Search results for: delayed diagnosis and poor outcome

Authors: Roongtiwa Chobchuen, Angkana Srikhan, Pattra Wattanapan

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Background: Neurogenic bowel is common condition after spinal cord injury. Most of spinal cord injured patients have motor weakness, mobility impairment which leads to constipation. Moreover, the neural pathway involving bowel function is interrupted. Therefore, the bowel management program should be implemented in nursing care in the earliest time after the onset of the disease to prevent the morbidity and mortality. Objective: To study the outcome of bowel management program of the patients with spinal cord injury who admitted for rehabilitation program. Study design: Descriptive study. Setting: Rehabilitation ward in Srinagarind Hospital. Populations: patients with subacute to chronic spinal cord injury who admitted at rehabilitation ward, Srinagarind hospital, aged over 18 years old. Instrument: The neurogenic bowel dysfunction score (NBDS) was used to determine the severity of neurogenic bowel. Procedure and statistical analysis: All participants were asked to complete the demographic data; age gender, duration of disease, diagnosis. The individual bowel function was assessed using NBDS at admission. The patients and caregivers were trained by nurses about the bowel management program which consisted of diet modification, abdominal massage, digital stimulation, stool evacuation including medication and physical activity. The outcome of the bowel management program was assessed by NBDS at discharge. The chi-square test was used to detect the difference in severity of neurogenic bowel at admission and discharge. Results: Sixteen spinal cord injured patients were enrolled in the study (age 45 ± 17 years old, 69% were male). Most of them (50%) were tetraplegia. On the admission, 12.5%, 12.5%, 43.75% and 31.25% were categorized as very minor (NBDS 0-6), minor (NBDS 7-9), moderate (NBDS 10-13) and severe (NBDS 14+) respectively. The severity of neurogenic bowel was decreased significantly at discharge (56.25%, 18.755%, 18.75% and 6.25% for very minor, minor, moderate and severe group respectively; p < 0.001) compared with NBDS at admission. Conclusions: Implementation of the effective bowel program decrease the severity of the neurogenic bowel in patient with spinal cord injury.

Keywords: neurogenic bowel, NBDS, spinal cord injury, bowel program

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Authors: J. Leige Lopes, L. Aparecida Bastos, R. Monteiro da Silva

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The objective of this paper is to study the work of children and adolescents and the vicious circle of poverty from the perspective of Guinar Myrdal’s Theory of Circular Cumulative Causation. The objective is to show that if a person starts working in the juvenile phase of life they will be classified as poor or extremely poor when they are adult, which can to be observed in the case of Brazil, more specifically in the north and northeast. To do this, the methodology used was statistical and econometric analysis by applying a probit model. The main results show that: if people reside in the northeastern region of Brazil, and if they have a low educational level and if they start their professional life before the age 18, they will increase the likelihood that they will be poor or extremely poor. There is a consensus in the literature that one of the causes of the intergenerational transmission of poverty is related to child labor, this because when one starts their professional life while still in the toddler or adolescence stages of life, they end up sacrificing their studies. Because of their low level of education, children or adolescents are forced to perform low-paid functions and abandon school, becoming in the future, people who will be classified as poor or extremely poor. As a result of poverty, parents may be forced to send their children out to work when they are young, so that in the future they will also become poor adults, a process that is characterized as the "vicious circle of poverty."

Keywords: children, adolescents, Gunnar Myrdal, poverty, vicious circle

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Authors: Anthony Nyamekeh-Armah Adjei, Toshiaki Aoki

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The unreliable and poor efficiency of electricity distribution leading to frequent power outages and high losses are the major challenge facing the power distribution sector in Ghana. Distribution system routes electricity from the power generating station at a higher voltage through the transmission grid and steps it down through the low voltage lines to end users. Approximately all electricity problems and disturbances that have increased the call for renewable and sustainable energy in recent years have their roots in the distribution system. Therefore, sustaining electricity distribution efficiency can potentially contribute to the reserve of natural energy resources use in power generation, reducing greenhouse gas emission (GHG), decreasing tariffs for consumers and effective human security. Human Security is a people-centered approach where individual human being is the principal object of concern, focuses on protecting the vital core of all human lives in ways for meeting basic needs that enhance the safety and protection of individuals and communities. The vulnerability is the diminished capacity of an individual or group to anticipate, resist and recover from the effect of natural, human-induced disaster. The research objectives are to explore the causes of frequent power outages to consumers, high losses in the distribution network and the effect of poor electricity distribution efficiency on the vulnerable (poor and ordinary) people that mostly depend on electricity for their daily activities or life to survive. The importance of the study is that in a developing country like Ghana where raising a capital for new infrastructure project is difficult, it would be beneficial to enhance the efficiency that will significantly minimize the high energy losses, reduce power outage, to ensure safe and reliable delivery of electric power to consumers to secure the security of people’s livelihood. The methodology used in this study is both interview and questionnaire survey to analyze the response from the respondents on causes of power outages and high losses facing the electricity company of Ghana (ECG) and its effect on the livelihood on the vulnerable people. Among the outcome of both administered questionnaire and the interview survey from the field were; poor maintenance of existing sub-stations, use of aging equipment, use of poor distribution infrastructure and poor metering and billing system. The main observation of this paper is that the poor network efficiency (high losses and power outages) affects the livelihood of the vulnerable people. Therefore, the paper recommends that policymakers should insist on all regulation guiding electricity distribution to improve system efficiency. In conclusion, there should be decentralization of off-grid solar PV technologies to provide a sustainable and cost-effective, which can increase daily productivity and improve the quality of life of the vulnerable people in the rural communities.

