thermosensitive Pluronic F127 hydrogel (BN NP) could prevent VNH/VS formation in a murine model of PTA with AVF. Scanning electron microscope and dynamic light scattering were used to characterize the BN NP and control nanoparticles (NP C). Liquid chromatography with tandem mass spectrometry (LC-MS/MS) was used to study drug release kinetics. Immediately after PTA, in a murine model of AVF stenosis, BN NP or NP C was administrated to the adventitia of outflow veins. Animals were sacrificed 3 and 21 days later for gene expression, histomorphometric, and immunohistochemical analyses. Doppler ultrasound was performed weekly. There was no difference in the size and storage modulus of BN NP compared to controls. The pharmacokinetic analysis demonstrated increased drug release from BN NP when compared to controls. BN NP-treated vessels had reduced MCP-1, MCP-2, and MCP-3 gene, and protein levels, reduced macrophage/monocyte abundance, proinflammatory cytokines, and venous fibrosis resulting in positive vascular remodeling and improved patency with reduced VNH/VS. There was increased peak velocity 21 days after PTA in the BN NP group. Adventitial administration of BN NP to the outflow vein after PTA results in decreased VNH/VS.

Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study

BACKGROUND

No effective pharmacological or non-pharmacological interventions exist for patients with long COVID. We aimed to describe recovery 1 year after hospital discharge for COVID-19, identify factors associated with patient-perceived recovery, and identify potential therapeutic targets by describing the underlying inflammatory profiles of the previously described recovery clusters at 5 months after hospital discharge.

METHODS

The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID-19 across the UK. Recovery was assessed using patient-reported outcome measures, physical performance, and organ function at 5 months and 1 year after hospital discharge, and stratified by both patient-perceived recovery and recovery cluster. Hierarchical logistic regression modelling was performed for patient-perceived recovery at 1 year. Cluster analysis was done using the clustering large applications k-medoids approach using clinical outcomes at 5 months. Inflammatory protein profiling was analysed from plasma at the 5-month visit. This study is registered on the ISRCTN Registry, ISRCTN10980107, and recruitment is ongoing.

FINDINGS

2320 participants discharged from hospital between March 7, 2020, and April 18, 2021, were assessed at 5 months after discharge and 807 (32·7%) participants completed both the 5-month and 1-year visits. 279 (35·6%) of these 807 patients were women and 505 (64·4%) were men, with a mean age of 58·7 (SD 12·5) years, and 224 (27·8%) had received invasive mechanical ventilation (WHO class 7-9). The proportion of patients reporting full recovery was unchanged between 5 months (501 [25·5%] of 1965) and 1 year (232 [28·9%] of 804). Factors associated with being less likely to report full recovery at 1 year were female sex (odds ratio 0·68 [95% CI 0·46-0·99]), obesity (0·50 [0·34-0·74]) and invasive mechanical ventilation (0·42 [0·23-0·76]). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate with cognitive impairment, and mild, relating to the severity of physical health, mental health, and cognitive impairment at 5 months. We found increased inflammatory mediators of tissue damage and repair in both the very severe and the moderate with cognitive impairment clusters compared with the mild cluster, including IL-6 concentration, which was increased in both comparisons (n=626 participants). We found a substantial deficit in median EQ-5D-5L utility index from before COVID-19 (retrospective assessment; 0·88 [IQR 0·74-1·00]), at 5 months (0·74 [0·64-0·88]) to 1 year (0·75 [0·62-0·88]), with minimal improvements across all outcome measures at 1 year after discharge in the whole cohort and within each of the four clusters.

INTERPRETATION

The sequelae of a hospital admission with COVID-19 were substantial 1 year after discharge across a range of health domains, with the minority in our cohort feeling fully recovered. Patient-perceived health-related quality of life was reduced at 1 year compared with before hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials.

FUNDING

UK Research and Innovation and National Institute for Health Research.

IN.PACT AV Access Trial: Economic Evaluation of Drug-Coated Balloon Treatment for Dysfunctional Arteriovenous Fistulae Based on 12-Month Clinical Outcomes

PURPOSE

To study, from a U.S. payer's perspective, the economic consequences of drug-coated balloon (DCB) versus standard percutaneous transluminal angioplasty (PTA) use for the treatment of stenotic lesions in dysfunctional hemodialysis arteriovenous fistulae.

MATERIALS AND METHODS

Cost differences between DCBs and PTA at year 1 and beyond were calculated via 2 methods. The first approach used the mean absolute number of trial-observed access circuit reinterventions through 12 months (0.65 ± 1.05 vs 1.05 ± 1.18 events per patient for DCBs and PTA, respectively) and projected treatment outcomes to 3 years. The second approach was based on the trial-observed access circuit primary patency rates at 12 months (53.8% vs 32.4%) and calculated the cost difference on the basis of previously published Medicare cost for patients who maintained or did not maintain primary patency. Assumptions regarding DCB device prices were tested in sensitivity analyses, and the numbers needed to treat were calculated.

