Search results for: non-chest trauma patients

Authors: Salehi Zahabi Saleh, Rajabi Hosaien, Rasaneh Samira

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Yttrium-90 (90Y) radioembolisation(RE) is increasingly used for the treatment of patients with unresectable primary or metastatic liver tumours. Image-based approaches to assess microsphere distribution after RE have gained interest but are mostly hampered by the limited imaging possibilities of the Isotope 90Y. Quantitative 90Y-SPECT imaging has limited spatial resolution because it is based on 90Y Bremsstrahlung whereas 90Y-PET has better spatial resolution but low sensitivity. As a consequence, new alternative methods of visualizing the microspheres have been investigated, such as MR imaging of iron-labelled microspheres. It was also shown that MRI combines high sensitivity with high spatial and temporal resolution and with superior soft tissue contrast and thus can be used to cover a broad range of clinically interesting imaging parameters.The aim of the study in this article was to investigate the capability of MRI to measure the intrahepatic microsphere distribution in order to quantify the absorbed radiation dose in RE.

Keywords: radioembolisation, MRI, imaging, dosimetry

Procedia PDF Downloads 320

Authors: Wasse Uddin Ahmed Saleh, Nawreenbinte Anwar

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A well-written operating note is crucial as a teaching tool for providing patients with high-quality medical care and fending off medico-legal claims. In this review article, some adjustments have been advised to the operative note guidelines by the Royal College of Surgeons (RCS) for different methods of ocular anesthesia and ophthalmic procedures like cataract surgeries, kerato-refractive surgeries, glaucoma surgeries, oculoplastic surgeries, etc. Some modifications of the WHO Surgical Safety Checklist have also been mentioned, including pre-operative responsibilities of the nurses, operative assistants and operating ophthalmologists. It has become essential to assemble globally accepted structured operative note guidelines modified for each ocular surgery.

Keywords: ocular surgeries, operation notes, cataract surgery, kerato-refractive surgery, Oculoplastic surgeries, guidelines

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Authors: Tarnai Tena, Strinić Dean

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Chronic non-communicable diseases are today the leading cause of mortality, morbidity and mortality disability at the world level and in Croatia. Among them are the most represented precisely cardiovascular diseases (CVD), so today we are talking about their global card epidemic. From 2018 to 2021, cardiovascular diseases are the leading cause of death for both women and men in the Dubrovnik- Neretva County. With regard to the COVID-19 pandemic, which has taken over, without forgetting how much these patients are additionally affected, we are still talking about the primary cause of sickness and death in the population of this county and region. In this record, we present collected data processed according to gender and disease classification. We also bring a kind of overview because, for years, we have been following how the population of one of the origins of the Mediterranean diet has been struggling with cardiovascular diseases.

Keywords: cardiovascular disease, burden, COVID-19, epidemiology, ishemic heart disease, cardiovascular medicine

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Authors: Razieh Khalafi

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Myocardial infarction (MI) or acute myocardial infarction (AMI), commonly known as a heart attack, occurs when blood flow stops to part of the heart causing damage to the heart muscle. An ECG can often show evidence of a previous heart attack or one that's in progress. The patterns on the ECG may indicate which part of your heart has been damaged, as well as the extent of the damage. In chaos theory, the correlation dimension is a measure of the dimensionality of the space occupied by a set of random points, often referred to as a type of fractal dimension. In this research by considering ECG signal as a random walk we work on forecasting the oncoming heart attack by analyzing the ECG signals using the correlation dimension. In order to test the model a set of ECG signals for patients before and after heart attack was used and the strength of model for forecasting the behavior of these signals were checked. Results shows this methodology can forecast the ECG and accordingly heart attack with high accuracy.

Keywords: heart attack, ECG, random walk, correlation dimension, forecasting

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Authors: Sarah Aldhalaan, Tanzila Saba

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Healthcare sectors are increasing rapidly to fulfill patient’s needs across the world. A patient identification is considered as the main aspect for a patient to be served in healthcare institutes. Nowadays, people are presenting their insurance card along with their identification card in order to get the needed treatment in hospitals however, this process lack security preferences. The aim of this research paper is to reveal a solution to introduce and use biometrics in healthcare hospitals. The findings show that the people know biometrics since they are interacting with them through different channels and that the need for biometrics techniques to identify patients is essential. Also, the survey relevant questions are used to analyze and add insights on what is are the suitable biometrics to be used in such cases. Moreover, results are presented to exhibit the effectiveness of the used methodology and in analyzing usage of biometrics in hospitals in an enhancing way. Finally, an interesting conclusion of overall work is presented at the end of paper.