Keywords: electricity efficiency, high losses, human security, power outage

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Authors: Jiahua Zhang, Qing Chang, Fengmei Yao

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Studying on the response of vegetation phenology to climate change at different temporal and spatial scales is important for understanding and predicting future terrestrial ecosystem dynamics andthe adaptation of ecosystems to global change. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) dataset and climate data were used to analyze the dynamics of grassland phenology as well as their correlation with climatic factors in different eco-geographic regions and elevation units across the Tibetan Plateau. The results showed that during 2003–2012, the start of the grassland greening season (SOS) appeared later while the end of the growing season (EOS) appeared earlier following the plateau’s precipitation and heat gradients from southeast to northwest. The multi-year mean value of SOS showed differences between various eco-geographic regions and was significantly impacted by average elevation and regional average precipitation during spring. Regional mean differences for EOS were mainly regulated by mean temperature during autumn. Changes in trends of SOS in the central and eastern eco-geographic regions were coupled to the mean temperature during spring, advancing by about 7d/°C. However, in the two southwestern eco-geographic regions, SOS was delayed significantly due to the impact of spring precipitation. The results also showed that the SOS occurred later with increasing elevation, as expected, with a delay rate of 0.66 d/100m. For 2003–2012, SOS showed an advancing trend in low-elevation areas, but a delayed trend in high-elevation areas, while EOS was delayed in low-elevation areas, but advanced in high-elevation areas. Grassland SOS and EOS changes may be influenced by a variety of other environmental factors in each eco-geographic region.

Keywords: grassland, phenology, MODIS, eco-geographic regions, elevation, climatic factors, Tibetan Plateau

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Authors: J. Byimana, I. A. Muhire, J. E. Nzabahimana, A. Nyombayire

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Introduction: A successful cardiopulmonary resuscitation during a sudden cardiac arrest can be delayed by different components including new hospital setting, lack of adequate training, lack of pre-established resuscitation team and ineffective communication and lead to an unexpected outcome which is death. The main objective of the study was to assess the readiness of resuscitation teams during cardiac arrest and the organizational approaches that would best support their functioning in a new hospital facility, and to detect any factor that may have contributed to responses. This study analyses the readiness of Resuscitation Team (RT) during cardiac arrest. —Material and methods: A prospective Analytic design was carried out at a newly established United Nations level 2 hospital facility, on four RTM (resuscitation team member). A semi structured questionnaire was used to collect data. —Results: This study highlights indicate that the response time during cardiac arrest simulation meet both American heart association (AHA) and European resuscitation council guidelines. The study offers useful evidence about the impact of a new facility on RTM performance and provides an exposure of staff to emergency events within the Work setting.

Keywords: cardiac arrest, code blue, simulation, resuscitation team member

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Authors: Victor Au, Khin Maung Than, Zaw Win Aung, Linawati Jumat

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Background & Objectives: Cardiac arrests can occur anywhere or anytime, and most of the cases will be brought to the emergency department except the cases that happened in at in-patient setting. Raja IsteriPangiran Anak Saleha (RIPAS) Hospital is the only tertiary government hospital which located in Brunei Muara district and received all referral from other Brunei districts. Data of cardiac arrests in Brunei Darussalam scattered between Emergency Medical Ambulance Services (EMAS), Emergency Department (ED), general inpatient wards, and Intensive Care Unit (ICU). In this audit, we only focused on cardiac arrest cases which had happened or presented to the emergency department RIPAS Hospital. Theobjectives of this audit were to look at demographic of cardiac arrest cases and the survival to discharge rate of In-Hospital Cardiac Arrest (IHCA) and Out-Hospital Cardiac Arrest (OHCA). Methodology: This audit retrospective study was conducted on all cardiac arrest cases that underwent Cardiopulmonary Resuscitation (CPR) in ED RIPAS Hospital, Brunei Muara, in the year 2019-2020. All cardiac arrest cases that happened or were brought in to emergency department were included. All the relevant data were retrieved from ED visit registry book and electronic medical record “Bru-HIMS” with keyword diagnosis of “cardiac arrest”. Data were analyzed and tabulated using Excel software. Result: 313 cardiac arrests were recorded in the emergency department in year 2019-2020. 92% cases were categorized as OHCA, and the remaining 8% as IHCA. Majority of the cases were male with age between 50-60 years old. In OHCA subgroup, only 12.4% received bystander CPR, and 0.4% received Automatic External Defibrillator (AED) before emergency medical personnel arrived. Initial shockable rhythm in IHCA group accounted for 12% compare to 4.9% in OHCA group. Outcome of ED resuscitation, 32% of IHCA group achieved return of spontaneous circulation (ROSC) with a survival to discharge rate was 16%. For OHCA group, 12.35% achieved ROSC, but unfortunately, none of them survive till discharge. Conclusion: Standardized registry for cardiac arrest in the emergency department is required to provide valid baseline data to measure the quality and outcome of cardiac arrest. Zero survival rate for out hospital cardiac arrest is very concerning, and it might represent the significant breach in cardiac arrest chains of survival. Systematic prospective data collection is needed to identify contributing factors and to improve resuscitation outcome.

