bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictors contributing to the estimation of pulmonary tuberculosis among adults in a resource-limited setting: A systematic review of diagnostic predictions
Authors: Gebregergs Gebremedhin Berhe , Berhe Gebretsadik , Gebrehiwot Kibrom Gebreslasie , Mulugeta Afework 
Published: May 2024

Background: Although tuberculosis is highly prevalent in low- and middle-income countries, millions of cases remain undetected using current diagnostic methods. To address this problem, researchers have proposed prediction rules. Objective: We analyzed existing prediction rules for the diagnosis of pulmonary tuberculosis and identified factors with a moderate to high strength of association with the disease. Methods: We conducted a comprehensive search of relevant databases (MEDLINE/PubMed, Cochrane Library, Science Direct, Global Health for Reports, and Google Scholar) up to 14 November 2022. Studies that developed diagnostic algorithms for pulmonary tuberculosis in adults from low and middle-income countries were included. Two reviewers performed study screening, data extraction, and quality assessment. The study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2. We performed a narrative synthesis. Results: Of the 26 articles selected, only half included human immune deficiency virus-positive patients. In symptomatic human immune deficiency virus patients, radiographic findings and body mass index were strong predictors of pulmonary tuberculosis, with an odds ratio of >4. However, in human immune deficiency virus-negative individuals, the biomarkers showed a moderate association with the disease. In symptomatic human immune deficiency virus patients, a C-reactive protein level ⩾10 mg/L had a sensitivity and specificity of 93% and 40%, respectively, whereas a trial of antibiotics had a specificity of 86% and a sensitivity of 43%. In smear-negative patients, anti-tuberculosis treatment showed a sensitivity of 52% and a specificity of 63%. Conclusions: The performance of predictors and diagnostic algorithms differs among patient subgroups, such as in human immune deficiency virus-positive patients, radiographic findings, and body mass index were strong predictors of pulmonary tuberculosis. However, in human immune deficiency virus-negative individuals, the biomarkers showed a moderate association with the disease. A few models have reached the World Health Organization’s recommendation. Therefore, more work should be done to strengthen the predictive models for tuberculosis screening in the future, and they should be developed rigorously, considering the heterogeneity of the population in clinical work.
Thai postmenopausal woman’s view in genitourinary syndrome of menopause
Authors: Wongapai Pattra , Jirasawas Titima , Vichinsartvichai Patsama 
Published: May 2024

Objectives To determine the prevalence of genitourinary syndrome of menopause (GSM) and their awareness, attitudes, and perception of this issue. Study design Using a specifically designed questionnaire, interviews were performed on 500 Thai postmenopausal women who attended at Vajira Hospital, Bangkok, Thailand, from August 2021 to April 2022. Results The mean age of the 500 participants was 60.39 ± 8.12 years. The prevalence of GSM was 47.2%. The common symptoms affected by GSM were vaginal dryness (38.5%), urinary urgency (24.6%), dyspareunia (13.6%), vaginal irritation (10.2%), vaginal burning (7.2%), and dysuria (5.9%). One-half of the women were uncomfortable talking about GSM. Three-quarters who did not reveal GSM symptoms believed that the problem was a part of aging. Only 20.3% of women who suffer from symptoms consulted a health care provider (HCP). Of the women who had been prescribed treatment, 84.6% of these women reported better quality of life. Conclusions GSM is a meaningful decrement in quality of life. Most Thai postmenopausal women who had symptoms believed that the problem was the aging process. Awareness of GSM and available treatment would be a further benefit.
Process mining and customer journey mapping in healthcare: Enhancing patient-centred care in stroke rehabilitation
Authors: Shafei Ingy , Karnon Jonathan , Crotty Maria 
Published: May 2024

