Search results for: aortic dissection detection risk score

Authors: Katleho Daniel Makatjane, Diteboho Lawrence Xaba, Ntebogang Dinah Moroke

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The current study investigates the behaviour of time-varying parameters that are based on the score function of the predictive model density at time t. The mechanism to update the parameters over time is the scaled score of the likelihood function. The results revealed that there is high persistence of time-varying, as the location parameter is higher and the skewness parameter implied the departure of scale parameter from the normality with the unconditional parameter as 1.5. The results also revealed that there is a perseverance of the leptokurtic behaviour in stock returns which implies the returns are heavily tailed. Prior to model estimation, the White Neural Network test exposed that the stock price can be modelled by a GAS model. Finally, we proposed further researches specifically to model the existence of time-varying parameters with a more detailed model that encounters the heavy tail distribution of the series and computes the risk measure associated with the returns.

Keywords: generalized autoregressive score model, South Africa, stock returns, time-varying

Procedia PDF Downloads 475

Authors: C. Caçador, M. J. Reis Lima, J. Oliveira, M. J. Veiga, M. Teixeira Veríssimo, F. Ramos, M. C. Castilho, E. Teixeira-Lemos

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In the present study we evaluated the nutritional status of 214 institutionalized elderly residents of both genders, aged 65 years and older of 11 care homes located in the district of Viseu (center of Portugal). The evaluation was based on anthropometric measurements and the Mini Nutritional Assessment (MNA) score. The mean age of the subjects was 82.3 ± 6.1 years-old. Most of the elderly residents were female (72.0%). The majority had 4 years of formal education (51.9%) and was widowed (74.3%) or married (14.0%). Men presented a mean age of 81.2±8.5 years-old, weight 69.3±14.5 kg and BMI 25.33±6.5 kg/m2. In women, the mean age was 84.5±8.2 years-old, weight 61.2±14.7 kg and BMI 27.43±5.6 kg/m2. The evaluation of the nutritional status using the MNA score showed that 24.0% of the residents show a risk of undernutrition and 76.0% of them were well nourished. There was a high prevalence of obese (24.8%) and overweight residents (33.2%) according to the BMI. 7.5% were considered underweight. We also found that according to their waist circumference measurements 88.3% of the residents were at risk for cardiovascular disease (CVD) and 64.0% of them presented very high risk for CVD (WC≥88 cm for women and WC ≥102 cm for men). The present study revealed the coexistence of a dual form of malnutrition (undernourished and overweight) among the institutionalized Portuguese concomitantly with an excess of abdominal adiposity. The high prevalence of residents at high risk for CVD should not be overlooked. Given the vulnerability of the group of institutionalized elderly, our study highlights the importance of the classification of nutritional status based on both instruments: the BMI and the MNA.

Keywords: nutritional satus, MNA, BMI, elderly

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Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

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Authors: Shanza Akram, Sameen Toor, Heba Harb Abu Alkass, Zainab Abdulsalam Altaha, Sara Taha Abdulla, Saleem Imran

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Acute pulmonary embolism (PE) is a common disease and can be fatal. The clinical presentation is variable and nonspecific, making accurate diagnosis difficult. Testing patients with suspected acute PE has increased dramatically. However, the overuse of some tests, particularly CT and D-dimer measurement, may not improve care while potentially leading to patient harm and unnecessary expense. CTPA is the investigation of choice for PE. Its easy availability, accuracy and ability to provide alternative diagnosis has lowered the threshold for performing it, resulting in its overuse. Guidelines have recommended the use of clinical pretest probability tools such as ‘Wells score’ to assess risk of suspected PE. Unfortunately, implementation of guidelines in clinical practice is inconsistent. This has led to low risk patients being subjected to unnecessary imaging, exposure to radiation and possible contrast related complications. Aim: To study the diagnostic yield of CT PA, clinical pretest probability of patients according to wells score and to determine whether or not there was an overuse of CTPA in our service. Methods: CT scans done on patients with suspected P.E in our hospital from 1st January 2014 to 31st December 2014 were retrospectively reviewed. Medical records were reviewed to study demographics, clinical presentation, final diagnosis, and to establish if Wells score and D-Dimer were used correctly in predicting the probability of PE and the need for subsequent CTPA. Results: 100 patients (51male) underwent CT PA in the time period. Mean age was 57 years (24-91 years). Majority of patients presented with shortness of breath (52%). Other presenting symptoms included chest pain 34%, palpitations 6%, collapse 5% and haemoptysis 5%. D Dimer test was done in 69%. Overall Wells score was low (<2) in 28 %, moderate (>2 - < 6) in 47% and high (> 6) in 15% of patients. Wells score was documented in medical notes of only 20% patients. PE was confirmed in 12% (8 male) patients. 4 had bilateral PE’s. In high-risk group (Wells > 6) (n=15), there were 5 diagnosed PEs. In moderate risk group (Wells >2 - < 6) (n=47), there were 6 and in low risk group (Wells <2) (n=28), one case of PE was confirmed. CT scans negative for PE showed pleural effusion in 30, Consolidation in 20, atelactasis in 15 and pulmonary nodule in 4 patients. 31 scans were completely normal. Conclusion: Yield of CT for pulmonary embolism was low in our cohort at 12%. A significant number of our patients who underwent CT PA had low Wells score. This suggests that CT PA is over utilized in our institution. Wells score was poorly documented in medical notes. CT-PA was able to detect alternative pulmonary abnormalities explaining the patient's clinical presentation. CT-PA requires concomitant pretest clinical probability assessment to be an effective diagnostic tool for confirming or excluding PE. . Clinicians should use validated clinical prediction rules to estimate pretest probability in patients in whom acute PE is being considered. Combining Wells scores with clinical and laboratory assessment may reduce the need for CTPA.