Keywords: cardiac arrest, OHCA, IHCA, resuscitation, emergency department

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Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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Authors: Chinelo Igwenagu

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Teenage childbearing in developing countries has been a thing of great concern as it has often led to a number of socioeconomic problems both to the society and to the families affected. The outcome of teenage pregnancy has been generally associated with higher rates of maternal morbidity and mortality, greater risks for delivery complications, low-birth weight infants and child mortality. As a result of teenagers’ physiological and social immaturity and their lack of adequate prenatal care, health risks associated with their pregnancies and childbearing are more pronounced than those of older women. Therefore this study has examined the relationship between the age of teenagers and the outcome of teenage pregnancy. Based on this study, the result of the analysis shows that both teenagers and older mothers suffer similarly during child bearing. Hence improve medical care is paramount in all the situations.

Keywords: childbearing, mortality, Nigeria, pregnancy, prematurity, teenagers

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Authors: O. P. Rahi, Manoj Kumar

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Power transformers are essential and expensive equipments in electrical power system. Dissolved gas analysis (DGA) is one of the most useful techniques to detect incipient faults in power transformers. However, the identification of the faulted location by conventional method is not always an easy task due to variability of gas data and operational variables. In this paper, an extension theory based power transformer fault diagnosis method is presented. Extension theory tries to solve contradictions and incompatibility problems. This paper first briefly introduces the basic concept of matter element theory, establishes the matter element models for three-ratio method, and then briefly discusses extension set theory. Detailed analysis is carried out on the extended relation function (ERF) adopted in this paper for transformer fault diagnosis. The detailed diagnosing steps are offered. Simulation proves that the proposed method can overcome the drawbacks of the conventional three-ratio method, such as no matching and failure to diagnose multi-fault. It enhances diagnosing accuracy.

Keywords: DGA, extension theory, ERF, fault diagnosis power transformers, fault diagnosis, fuzzy logic

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Authors: Auni Idi Muhire

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Background: Prior to April 2012, resuscitations were often ineffective resulting in poor patient outcomes. An initiative was implemented at Rwanda Military Hospital (RMH) to review root causes and plan strategies to improve patient outcomes. An interdisciplinary committee was developed to review this problem. Purpose: Analyze the frequency, obstacles, and outcome of patient resuscitation following cardiac and/or respiratory arrest. Methods: A form was developed to allow recording of all actions taken during resuscitation including response times, staff present, and equipment and medications used. Results:-The patient population requiring the most resuscitation effort are the intensive care patients, most frequently the neonatal the intensive care patients (42.8%) -Despite having trained staff representatives, not all resuscitations follow protocol -Lack of compliance with drug administration guidelines was noted, particularly in initiating use of drugs despite the drug being available (59%). Lesson Learned: Basic Life Support training for interdisciplinary staff resulted in more effective response to cardiac and/or respiratory arrest at RMH. Obstacles to effective resuscitation included number of staff, knowledge and skill level of staff, availability of appropriate equipment and medications, staff communication, and patient Do not Attempt Resuscitation (DNR) status.

Keywords: resuscitation, case analysis of knowledge versus practice, intensive care, critical care

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Authors: Ahmad FAROOQ, Xinfeng Zhang, Fahad Sabah, Raheem Sarwar

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In Traditional Chinese Medicine, tongue diagnosis is a vital inspection tool (TCM). In this study, we explore the potential of machine learning in tongue diagnosis. It begins with the cataloguing of the various classifications and characteristics of the human tongue. We infer 24 kinds of tongues from the material and coating of the tongue, and we identify 21 attributes of the tongue. The next step is to apply machine learning methods to the tongue dataset. We use the Weka machine learning platform to conduct the experiment for performance analysis. The 457 instances of the tongue dataset are used to test the performance of five different machine learning methods, including SVM, Random Forests, Decision Trees, and Naive Bayes. Based on accuracy and Area under the ROC Curve, the Support Vector Machine algorithm was shown to be the most effective for tongue diagnosis (AUC).