Background Patient-centred care and enhancing patient experience is a priority across Australia. Stroke rehabilitation has multiple consumer touchpoints that would benefit from a better understanding of customer journeys, subsequently impacting better patient-centred care, and contributing to process improvements and better patient outcomes. Customer journey mapping through process mining extracts process data from event logs in existing information systems discovering patient journeys, which can be utilized to monitor guideline compliance and uncover nonconformance. Methodology Utilizing process mining and variant analysis, customer journey maps were developed for 130 stroke rehabilitation patients from referral to discharge. In total, 168 cases from the Australasian Rehabilitation Outcomes Centre dataset were matched with 6291 cases from inpatient stroke data. Variants were explored for age, gender, outcome measures, length of stay and functional independence measure (FIM) change. Results The study illustrated the process, process variants and patient journey map in stroke rehabilitation. Process characteristics of stroke rehabilitation patients were extracted and represented utilizing process mining and results highlighted process variation, attributes, touchpoints and timestamps across stroke rehabilitation patient journeys categorized by patient demographics and outcome variables. Patients demonstrated a mean and median duration of 49.5 days and 44 days, respectively, across the patient journeys. Nine variants were discovered, with 78.46% ( n = 102) of patients following the expected sequence of activities in their stroke rehabilitation patient journey. Relationships involving age, gender, length of stay and FIM change along the patient journeys were evident, with four cases experiencing stroke rehabilitation journeys of more than 100 days, warranting further investigation. Conclusion Process mining can be utilized to visualize and analyse patient journeys and identify gaps in service quality, thus contributing to better patient-centred care and improved patient outcomes and experiences in stroke rehabilitation.
Physical activity and sedentary behaviour of Bahraini people with type 2 diabetes: A cross-sectional study
Authors: Rajab Ebrahim , Wasif Pearl , Doherty Sally , Gaynor Declan , Malik Hani , Fredericks Salim , Al-Qallaf Amal , Almuqahwi Rabab , Alsharbati Wafa , Rashid-Doubell Fiza 
Published: May 2024

Objective Study patterns of physical activity and sedentary behaviour and the influence of demographics and body mass index (BMI) on these behaviours amongst Bahraini adults with type 2 diabetes over 10 weeks using an activity tracker. Method This cross-sectional observational study was conducted at a Bahrain government health centre. Thirty-three Bahraini Arab adults, 30–60 years old, with controlled type 2 diabetes, wore a Fitbit Flex 2TM activity tracker for 10 weeks. Data on age, sex, marital and employment status, education and BMI were collected at the start of the study. Results A total of N = 32 participants completed the study. The average steps per day were 7859 ± 4131, and there were no differences between baseline, week 5 and 10. A third of participants were sedentary, based on a threshold of 5000 steps/day. Females accumulated fewer average daily steps than males (6728 ± 2936 vs. 10,281 ± 4623, p = 0.018). Daily averages for physical activity intensity were as follows: sedentary (786 ± 109 min), light (250 ± 76 min), moderate (9 ± 10 min) and vigorous (12 ± 18 min). Males had higher daily averages versus females for moderate (13 ± 9 vs. 5 ± 9 min, p = 0.018) and vigorous physical activity (21 ± 23 vs. 5 ± 7 min, p = 0.034). 91% of participants wore the device ≥10 h/day. The adherence rate was 79% based on percentage of days the device was worn continuously over 10 weeks. Conclusion Future physical activity interventions should target sedentary and female participants with type 2 diabetes. In addition, we need to understand the facilitators and barriers to physical activity and the physical activity preferences of these two subgroups.
Early Hip Fracture Surgery Within 24 hours did not Reduce the Mortality Rate but Resulted in Less Postoperative Opioid use and a Shorter Length of Stay: A Retrospective Study of 276 Patients From a Tertiary Private Hospital in Thailand
Authors: Unnanuntana Aasis , Anusitviwat Chirathit , Lertsiripatarajit Vasu , Riawraengsattha Peerapol , Raksakietisak Manee 
Published: May 2024