Keywords: biometrics, healthcare, fingerprint, Saudi Arabia

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Authors: Adel Edwar Waheeb Louka

Abstract:

Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: J. Fernandez, N. Aguilar, R. Fernandez de Canete, J. C. Ramos-Diaz

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In this paper, a simulation model of the glucose-insulin system for a patient undergoing diabetes Type 1 is developed by using a causal modeling approach under system dynamics. The OpenModelica simulation environment has been employed to build the so called causal model, while the glucose-insulin model parameters were adjusted to fit recorded mean data of a diabetic patient database. Model results under different conditions of a three-meal glucose and exogenous insulin ingestion patterns have been obtained. This simulation model can be useful to evaluate glucose-insulin performance in several circumstances, including insulin infusion algorithms in open-loop and decision support systems in closed-loop.

Keywords: causal modeling, diabetes, glucose-insulin system, diabetes, causal modeling, OpenModelica software

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Authors: Vasudha Govil, Suresh Singhal

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Introduction: Patients with oropharyngeal masses pose a challenge for an anaesthetist in terms of ventilation and tracheal intubation. Thus, preoperative assessment and preparation become an integral part of managing such anticipated difficult airway cases. Case report: A 45- year old female presented with growth in the oropharynx causing dysphagia and hoarseness of voice. Clinical examination and investigations predicted a difficult airway. It was managed with fibreoptic nasotracheal intubation with a successful perioperative outcome. Tracheostomy was kept as plan B in case of the CVCI situation. Conclusion: Careful preoperative examination and assessment is required to prepare oneself for difficult airway. Fibreoptic bronchoscope-guided nasotracheal intubation in a spontaneously breathing patient is a safe and successful airway management technique in difficult airway cases.

Keywords: airway, difficult, mass, oropharyngeal

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Authors: Kathrina Aseanne Acapulco-Gomez, Shayne Julieane Morales, Tzar Francis Verame

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Mean platelet volume (MPV) is the most accurate measure of the size of platelets and is routinely measured by most automated hematological analyzers. Several studies have shown associations between MPV and cardiovascular risks and outcomes. Although its measurement may provide useful data, MPV remains to be a diagnostic tool that is yet to be included in routine clinical decision making. The aim of this systematic review and meta-analysis is to determine summary estimates of the diagnostic accuracy of mean platelet volume for the diagnosis of myocardial infarction among adult patients with angina and/or its equivalents in terms of sensitivity, specificity, diagnostic odds ratio, and likelihood ratios, and to determine the difference of the mean MPV values between those with MI and those in the non-MI controls. The primary search was done through search in electronic databases PubMed, Cochrane Review CENTRAL, HERDIN (Health Research and Development Information Network), Google Scholar, Philippine Journal of Pathology, and Philippine College of Physicians Philippine Journal of Internal Medicine. The reference list of original reports was also searched. Cross-sectional, cohort, and case-control articles studying the diagnostic performance of mean platelet volume in the diagnosis of acute myocardial infarction in adult patients were included in the study. Studies were included if: (1) CBC was taken upon presentation to the ER or upon admission (within 24 hours of symptom onset); (2) myocardial infarction was diagnosed with serum markers, ECG, or according to accepted guidelines by the Cardiology societies (American Heart Association (AHA), American College of Cardiology (ACC), European Society of Cardiology (ESC); and, (3) if outcomes were measured as significant difference AND/OR sensitivity and specificity. The authors independently screened for inclusion of all the identified potential studies as a result of the search. Eligible studies were appraised using well-defined criteria. Any disagreement between the reviewers was resolved through discussion and consensus. The overall mean MPV value of those with MI (9.702 fl; 95% CI 9.07 – 10.33) was higher than in those of the non-MI control group (8.85 fl; 95% CI 8.23 – 9.46). Interpretation of the calculated t-value of 2.0827 showed that there was a significant difference in the mean MPV values of those with MI and those of the non-MI controls. The summary sensitivity (Se) and specificity (Sp) for MPV were 0.66 (95% CI; 0.59 - 0.73) and 0.60 (95% CI; 0.43 – 0.75), respectively. The pooled diagnostic odds ratio (DOR) was 2.92 (95% CI; 1.90 – 4.50). The positive likelihood ratio of MPV in the diagnosis of myocardial infarction was 1.65 (95% CI; 1.20 – 22.27), and the negative likelihood ratio was 0.56 (95% CI; 0.50 – 0.64). The intended role for MPV in the diagnostic pathway of myocardial infarction would perhaps be best as a triage tool. With a DOR of 2.92, MPV values can discriminate between those who have MI and those without. For a patient with angina presenting with elevated MPV values, it is 1.65 times more likely that he has MI. Thus, it is implied that the decision to treat a patient with angina or its equivalents as a case of MI could be supported by an elevated MPV value.

