Search results for: aortic dissection detection risk score

Authors: Hatem A. El-Mezayen, Hossam Darwesh

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Background/Aim: Hepatocellular carcinoma (HCC) is often diagnosed at advanced stage where effective therapies are lacking. Identification of new scoring system is needed to discriminate HCC patients from those with chronic liver disease. Based on the link between vascular endothelial growth factor (VEGF) and HCC progression, we aimed to develop a novel score based on combination of VEGF and routine laboratory tests for early prediction of HCC. Methods: VEGF was assayed for HCC group (123), liver cirrhosis group (210) and control group (50) by Enzyme Linked Immunosorbent Assay (ELISA). Data from all groups were retrospectively analyzed including α feto protein (AFP), international normalized ratio (INR), albumin and platelet count, transaminases, and age. Areas under ROC curve were used to develop the score. Results: A novel index named hepatocellular carcinoma-vascular endothelial growth factor score (HCC-VEGF score)=1.26 (numerical constant) + 0.05 ×AFP (U L-1)+0.038 × VEGF(ng ml-1)+0.004× INR –1.02 × Albumin (g l-1)–0.002 × Platelet count × 109 l-1 was developed. HCC-VEGF score produce area under ROC curve of 0.98 for discriminating HCC patients from liver cirrhosis with sensitivity of 91% and specificity of 82% at cut-off 4.4 (ie less than 4.4 considered cirrhosis and greater than 4.4 considered HCC). Conclusion: Hepatocellular carcinoma-VEGF score could replace AFP in HCC screening and follow up of cirrhotic patients.

Keywords: Hepatocellular carcinoma, cirrhosis, HCV, diagnosis, tumor markers

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Authors: Ruqayya Naheed Khan, Romaisa Shamim, Awais Amjad Malik, Awais Naeem, Amina Iqbal Khan, Asad Parvaiz

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Objective: Patients undergoing axillary lymph node dissection (ALND) for metastatic lymph nodes in our hospital usually have drains placed in their axilla for a period of 6-10 days. We evaluated the post-op course of patients who underwent breast conservation surgery (BCS) along with ALND. Methods: A prospective cohort study was conducted at Shaukat Khanam Memorial Cancer Hospital from April 2017 to August 2017 including all lymph node positive breast cancer patients undergoing BCS with ALND. Patients were divided into two groups. Group A had no axillary drain while in Group B a drain was placed in axilla. Results: A total of 76 patients were included. 41 patients were included in group A and 35 patients in Group B. Median number of LNs dissected in group A was 17 and in group B was 15 (p value 0.443). Median operative time in group A was 84 min and in group B was 79 min (p value 0.223). Median hospital stay in both groups was 1 day (p value 0.78). At 2 weeks all patients in group A developed seroma as compared to none in group B (p value < 0.001). 3 of these patients in group A required aspiration of seroma due to pressure effects. Rest were managed conservatively. At 6 weeks only 50% patients had a seroma radiologically in Group A as compared to 33% in group B (p value 0.023). No intervention was required in any patients at week 6. QOL at 2 weeks was much better in Group A (7/41 patients had unsatisfactory response) as compared to group B (10/31 had unsatisfactory response). Results were statistically significant (p value 0.045). However, there wasn’t much difference in QOL at 6 weeks. Only 1 patient in group A had an unsatisfactory response. Average pain score at 2 weeks was similar in both groups (4.2 v/s 4.1 p value 0.73). Infection was seen in 1 patient in each group at 2 weeks (p value 0.668) and in only 1 patient in group A at 6 weeks (p value 0.067). Conclusion: We conclude from our study that there isn’t much difference in drain and no drain group in terms of wound infection and pain scores. No drain group is however associated with a better QOL in early post-op period.