Keywords: medical imaging, image retrieval, machine learning, tongue

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Authors: Ana Ferraz, Martim Santos, M. Graça Pereira

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Distress among parents of children with acute lymphoblastic leukemia (ALL) is common during treatment and can persist several years post-diagnosis, impacting the adjustment of children and parents themselves. Current evidence is needed to examine the scope and nature of parental distress in childhood ALL. This review focused on associated variables, predictors, and outcomes of parental distress following their ALL diagnosis of their child. PubMed, Web of Science, and PsycINFO databases were searched for English and Spanish papers published from 1983 to 2021. PRISMA statement was followed, and papers were evaluated through a standardized methodological quality assessment tool (NHLBI). Of the 28 papers included, 16 were evaluated as fair, eight as good, and four as poor. Regarding results, 11 papers reported subgroup differences, and 15 found potential predictors of parental distress, including sociodemographic, psychosocial, psychological, family, health, and ALL-specific variables. Significant correlations were found between parental distress, social support, illness cognitions, and resilience, as well as contradictory results regarding the impact of sociodemographic variables on parental distress. Family cohesion and caregiver burden were associated with distress, and the use of healthy coping strategies was associated with less anxiety. Caregiver strain contributed to distress, and the overall impact of illness positively predicted anxiety in mothers and somatization in fathers. Differences in parental distress were found regarding group risk, time since diagnosis, and treatment phases. Thirteen papers explored the outcomes of parental distress on psychological, family, health, and social/education outcomes. Parental distress was the most important predictor of family strain. Significant correlations were found between parental distress at diagnosis and further psychological adjustment of parents themselves and their children. Most papers reported correlations between parental distress on children’s adjustment and quality of life, although few studies reported no association. Correlations between maternal depression and child participation in education and social life were also found. Longitudinal studies are needed to better understand parental distress and its consequences on health outcomes, in particular. Future interventions should focus mainly on parents on distress reduction and psychological adjustment, both in parents and children over time.

Keywords: childhood acute lymphoblastic leukemia, family, parental distress, psychological adjustment, quality of life

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Authors: F. Sallem, B. Dahhou, A. Kamoun

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In this work, the main problem considered is the detection and the isolation of the actuator fault. A new formulation of the linear system is generated to obtain the conditions of the actuator fault diagnosis. The proposed method is based on the representation of the actuator as a subsystem connected with the process system in cascade manner. The designed formulation is generated to obtain the conditions of the actuator fault detection and isolation. Detectability conditions are expressed in terms of the invertibility notions. An example and a comparative analysis with the classic formulation illustrate the performances of such approach for simple actuator fault diagnosis by using the linear model of nuclear reactor.

Keywords: actuator fault, Fault detection, left invertibility, nuclear reactor, observability, parameter intervals, system inversion

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Authors: Frantisek Kopriva, Kamila Michalkova, Radim Dudek, Jana Volejnikova

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Rationale: Diagnostic criteria of asthma–COPD overlap syndrome (ACOS) are controversial in pediatrics. Emphysema is characteristic of COPD and usually does not occur in typical asthma; its presence in patients with asthma suggests the concurrence with COPD. Low-dose chest computed tomography (CT) allows a non-invasive assessment of the lung tissue structure. Here we present CT findings of emphysematous changes in a child with ACOS. Patient and Methods: In a 6-year-old boy, atopy was confirmed by a skin prick test using common allergen extracts (grass and tree pollen, house dust mite, molds, cat, dog; manufacturer Stallergenes Greer, London, UK), where reactions over 3 mm were considered positive. Treatment with corticosteroids was started during the course of severe asthma. At 12 years of age, his spirometric parameters deteriorated despite treatment adjustment (VC 1.76 L=85%, FEV1 1.13 L=67%, TI%VCmax 64%, MEF25 19%, TLC 144%) and the bronchodilator test became negative. Results: Low-dose chest CT displayed irregular regions with increased radiolucency of pulmonary parenchyma (typical for hyperinflation in emphysematous changes) in both lungs. This was in accordance with the results of spirometric examination. Conclusions: ACOS is infrequent in children. However, low-dose chest CT scan can be considered to confirm this diagnosis or eliminate other diagnoses when the clinical condition is deteriorating and treatment response is poor.

Keywords: child, asthma, low-dose chest CT, ACOS

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Authors: Andres Frederic

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We present the MindFlow system supporting the detection and the diagnosis of stresses. The heart of the system is a knowledge synthesis engine allowing occupational health stakeholders (psychologists, occupational therapists and human resource managers) to formulate queries related to stress and responding to users requests by recommending a pattern of stress if one exists. The stress pattern diagnosis is based on expert knowledge stored in the MindFlow stress ontology including stress feature vector. The query processing may involve direct access to the MindFlow system by occupational health stakeholders, online communication between the MindFlow system and the MindFlow domain experts, or direct dialog between a occupational health stakeholder and a MindFlow domain expert. The MindFlow knowledge model is generic in the sense that it supports the needs of psychologists, occupational therapists and human resource managers. The system presented in this paper is currently under development as part of a Dutch-Japanese project and aims to assist organisation in the quick diagnosis of stress patterns.