Keywords: CT PA, D dimer, pulmonary embolism, wells score

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Authors: Semachew M. Kassa, Africa M Geremew, Tezera F. Azmatch, Nandyala Darga Kumar

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Frequency ratio (FR) and analytical hierarchy process (AHP) methods are developed based on past landslide failure points to identify the landslide susceptibility mapping because landslides can seriously harm both the environment and society. However, it is still difficult to select the most efficient method and correctly identify the main driving factors for particular regions. In this study, we used fourteen landslide conditioning factors (LCFs) and five soft computing algorithms, including Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR), Artificial Neural Network (ANN), and Naïve Bayes (NB), to predict the landslide susceptibility at 12.5 m spatial scale. The performance of the RF (F1-score: 0.88, AUC: 0.94), ANN (F1-score: 0.85, AUC: 0.92), and SVM (F1-score: 0.82, AUC: 0.86) methods was significantly better than the LR (F1-score: 0.75, AUC: 0.76) and NB (F1-score: 0.73, AUC: 0.75) method, according to the classification results based on inventory landslide points. The findings also showed that around 35% of the study region was made up of places with high and very high landslide risk (susceptibility greater than 0.5). The very high-risk locations were primarily found in the western and southeastern regions, and all five models showed good agreement and similar geographic distribution patterns in landslide susceptibility. The towns with the highest landslide risk include Amhara Saint Town's western part, the Northern part, and St. Gebreal Church villages, with mean susceptibility values greater than 0.5. However, rainfall, distance to road, and slope were typically among the top leading factors for most villages. The primary contributing factors to landslide vulnerability were slightly varied for the five models. Decision-makers and policy planners can use the information from our study to make informed decisions and establish policies. It also suggests that various places should take different safeguards to reduce or prevent serious damage from landslide events.

Keywords: artificial neural network, logistic regression, landslide susceptibility, naïve Bayes, random forest, support vector machine

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Authors: Amani Waheed, Adel Mishriky, Rasha Farouk, Essam Abdallah, Sarah Hussein

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Background: Occupational stress plays a crucial role in professional drivers' health. They are exposed to high workloads, low physical activity, high demand and low decisions as well as poor lifestyle factors including poor diet, sedentary work, and smoking. Dyslipidemia is a well-established modifiable cardiovascular risk factor. Occupational stress and other forms of chronic stress have been associated with raised levels of atherogenic lipids. Although stress management has some evidence in improving lipid profile, the association between occupational stress and dyslipidemia is not clear. Objectives: To assess the relational between occupational stress and lipid profile among professional drivers. Methodology: A cross-sectional study conducted at a large company in Ismailia City, Egypt, where, 131 professional drivers divided into 44 car drivers, 43 bus drivers, and 44 truck drivers were eligible after applying exclusion criteria. Occupational stress index (OSI), non-occupational risk factors of dyslipidemia were assessed using interview structured questionnaire. Blood pressure, body mass index (BMI) and lipid profile were measured. Results: The mean of total OSI score was 79.98 ± 6.14. The total OSI score is highest among truck drivers (82.16 ± 4.62), then bus drivers (80.26 ± 6.02) and lowest among car drivers (77.55 ± 6.79) with statistically significant. Eighty percent had Dyslipidemia. The duration of driving hours per day, exposure to passive smoking and increased BMI were the risk factors. No statistical significance between Total OSI score and dyslipidemia. Using, logistic regression analysis, occupational stress, duration of driving hours per day, and BMI were positive significant predictors for dyslipidemia. Conclusion: Professional drivers are exposed to occupational stress. A high proportion of drivers have dyslipidemia. Total OSI score doesn't have statistically significant relation with dyslipidemia.

Keywords: body mass index, dyslipidaemia, occupational stress, professional drivers

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Authors: Noor A. Hakim

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Several studies in the developed countries investigated the prevalence of diabetes and obesity among individuals from different socioeconomic levels and suggested lower rates among the higher socioeconomic groups. However, studies evaluating diabetes risk and prevalence of obesity among the population of middle- to high-income status in developing countries are limited. The aim of this study is to evaluate the risk of developing type-2 diabetes mellitus (T2DM) and the weight status of female students in private universities in Jeddah City, Saudi Arabia. This is a cross-sectional study of 121 female students aged ≤ 25 years old was conducted; participants were recruited from two private universities. Diabetes risk was evaluated using the Finnish Diabetes Risk Score. Anthropometric measurements were assessed, and body-mass-index (BMI) was calculated. Diabetes risk scores indicated that 35.5% of the female students had a slightly elevated risk, and 10.8% had a moderate to high risk to develop T2DM. One-third of the females (29.7%) were overweight or obese. The majority of the normal weight and underweight groups were classified to have a low risk of diabetes, 22.2% of the overweight participants were classified to have moderate to high risk, and over half of the obese participants (55.5%) were classified to be at the moderate to high-risk category. Conclusions: Given that diabetes risk is alarming among the population in Saudi Arabia, healthcare providers should utilize a simple screening tool to identify high-risk individuals and initiate diabetes preventive strategies to prevent, or delay, the onset of T2DM and improve the quality of life.