Introduction The comparative results of early hip fracture surgery including mortality and postoperative complications in Thailand were not reported. Therefore, we conducted this study to compare the outcomes between patients who received hip surgery within and after 24 hours. Methods A retrospective study was conducted at a single center, a tertiary private hospital in Thailand. The medical records of patients who were admitted from 2018 to 2020 were reviewed. Patients aged <50 years, high-energy fracture, pathological fractures, or multiple traumas were excluded. The patients were categorized into two groups for comparison: surgery within and surgery after 24 hours groups. The outcome measures were in-hospital, 30-day, and 1-year mortality rates, length of stay, and the incidences and severities of postoperative complications. Results A total of 276 hip fracture patients were analyzed, with the majority (77.9%) undergoing surgery within 24 hours. Patients who underwent earlier surgery had a significantly shorter hospital stay [6 (4, 9) vs 8 (7, 13) days, P < .001]. The cumulative mortality rates at in-hospital, 30 days, and 1 year were 0%, 1.1%, and 2.5%, respectively. The most common postoperative complications observed were anemia (43.1%) and acute kidney injury (32.6%). However, there were no statistically significant differences in mortality rates ( P > .05) or postoperative complications ( P = .410) between the two groups. Conclusion While surgery within 24 hours showed some benefits, such as a shorter hospital stay and reduced pain rescue, it did not reduce mortality or major complications in hip fracture patients.
Digital Technologies 4.0 in Small and Medium-Sized Manufacturing Industries: Cases of the Central Region of Argentina and the Biobio Region of Chile
Authors: Gatica-Neira Francisco , Ramos-Maldonado Mario , Andrés Ascua Rubén , Revale Hernán , Fernández Valentina 
Published: May 2024

The Fourth Industrial Revolution has built upon the lessons learned from Covid-19 and has emphasized the urgent need for digital transformation in Small and Medium Enterprises (SMEs) in Latin America. This study aims to identify the factors that can explain the varying degrees of adoption of digital technologies 4.0 (DT 4.0). The research analyzes the results of surveys conducted among 35 companies located in the Central Region of Argentina and the Biobio Region of Chile. By utilizing the Technology, Organization, and Environment (TOE) model of adoption and employing data science tools, such as cluster analysis (K-means) and decision trees (J48), the study parameterizes the different responses and generates valuable insights. Our work provides a complementary view to existing studies, analyzing the key factors in the adoption of DT 4.0 in a group of SMEs located in regions, not national capitals, of two Latin American countries with different growth models. The results highlight the significance of business leaders possessing knowledge of DT 4.0, the importance of having specialized human capital, and the need for an organizational culture that embraces innovation. Public policy should focus on transforming business leadership and organizational dynamics to stimulate digital transformation. JEL Classification: O330, O140, O570
Hospital Discharge Opioid Prescribing Trends in a Multistate Institution Following the Introduction of Opioid Prescribing Guidelines and Key Metrics Dashboard
Authors: Lai Benjamin , O’Keefe Nancy , Cunningham Julie 
Published: May 2024

Background Despite the introduction of the Centers for Disease Control and Prevention's opioid prescribing guidelines, studies indicate that a significant proportion of opioids prescribed at hospital discharge remains unused. Little is known if improved provider awareness of guidelines and metrics would facilitate rightsizing opioid prescriptions at hospital discharge. Our institution created opioid prescribing guidelines and a key metrics dashboard and subsequently disseminated these tools to our institution's leadership and prescribers. We aim to evaluate the effectiveness of these efforts in reducing hospital discharge opioid prescriptions, especially those for acute pain exceeding 100 morphine milligram equivalents (MME). Methods Following the development of practice-specific opioid prescribing guidelines in 2017, a key metrics dashboard was created in 2021 to display the percentage of hospital discharges with opioids prescribed and the percentage of discharges with opioids prescribed for acute pain exceeding 100 MME. These metrics were broken down into calendar years between 2018 and 2022, and by the 7 major practice regions across our institution spanning 5 U.S. States. Results From 2018 to 2022, all regions showed a decline in the percentage of hospital discharges with opioids prescribed (range 2.7%-9.4%). In the same period, 5 of 7 regions showed a decline in discharge opioid prescriptions exceeding 100 MME for acute pain (range 8.8%-23.2%). Two sites showed an increase of 2.4% and 2.7%. Conclusion Downward trends in hospital discharge opioid prescriptions were observed for most practice regions following the introduction of our institution's opioid prescribing guidelines and key metrics dashboard.
What Faculty and Students Value When Evaluating Human Digital Anatomy Platforms: A Mixed-Methods Study
Authors: Lee Jason Wen Yau , Susanto Johan , Lai Siang Hui , Cheow Peng Chung , Low Li Xiang Tessa , Bello Fernando 
Published: May 2024