Keywords: occupational stress, stress management, physiological measurement, accident prevention

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Authors: Rajamani Doraiswami, Lahouari Cheded

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Fault diagnosis of Linear Parameter-Varying (LPV) system using an adaptive Kalman filter is proposed. The LPV model is comprised of scheduling parameters, and the emulator parameters. The scheduling parameters are chosen such that they are capable of tracking variations in the system model as a result of changes in the operating regimes. The emulator parameters, on the other hand, simulate variations in the subsystems during the identification phase and have negligible effect during the operational phase. The nominal model and the influence vectors, which are the gradient of the feature vector respect to the emulator parameters, are identified off-line from a number of emulator parameter perturbed experiments. A Kalman filter is designed using the identified nominal model. As the system varies, the Kalman filter model is adapted using the scheduling variables. The residual is employed for fault diagnosis. The proposed scheme is successfully evaluated on simulated system as well as on a physical process control system.

Keywords: identification, linear parameter-varying systems, least-squares estimation, fault diagnosis, Kalman filter, emulators

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Authors: Khader A. Almhdawi, Hassan Alrabbaie

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Background: Musculoskeletal disorders (MSDs) represent a significant challenge for registered nurses. To our best knowledge, there is no published study that investigated the prevalence of MSDs among nurses and their associated factors comprehensively in Jordan. This study aimed to find the prevalence of MSDs, their possible predictors among registered nurses in Jordanian hospitals. Methods: A cross-sectional design was used. Outcome measures included Nordic Musculoskeletal Questioner (NMQ), Depression Anxiety Stress Scale (DASS), Pittsburgh Sleep Quality Index (PSQI), IPAQ, and sociodemographic data. Prevalence of musculoskeletal complaints was reported using descriptive analysis. Logistic regression analyses were conducted to identify predictors of MSDs. Results: 597 nurses from different hospitals in Jordan participated in this study. Reported MSDs prevalence was the highest at neck (61.1%), followed by upper back (47.2%), shoulder (46.7%), wrist and hands (27.3%), and elbow (13.9%). Significant predictors of MSDs among Jordanian nurses included: being a female, poor sleep quality, high physical activity levels, poor ergonomics, increased workload, and mental stress. Conclusion: This study showed a high prevalence of MSDs among Jordanian nurses and identified their significant predictors. Future studies are needed to investigate the progressive nature of MSDs and their effective treatment strategies.

Keywords: musculoskeletal disorders, nursing, ergonomic, occupational stress

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Authors: Bin Feng, Zhulin Zong

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Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

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Authors: Shih-Heng Sun, Hsiu-Yu Chang

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“Family centered service model” becomes mainstream in early intervention. Family outcome should be evaluated in addition child improvement in terms of outcome evaluation in early intervention. The purpose of this study is to develop a surveys to evaluate family outcomes in early intervention. Method: “Family Outcomes Survey- Revised Taiwan Version” (FOS-RT) was developed through translation, back-translation, and review by the original author. Expert meeting was held to determine the content validity. Two hundred and eighty six parent-child dyads recruited from 10 local Early Intervention Resource Centers (EIRC) participated in the study after they signed inform consent. The results showed both parts of FOS-RT exhibits good internal consistency and test-retest reliability. The result of confirmatory factor analysis indicated moderate fit of 5 factor structure of part A and 3 factor structure of part B of FOS-RT. The correlation between different sessions reached moderate to high level reveals some sessions measure similar latent trait of family outcomes. Correlation between FOS-RT and Parents‘ Perceived Parenting Skills Questionnaire was calculated to determine the convergence validity. The moderate correlation indicates the two assessments measure different parts of early intervention outcome although both assessments have similar sub-scales. The results of this study support FOS-RT is a valid and reliable tool to evaluate family outcome after the family and children with developmental disability receive early intervention services.

Keywords: early intervention, family service, outcome evaluation, parenting skills, family centered

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Authors: S. Hallal, Z. Chami, A. Hadji-Lehtihet, S. Sokhal-Boudella, A. Berhoune, L. Yargui

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Gaucher disease is the most common lysosomal storage in our population, it is due to a deficiency of β –glucosidase acid. The enzyme deficiency causes a pathological accumulation of undegraded substrate in lysosomes. This metabolic overload is responsible for a multisystemic disease with hepatosplenomegaly, anemia, thrombocytopenia, and bone involvement. Neurological involvement is rare. The laboratory diagnosis of Gaucher disease consists of phenotypic diagnosis by determining the enzymatic activity of β - glucosidase by fluorimetric method, a study by genotypic diagnosis in the GBA gene, limiting the search recurrent mutations (N370S, L444P, 84 GG); PCR followed by an enzymatic digestion. Abnormal profiles were verified by sequencing. Monitoring of treated patients is provided by the determination of chitotriosidase. Our experience spaning a period of 6 years (2007-2014) has enabled us to diagnose 78 patients out of a total of 328 requests from the various departments of pediatrics, internal medicine, neurology. Genotypic diagnosis focused on the entire family of 9 children treated at pediatric CHU Mustapha, which help define the clinical form; or 5 of them had type III disease, carrying the L444P mutation in the homozygous state. Three others were composite (N370/L444P) (N370S/other unintended mutation in our study), and only in one family no recurrent mutation has been found. This molecular study permits screening of heterozygous essential for genetic counseling.