Keywords: axillary drainage, axillary lymph node dissection, breast cancer, no drain in axilla

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Authors: Issam M Hajjaji, Adel Tajoury, Salah R Benhamid

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The MENA region has the highest prevalence of diabetes in the world. Various risk scores were developed, not all appropriate locally. The objective of this study is to apply the FINDRISC Score to adult Libyan males to determine its significance, sensitivity, specificity and Positive Predictive Values as an initial screening tool for type 2 diabetes, and suggest a cut-off point. Methods: 600 subjects answered the questionnaire at their place of work, and their waist, weight, height & BP were measured. Thereafter, after excluding those with known diabetes, an Oral Glucose Tolerance Test was done. Results: 414 subjects aged 19-78 completed the questionnaire and tests. 35 (8.4%) had impaired glucose tolerance (IGT) and 13 (3.1%) had diabetes (DM). The AUC-ROC for IGT was 0.614 (95% CI: 0.527-0.701), for DM 0.810 (95% CI: 0.709-0.911) and for both 0.689 (95% CI: 0.609-0.769). The Positive Predictive Value for a cut-off score of 5 were 15.5%, 11.7% & 5.7% for both conditions combined, prediabetes & diabetes respectively. The equivalent values for a cut-off score of 8 were 16.1%, 9.0% & 7.7%. The Negative Predictive Values were uniformly above 90%. Conclusions & Recommendations: The FINDRISC Score had a low predictive value for dysglycaemia in this sample and performed at a level of significance for IGT that is similar to other MENA countries, but did better for DM. A larger sample that included women is suggested, with a view of adjusting the Score to suit the local population.

Keywords: diabetes, FINDRISK, Libya, prediabetes

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Authors: Swati Srivastava, Ashish Kumar Upadhyay

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Using longitudinal data from three waves of Young Lives Study and Ordinary Least Square methods, study has investigated the effect of birth order and arrival of younger siblings on child development in India. Study used child’s height for age z-score, weight for age z-score, BMI for age z-score, Peabody Picture Vocabulary Test (PPVT-Score)c, maths score, Early Grade Reading Assessment Test (ERGA) score, and memory score to measure the physical and cognitive development of child during wave-3. Findings suggest that having a high birth order is detrimental for child development and the gap between adjacent siblings is larger for children late in the birth sequences than early in the birth sequences. Study also reported that not only older siblings but arrival of younger siblings before assessment of test also reduces the development of a child. The effects become stronger in case of female children than male children.

Keywords: height for age z-score, weight for age z-score, BMI for z-score, PPVT score, math score, EGRA score, memory score, birth order, siblings, Young Lives Study, India

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Authors: Maomao Cao

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Objective: To test the performance of ctDNA methylation for the detection of liver cancer. Methods: A total of 1233 individuals have been recruited in 2017. 15 male and 15 female samples (including 10 cases of liver cancer) were randomly selected in the present study. CfDNA was extracted by MagPure Circulating DNA Maxi Kit. The concentration of cfDNA was obtained by Qubit™ dsDNA HS Assay Kit. A pre-constructed predictive model was used to analyze methylation data and to give a predictive score for each cfDNA sample. Individuals with a predictive score greater than or equal to 80 were classified as having liver cancer. CT tests were considered the gold standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for the diagnosis of liver cancer were calculated. Results: 9 patients were diagnosed with liver cancer according to the prediction model (with high sensitivity and threshold of 80 points), with scores of 99.2, 91.9, 96.6, 92.4, 91.3, 92.5, 96.8, 91.1, and 92.2, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of ctDNA methylation for the diagnosis of liver cancer were 0.70, 0.90, 0.78, and 0.86, respectively. Conclusions: ctDNA methylation could be an acceptable diagnostic modality for the detection of liver cancer.

Keywords: liver cancer, ctDNA methylation, detection, diagnostic performance

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Authors: Alexander Kelíšek, Denisa Janasová, Veronika Mitašová

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Weak signals using is often associated with early warning. It is possible to find a link between early warning, respectively early problems detection and risk management. The idea of early warning is very important in the context of crisis management because of the risk prevention possibility. Weak signals are likened to risk symptoms. Nowadays, their usefulness as a tool of proactive problems solving is emphasized. Based on it, it is possible to use weak signals not only in strategic planning, project management, or early warning system, but also as a subsidiary element in risk management. The main question is how to effectively integrate weak signals into risk management. The main aim of the paper is to point out the possibilities of weak signals using in small and medium enterprises risk management.