Keywords: risk of type 2 diabetes, weight status, college students, socioeconomic status

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Authors: Markus Stralla

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This study employs a GMM framework to examine the impact of potential regulatory intervention regarding the occupations of supervisory board members in cooperative banking. To achieve insights, the study proceeds in two different ways. First, it investigates the changes in board structure prior and following to the German Act to Strengthen Financial Market and Insurance Supervision (FinVAG). Second, the study estimates the influence of Ph.D.Share, professional concentration and supervisory power on bank-risk changes in consideration of the implementation of FinVAG. Therefore, the study is based on a sample of 246 German cooperative banks from 2006-2011 while applying four different measures of bank risk, namely credit-, equity-, liquidity-risk, and Z-Score, with the former three also being addressed in FinVAG. Results indicate that the implementation of FinVAG results in (most likely unintentional) structural changes, especially at the expense of farmers, and affects all risk measures and relations between risk measures and supervisory board characteristics in a risk-reducing and therefore intended way. To disentangle the complex relationship between board characteristics and risk measures, the study utilizes two-step system GMM estimator to account for unobserved heterogeneity and simultaneity in order to reduce endogeneity problems. The findings may be especially relevant for stakeholders, regulators, supervisors and managers.

Keywords: bank governance, bank risk-taking, board of directors, regulation

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Authors: Phang Moon Leng

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Automated Early Warning Scores is a newly developed clinical decision tool that is used to streamline and improve the process of obtaining a patient’s vital signs so a clinical decision can be made at an earlier stage to prevent the patient from further deterioration. This technology provides immediate update on the score and clinical decision to be taken based on the outcome. This paper aims to study the use of an automated early warning score system on whether the technology has assisted the hospital in early detection and escalation of clinical condition and improve patient outcome. The hospital adopted the Modified Early Warning Scores (MEWS) Scoring System and MEWS Clinical Response into Philips IntelliVue Guardian Automated Early Warning Score equipment and studied whether the process has been leaned, whether the use of technology improved the usage & experience of the nurses, and whether the technology has improved patient care and outcome. It was found the steps required to obtain vital signs has been significantly reduced and is used more frequently to obtain patient vital signs. The number of deaths, and length of stay has significantly decreased as clinical decisions can be made and escalated more quickly with the Automated EWS. The automated early warning score equipment has helped improve work efficiency by removing the need for documenting into patient’s EMR. The technology streamlines clinical decision-making and allows faster care and intervention to be carried out and improves overall patient outcome which translates to better care for patient.

Keywords: automated early warning score, clinical quality and safety, patient safety, medical technology

Procedia PDF Downloads 152

Authors: Prasad Urvashi, Wynn Yezarni, Williams Shehan, Ravindran Arun

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Introduction: Primary health services are often the first point of contact that patients with mental illness have with the healthcare system. A number of tools have been developed to increase detection of depression in the context of primary care. However, one challenge amongst many includes utilizing these tools within the limited primary care consultation timeframe. Therefore, short questionnaires that screen for depression that are just as effective as more comprehensive diagnostic tools may be beneficial in improving detection rates of patients visiting a primary care setting. Objective: To develop and determine the sensitivity and specificity of a 2-Question Questionnaire (2-QQ) to screen for depression in in a suburban primary care clinic in Ragama, Sri Lanka. The purpose is to develop a short screening tool for depression that is culturally adapted in order to increase the detection of depression in the Sri Lankan patient population. Methods: This was a cross-sectional study involving two steps. Step one: verbal administration of 2-QQ to patients by their primary care physician. Step two: completion of the Peradeniya Depression Scale, a validated diagnostic tool for depression, the patient after their consultation with the primary care physician. The results from the PDS were then correlated to the results from the 2-QQ for each patient to determine sensitivity and specificity of the 2-QQ. Results: A score of 1/+ on the 2-QQ was most sensitive but least specific. Thus, setting the threshold at this level is effective for correctly identifying depressed patients, but also inaccurately captures patients who are not depressed. A score of 6 on the 2-QQ was most specific but least sensitive. Setting the threshold at this level is effective for correctly identifying patients without depression, but not very effective at capturing patients with depression. Discussion: In the context of primary care, it may be worthwhile setting the 2-QQ screen at a lower threshold for positivity (such as a score of 1 or above). This would generate a high test sensitivity and thus capture the majority of patients that have depression. On the other hand, by setting a low threshold for positivity, patients who do not have depression but score higher than 1 on the 2-QQ will also be falsely identified as testing positive for depression. However, the benefits of identifying patients who present with depression may outweigh the harms of falsely identifying a non-depressed patient. It is our hope that the 2-QQ will serve as a quick primary screen for depression in the primary care setting and serve as a catalyst to identify and treat individuals with depression.