OBJECTIVES There is an increasing availability of digital technologies for teaching and learning of human anatomy. Studies have shown that such applications allow for better spatial awareness than traditional methods. These digital human anatomy platforms offer users myriad features, such as the ability to manipulate 3D models, conduct prosection, investigate anatomical regions through virtual reality, or perform knowledge tests on themselves. This study examined what faculty members’ value when using digital human anatomy platforms for teaching and what students value when using these platforms for learning. METHODS Six anatomy faculty members and 21 students were selected to participate in this study. After using the three digital anatomy platforms for at least 1 week, a survey was conducted to record their feedback in 4 categories: usability, interactive features, level of detail, and learning support. Respondents’ Qualitative feedback within each category was also analyzed to strengthen the study's findings. RESULTS The study's findings showed that faculty members and students have different priorities when evaluating digital anatomy platforms. Faculty members valued platforms that provided better accuracy and detailed anatomical structures, while students prioritized usability above the rest of the features. CONCLUSION Given that faculty and students have different preferences when selecting digital anatomy platforms, this article proposed that educators maximize the specific affordances offered by the technology by having a clear pedagogy and strategy on how the technology will be incorporated into the curriculum to help students achieve the desired learning outcomes.
Incidence and predictors of intracranial hemorrhage after intravenous thrombolysis with tenecteplase
Authors: Marnat Gaultier , Gerschenfeld Gaspard , Olindo Stephane , Sibon Igor , Seners Pierre , Clarençon Frederic , Smadja Didier , Chausson Nicolas , Ben Hassen Wagih , Piotin Michel , Caroff Jildaz , Alamowitch Sonia , Turc Guillaume 
Published: May 2024

Background: Despite its increasing use, there are limited data on the risk of intracranial hemorrhage (ICH) after intravenous thrombolysis with tenecteplase in the setting of acute ischemic stroke. Our aim was to investigate the incidence and predictors of ICH after tenecteplase administration. Methods: We reviewed data from the prospective ongoing multicenter TETRIS (Tenecteplase Treatment in Ischemic Stroke) registry. Patients with available day-1 imaging were included in this study. Clinical, imaging and biological variables were collected. Follow-up imaging performed 24 h after IVT was locally reviewed by senior neuroradiologists and neurologists. The incidence of parenchymal hematoma (PH) and any ICH were investigated. Potential predictors of PH and any ICH were assessed in multivariable logistic regressions. Subgroup analyses focusing on patients intended for endovascular treatment were performed. Results: PH and any ICH occurred in 126/1321 (incidence rate: 9.5%, 95% CI 8.1–11.2) and 521/1321 (39.4%, 95% CI 36.8–42.1) patients, respectively. Symptomatic ICH was observed in 77/1321 (5.8%; 95% CI 4.7–7.2). PH occurrence was significantly associated with poorer functional outcomes ( p < 0.0001) and death ( p < 0.0001) after 3 months. Older age (aOR = 1.03; 95% CI 1.01–1.05), male gender (aOR = 2.07; 95% CI 1.28–3.36), a history of hypertension (aOR = 2.08; 95% CI 1.19–3.62), a higher baseline NIHSS (aOR = 1.07; 95% CI 1.03–1.10) and higher admission blood glucose level (aOR = 1.12; 95% CI 1.05–1.19) were independently associated with PH occurrence. Similar associations were observed in the subgroup of patients intended for endovascular treatment. Conclusion: We quantified the incidence of ICH after IVT with tenecteplase in a real-life prospective registry and determined independent predictors of ICH. These findings allow to identify patients at high risk of ICH.
Synthetic Marijuana: Assessment of Usage, Motivation and Associated Risks in Adolescent Substance Users
Authors: Baweja Raman , Mills-Huffnagle Sara , Jernigan Amanda , Chongtham Nungshitombi , Waschbusch Daniel , Waxmonsky James G 
Published: May 2024