Keywords: early warning system, weak signals, risk management, small and medium enterprises (SMEs)

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Authors: Philippe Dillien, Patrice Forget, Harald Engel, Olivier Cornu, Marc De Kock, Jean Cyr Yombi

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Introduction: Hip fracture precedes commonly death in elderly people. Identification of high-risk patients may contribute to target patients in whom optimal management, resource allocation and trials efficiency is needed. The aim of this study is to construct a predictive score of mortality after hip fracture on the basis of the objective prognostic factors available: Neutrophil-to-lymphocyte ratio (NLR), age, and sex. C-Reactive Protein (CRP), is also considered as an alternative to the NLR. Patients and methods: After the IRB approval, we analyzed our prospective database including 286 consecutive patients with hip fracture. A score was constructed combining age (1 point per decade above 74 years), sex (1 point for males), and NLR at postoperative day+5 (1 point if >5). A receiver-operating curve (ROC) curve analysis was performed. Results: From the 286 patients included, 235 were analyzed (72 males and 163 females, 30.6%/69.4%), with a median age of 84 (range: 65 to 102) years, mean NLR values of 6.47+/-6.07. At one year, 82/280 patients died (29.3%). Graphical analysis and log-rank test confirm a highly statistically significant difference (P<0.001). Performance analysis shows an AUC of 0.72 [95%CI 0.65-0.79]. CRP shows no advantage on NLR. Conclusion: We have developed a score based on age, sex and the NLR to predict the risk of mortality at one year in elderly patients after surgery for a hip fracture. After external validation, it may be included in clinical practice as in clinical research to stratify the risk of postoperative mortality.

Keywords: neutrophil-to-lymphocyte ratio, hip fracture, postoperative mortality, medical and health sciences

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Authors: Mohammad Aziz Shah Mohamed Arip, Aslina Ahmad, Fauziah Mohd Sa'ad, Samsiah Mohd Jais, Syed Sofian Syed Salim

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This experimental study evaluates the effect of using Cognitive-Behavioral Therapy (CBT) and Multidimensional Self-Concept Model (MSCM) in a drug prevention programme to increase resiliency and reduce aggression among at-risk youth in Malaysia. A number of 60 (N=60) university students who were at-risk of taking drugs were involved in this study. Participants were identified with self-rating scales, Adolescent Resilience Attitude Scale (ARAS) and Aggression Questionnaire. Based on the mean score of these instruments, the participants were divided into the treatment group, and the control group. Data were analyzed using t-test. The finding showed that the mean score of resiliency was increased in the treatment group compared to the control group. It also shows that the mean score of aggression was reduced in the treatment group compared to the control group. Drug Prevention Programme was found to help in enhancing resiliency and reducing aggression among participants in the treatment group compared to the controlled group. Implications were given regarding the preventive actions on drug abuse among youth in Malaysia.

Keywords: drug prevention programme, cognitive-behavioral therapy (CBT), multidimensional self concept model (MSCM), resiliency, aggression, at-risk youth

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Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

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Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: connected component labeling, image processing, morphological processing, optical musical recognition

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Authors: Zehra Buyuktuncer, Aylin H. Büyükkaragöz, Tuğçe N. Balcı, Nevin Ergun

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Background: Undergoing rigid dietary habits for enhancing athletic performance could lead to eating disorders. High prevalence of eating disorders among female athletes has been already reported. However, the risk of disordered eating among disabled athletes is not known. A better knowledge of the different eating behaviors and their prevalence in disabled athletes would be helpful to understand interactions between eating and health. This study aimed to examine the cognitive restraint, uncontrolled eating and emotional eating behaviors in a disabled athlete population. Method: A total of 70 disabled Turkish national athletes (33 female, 37 male) from 5 sport branches (soccer, weight lifting, shooting, table tennis and basketball) were involved in the study. The cognitive restraint, uncontrolled eating and emotional eating behaviors were assessed using the revised version of Three Factor Eating Questionnaire-R18 (TFEQ-R18). The questionnaires were conducted by dietitian during the preparation camps of athletes. Body weight, height and waist circumference (WC) were measured; and body composition was analyzed by bioelectrical impedance analysis method. Results: The TFEQ scales showed a cognitive dietary restraint score of 13.9±4.2, uncontrolled eating score of 17.7±5.8 and emotional eating score of 4.9±2.5. The mean score of total TFEQ-R18 was 36.5±8.62. Neither total TFEQ-R18 score nor subscale scores differed significantly by gender or sport branches (p>0.05, for each). The scores were also similar in BMI groups (n=63; p>0.05). Total TFEQ, uncontrolled eating and emotional eating scores were significantly higher among the athletes with congenital disabilities compared to the scores of the athletes with acquired disabilities (p<0.05, for each). Moreover, the cognitive dietary restraint score was significantly high in athletes who would like to lose weight (p=0.009). Conclusion: Disabled athletes might have a risk of disordered eating. The different eating behaviors among disabled athletes should be assessed using validated tools to develop personalized nutritional strategies for those athletes.