Keywords: depression, primary care, screening tool, Sri Lanka

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Authors: Sana Gul, Sheeba Murad, Aneela Javed

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Introduction: Human Papilloma Virus (HPV) is small DNA virus mostly infecting mucosa and cutaneous keratinocytes. So far, more than 200 Human papillomaviruses are known. HPV have been divided into high- and low-risk on the basis of their oncogenic potential. High risk HPV is considered to be the main etiological cause for cervical cancer. Objective: Current study was designed to screen the local cervical cancer patients from the twin cities of Pakistan for the occurance of high risk HPV. Methodology: A total of 67 formalin fixed paraffin-embedded samples of cervical cancer biopsies were obtained from the government hospitals in Islamabad and Rawalpindi. Cervical cancer biopsies were examined for the presence of HPV DNA. Polymerase chain reaction (PCR) was used for the amplification of a region in the HPV-L1 gene for the general detection of the Papilloma virus and for the genotype specific detection of high risk HPV 16 and 18 using the GP5/GP6 primers and genotype specific primers respectively. Results: HPV DNA was detected in 59 out of 67 samples analyzed. 30 samples showed the presence of HPV16 while 22 samples were positive for HPV 18 . HPV subtype could not be determined in 7 samples. Conclusion: Our results show a strong association between HPV infection and cervical cancer among women in twin cities of Pakistan. One way to minimize the disease burden in relation to HPV infection in Pakistani population is the use of prophylactic vaccines and routine screening. An early diagnosis of HPV infection will allow better health management to reduce the risk of developing cervical cancer.

Keywords: cervical cancer, Pakistan, human papillomavirus, HPV 16

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Jae-Jeong Kim, Ki-Ro Kim, Hyoung-Kyu Song

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In this paper, we propose an efficient signal detector that switches M parameter of QRD-M detection scheme is proposed for MIMO-OFDM system. The proposed detection scheme calculates the threshold by 1-norm condition number and then switches M parameter of QRD-M detection scheme according to channel information. If channel condition is bad, the parameter M is set to high value to increase the accuracy of detection. If channel condition is good, the parameter M is set to low value to reduce complexity of detection. Therefore, the proposed detection scheme has better trade off between BER performance and complexity than the conventional detection scheme. The simulation result shows that the complexity of proposed detection scheme is lower than QRD-M detection scheme with similar BER performance.

Keywords: MIMO-OFDM, QRD-M, channel condition, BER

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Authors: K. Sekulová, M. Šimon

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This article focuses on upper-extremity musculoskeletal disorders risk assessment model at workplace. In this model are used risk factors that are responsible for musculoskeletal system damage. Based on statistic calculations the model is able to define what risk of MSD threatens workers who are under risk factors. The model is also able to say how MSD risk would decrease if these risk factors are eliminated.

Keywords: ergonomics, musculoskeletal disorders, occupational diseases, risk factors

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Authors: Nazanin Ahmadi Daryakenari

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Background: Diabetes significantly influences the risk of heart failure. The interplay between distinct types of diabetes, heart failure, and their distribution across various age groups remains an area of active exploration. This study endeavors to scrutinize the age group distribution in publications addressing Type 1 and Type 2 diabetes and heart failure on PubMed while also examining the evolving publication trends. Methods: We leveraged E-utilities and RegEx to search and extract publication data from PubMed using various mesh terms. Subsequently, we conducted descriptive statistics and t-tests to discern the differences between the two diabetes types and the distribution across age groups. Finally, we analyzed the temporal trends of publications concerning both types of diabetes and heart failure. Results: Our findings revealed a divergence in the age group distribution between Type 1 and Type 2 diabetes within heart failure publications. Publications discussing Type 2 diabetes and heart failure were more predominant among older age groups, whereas those addressing Type 1 diabetes and heart failure displayed a more balanced distribution across all age groups. The t-test revealed no significant difference in the means between the two diabetes types. However, the number of publications exploring the relationship between Type 2 diabetes and heart failure has seen a steady increase over time, suggesting an escalating interest in this area. Conclusion: The dissection of publication patterns on PubMed uncovers a pronounced association between Type 2 diabetes and heart failure within older age groups. This highlights the critical need to comprehend the distinct age group differences when examining diabetes and heart failure to inform and refine targeted prevention and treatment strategies.

Keywords: Type 1 diabetes, Type 2 diabetes, heart failure, age groups, publication patterns, PubMed

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Authors: Jae-Hyun Ro, Yong-Jun Kim, Chang-Bin Ha, Hyoung-Kyu Song

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In multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems, many detection schemes have been developed to improve the error performance and to reduce the complexity. Maximum likelihood (ML) detection has optimal error performance but it has very high complexity. Thus, this paper proposes reduced complexity of ML detection combined with decision feedback equalizer (DFE). The error performance of the proposed detection scheme is higher than the conventional DFE. But the complexity of the proposed scheme is lower than the conventional ML detection.