Keywords: mean platelet volume, MPV, myocardial infarction, angina, chest pain

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Authors: K. Vallianou, T. Alexopoulos, V. Plaka, M. K. Seleventi, V. Skanavis, C. Skanavis

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The present research addresses the role of place attachment and emotions in community resiliency and recovery within the context of a disaster. Natural disasters represent a disruption in the normal functioning of a community, leading to a general feeling of disorientation. This study draws on the trauma caused by a natural hazard such as a forest fire. The changes of the sense of togetherness are being assessed. Finally this research determines how the place attachment of the inhabitants was affected during the reorientation process of the community. The case study area is Mati, a small coastal town in eastern Attica, Greece. The fire broke out on July 23^rd, 2018. A quantitative research was conducted through questionnaires via phone interviews, one year after the disaster, to address community resiliency in the long-run. The sample was composed of 159 participants from the rural community of Mati plus 120 coming from Skyros Island that was used as a control group. Inhabitants were prompted to answer items gauging their emotions related to the event, group identification and emotional significance of their community, and place attachment before and a year after the fire took place. Importantly, the community recovery and reorientation were examined within the context of a relative absence of government backing and official support. Emotions related to the event were aggregated into 4 clusters related to: activation/vigilance, distress/disorientation, indignation, and helplessness. The findings revealed a decrease in the level of place attachment in the impacted area of Mati as compared to the control group of Skyros Island. Importantly, initial distress caused by the fire prompted the residents to identify more with their community and to report more positive feelings toward their community. Moreover, a mediation analysis indicated that the positive effect of community cohesion on place attachment one year after the disaster was mediated by the positive feelings toward the community. Finally, place attachment contributes to enhanced optimism and a more positive perspective concerning Mati’s future prospects. Despite an insufficient state support to this affected area, the findings suggest an important role of emotions and place attachment during the process of recovery. Implications concerning the role of emotions and social dynamics in meshing place attachment during the disaster recovery process as well as community resiliency are discussed.

Keywords: community resilience, natural disasters, place attachment, wildfire

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Authors: Ray Bryant

Abstract:

3Strands Global Foundation (3SGF), a non-profit with a mission to mobilize communities to combat human trafficking through prevention education and reintegration programs, launched a groundbreaking study that calls out the usage and benefits of artificial intelligence in the war against human trafficking. Having gathered more than 30,000 stories from counselors and school staff who have gone through its PROTECT Prevention Education program, 3SGF sought to develop a methodology to measure the effectiveness of the training, which helps educators and school staff identify physical signs and behaviors indicating a student is being victimized. The program further illustrates how to recognize and respond to trauma and teaches the steps to take to report human trafficking, as well as how to connect victims with the proper professionals. 3SGF partnered with Levity, a leader in no-code Artificial Intelligence (AI) automation, to create the research study utilizing natural language processing, a branch of artificial intelligence, to measure the effectiveness of their prevention education program. By applying the logic created for the study, the platform analyzed and categorized each story. If the story, directly from the educator, demonstrated one or more of the desired outcomes; Increased Awareness, Increased Knowledge, or Intended Behavior Change, a label was applied. The system then added a confidence level for each identified label. The study results were generated with a 99% confidence level. Preliminary results show that of the 30,000 stories gathered, it became overwhelmingly clear that a significant majority of the participants now have increased awareness of the issue, demonstrated better knowledge of how to help prevent the crime, and expressed an intention to change how they approach what they do daily. In addition, it was observed that approximately 30% of the stories involved comments by educators expressing they wish they’d had this knowledge sooner as they can think of many students they would have been able to help. Objectives Of Research: To solve the problem of needing to analyze and accurately categorize more than 30,000 data points of participant feedback in order to evaluate the success of a human trafficking prevention program by using AI and Natural Language Processing. Methodologies Used: In conjunction with our strategic partner, Levity, we have created our own NLP analysis engine specific to our problem. Contributions To Research: The intersection of AI and human rights and how to utilize technology to combat human trafficking.

Keywords: AI, technology, human trafficking, prevention

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Authors: Fatemeh Sadeghi, Peyman Sheikhzadeh