Keywords: disabled athletes, eating behaviour, three-factor eating questionnaire-r18, body composition

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Authors: M. V. Shivaani, P. K. Jain, Surendra S. Yadav

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Risk management has been gaining extensive focus from international organizations like Committee of Sponsoring Organizations and Financial Stability Board, and, the foundation of such an effective and efficient risk management system lies in a strong risk governance structure. In view of this, an attempt (perhaps a first of its kind) has been made to develop a risk governance index, which could be used as proxy for quality of risk governance structures. The index (normative framework) is based on eleven variables, namely, size of board, board diversity in terms of gender, proportion of executive directors, executive/non-executive status of chairperson, proportion of independent directors, CEO duality, chief risk officer (CRO), risk management committee, mandatory committees, voluntary committees and existence/non-existence of whistle blower policy. These variables are scored on a scale of 1 to 5 with the exception of the variables, namely, status of chairperson and CEO duality (which have been scored on a dichotomous scale with the score of 3 or 5). In case there is a legal/statutory requirement in respect of above-mentioned variables and there is a non-compliance with such requirement a score of one has been envisaged. Though there is no legal requirement, for the larger part of study, in context of CRO, risk management committee and whistle blower policy, still a score of 1 has been assigned in the event of their non-existence. Recognizing the importance of these variables in context of risk governance structure and the fact that the study basically focuses on risk governance, the absence of these variables has been equated to non-compliance with a legal/statutory requirement. Therefore, based on this the minimum score is 15 and the maximum possible is 55. In addition, an attempt has been made to explore the determinants of this index. For this purpose, the sample consists of non-financial companies (429) that constitute S&P CNX500 index. The study covers a 10 years period from April 1, 2005 to March 31, 2015. Given the panel nature of data, Hausman test was applied, and it suggested that fixed effects regression would be appropriate. The results indicate that age and size of firms have significant positive impact on its risk governance structures. Further, post-recession period (2009-2015) has witnessed significant improvement in quality of governance structures. In contrast, profitability (positive relationship), leverage (negative relationship) and growth (negative relationship) do not have significant impact on quality of risk governance structures. The value of rho indicates that about 77.74% variation in risk governance structures is due to firm specific factors. Given the fact that each firm is unique in terms of its risk exposure, risk culture, risk appetite, and risk tolerance levels, it appears reasonable to assume that the specific conditions and circumstances that a company is beset with, could be the biggest determinants of its risk governance structures. Given the recommendations put forth in the paper (particularly for regulators and companies), the study is expected to be of immense utility in an important yet neglected aspect of risk management.

Keywords: corporate governance, ERM, risk governance, risk management

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Authors: Rohin Rameswarapu, Sameer Valsangkar