Keywords: detection, DFE, MIMO-OFDM, ML

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Authors: Von Jerick Tenorio, Jonald Lucero, Marivic Vestal, Edwin Tiempo

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In patients with hostile aortic neck anatomy, the risks of proximal seal complications and stent migration remain with EVAR despite improved endograft technology. This case report discusses how the technical challenges of the hostile neck anatomy, proximal penetrating atherosclerotic ulcer (PAU) and tortuous femoral access were addressed. The CT aortogram of a 63-year-old hypertensive and diabetic man with recurring abdominal discomfort revealed a fusiform infra-renal aneurysm measuring 8.8 cm in length and 5.7 cm in diameter. The proximal landing zone only has a 3 mm healthy neck with a conicity of > 10% and a thrombus of 4 mm thick. Proximal to the aneurysm is a PAU with a circumferential mural thrombus. The right femoral artery is tortuous with > 90o angulation. A 20% oversized Endurant II endograft and Aptus Heli-FX EndoAnchors were deployed as prophylaxis for type I endoleaks and endograft migration consequent to the conical neck and proximal aneurysm extension consequent to the PAU. A stiff Backup Meier guide wire facilitated the deployment of the endograft. Coil embolization of the right internal iliac artery was performed as prophylaxis for type II endoleaks. EndoAnchors can be used as an adjunct to EVAR as prophylaxis for proximal seal complications and stent migration in patients with hostile aortic aneurysm neck anatomy and concomitant proximal PAU.

Keywords: endoAnchors, endoleaks, EVAR, hostile neck

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Authors: Anna Jeon, Seung-Ho Han, Je-Hun Lee

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The aim of this study was to determine the location and distribution pattern of neurovascular structures superior and inferior to the clavicle by detailed dissection. Fifteen adult non-embalmed cadavers with a mean age of 71.5 years were studied. For measurements, the most prominent point of the sternal end of the clavicle (SEC) on anterior view and the most prominent point of the acromial end of the clavicle (AEC) were identified before dissection. A line connecting the SEC and AEC was used as a reference line. The surrounding neurovascular structures were investigated. The supraclavicular nerve was densely distributed at 71.73% on the reference line. Branches of the thoracoacromial artery were located at 76.92%. Branches of subclavian vein were evenly distributed at all sections. The subclavian vein and artery and brachial plexus were located from 31.3% to 57.5%. That area needs caution because major neurovascular structures run underneath the clavicle.

Keywords: clavicle, ORIF, neurovascular structure, anatomical study

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Authors: Seyedmohammad Mousavian, Hanlu Fan, Quingliang Tang

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Climate change is emerging as a severe threat to our society, so businesses are expected to take actions to mitigate carbon emissions. However, the actions to be taken depend on managers’ perceptions of climate change risks. Yet, there is scant research on this issue, and understanding of the determinants of corporate perceptions of climate change is extremely limited. The purpose of this study is to close this gap by examining the relationship between perceptions of climate risk and firm-level and country-level factors. In this study, climate change risk captures physical, regulatory, and other risks, and we use data from European companies that participated in CDP from 2010 to 2017. This study reveals those perceptions of climate change risk are significantly positively associated with the environmental, social, and governance score, firm size, and membership in a carbon-intensive sector. In addition, we find that managers in firms operating in a geographic area that is sensitive to the consequences of global warming are more likely to perceive and formally recognize carbon-related risks in their CDP reports.

Keywords: carbon actions, CDP, climate change risk, risk perception

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Authors: Todd Zhou, Mikhail Yurochkin

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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

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Authors: Junaid Asimiyu Mohammed, Olakunle Docas Tosin

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The housing environment in many developing countries is fraught with risks that have potential negative impacts on the lives of the residents. The study examined the risk factors in residential areas of two neighborhoods in Bosso Local Government Areas of Minna in Nigeria with a view to determining the level of their potential impacts. A sample of 378 households was drawn from the estimated population of 22,751 household heads. The questionnaire and direct observation were used as instruments for data collection. The data collected were analyzed using the Relative Importance Index (RII) rule to determine the level of the potential impact of the risk factors while ArcGIS was used for mapping the spatial distribution of the risks. The study established that the housing environment of Angwan Biri and El-Waziri areas of Bosso is poor and vulnerable as 26% of the houses were not habitable and 57% were only fairly habitable. The risks of epidemics, building collapse and rainstorms were evident in the area as 53% of the houses had poor ventilation; 20% of residents had no access to toilets; 47% practiced open waste dumping; 46% of the houses had cracked walls while 52% of the roofs were weak and sagging. The results of the analysis of the potential impact of the risk factors indicate a RII score of 0.528 for building collapse, 0.758 for rainstorms and 0.830 for epidemics, indicating a moderate to very high level of potential impacts. The mean RII score of 0.639 shows a significant potential impact of the risk factors. The study recommends the implementation of sanitation measures, provision of basic urban facilities and neighborhood revitalization through housing infrastructure retrofitting as measures to mitigate the risks of disasters and improve the living conditions of the residents of the study area.