Keywords: Gaucher disease, mutations, N370S, L444P

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Authors: Birendra Kumar Bista, Rhitik Bista, Prafulla Koirala, Lokendra Mandal, Nikrsh Raj Shrestha, Vivek Kattel

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Introduction: Poorly controlled diabetes is associated with cause and poor outcome of stroke. High blood sugar reduces cerebral blood flow, increases intracranial pressure, cerebral edema and neuronal death, especially among patients with poorly controlled diabetes.1 SGLT2 inhibitors are associated with 50% reduction in hemorrhagic stroke compared with placebo. SGLT2 inhibitors decrease cardiovascular events via reducing glucose, blood pressure, weight, arteriosclerosis, albuminuria and reduction of atrial fibrillation.2,3 No study has been documented in low income countries to see the role of post stroke SGLT2 inhibitors on diabetic patients at and after ICU admission. Aims: The aim of the study was to measure the 12 months outcome of diabetic patients with acute stroke admitted in ICU set up with naïve SGLT2 inhibitors add on therapy. Method: It was prospective cohort study carried out in a 250 bedded tertiary neurology care hospital at the province capital Biratnagar Nepal. Diabetic patient with acute stroke admitted in ICU from 1st January 2022 to 31st December 2022 who were not under SGLT2 inhibitors were included in the study. These patients were managed as per hospital protocol. Empagliflozin was added to the alternate enrolled patients. Empagliflozin was continued at the time of discharged and during follow up unless contraindicated. These patients were followed up for 12 months. Outcome measured were mortality, morbidity requiring readmission or hospital visit other than regular follow up, SGLT2 inhibitors related adverse events, neuropsychiatry comorbidity, functional status and biochemical parameters. Ethical permission was taken from hospital administration and ethical board. Results: Among 147 diabetic cases 68 were not treated with empagliflozin whereas 67 cases were started the SGLT2 inhibitors. HbA1c level and one year mortality was significantly low among patients on empaglifozin arm. Over a period of 12 months 427 acute stroke patients were admitted in the ICU. Out of them 44% were female, 61% hypertensive, 34% diabetic, 57% dyslipidemia, 26% smoker and with median age of 45 years. Among 427 cases 4% required neurosurgical interventions and 76% had hemorrhagic CVA. The most common reason for ICU admission was GCS<8 (51%). The median ICU stay was 5 days. ICU mortality was 21% whereas 1 year mortality was 41% with most common reason being pneumonia. Empaglifozin related adverse effect was seen in 11% most commonly lower urinary tract infection in 6%. Conclusion: Empagliflozin can safely be started among acute stroke with better Hba1C control and low mortality outcome compared to treatment without SGLT2 inhibitor.

Keywords: diabetes, ICU, mortality, SGLT2 inhibitors, stroke

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Authors: Jiajia Peng, Jianqing Qiu, Jianjun Ren, Yu Zhao

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Background: Insufficient sleep has been focused on as a public health epidemic. However, a comprehensive analysis of disease trajectory associated with unhealthy sleep habits is still unclear currently. Objective: This study sought to comprehensively clarify the disease's trajectory in relation to the overall poor sleep pattern and unhealthy sleep behaviors separately. Methods: 410,682 participants with available information on sleep behaviors were collected from the UK Biobank at the baseline visit (2006-2010). These participants were classified as having high- and low risk of each sleep behavior and were followed from 2006 to 2020 to identify the increased risks of diseases. We used Cox regression to estimate the associations of high-risk sleep behaviors with the elevated risks of diseases, and further established diseases trajectory using significant diseases. The low-risk unhealthy sleep behaviors were defined as the reference. Thereafter, we also examined the trajectory of diseases linked with the overall poor sleep pattern by combining all of these unhealthy sleep behaviors. To visualize the disease's trajectory, network analysis was used for presenting these trajectories. Results: During a median follow-up of 12.2 years, we noted 12 medical conditions in relation to unhealthy sleep behaviors and the overall poor sleep pattern among 410,682 participants with a median age of 58.0 years. The majority of participants had unhealthy sleep behaviors; in particular, 75.62% with frequent sleeplessness, and 72.12% had abnormal sleep durations. Besides, a total of 16,032 individuals with an overall poor sleep pattern were identified. In general, three major disease clusters were associated with overall poor sleep status and unhealthy sleep behaviors according to the disease trajectory and network analysis, mainly in the digestive, musculoskeletal and connective tissue, and cardiometabolic systems. Of note, two circularity disease pairs (I25→I20 and I48→I50) showed the highest risks following these unhealthy sleep habits. Additionally, significant differences in disease trajectories were observed in relation to sex and sleep medication among individuals with poor sleep status. Conclusions: We identified the major disease clusters and high-risk diseases following participants with overall poor sleep health and unhealthy sleep behaviors, respectively. It may suggest the need to investigate the potential interventions targeting these key pathways.