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Background: Globally, musculoskeletal disorders are the largest single cause of work-related illnesses accounting for over 33% of all newly reported occupational illnesses. Risk factors for MSD need to be delineated to suggest means for amelioration. Material and methods: In this current cross-sectional study, the prevalence of MSDs among workers in an electrical company assembly line, the socio-demographic and job characteristics associated with MSD were obtained through a semi-structured questionnaire. A quantitative assessment of the physical risk factors through the Rapid Upper Limb Assessment (RULA) tool, and measurement of psychosocial risk factors through a Likert scale was obtained. Statistical analysis was conducted using Epi-info software and descriptive and inferential statistics including chi-square and unpaired t test were obtained. Results: A total of 263 workers consented and participated in the study. Among these workers, 200 (76%) suffered from MSD. Most of the workers were aged between 18–27 years and majority of the workers were women with 198 (75.2%) of the 263 workers being women. A chi square test was significant for association between male gender and MSD with a P value of 0.007. Among the MSD positive group, 4 (2%) had a grand score of 5, 10 (5%) had a grand score of 6 and 186 (93%) had a grand score of 7 on RULA. There were significant differences between the non-MSD and MSD group on five out of the seven psychosocial domains, namely job demand, job monotony, co-worker support, decision control and family and environment domains. Discussion: The current cross-sectional study demonstrates a high prevalence of MSD among assembly line works with inherent physical and psychosocial risk factors and recommends that not only physical risk factors, addressing psychosocial risk factors through proper ergonomic means is also essential to the well-being of the employee.

Keywords: musculoskeletal disorders, India, occupational health, Rapid Upper Limb Assessment (RULA)

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Authors: Thitaporn Thoopputra, Tipaporn Pongmesa, Shuchuen Li

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Aims: To evaluate the application of non-invasive diabetes risk assessment tool in community pharmacy setting. Methods: Thai diabetes risk score was applied to assess individuals at risk of developing type 2 diabetes. Interactive computer-based risk screening (IT) and paper-based risk screening (PT) tools were applied. Participants aged over 25 years with no known diabetes were recruited in six participating pharmacies. Results: A total of 187 clients, mean aged (+SD) was 48.6 (+10.9) years. 35% were at high risk. The mean value of willingness-to-pay for the service fee in IT group was significantly higher than PT group (p=0.013). No significant difference observed for the satisfaction between groups. Conclusions: Non-invasive risk assessment tool, whether paper-based or computerized-based can be applied in community pharmacy to support the enhancing role of pharmacists in chronic disease management. Long term follow up is needed to determine the impact of its application in clinical, humanistic and economic outcomes.

Keywords: community pharmacy, intervention, prevention, risk assessment, type 2 diabetes

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Authors: Ahmad Shahfarhat, Ashraf Mohammadzade, Reza Saeedi, Hadi Hesari

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Background: Mothers of infants admitted at NICU are vulnerable to depression (affecting 10 to 20% of mothers during the first year after delivery) As you know, about half of women with prominent postpartum depression (PPD) symptoms are not diagnosed. The Edinburgh Postnatal Depression Scale (EPDS) is the most widely used screening instrument for PPD. In this study, we checked EPDS score of 12 or more on the second day (D2), discharge, day 28(D28), and day42 (D42) postpartum to determine the risk factors as well as the prevalence of PPD in a sample of mothers of NICU admitted neonates. Methods: A sample of 682 women used the EPDS on admission and at discharge. An assessment for PPD was performed on D28 and D42 by a telephone interview. Results: On admission, the average score on EPDS was 9.72 (SD = 4.4), and 27.4% of women (187) had an EPDS score ≥12. On Discharge, 4weeks and 6weeks postpartum the average score was ordinary 9.34 (SD = 3.8), 9.12 (SD = 3.7), 8.52(SD = 3.36), and (173)25.4 %,( 141)23.3 %,( 88)15.3% of women presented with PPD. a positive correlation was found between scores on EPDS on admission and D42 (P = 0.001). An analysis shows that mothers of twins (P = 0.001) and higher age mothers (P=0.001) are significantly associated with PPD. Conclusion: Women with EPDS score more than 12 and/or older will benefit from a closer follow-up during the rest of the post-partum period, and it is better to be under psychological support.

Keywords: NICU, depression, pregnancy, mothers

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Authors: Hao-Hsi Tseng, Hsin-Yun Lee

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The Most Advantageous Tender (MAT) has been criticized for its susceptibility to dictatorial situations and for its processing of same score, same rank issues. This study applies the four criteria from Arrow's Impossibility Theorem to construct a mechanism for revealing illegitimate scores in scoring methods. While commonly be used to improve on problems resulting from extreme scores, ranking methods hide significant defects, adversely affecting selection fairness. To address these shortcomings, this study relies mainly on the overall evaluated score method, using standardized scores plus normal cumulative distribution function conversion to calculate the evaluation of vender preference. This allows for free score evaluations, which reduces the influence of dictatorial behavior and avoiding same score, same rank issues. Large-scale simulations confirm that this method outperforms currently used methods using the Impossibility Theorem.