Keywords: assessment, risk, residential, Nigeria

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Authors: Allyson Augusta Shrikhande, Alexa Rains, Tayyaba Ahmed, Marjorie Mamsaang, Rakhi Vyas, Janaki Natarajan, Erika Moody, Christian Reutter, Kimberlee Leishear, Yogita Tailor, Sandra Sandhu-Restaino, Lora Liu, Neha James, Rosemarie Filart

Abstract:

Characterized by consistent difficulty getting and keeping an erection firm enough for intercourse, Erectile Dysfunction may affect up to 15% of adult men. Although awareness and access to treatment have improved in recent years, many patients do not actively seek diagnosis or treatment due to the stigma surrounding this condition. Patients who do seek treatment are often dissatisfied by the efficacy of the medication. The condition inhibits patients’ quality of life by worsening mental health and relationships. The purpose of this study was to test the effectiveness of an outpatient neuromuscular treatment protocol in treating the symptoms of Chronic Pelvic Pain and Erectile Dysfunction, improving pain and function. 56 patients ages 20-79 presented to an outpatient clinic for treatment of pelvic pain and Erectile Dysfunction symptoms. These symptoms had persisted for an average of 4 years. All patients underwent external ultrasound-guided hydro-dissection technique targeted at pelvic peripheral nerves in combination with pelvic floor musculature trigger-point injections. To measure the effects of this treatment, a five question Erectile Dysfunction questionnaire was completed by each patient at their first visit to a clinic and three months after treatment began. Answers were summed for a total score of 5-25, with a higher score indicating optimal function. The average score before treatment was 14.125 (SD 5.411) (a=0.05; CI 12.708-15.542), which increased by 18% to an average of 16.625 (SD 6.423) (a=0.05; CI 14.943-18.307) after treatment (P=0.0004). Secondary outcome variables included a Visual Analogue Scale (VAS) to measure pelvic pain intensity and the Functional Pelvic Pain Scale (FPPS) to measure function across multiple areas. VAS scores reduced by 51% after three months. Before treatment, the mean VAS score was 5.87, and the posttreatment mean VAS score was 2.89. Pelvic pain functionality improved by 34% after three months. Pretreatment FPPS scores averaged at 7.48, decreasing to 4.91 after treatment. These results indicate that this unique treatment was very effective at relieving pain and increasing function for patients with Erectile Dysfunction.

Keywords: chronic pelvic pain, erectile dysfunction, nonsurgical, outpatient, trigger point injections

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Authors: Marek Kuźniewski, Magdalena B. Kaziuk , Danuta Fedak, Paulina Dumnicka, Ewa Stępień, Beata Kuśnierz-Cabala, Władysław Sułowicz

Abstract:

Background: The high prevalence of cardiovascular morbidity and mortality among patients with chronic kidney disease (CKD) is observed especially in those undergoing dialysis. Osteoprotegerin (OPG) and its ligands, receptor activator of nuclear factor kappa-B ligand (RANKL) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) have been associated with cardiovascular complications. Our aim was to study their role as cardiovascular risk factors in stage 5 CKD patients. Methods: OPG, RANKL and TRAIL concentrations were measured in 69 hemodialyzed CKD patients and 35 healthy volunteers. In CKD patients, cardiovascular dysfunction was assessed with aortic pulse wave velocity (AoPWV), carotid artery intima-media thickness (CCA-IMT), coronary artery calcium score (CaSc) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) serum concentration. Cardiovascular and overall mortality data were collected during a 7-years follow-up. Results: OPG plasma concentrations were higher in CKD patients comparing to controls. Total soluble RANKL was lower and OPG/RANKL ratio higher in patients. Soluble TRAIL concentrations did not differ between the groups and OPG/TRAIL ratio was higher in CKD patients. OPG and OPG/TRAIL positively predicted long-term mortality (all-cause and cardiovascular) in CKD patients. OPG positively correlated with AoPWV, CCA-IMT and NT-proBNP whereas OPG/TRAIL with AoPWV and NT-proBNP. Described relationships were independent of classical and non-classical cardiovascular risk factors, with exception of age. Conclusions: Our study confirmed the role of OPG as a biomarker of cardiovascular dysfunction and a predictor of mortality in stage 5 CKD. OPG/TRAIL ratio can be proposed as a predictor of cardiovascular dysfunction and mortality.

Keywords: osteoprotegerin, tumor necrosis factor-related apoptosis-inducing ligand, receptor activator of nuclear factor kappa-B ligand, hemodialysis, chronic kidney disease, cardiovascular disease

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Authors: N. Reza Pour, S. Chuah, T. Vo

Abstract:

Background: Vertebral artery dissection (VAD) is a rare complication of pregnancy. It can occur spontaneously or following a traumatic event. The pathogenesis is unclear. Predisposing factors include chronic hypertension, Marfan’s syndrome, fibromuscular dysplasia, vasculitis and cystic medial necrosis. Physiological changes of pregnancy have also been proposed as potential mechanisms of injury to the vessel wall. The clinical presentation varies and it can present as a headache, neck pain, diplopia, transient ischaemic attack, or an ischemic stroke. Isolated cases of VAD in pregnancy and puerperium have been reported in the literature. One case was found to have posterior circulation stroke as a result of bilateral VAD and labour was induced at 37 weeks gestation for preeclampsia. Another patient at 38 weeks with severe neck pain that persisted after induction for elevated blood pressure and arteriography showed right VAD postpartum. A single case of lethal VAD in pregnancy with subsequent massive subarachnoid haemorrhage has been reported which was confirmed by the autopsy. Case Presentation: We report two cases of vertebral artery dissection in pregnancy. The first patient was a 32-year-old primigravida presented at the 38th week of pregnancy with the onset of early labour and blood pressure (BP) of 130/70 on arrival. After 2 hours, the patient developed a severe headache with blurry vision and BP was 238/120. Despite treatment with an intravenous antihypertensive, she had eclamptic fit. Magnesium solfate was started and Emergency Caesarean Section was performed under the general anaesthesia. On the second day after the operation, she developed left-sided neck pain. Magnetic Resonance Imaging (MRI) angiography confirmed a short segment left vertebral artery dissection at the level of C3. The patient was treated with aspirin and remained stable without any neurological deficit. The second patient was a 33-year-old primigavida who was admitted to the hospital at 36 weeks gestation with BP of 155/105, constant headache and visual disturbances. She was medicated with an oral antihypertensive agent. On day 4, she complained of right-sided neck pain. MRI angiogram revealed a short segment dissection of the right vertebral artery at the C2-3 level. Pregnancy was terminated on the same day with emergency Caesarean Section and anticoagulation was started subsequently. Post-operative recovery was complicated by rectus sheath haematoma requiring evacuation. She was discharged home on Aspirin without any neurological sequelae. Conclusion: Because of collateral circulation, unilateral vertebral artery dissections may go unrecognized and may be more common than suspected. The outcome for most patients is benign, reflecting the adequacy of the collateral circulation in young patients. Spontaneous VAD is usually treated with anticoagulation or antiplatelet therapy for a minimum of 3-6 months to prevent future ischaemic events, allowing the dissection to heal on its own. We had two cases of VAD in the context of hypertensive disorders of pregnancy with an acceptable outcome. A high level of vigilance is required particularly with preeclamptic patients presenting with head/neck pain to allow an early diagnosis. This is as we hypothesize, early and aggressive management of vertebral artery dissection may potentially prevent further complications.

Keywords: eclampsia, preeclampsia, pregnancy, Vertebral Artery Dissection

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Authors: Nantakrit Yodpijit, Teppakorn Sittiwanchai

Abstract:

The number of older adults is rising rapidly. The world’s population becomes aging. Falls is one of common and major health problems in the elderly. Falls may lead to acute and chronic injuries and deaths. The fall-prone individuals are at greater risk for decreased quality of life, lowered productivity and poverty, social problems, and additional health problems. A number of studies on falls prevention using fall detection system have been conducted. Many available technologies for fall detection system are laboratory-based and can incur substantial costs for falls prevention. The utilization of alternative technologies can potentially reduce costs. This paper presents the new design and development of a wearable-based fall detection system using an Accelerometer and Gyroscope as motion sensors for the detection of body orientation and movement. Algorithms are developed to differentiate between Activities of Daily Living (ADL) and falls by comparing Threshold-based values with Artificial Neural Networks (ANN). Results indicate the possibility of using the new threshold-based method with neural network algorithm to reduce the number of false positive (false alarm) and improve the accuracy of fall detection system.

Keywords: aging, algorithm, artificial neural networks (ANN), fall detection system, motion sensorsthreshold

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Authors: Venencia Albert, Arulselvi Subramanian, Hara Prasad Pati, Asok K. Mukhophadhyay

Abstract:

Acute traumatic coagulopathy in an endogenous dysregulation of the intrinsic coagulation system in response to the injury, associated with three-fold risk of poor outcome, and is more amenable to corrective interventions, subsequent to early identification and management. Multiple definitions for stratification of the patients' risk for early acute coagulopathy have been proposed, with considerable variations in the defining criteria, including several trauma-scoring systems based on prehospital data. We aimed to develop a clinically relevant definition for acute coagulopathy of trauma based on conventional coagulation assays and to assess its efficacy in comparison to recently established prehospital prediction models. Methodology: Retrospective data of all trauma patients (n = 490) presented to our level I trauma center, in 2014, was extracted. Receiver operating characteristic curve analysis was done to establish cut-offs for conventional coagulation assays for identification of patients with acute traumatic coagulopathy was done. Prospectively data of (n = 100) adult trauma patients was collected and cohort was stratified by the established definition and classified as "coagulopathic" or "non-coagulopathic" and correlated with the Prediction of acute coagulopathy of trauma score and Trauma-Induced Coagulopathy Clinical Score for identifying trauma coagulopathy and subsequent risk for mortality. Results: Data of 490 trauma patients (average age 31.85±9.04; 86.7% males) was extracted. 53.3% had head injury, 26.6% had fractures, 7.5% had chest and abdominal injury. Acute traumatic coagulopathy was defined as international normalized ratio ≥ 1.19; prothrombin time ≥ 15.5 s; activated partial thromboplastin time ≥ 29 s. Of the 100 adult trauma patients (average age 36.5±14.2; 94% males), 63% had early coagulopathy based on our conventional coagulation assay definition. Overall prediction of acute coagulopathy of trauma score was 118.7±58.5 and trauma-induced coagulopathy clinical score was 3(0-8). Both the scores were higher in coagulopathic than non-coagulopathic patients (prediction of acute coagulopathy of trauma score 123.2±8.3 vs. 110.9±6.8, p-value = 0.31; trauma-induced coagulopathy clinical score 4(3-8) vs. 3(0-8), p-value = 0.89), but not statistically significant. Overall mortality was 41%. Mortality rate was significantly higher in coagulopathic than non-coagulopathic patients (75.5% vs. 54.2%, p-value = 0.04). High prediction of acute coagulopathy of trauma score also significantly associated with mortality (134.2±9.95 vs. 107.8±6.82, p-value = 0.02), whereas trauma-induced coagulopathy clinical score did not vary be survivors and non-survivors. Conclusion: Early coagulopathy was seen in 63% of trauma patients, which was significantly associated with mortality. Acute traumatic coagulopathy defined by conventional coagulation assays (international normalized ratio ≥ 1.19; prothrombin time ≥ 15.5 s; activated partial thromboplastin time ≥ 29 s) demonstrated good ability to identify coagulopathy and subsequent mortality, in comparison to the prehospital parameter-based scoring systems. Prediction of acute coagulopathy of trauma score may be more suited for predicting mortality rather than early coagulopathy. In emergency trauma situations, where immediate corrective measures need to be taken, complex multivariable scoring algorithms may cause delay, whereas coagulation parameters and conventional coagulation tests will give highly specific results.