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Introduction: Block Sequential Regularized Expectation Maximization (BSREM) reconstruction algorithm was recently developed to suppress excessive noise by applying a relative difference penalty. The aim of this study was to investigate the effect of various strengths of noise penalization factor in the BSREM algorithm under different acquisition duration and lesion sizes in order to determine an optimum penalty factor by considering both quantitative and qualitative image evaluation parameters in clinical uses. Materials and Methods: The NEMA IQ phantom and 15 clinical whole-body patients with prostate cancer were evaluated. Phantom and patients were injected withGallium-68 Prostate-Specific Membrane Antigen(68 Ga-PSMA)and scanned on a non-time-of-flight Discovery IQ Positron Emission Tomography/Computed Tomography(PET/CT) scanner with BGO crystals. The data were reconstructed using BSREM with a β-value of 100-500 at an interval of 100. These reconstructions were compared to OSEM as a widely used reconstruction algorithm. Following the standard NEMA measurement procedure, background variability (BV), recovery coefficient (RC), contrast recovery (CR) and residual lung error (LE) from phantom data and signal-to-noise ratio (SNR), signal-to-background ratio (SBR) and tumor SUV from clinical data were measured. Qualitative features of clinical images visually were ranked by one nuclear medicine expert. Results: The β-value acts as a noise suppression factor, so BSREM showed a decreasing image noise with an increasing β-value. BSREM, with a β-value of 400 at a decreased acquisition duration (2 min/ bp), made an approximately equal noise level with OSEM at an increased acquisition duration (5 min/ bp). For the β-value of 400 at 2 min/bp duration, SNR increased by 43.7%, and LE decreased by 62%, compared with OSEM at a 5 min/bp duration. In both phantom and clinical data, an increase in the β-value is translated into a decrease in SUV. The lowest level of SUV and noise were reached with the highest β-value (β=500), resulting in the highest SNR and lowest SBR due to the greater noise reduction than SUV reduction at the highest β-value. In compression of BSREM with different β-values, the relative difference in the quantitative parameters was generally larger for smaller lesions. As the β-value decreased from 500 to 100, the increase in CR was 160.2% for the smallest sphere (10mm) and 12.6% for the largest sphere (37mm), and the trend was similar for SNR (-58.4% and -20.5%, respectively). BSREM visually was ranked more than OSEM in all Qualitative features. Conclusions: The BSREM algorithm using more iteration numbers leads to more quantitative accuracy without excessive noise, which translates into higher overall image quality and lesion detectability. This improvement can be used to shorter acquisition time.

Keywords: BSREM reconstruction, PET/CT imaging, noise penalization, quantification accuracy

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Authors: Thi Huong Vu, Vijay Jayasena, Zhongxiang Fang, Gary Dykes

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D-pinitol (3-O-methyl ether of D-chiro-inosito) has been known to have health benefits for diabetic patients. Carob kibble has received attention due to the presence of high value D-pinitol and polyphenol antioxidants. D-pinitol was concentrated from carob kibble using submerged fermentation with Saccharomyces cerevisiae. Total carbohydrates and D-pinitol were determined by the phenol-sulphuric acid method and HPLC, respectively. The content of D-pinitol increased from approximately 43 to 70 mg/g dry weight after fermentation. The yeast consumed over 70% of total carbohydrates in carob kibble without any negative effect on D-pinitol content. A range of substrate medium pH’s from 5.0 – 7.0 had no significant effect on the removal of carbohydrates and D-pinitol. This method may provide a practical solution for production of D-pinitol from carob in a cost effective manner.

Keywords: carob kibble, d-pinitol, saccharomyces cerevisiae, submerged fermentation, total carbohydrates

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Authors: S. Selman, T. Gout

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Microbial keratitis is a serious complication of contact lens wear that can be vision and eye-threatening. Diverse presentations relating to contact lens wear include dry corneal surface, corneal infiltrate, ulceration, scarring, and complete corneal melt leading to perforation. Contact lens wear is a major risk factor and, as such, is an important consideration in any patient presenting with a red eye in the primary care setting. This paper aims to provide an overview of the risk factors, common organisms, and spectrum of contact lens-associated keratitis (CLAK) complications. It will highlight some of the salient points relevant to the assessment and workup of patients suspected of CLAK in the emergency department based on the recent literature and therapeutic guidelines. An overview of the management principles will also be provided.

Keywords: microbial keratitis, corneal pathology, contact lens-associated complications, painful vision loss

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

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Authors: Kristina De Milt, Nicole Huang, Jihye Park

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Opioids have been a mainstay of the treatment of chronic pain, but their overprescription and misuse have led to an opioid epidemic. Recently, as an attempt to decrease the number of opioids prescribed, the use of cannabinoid therapy has become an increasingly popular adjunctive chronic pain management choice among providers. This review of literature investigates the effects of adjunctive cannabinoids to opioids in the management of chronic pain. The nine articles are included in the literature review range from observational studies to meta-analyses published in the year 2016 and after. A majority of the studies showed a decrease in the need for opioids after adjunctive cannabinoids were introduced and, in some instances, the cessation of opioid consumption. More high-quality evidence is needed to further support this stance and providers should weigh the benefits and risks of adjunctive cannabinoids according to the clinical picture.

Keywords: cannabis, chronic pain, opioids, pain management

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Authors: Ayman M. Mansour, Bilal Hawashin, Mohammed A. Mansour

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In this paper, we propose a cooperative learning mechanism in a multi-agent intelligent system. The basic idea is that intelligent agents are capable of collaborating with one another by sharing their knowledge. The agents will start collaboration by providing their knowledge rules to the other agents. This will allow the most important and insightful detection rules produced by the most experienced agent to bubble up for the benefit of the entire agent community. The updated rules will lead to improving the agents’ decision performance. To evaluate our approach, we designed a five–agent system and implemented it using JADE and FuzzyJess software packages. The agents will work with each other to make a decision about a suspicious medical case. This system provides quick response rate and the decision is faster than the manual methods. This will save patients life.