Keywords: sleep, poor sleep, unhealthy sleep behaviors, disease trajectory, UK Biobank

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Authors: Shahabeddin Sotudian, M. H. Fazel Zarandi, I. B. Turksen

Abstract:

Hepatitis is one of the most common and dangerous diseases that affects humankind, and exposes millions of people to serious health risks every year. Diagnosis of Hepatitis has always been a challenge for physicians. This paper presents an effective method for diagnosis of hepatitis based on interval Type-II fuzzy. This proposed system includes three steps: pre-processing (feature selection), Type-I and Type-II fuzzy classification, and system evaluation. KNN-FD feature selection is used as the preprocessing step in order to exclude irrelevant features and to improve classification performance and efficiency in generating the classification model. In the fuzzy classification step, an “indirect approach” is used for fuzzy system modeling by implementing the exponential compactness and separation index for determining the number of rules in the fuzzy clustering approach. Therefore, we first proposed a Type-I fuzzy system that had an accuracy of approximately 90.9%. In the proposed system, the process of diagnosis faces vagueness and uncertainty in the final decision. Thus, the imprecise knowledge was managed by using interval Type-II fuzzy logic. The results that were obtained show that interval Type-II fuzzy has the ability to diagnose hepatitis with an average accuracy of 93.94%. The classification accuracy obtained is the highest one reached thus far. The aforementioned rate of accuracy demonstrates that the Type-II fuzzy system has a better performance in comparison to Type-I and indicates a higher capability of Type-II fuzzy system for modeling uncertainty.

Keywords: hepatitis disease, medical diagnosis, type-I fuzzy logic, type-II fuzzy logic, feature selection

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

Abstract:

Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

Abstract:

Vibration analysis has been frequently applied in the condition monitoring and fault diagnosis of rolling element bearings. Unfortunately, the vibration signals collected from a faulty bearing are generally non stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, condition monitoring, local mean decomposition, rolling element bearing, vibration analysis

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Authors: Alejandro Paz Parra, Jose Luis Oslinger Gutierrez, Javier Olaya Ochoa

Abstract:

In the present paper, five electric current based methods to analyze electric faults on the stator of induction motors (IM) are used and compared. The analysis tries to extend the application of the multiple reference frames diagnosis technique. An eccentricity indicator is presented to improve the application of the Park’s Vector Approach technique. Most of the fault indicators are validated and some others revised, agree with the technical literatures and published results. A tri-phase 3hp squirrel cage IM, especially modified to establish different fault levels, is used for validation purposes.

Keywords: motor fault diagnosis, induction motor, MCSA, ESA, Extended Park´s vector approach, multiparameter analysis

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Authors: Farman Ali, Asif Mahmood

Abstract:

The utilization of genetic markers in prostate cancer management represents a significant advance in personalized medicine, offering the potential for more precise diagnosis and tailored treatment strategies. This paper explores the pivotal role of genetic markers in the diagnosis and treatment of prostate cancer, emphasizing their contribution to the identification of individual risk profiles, tumor aggressiveness, and response to therapy. By integrating current research findings, we discuss the application of genetic markers in developing targeted therapies and the implications for patient outcomes. Despite the promising advancements, challenges such as accessibility, cost, and the need for further validation in diverse populations remain. The paper concludes with an outlook on future directions, underscoring the importance of genetic markers in revolutionizing prostate cancer care.

Keywords: prostate cancer, genetic markers, personalized medicine, BRCA1 and BRCA2

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Authors: I. Caldas, T. Duarte

Abstract:

Avoidant Restrictive Food Intake Disorder (ARFID) was included for the first time in DSM-5, replacing the old diagnosis of DSM-4 'Early Childhood Eating Disorder'. An ARFID is characterized by a restrictive/avoidant eating pattern that can lead to severe nutritional deficiency, weight loss, nutritional supplementation dependence, and poor psychosocial functioning. This eating pattern is associated with decreased interest in food, worries about food characteristics or the act of ingestion, and lack of concern with weight or body image. This paper aims to understand the impact of this new diagnosis in other Eating Disorders (ED) prevalence, as well as to compare their therapeutic approaches. Methodology: Literature reviewed by PubMed with the following keywords: 'ARFID', 'Prevalence', and 'Eating Disorders'. We selected articles related to this theme, written since 2016. Results: In a population of children hospitalized with ED, 5% to 14% was diagnosed with ARFID, and, as outpatient treatment, the prevalence was 22%. People diagnosed with ARFID have more prevalence of other comorbidities, especially autism spectrum, are younger, and are more often male. Regarding the treatment of ARFID, it most often required nasogastric feeding, and with less suffering associated with this procedure, compared to AN. Despite these differences, 12% of patients diagnosed with ARFID transited to AN during treatment, suggesting that the first pathology may be a risk factor for the development of AN. Conclusions: The differences identified between ARFID and the other EDs are important when analyzed as differential diagnostic hypotheses and therapeutic approaches. Further study is necessary regarding its prevalence, risk factors, and treatment.