Keywords: Arrow’s impossibility theorem, cumulative normal distribution function, most advantageous tender, scoring method

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Authors: Qianhui Li, Christoph H. Bruecker

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Atherosclerotic plaques are typically found where flow separation and variations of shear stress occur. Although helical flow patterns and flow separations have been recorded in the aorta, their relation has not been clearly clarified and especially in the condition of artificial heart valve prostheses. Therefore, an experimental study is performed to investigate the hemodynamic performance of different mechanical heart valves (MHVs), i.e. the SJM Regent bileaflet mechanical heart valve (BMHV) and the Lapeyre-Triflo FURTIVA trileaflet mechanical heart valve (TMHV), in a transparent model of the human aorta under a physiological pulsatile right-hand helical flow condition. A typical systolic flow profile is applied in the pulse-duplicator to generate a physiological pulsatile flow which thereafter flows past an axial turbine blade structure to imitate the right-hand helical flow induced in the left ventricle. High-speed particle image velocimetry (PIV) measurements are used to map the flow evolution. A circular open orifice nozzle inserted in the valve plane as the reference configuration initially replaces the valve under investigation to understand the hemodynamic effects of the entered helical flow structure on the flow evolution in the aortic arch. Flow field analysis of the open orifice nozzle configuration illuminates the helical flow effectively delays the flow separation at the inner radius wall of the aortic arch. The comparison of the flow evolution for different MHVs shows that the BMHV works like a flow straightener which re-configures the helical flow pattern into three parallel jets (two side-orifice jets and the central orifice jet) while the TMHV preserves the helical flow structure and therefore prevent the flow separation at the inner radius wall of the aortic arch. Therefore the TMHV is of better hemodynamic performance and reduces the pressure loss.

Keywords: flow separation, helical aortic flow, mechanical heart valve, particle image velocimetry

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Authors: Aml M. El-Sharkawy, Hossam M. Darwesh

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Abstract— Background/Aim: Hepatocellular carcinoma (HCC) is often diagnosed at advanced stage where effective therapies are lacking. Identification of new scoring system is needed to discriminate HCC patients from those with chronic liver disease. Based on the link between tumor associated trypsin inhibitor (TATI) and HCC progression, we aimed to develop a novel score based on combination of TATI and routine laboratory tests for early prediction of HCC. Methods: TATI was assayed for HCC group (123), liver cirrhosis group (210) and control group (50) by Enzyme Linked Immunosorbent Assay (ELISA). Data from all groups were retrospectively analyzed including α feto protein (AFP), international normalized ratio (INR), albumin and platelet count, transaminases, and age. Areas under ROC curve were used to develop the score. Results: A novel index named hepatocellular carcinoma-vascular endothelial growth factor score (HCC-TATI score) = 3.1 (numerical constant) + 0.09 ×AFP (U L-1) + 0.067 × TATI (ng ml-1) + 0.16 × INR – 1.17 × Albumin (g l-1) – 0.032 × Platelet count × 109 l-1 was developed. HCC-TATI score produce area under ROC curve of 0.98 for discriminating HCC patients from liver cirrhosis with sensitivity of 91% and specificity of 82% at cut-off 6.5 (ie less than 6.5 considered cirrhosis and greater than 4.4 considered HCC). Conclusion: Hepatocellular carcinoma-TATI score could replace AFP in HCC screening and follow up of cirrhotic patients.