Keywords: intelligent, multi-agent system, cooperative, fuzzy, learning

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Authors: Peter J. Riley

Abstract:

Medical Imaging students must understand the roles of Photo-electric Absorption (PE) and Compton Scatter (CS) interactions in patients to enable optimal X-ray imaging in clinical practice. A simulator has been developed that shows relative interaction probabilities, color bars for patient dose from PE, % penetration to the detector, and obscuring CS as Peak Kilovoltage (kVp) changes. Additionally, an anthropomorphic chest X-ray image shows the relative tissue contrasts and overlying CS-fog at that kVp, which determine the detectability of a lesion in the image. A series of interactive exercises with MCQs evaluate the student's understanding; the simulation has improved student perception of the need to acquire "sufficient" rather than maximal contrast to enable patient dose reduction at higher kVp.

Keywords: patient dose optimization, radiological physics, simulation, tissue contrast

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Authors: Pırıl Tekin, Rızvan Erol

Abstract:

Risk management has become very important and popular in developing countries in recent years. Especially making patient and employee health and safety issues compulsory in the hospitals, raised the number of studies in Turkey. Also risk management become more important for hospital senior management from clinics to the laboratories. Because quality is really important to be chosen for both patients to consult and employees to prefer to work. And also risk management studies can lead to hospital management team about future works and methods. By this point of view, this study is the risk assessment carried out in the biggest dental hospital in the south part of Turkey. This study was conducted as a research case study, covering two different health care place; A Clinic and A Laboratory. It shows that the problems in this dental hospital and how it can solve all.

Keywords: risk management, healthcare, dental hospital, quality management

Procedia PDF Downloads 377

Authors: Razi Khalafi

Abstract:

Myocardial Infarction (MI) or acute Myocardial Infarction (AMI), commonly known as a heart attack, occurs when blood flow stops to part of the heart causing damage to the heart muscle. An ECG can often show evidence of a previous heart attack or one that's in progress. The patterns on the ECG may indicate which part of your heart has been damaged, as well as the extent of the damage. In chaos theory, the correlation dimension is a measure of the dimensionality of the space occupied by a set of random points, often referred to as a type of fractal dimension. In this research by considering ECG signal as a random walk we work on forecasting the oncoming heart attack by analysing the ECG signals using the correlation dimension. In order to test the model a set of ECG signals for patients before and after heart attack was used and the strength of model for forecasting the behaviour of these signals were checked. Results show this methodology can forecast the ECG and accordingly heart attack with high accuracy.

Keywords: heart attack, ECG, random walk, correlation dimension, forecasting

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Authors: Huidan Yu, Anurag Deb, Rou Chen, I-Wen Wang

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The use of left ventricle assist devices (LVADs) in patients with heart failure has been a proven and effective therapy for patients with severe end-stage heart failure. Due to the limited availability of suitable donor hearts, LVADs will probably become the alternative solution for patient with heart failure in the near future. While the LVAD is being continuously improved toward enhanced performance, increased device durability, reduced size, a better understanding of implantation management becomes critical in order to achieve better long-term blood supplies and less post-surgical complications such as thrombi generation. Important issues related to the LVAD implantation include the location of outflow grafting (OG), the angle of the OG, the combination between LVAD and native heart pumping, uniform or pulsatile flow at OG, etc. We have hypothesized that an optimal implantation of LVAD is patient specific. To test this hypothesis, we employ a novel in-house computational modeling technique, named InVascular, to conduct a systematic evaluation of cardiac output at aortic arch together with other pertinent hemodynamic quantities for each patient under various implantation scenarios aiming to get an optimal implantation strategy. InVacular is a powerful computational modeling technique that integrates unified mesoscale modeling for both image segmentation and fluid dynamics with the cutting-edge GPU parallel computing. It first segments the aortic artery from patient’s CT image, then seamlessly feeds extracted morphology, together with the velocity wave from Echo Ultrasound image of the same patient, to the computation model to quantify 4-D (time+space) velocity and pressure fields. Using one NVIDIA Tesla K40 GPU card, InVascular completes a computation from CT image to 4-D hemodynamics within 30 minutes. Thus it has the great potential to conduct massive numerical simulation and analysis. The systematic evaluation for one patient includes three OG anastomosis (ascending aorta, descending thoracic aorta, and subclavian artery), three combinations of LVAD and native heart pumping (1:1, 1:2, and 1:3), three angles of OG anastomosis (inclined upward, perpendicular, and inclined downward), and two LVAD inflow conditions (uniform and pulsatile). The optimal LVAD implantation is suggested through a comprehensive analysis of the cardiac output and related hemodynamics from the simulations over the fifty-four scenarios. To confirm the hypothesis, 5 random patient cases will be evaluated.