Keywords: avoidant restrictive food intake disorder, ARFID, differential diagnoses, eating disorders, prevalence

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Authors: Rahy Farooq, Maria Ahmad Khan, Ayesha Isani Majeed

Abstract:

Objective: The main aim of this research is to assess the knowledge, attitude and practices of female nursing staff and nursing students regarding breast cancer, to provide a baseline for monitoring trends of breast cancer awareness in them. Background: Healthcare professionals are a direct source of information for the patients and the general public as a whole. It is, therefore, essential that the information they convey be accurate and helps in building additional awareness. However, clinical experience does not influence the knowledge, attitude and practices regarding breast cancer. Nurses, being the prime part of the healthcare professionals, play a significant role and hence, their awareness regarding this pressing issue is pertinent. Lack of awareness regarding common presenting symptoms or breast cancer risk factors translates to poor breast cancer screening practices and late diagnosis. Methodology: A cross-sectional study of 280 female nurses was conducted at a tertiary care hospital in Islamabad, Pakistan. A pre-tested structured questionnaire with additional variables like cultural barriers to seeking medical help was used. The scores for outcome variables including knowledge, attitude and practices were pre-defined. Data was analyzed using SPSSv23. Results: Of the 280 participants with a mean age of 28.99±9.98 years, 142 (50.7%) were married, and 138 (49.3%) were unmarried. Mean scores were computed to be 6.14±2.93 (out of 12), 0.30±0.7 (out of 3) and 9.53±1.92 (out of 16) for knowledge, attitude and practice respectively. Using independent sample T-test, a statistically significant correlation was found when means for the score of Attitude was compared with age. With a p-value of 0.018, 117 nurses of age more than 30 years, faced more practical, financial, emotional and service barriers as compared to 163 women younger than 30 years of age. Knowledge of age-related lifetime risks was also significantly poor more in single women; with a p-value of 0.006 for identification of correct age as a risk factor and a p-value of 0.005 for correct identification of risk for development of breast cancer in the lifetime of women. By application of Chi-square test, there was a significant correlation between marital status and cultural barriers to seeking medical help, showing that single women (58.7%) shy away from talking about breast cancer considering it a taboo (p-value 0.028) whereas, more married nurses (59.2%) were apprehensive that they might be considered at fault by the society, as compared to 40.8% of single nurses. (p-value 0.038). Conclusion: Owing to the scarcity of awareness among nurses, this study recognizes the need for delivering effective information to the female nurses regarding breast cancer. Educating patients is likely to be effective if the female nurses play their part and have correct attitudes towards breast cancer practices. A better understanding of the knowledge and practices regarding breast cancer among the nursing population will enable high-risk patients to be recognized early. Therefore, we recommend arrangement of special courses and seminars for all healthcare professionals including the nursing staff.

Keywords: breast cancer, cultural barriers, kap, nurses

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Authors: Fae Princess Bermudez

Abstract:

Background: One of the least significant leads on a 12-lead electrocardiogram is the augmented right lead (aVR), as it is not as specific compared to the other leads. In this case series, the value of lead aVR, which is more often than not ignored, is highlighted. Three cases of aVR ST segment elevation on 12-lead electrocardiogram are described, with the end outcome of demise of all three patients. The importance of immediate revascularization is described to improve prognosis in this group of patients. Objectives: This case series aims to primarily present under-reported cases of isolated aVR ST-segrment elevation myocardial infarction (STEMI), their course and outcome. More specific aims are to identify the criteria in determination of isolated aVR STEMI, know its clinical significance, and determine appropriate management for patients with this ECG finding. Method: A short review of previous studies, case reports, articles and guidelines from 2011-2016 was done. The author reviewed available literature, sorted out those that proved to be significant for the presented cases, and described them in conjunction with the aforementioned cases. Findings: Based on the limited information on these rare or under-reported cases, it was found that isolated aVR STEMI had a poorer prognosis that led to significant mortality and morbidity of patients. The significance of aVR ST-elevation was that of an occlusion of the left coronary artery or a severe three-vessel disease in the presence of an Acute Coronary Syndrome. Guidelines from American Heart Association/American College of Cardiology Foundation in 2013 already recognized ST-elevation of lead aVR in isolation as a STEMI; hence, recommended that patients with this particular ECG finding should undergo reperfusion strategies to improve prognosis. Conclusion: The indispensability of isolated aVR ST-segment elevation on ECG should alert physicians, especially Emergency physicians, to the high probability of Acute Coronary Syndrome with a very poor prognosis. If this group of patients is not promptly managed, demise may ensue, with cardiogenic shock as the most probable cause. With this electrocardiogram finding, physicians must be quick to make clinical decisions to increase chances of survival of this group of patients.

Keywords: AVR ST-elevation, diffuse ST-segment depression, left coronary artery infarction, myocardial infarction

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