Keywords: Hepatocellular carcinoma, cirrhosis, HCV, diagnosis, TATI

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Authors: Yuki Irie, Shota Ogawa, Hitomi Kosugi, Hiromitsu Shinozaki

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Background: Dropout from higher educational institutions is a major problem both for students and institutions, and poor mental health is one of the risk factors. Medical college students are at higher risk of poor mental health than general students because of their hard academic schedules. On the other hand, food insecurity has negative impacts on mental health. The healthcare college of the project site is located heavily snowy area. The students without own vehicles may be at higher risk of food insecurity, especially in the winter season. Therefore, they have many risks to mental health. The aim of the study is to clarify the relationship between mental health and its risk factors to promote students’ mental well-being. Method: A cross-sectional design was used to investigate the relationship between mental health status and lifestyle, including diet and food security among the students (n=421, 147 male, 274 females; 20.7 ± 2.8 years old). Participants were required to answer 3 questionnaires which consisted of diet, lifestyle, food security, and mental health. The survey was conducted during the snowy season from Dec. 2022 to Jan. 2023. Results: Mean mental score was 6.7±4.6 (max. score 27, a higher score means worse mental health). Significant risk factors in mental health were breakfast habit (p=0.02), subjective dietary habit (p=0.00), subjective health (p=0.00), exercise habit (p=0.02), food insecurity in the winter season (p=0.01), and vitamin A intakes (p=0.03). Conclusions: Nutrients intakes are not associated with mental health except vitamin A; however, some other lifestyle factors are significantly associated with mental health. Nutrition doesn’t lead to poor mental health directly; however, the promotion of a healthy lifestyle and improved food security in winter may be effective in better mental health.

Keywords: mental health, winter, lifestyle, students

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Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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Authors: Petar Dobrev

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There is no agreed-upon definition of firm quality. While profitability and stock performance often qualify as popular proxies of quality, in this project, we aim to identify quality without relying on a firm’s financial statements or stock returns as selection criteria. Instead, we use firm-level data on management practices across small to medium-sized U.S. manufacturing firms from the World Management Survey (WMS) to measure firm quality. Each firm in the WMS dataset is assigned a mean management score from 0 to 5, with higher scores identifying better-managed firms. This management score serves as our proxy for firm quality and is the sole criteria we use to separate firms into portfolios comprised of high-quality and low-quality firms. We define high-quality (low-quality) firms as those firms with a management score of one standard deviation above (below) the mean. To study whether this proxy for firm quality can identify better-performing firms, we link this data to Compustat and The Center for Research in Security Prices (CRSP) to obtain firm-level data on financial performance and monthly stock returns, respectively. We find that from 1999 to 2019 (our sample data period), firms in the high-quality portfolio are consistently more profitable — higher operating profitability and return on equity compared to low-quality firms. In addition, high-quality firms also exhibit a lower risk of bankruptcy — a higher Altman Z-score. Next, we test whether the stocks of the firms in the high-quality portfolio earn superior risk-adjusted excess returns. We regress the monthly excess returns on each portfolio on the Fama-French 3-factor, 4-factor, and 5-factor models, the betting-against-beta factor, and the quality-minus-junk factor. We find no statistically significant differences in excess returns between both portfolios, suggesting that stocks of high-quality (well managed) firms do not earn superior risk-adjusted returns compared to low-quality (poorly managed) firms. In short, our proxy for firm quality, the WMS management score, can identify firms with superior financial performance (higher profitability and reduced risk of bankruptcy). However, our management proxy cannot identify stocks that earn superior risk-adjusted returns, suggesting no statistically significant relationship between managerial quality and stock performance.

Keywords: excess stock returns, management, profitability, quality

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Authors: Adeep Hande, Shubham Agarwal

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This paper presents a study on identifying sexism in online texts using various state-of-the-art deep learning models based on BERT. We experimented with different feature sets and model architectures and evaluated their performance using precision, recall, F1 score, and accuracy metrics. We also explored the use of pseudolabeling technique to improve model performance. Our experiments show that the best-performing models were based on BERT, and their multilingual model achieved an F1 score of 0.83. Furthermore, the use of pseudolabeling significantly improved the performance of the BERT-based models, with the best results achieved using the pseudolabeling technique. Our findings suggest that BERT-based models with pseudolabeling hold great promise for identifying sexism in online texts with high accuracy.