Keywords: graphic processing unit (GPU) parallel computing, left ventricle assist device (LVAD), lumped-parameter model, patient-specific computational hemodynamics

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Authors: M. Ekiert, T. Uhl, A. Mlyniec

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Tendons are the biological soft tissue structures composed of collagen, proteoglycan, glycoproteins, water and cells of extracellular matrix (ECM). Tendons, which primary function is to transfer force generated by the muscles to the bones causing joints movement, are exposed to many micro and macro damages. In fact, tendons and ligaments trauma are one of the most numerous injuries of human musculoskeletal system, causing for many people (particularly for athletes and physically active people), recurring disorders, chronic pain or even inability of movement. The number of tendons reconstruction and transplantation procedures is increasing every year. Therefore, studies on soft tissues storage conditions (influencing i.e. tissue aging) seem to be an extremely important issue. In this study, an atomic-scale investigation on the kinetics of decomposition of two selected tendon components – collagen type I (which forms a 60-85% of a tendon dry mass) and elastin protein (which combine with ECM creates elastic fibers of connective tissues) is presented. A molecular model of collagen and elastin was developed based on crystal structure of triple-helical collagen-like 1QSU peptide and P15502 human elastin protein, respectively. Each model employed 4 linear strands collagen/elastin strands per unit cell, distributed in 2x2 matrix arrangement, placed in simulation box filled with water molecules. A decomposition phenomena was simulated with molecular dynamics (MD) method using ReaxFF force field and periodic boundary conditions. A set of NVT-MD runs was performed for 1000K temperature range in order to obtained temperature-depended rate of production of decomposition by-products. Based on calculated reaction rates activation energies and pre-exponential factors, required to formulate Arrhenius equations describing kinetics of decomposition of tested soft tissue components, were calculated. Moreover, by adjusting a model developed for collagen, system scalability and correct implementation of the periodic boundary conditions were evaluated. An obtained results provide a deeper insight into decomposition of selected tendon components. A developed methodology may also be easily transferred to other connective tissue elements and therefore might be used for further studies on soft tissues aging.

Keywords: decomposition, molecular dynamics, soft tissue, tendons

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Authors: Alexandra Shipley

Abstract:

Background: Undergraduate paediatric teaching must overcome two major challenges: 1) balancing patient safety with active student engagement and 2) exposing students to a comprehensive range of pathologies within a relatively short clinical placement. Whilst lectures and shadowing on paediatric wards constitute the mainstay of learning, Simulation and Virtual Reality (VR) are emerging as effective teaching tools, which - immune to the unpredictability and seasonal variation of hospital presentations - could expose students to the entire syllabus more reliably, efficiently, and independently. We aim to evaluate the potential utility of Simulation and VR in addressing gaps within the traditional paediatric curriculum from the perspective of medical students. Summary of Work: Exposure to and perceived utility of various learning opportunities within the Paediatric and Emergency Medicine courses were assessed through a questionnaire completed by 5th year medical students (n=23). Summary of Results: Students reported limited exposure to several common acute paediatric presentations, such as bronchiolitis (41%), croup (32%) or pneumonia (14%), and to clinical emergencies, including cardiac/respiratory arrests or trauma calls (27%). Across all conditions, average self-reported confidence in assessment and management to the level expected of an FY1 is greater amongst those who observed at least one case (e.g. 7.6/10 compared with 3.6/10 for croup). Students rated exposure through Simulation or VR to be of similar utility to witnessing a clinical scenario on the ward. In free text responses, students unanimously favoured being ‘challenged’ through ‘hands-on’ patient interaction over passive shadowing, where it is ‘easy to zone out.’ In recognition of the fact that such independence is only appropriate in certain clinical situations, many students reported wanting more Simulation and VR teaching. Importantly, students raised the necessity of ‘proper debriefs’ after these sessions to maximise educational value. Discussion and Conclusion: Our questionnaire elicited several student-perceived challenges in paediatric education, including incomplete exposure to common pathologies and limited opportunities for active involvement in patient care. Indeed, these experiences seem to be important predictors of confidence. Quantitative and qualitative feedback suggests that VR and Simulation satisfy students’ self-reported appetite for independent engagement with authentic clinical scenarios. Take-aways: Our findings endorse further development of VR and Simulation as high-yield adjuncts to paediatric education.