RESULTS

Using the absolute number of access circuit reinterventions approach, the DCB strategy resulted in an estimated per-patient savings of $1,632 at 1 year and $4,263 at 3 years before considering the DCB device cost. The access circuit primary patency approach was associated with a per-patient cost savings of $2,152 at 1 year and $3,894 at 2.5 years of follow-up. At the theoretical DCB device reimbursement of $1,800, savings were $1,680 and $2,049 at 2.5 and 3 years, respectively. The one-year NNT of DCB compared to PTA was 2.48.

CONCLUSIONS

Endovascular therapy for arteriovenous access stenosis with the IN.PACT AV DCB can be expected to be cost-saving if longer follow-up data confirm its clinical effectiveness.

Revascularization for Renovascular Disease: A Scientific Statement From the American Heart Association

Renovascular disease is a major causal factor for secondary hypertension and renal ischemic disease. However, several prospective, randomized trials for atherosclerotic disease failed to demonstrate that renal revascularization is more effective than medical therapy for most patients. These results have greatly reduced the generalized diagnostic workup and use of renal revascularization. Most guidelines and review articles emphasize the limited average improvement and fail to identify those clinical populations that do benefit from revascularization. On the basis of the clinical experience of hypertension centers, specialists have continued selective revascularization, albeit without a summary statement by a major, multidisciplinary, national organization that identifies specific populations that may benefit. In this scientific statement for health care professionals and the public-at-large, we review the strengths and weaknesses of randomized trials in revascularization and highlight (1) when referral for consideration of diagnostic workup and therapy may be warranted, (2) the evidence/rationale for these selective scenarios, (3) interventional and surgical techniques for effective revascularization, and (4) areas of research with unmet need.

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

BACKGROUND

Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications.

METHODS

We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC).

FINDINGS

In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683-0·717]).

INTERPRETATION

In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required.

FUNDING

British Journal of Surgery Society.

Behavior or culture? Investigating the use of cryptocurrencies for electronic commerce across the USA and China

Purpose

This paper claims to identify the behavioral and cultural features that push to use, or not, cryptocurrencies for electronic commerce. Indeed, despite the use of cryptocurrencies for electronic commerce spreading worldwide at a fast and growing pace, there are supporters and detractors among their users. The analysis of what distinguish these two groups of users is fundamental for understanding their different intention to use cryptocurrencies for electronic commerce.

Design/methodology/approach

A survey has been administered to 2,532 cryptocurrencies’ users across the USA and China, collecting data on their behavioral predispositions and cultural features. Results were then analyzed through structured equation modeling.

Findings

Results showed that while attitude, subjective norms, perceived behavioral control and herding behavior have a positive impact on the intention to use cryptocurrencies for electronic commerce, financial literacy has no influence. Cultural dimensions amplified or reduced the discovered relationships and caused different effects: positive for the USA and negative for China when considering illegal attitude and perceived risk.

Originality/value

Theory of planned behavior, financial behavior and cultural factors can, all together, represent a useful framework for envisioning the behavior of users in adopting cryptocurrencies for electronic commerce purposes through a test of all its elements. To the best of the authors’ knowledge, this is the first study considering behavior and cultural variables on the intention to use cryptocurrencies for electronic commerce as well as being the largest carried out, in terms of sample, on the cryptocurrency topic.

Neuropilin-1 deficiency in vascular smooth muscle cells is associated with hereditary hemorrhagic telangiectasia arteriovenous malformations

Patients with hereditary hemorrhagic telangiectasia (HHT) have arteriovenous malformations (AVMs) with genetic mutations involving the activin-A receptor like type 1 (ACVRL1 or ALK1) and endoglin (ENG). Recent studies have shown that Neuropilin-1 (NRP-1) inhibits ALK1. We investigated the expression of NRP-1 in livers of patients with HHT and found that there was a significant reduction in NRP-1 in perivascular smooth muscle cells (SMCs). We used Nrp1^SM22KO mice (Nrp1 was ablated in SMCs) and found hemorrhage, increased immune cell infiltration with a decrease in SMCs, and pericyte lining in lungs and liver in adult mice. Histologic examination revealed lung arteriovenous fistulas (AVFs) with enlarged liver vessels. Evaluation of the retina vessels at P5 from Nrp1^SM22KO mice demonstrated dilated capillaries with a reduction of pericytes. In inflow artery of surgical AVFs from the Nrp1^SM22KO versus WT mice, there was a significant decrease in Tgfb1, Eng, and Alk1 expression and phosphorylated SMAD1/5/8 (pSMAD1/5/8), with an increase in apoptosis. TGF-β1–stimulated aortic SMCs from Nrp1^SM22KO versus WT mice have decreased pSMAD1/5/8 and increased apoptosis. Coimmunoprecipitation experiments revealed that NRP-1 interacts with ALK1 and ENG in SMCs. In summary, NRP-1 deletion in SMCs leads to reduced ALK1, ENG, and pSMAD1/5/8 signaling and reduced cell death associated with AVM formation.