Objectives: Use of Synthetic and designer products, including synthetic marijuana (SM), among adolescents poses a major risk to public health. Little is known about the motivating factors of synthetic substance use in adolescents. This study examined the motivations, predictors, perceived risks and benefits, and differences with SM versus natural marijuana among adolescents. Methods: Between April 2016 and May 2018, a convenience sample of adolescents receiving substance use treatment from a local counseling center completed an anonymous survey to assess the use of natural and synthetic marijuana use, the Strengths and Difficulties Questionnaire to assess levels of current psychiatric symptoms and the Community Assessment of Psychic Experiences-Positive Scale to assess symptoms of psychosis. Results: A total of 80 adolescents (age range of 14-18 years; 71% male; 53% Caucasian) completed the study. Of these, 39 (49%) reported natural marijuana use (natural marijuana users) and 41 (51%) reported both synthetic and natural marijuana use (dual users). The most commonly reported reasons for using SM were its low cost and reduced risk of detection. Participants who were familiar with SM and reported a desire to avoid detection on drug tests were likelier to use SM (all P < .05). Dual users reported more benefits and risks associated with SM use when compared to natural marijuana users ( P ⩽ .05). The use of SM also heightened the perceived medical risks of natural marijuana, including seizures and respiratory issues ( P < .05), compared with natural marijuana users. While dual users self-reported more conduct ( P = .009) and externalizing problems ( P = .024) when compared to natural marijuana users, there were no group differences in psychotic symptoms, nor correlations with the frequency of synthetic or natural marijuana use and psychotic symptoms except that persecutory ideation correlated with the frequency of natural marijuana use during the past 12 months ( rp = 0.28, P = .04). Conclusions: These results suggest that reports of cost savings, and lack of detection on urine drug screens are common reasons for SM use in adolescents despite being aware of the risks of using SM. Perceived benefits of using synthetics and other novel substances appear diverse, and merit further exploration as a better understanding of what motivates adolescents to use specific novel substances may guide prevention and treatment efforts.
Unstructured Road Extraction in UAV Images based on Lightweight Model
Authors: Zhang Di , An Qichao , Feng Xiaoxue , Liu Ronghua , Han Jun , Pan Feng 
Published: May 2024

AbstractThere is no unified planning standard for unstructured roads, and the morphological structures of these roads are complex and varied. It is important to maintain a balance between accuracy and speed for unstructured road extraction models. Unstructured road extraction algorithms based on deep learning have problems such as high model complexity, high computational cost, and the inability to adapt to current edge computing devices. Therefore, it is best to use lightweight network models. Considering the need for lightweight models and the characteristics of unstructured roads with different pattern shapes, such as blocks and strips, a TMB (Triple Multi-Block) feature extraction module is proposed, and the overall structure of the TMBNet network is described. The TMB module was compared with SS-nbt, Non-bottleneck-1D, and other modules via experiments. The feasibility and effectiveness of the TMB module design were proven through experiments and visualizations. The comparison experiment, using multiple convolution kernel categories, proved that the TMB module can improve the segmentation accuracy of the network. The comparison with different semantic segmentation networks demonstrates that the TMBNet network has advantages in terms of unstructured road extraction.
Reinforcement Learning-Based Energy Management for Hybrid Power Systems: State-of-the-Art Survey, Review, and Perspectives
Authors: Tang Xiaolin , Chen Jiaxin , Qin Yechen , Liu Teng , Yang Kai , Khajepour Amir , Li Shen 
Published: May 2024

AbstractThe new energy vehicle plays a crucial role in green transportation, and the energy management strategy of hybrid power systems is essential for ensuring energy-efficient driving. This paper presents a state-of-the-art survey and review of reinforcement learning-based energy management strategies for hybrid power systems. Additionally, it envisions the outlook for autonomous intelligent hybrid electric vehicles, with reinforcement learning as the foundational technology. First of all, to provide a macro view of historical development, the brief history of deep learning, reinforcement learning, and deep reinforcement learning is presented in the form of a timeline. Then, the comprehensive survey and review are conducted by collecting papers from mainstream academic databases. Enumerating most of the contributions based on three main directions—algorithm innovation, powertrain innovation, and environment innovation—provides an objective review of the research status. Finally, to advance the application of reinforcement learning in autonomous intelligent hybrid electric vehicles, future research plans positioned as “Alpha HEV” are envisioned, integrating Autopilot and energy-saving control.