Keywords: paediatric emergency education, simulation, virtual reality, medical education

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Authors: Seyed Kian Haji Seyed Javadi, Aisan Nouri

Abstract:

Patient satisfaction in dental care is shaped by experiences throughout the treatment journey. Challenges such as fear, lack of trust and poor communication can impact patient contentment and willingness to seek dental care. This narrative review explores these issues and presents innovative solutions to address them by searching PubMed and Scopus data sources. It examines factors affecting patient satisfaction and adherence across three phases—before, during and after treatment—emphasizing the roles of effective communication, payment and follow-up systems, appointment scheduling, welcoming reception and the treatment environment. The factors discussed in this study motivate patients to return for routine check-ups and preventive care, even if their initial visit was for an emergency.

Keywords: patient satisfaction, dentistry, dental access, dental care services

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Authors: Duhania O. Mahara, Santi W. Purnami, Aulia N. Fitria, Merissa N. Z. Wirontono, Revina Musfiroh, Shofi Andari, Sagiran Sagiran, Estiana Khoirunnisa, Wahyudi Widada

Abstract:

For assessing interventions in numerous disease areas, the use of multiple time-to-event outcomes is common. An individual might experience two different events called bivariate time-to-event data, the events may be correlated because it come from the same subject and also influenced by individual characteristics. The bivariate time-to-event case can be applied by copula-based bivariate Cox survival model, using the Clayton and Frank copulas to analyze the dependence structure of each event and also the covariates effect. By applying this method to modeling the recurrent event infection of hemodialysis insertion on chronic kidney disease (CKD) patients, from the AIC and BIC values we find that the Clayton copula model was the best model with Kendall’s Tau is (τ=0,02).

Keywords: bivariate cox, bivariate event, copula function, survival copula

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Authors: Dessy Arumsari, Ais Assana Athqiya, Mulyaminingrum

Abstract:

Healthcare in remote areas is one of the major concerns in Indonesia. Building hospitals in a nation of 18.000 islands with a larger-than-life bureaucracy and problems with corruption, a critical shortage of qualified medical professionals and well-heeled patients resigned to traveling abroad for health care is a hard feat to accomplish. To assuring that all populations have access to appropriate and cost-effective care, a new solution to tackle this problem is with the presence of RV Car Clinic. This car has a concept such as a walking hospital that provides health facilities inside it. All of the health professionals who work in RV Car Clinic will do the rotation for a year in order to the equitable distribution of health workers. We need to advocate the policy makers to help realize RV Car Clinic in remote areas. Health services can be disseminated by the present of RV Car Clinic. Summarily, the local communities can get cost effectively because RV Car Clinic will come to their place and serve the health services.

Keywords: health policy, health professional, remote areas, RV Car Clinic

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Authors: Kenny Chi Man Chui

Abstract:

Background: In Chinese culture, the traditional equivalent term for English dementia is chi dai zheng, which, whether translated as ‘insanity’ or ‘idiocy’ carries a sharply negative connotation. In fact, even though the traditional name for dementia has evolved, from chi dai zheng to shi zhi zheng, nao tui hua zheng or ren zhi zhang ai zheng, educating the population about more respectful terms for the condition and promoting a positive understanding about people with dementia in society have proven to be time-intensive endeavors. By extension, the use of such terms promotes the perception that people with dementia undergo a ‘total loss of self’ or experience a ‘living death’ or ‘social death’. Both in Asia and elsewhere, the appropriate nomenclature for dementia remains controversial, and different medical and healthcare professionals in Hong Kong have taken various stances on how to refer to the condition there. Indeed, how this negative perception affects the interaction between people with dementia and the surrounding others? Methodology: Qualitative research with the concept of postmodernism, interpretivism, and Foucauldian theory was adopted as frameworks in applying participatory observations, in-depth interviews, and other qualitative methods. First, ten people with dementia—one man and nine women—living in two residential care homes in Hong Kong were interviewed, as were ten members of the care staff, all of whom were women. Next, to coach the staff in understanding the feelings and self-perceptions of people with dementia, two reflective training sessions were provided. Afterward, to assess the impact of the training sessions on the staff, two focus groups were held. Findings: The findings revealed that residents with dementia did not perceive themselves as being ‘demented’ and were confused by not getting responses from the others. From the understanding of care staff, they perceived the residents as being ‘demented’, desolate troublemakers. They described people with dementia as ‘naughty children’ who should be controlled and be punished while treated them as ‘psychiatric patients’ who could be ignored and be mute. “Psychosocial restraint” happened regarding the discrepancy of perception between people with dementia and the care staff. People with dementia did not think that their confusion of memory was related to dementia or, frankly speaking, they did not know what dementia was. When others treated them as ‘demented patients, the residents with mild to moderate dementia fiercely rejected that designation and reported a host of negative feelings, hence the fluctuations of mood and emotion noted by the care staff. Conclusion: As the findings revealed, the people with dementia were also discontent with the care arrangements in the care homes, felt abandoned by others and worried about bothering others. Their shifting emotional states and moods were treated as the Behavioral and Psychological symptoms of Dementia (BPSD), which nothing can do reported by the care staff in the residential care homes. People with dementia become social withdrawal or isolated in daily living, which should be alert and be changed by the social work professionals about the occurrence of “psychosocial restraint” in dementia care.