Keywords: trauma, coagulopathy, prediction, model

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Authors: Wei Li, Tuo Yang

Abstract:

In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

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Authors: Bo Liu, Qingshan Kong, Weiqing Huang

Abstract:

With the rapid development of modern communication, diagnosing the fiber-optic quality and faults in real-time is widely focused. In this paper, a Labview-based system is proposed for fiber-optic faults detection. The wavelet threshold denoising method combined with Empirical Mode Decomposition (EMD) is applied to denoise the optical time domain reflectometer (OTDR) signal. Then the method based on Gabor representation is used to detect events. Experimental measurements show that signal to noise ratio (SNR) of the OTDR signal is improved by 1.34dB on average, compared with using the wavelet threshold denosing method. The proposed system has a high score in event detection capability and accuracy. The maximum detectable fiber length of the proposed Labview-based system can be 65km.

Keywords: empirical mode decomposition, events detection, Gabor transform, optical time domain reflectometer, wavelet threshold denoising

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Authors: Chaiyaporn Yuksen

Abstract:

Backgroud: Supraventricular tachycardia (SVT) is an abnormally fast atrial tachycardia characterized by narrow (≤ 120 ms) and constant QRS. Adenosine was the drug of choice; the first dose was 6 mg. It can be repeated with the second and third doses of 12 mg, with greater than 90% success. The study found that patients observed at 4 hours after normal sinus rhythm was no recurrence within 24 hours. The objective of this study was to investigate the factors that influence the recurrence of SVT after adenosine in the emergency department (ED). Method: The study was conducted retrospectively exploratory model, prognostic study at the Emergency Department (ED) in Faculty of Medicine, Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand. The study was conducted for ten years period between 2010 and 2020. The inclusion criteria were age > 15 years, visiting the ED with SVT, and treating with adenosine. Those patients were recorded with the recurrence SVT in ED. The multivariable logistic regression model developed the predictive model and prediction score for recurrence PSVT. Result: 264 patients met the study criteria. Of those, 24 patients (10%) had recurrence PSVT. Five independent factors were predictive of recurrence PSVT. There was age>65 years, heart rate (after adenosine) > 100 per min, structural heart disease, and dose of adenosine. The clinical risk score to predict recurrence PSVT is developed accuracy 74.41%. The score of >6 had the likelihood ratio of recurrence PSVT by 5.71 times Conclusion: The clinical predictive score of > 6 was associated with recurrence PSVT in ED.

Keywords: clinical prediction score, SVT, recurrence, emergency department

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Authors: Ergun Sakalar, Kubra Bilgic

Abstract:

Faster detection and characterization of pathogens are the basis of the evoid from foodborne pathogens. Salmonella spp., Shigella spp. and Listeria monocytogenes are common foodborne bacteria that are among the most life-threatining. It is important to rapid and accurate detection of these pathogens to prevent food poisoning and outbreaks or to manage food chains. The present work promise to develop a sensitive, species specific and reliable PCR based detection system for simultaneous detection of Salmonella spp., Shigella spp. and Listeria monocytogenes. For this purpose, three genes were picked out, ompC for Salmonella spp., ipaH for Shigella spp. and hlyA for L. monocytogenes. After short pre-enrichment of milk was passed through a vacuum filter and bacterial DNA was exracted using commercially available kit GIDAGEN®(Turkey, İstanbul). Detection of amplicons was verified by examination of the melting temperature (Tm) that are 72° C, 78° C, 82° C for Salmonella spp., Shigella spp. and L. monocytogenes, respectively. The method specificity was checked against a group of bacteria strains, and also carried out sensitivity test resulting in under 10² CFU mL⁻¹ of milk for each bacteria strain. Our results show that the flourescence based triplex qPCR method can be used routinely to detect Salmonella spp., Shigella spp. and L. monocytogenes during the milk processing procedures in order to reduce cost, time of analysis and the risk of foodborne disease outbreaks.

Keywords: evagreen, food-born bacteria, pathogen detection, real-time pcr

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