An Ensemble Learning Model for COVID-19 Detection from Blood Test Samples

Current research endeavors in the application of artificial intelligence (AI) methods in the diagnosis of the COVID-19 disease has proven indispensable with very promising results. Despite these promising results, there are still limitations in real-time detection of COVID-19 using reverse transcription polymerase chain reaction (RT-PCR) test data, such as limited datasets, imbalance classes, a high misclassification rate of models, and the need for specialized research in identifying the best features and thus improving prediction rates. This study aims to investigate and apply the ensemble learning approach to develop prediction models for effective detection of COVID-19 using routine laboratory blood test results. Hence, an ensemble machine learning-based COVID-19 detection system is presented, aiming to aid clinicians to diagnose this virus effectively. The experiment was conducted using custom convolutional neural network (CNN) models as a first-stage classifier and 15 supervised machine learning algorithms as a second-stage classifier: K-Nearest Neighbors, Support Vector Machine (Linear and RBF), Naive Bayes, Decision Tree, Random Forest, MultiLayer Perceptron, AdaBoost, ExtraTrees, Logistic Regression, Linear and Quadratic Discriminant Analysis (LDA/QDA), Passive, Ridge, and Stochastic Gradient Descent Classifier. Our findings show that an ensemble learning model based on DNN and ExtraTrees achieved a mean accuracy of 99.28% and area under curve (AUC) of 99.4%, while AdaBoost gave a mean accuracy of 99.28% and AUC of 98.8% on the San Raffaele Hospital dataset, respectively. The comparison of the proposed COVID-19 detection approach with other state-of-the-art approaches using the same dataset shows that the proposed method outperforms several other COVID-19 diagnostics methods.

Endovascular Versus Surgical Arteriovenous Fistulas: A Systematic Review and Meta-analysis

Rationale & Objective

To facilitate the process of dialysis for patients with kidney failure, an arteriovenous fistula (AVF) is created using either a surgical or percutaneous approach. We sought to compare the efficacy and procedural outcomes in creating an AVF percutaneously using Ellipsys (Avenu Medical) or WavelinQ (Becton Dickinson Medical) with surgery in all patients with kidney failure requiring a permanent AVF for dialysis.

Study Design

Systematic review and meta-analysis.

Setting & Study Populations

All patients requiring a permanent AVF for dialysis.

Selection Criteria for Studies

We included studies that compared either the Ellipsys device or WavelinQ directly with surgery to create an AVF for long-term dialysis.

Data Extraction

Two reviewers independently reviewed the studies and extracted the data. Conflicts were resolved with a discussion and approval from the senior author.

Analytical Approach

Fixed-effects or random-effects models were used to pool the fixed sizes and 95% CIs based on the level of heterogeneity.

Results

There was no statistically significant difference observed between surgical AVF and endovascular AVF when comparing the primary outcomes of procedural success (OR = 1.44; 95% CI, 0.35, 5.88; P = 0.61; I2 = 0%), complications (OR = 0.28; 95% CI, 0.06, 1.46; P = 0.13; I2 = 69%), and the secondary outcomes of interest that included follow-up time (mean difference [MD] = -17.71; 95% CI, -189.53, 154.12; P = 0.84; I2 = 94%), failure rate (OR = 1.03; 95% CI, 0.21, 5.13; P = 0.97; I2 = 85%), and time to 2-needle cannulation (MD = -5.40; 95% CI, -38.88, 28.08; P = 0.75; I2 = 0%). However, a statistically significant difference was seen among the 2 groups for procedural time (MD = -54.25; 95% CI, -59.78, -48.71; P < 0.001; I2 = 98%), number of interventions needed to maintain patency (OR = 1.73; 95% CI, 1.22, 2.45; P < 0.01; I2 = 94%), and primary patency rate (OR = 0.34; 95% CI, 0.23,0.52; P < 0.001; I2 = 0%).

Limitations

The total number of studies included in this review was limited, with 3 of the 4 included studies being retrospective and only 1 being prospective. There was a lack of heterogeneity and randomization.

Conclusions

Percutaneous fistula creation using Ellipsys or WavelinQ is a unique and safe alternative with outcomes comparable to surgery. Future studies are needed, including observational studies in current clinical practice, to evaluate the efficacy and outcomes of endovascular AVF creation in clinical populations.