Keywords: psychosocial restraint, qualitative research, social work with dementitude, voice of people with dementia

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Authors: A. Venkatakrishnan, M. Juneja, S. Kapoor

Abstract:

Background: Gastrointestinal dysfunction is an emerging co morbidity seen in autism and may further strengthen the association between autism and celiac disease. This is supported by increased rates (22-70%) of gastrointestinal symptoms like diarrhea, constipation, abdominal discomfort/pain, and gastrointestinal inflammation in children with the etiology of autism is still elusive. In addition to genetic factors, environmental factors such as toxin exposure, intrauterine exposure to certain teratogenic drugs, are being proposed as possible contributing factors in the etiology of Autism Spectrum Disorders (ASD) in cognizance with reports of increased gut permeability and high rates of gastrointestinal symptoms noted in children with ASD, celiac disease has also been proposed as a possible etiological factor. Despite insufficient evidence regarding the benefit of restricted diets in Autism, GFD has been promoted as an alternative treatment for ASD. This study attempts to discern any correlation between ASD and celiac disease. Objective: This cross sectional study aims to determine the proportion of celiac disease in children with ASD. Methods: Study included 155 participants aged 2-12 yrs, diagnosed as ASD as per DSM-5 attending the child development center at a tertiary care hospital in Northern India. Those on gluten free diet or having other autoimmune conditions were excluded. A detailed Performa was filled which included sociodemographic details, history of gastrointestinal symptoms, anthropometry, systemic examination, and pertinent psychological testing was done using was assessed using Developmental Profile-3(DP-3) for Developmental Quotient, Childhood Autism Rating Scale-2 (CARS-2) for severity of ASD, Vineland Adaptive Behavior Scales (VABS) for adaptive behavior, Child Behavior Checklist (CBCL) for behavioral problems and BAMBI (Brief Autism Mealtime Behavior Scales) for feeding problems. Screening for celiac was done by TTG-IgA levels, and total serum IgA levels were measured to exclude IgA deficiency. Those with positive screen were further planned for HLA typing and endoscopic biopsy. Results: A total of 155 cases were included, out of which 5 had low IgA levels and were hence excluded from the study. The rest 150 children had TTG levels below the ULN and normal total serum IgA level. History of Gastrointestinal symptoms was present in 51 (34%) cases abdominal pain was the most frequent complaint (16.6%), followed by constipation (12.6%). Diarrhea was seen in 8 %. Gastrointestinal symptoms were significantly more common in children with ASD above 5 yrs (p-value 0.006) and those who were verbal (p = 0.000). There was no significant association between socio-demographic factors, anthropometric data, or severity of autism with gastrointestinal symptoms. Conclusion: None of the150 patients with ASD had raised TTG levels; hence no association was found between ASD and celiac disease. There is no justification for routine screening for celiac disease in children with ASD. Further studies are warranted to evaluate association of Non Celiac Gluten Sensitivity with ASD and any role of gluten-free diet in such patients.

Keywords: autism, celiac, gastrointestinal, gluten

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Authors: Diego Luján Villarreal

Abstract:

Retinal prosthetic devices aim to repair some vision in visual impairment patients by stimulating electrically neural cells in the visual system. In this study, the 3D linear electrode carrier is presented. A simulation framework was developed by placing the 3D carrier 1 mm away from the fovea center at the highest-density cell. Cell stimulation is verified in COMSOL Multiphysics by developing a 3D computational model which includes the relevant retinal interface elements and dynamics of the voltage-gated ionic channels. Current distribution resulting from low threshold amplitudes produces a small volume equivalent to the volume confined by individual cells at the highest-density cell using small-sized electrodes. Delicate retinal tissue is protected by excessive charge density

Keywords: retinal prosthetic devices, visual devices, retinal implants., visual prosthetic devices

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Authors: Naseem M. Twaissi

Abstract:

Medical professionals play an important role in society, and in general, they care more about their patients than about their personal well-being. They need to take a professional approach to maintain a work-life balance. Through a collection of primary data from 1020 medical professionals and the application of relevant statistical tools, this paper explores the pressures on medical professionals with reference to their work-life balance. This study highlights how hospital management, in addition to economic reasons, needs to identify variables to enhance the work-life balance of medical professionals so that quality healthcare facilities may be provided to the citizens of Jordan. Results indicate that formulation and implementation of policies for enhancing work-life balance together with career and retention plans for medical professionals would enhance the performance of hospitals and the quality of health care in Jordan, leading to greater societal well-being.

Keywords: work life balance, job environment, job satisfaction, employee well-being, stress, hospital industry

Procedia PDF Downloads 141