Keywords: large language models, semi-supervised learning, sexism detection, data sparsity

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Authors: Naomi Sakamoto, Eisuke Fukuma, Mika Nashimoto, Yoshitomo Koshida

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Background: Selective localization of the metastatic lymph node with clip and removal of clipped nodes with sentinel lymph node (SLN), known as targeted axillary dissection (TAD), reduced false-negative rates (FNR) of SLN biopsy (SLNB) after neoadjuvant chemotherapy (NAC). For the patients who achieved nodal pathologic complete response (pCR), accurate staging of axilla by TAD lead to omit axillary lymph node dissection (ALND), decreasing postoperative arm morbidity without a negative effect on overall survival. This study aimed to investigate the ultrasound (US) identification rate and success removal rate of two kinds of ultrasound-visible clips placed in metastatic lymph nodes during TAD procedure. Methods: This prospective study was conducted using patients with clinically T1-3, N1, 2, M0 breast cancer undergoing NAC followed by surgery. A US-visible clip was placed in the suspicious lymph node under US guidance before neoadjuvant chemotherapy. Before surgery, US examination was performed to evaluate the detection rate of clipped node. During the surgery, the clipped node was removed using several localization techniques, including hook-wire localization, dye-injection, or fluorescence technique, followed by a dual-technique SLNB and resection of palpable nodes if present. For the fluorescence technique, after injection of 0.1-0.2 mL of indocyanine green dye (ICG) into the clipped node, ICG fluorescent imaging was performed using the Photodynamic Eye infrared camera (Hamamatsu Photonics k. k., Shizuoka, Japan). For the dye injection method, 0.1-0.2 mL of pyoktanin blue dye was injected into the clipped node. Results: A total of 29 patients were enrolled. Hydromark™ breast biopsy site markers (Hydromark, T3 shape; Devicor Medical Japan, Tokyo, Japan) was used in 15patients, whereas a UltraCor™ Twirl™ breast marker (Twirl; C.R. Bard, Inc, NJ, USA) was placed in 14 patients. US identified the clipped node marked with the UltraCore Twirl in 100% (14/14) and with the Hydromark in 93.3% (14/15, p = ns). Success removal of clipped node marked with the UltraCore Twirl was achieved in 100% (14/14), whereas the node marked with the Hydromark was removed in 80% (12/15) (p = ns). Conclusions: The ultrasound identification rate differed between the two types of ultrasound-visible clips, which also affected the success removal rate of clipped nodes. Labelling the positive node with a US-highly-visible clip allowed successful TAD.

Keywords: breast cancer, neoadjuvant chemotherapy, targeted axillary dissection, breast tissue marker, clip

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Authors: M. C. Arcuri, L. Gai, F. Ielasi

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Italian Central Guarantee Fund (CGF) has the purpose to facilitate Small and Medium-sized Enterprises (SMEs)’ access to credit. The aim of the paper is to study the evaluation method adopted by the CGF with regard to SMEs requiring its intervention. This is even more important in the light of the recent CGF reform. We analyse an initial sample of more than 500.000 guarantees from 2012 to 2018. We distinguish between a counter-guarantee delivered to a mutual guarantee institution and a guarantee directly delivered to a bank. We investigate the impact of variables related to the operations and the SMEs on Altman Z’’-score and the score consistent with CGF methodology. We verify that the type of intervention affects the scores and the initial condition changes with the new assessment criterions. 

Keywords: banks, default risk, Italian guarantee fund, mutual guarantee institutions

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Authors: Radhika Ranjan Roy

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Deployment of machine learning (ML)/deep learning (DL) algorithms for cyberattack detection in operational communications networks (wireless and/or wire-line) is being delayed because of low-performance parameters (e.g., recall, precision, and f₁-score). If datasets become imbalanced, which is the usual case for communications networks, the performance tends to become worse. Complexities in handling reducing dimensions of the feature sets for increasing performance are also a huge problem. Mahalanobis algorithms have been widely applied in scientific research because Mahalanobis distance metric learning is a successful framework. In this paper, we have investigated the Mahalanobis binary classifier algorithm for increasing cyberattack detection performance over communications networks as a proof of concept. We have also found that high-dimensional information in intermediate features that are not utilized as much for classification tasks in ML/DL algorithms are the main contributor to the state-of-the-art of improved performance of the Mahalanobis method, even for imbalanced and sparse datasets. With no feature reduction, MD offers uniform results for precision, recall, and f₁-score for unbalanced and sparse NSL-KDD datasets.

Keywords: Mahalanobis distance, machine learning, deep learning, NS-KDD, local intrinsic dimensionality, chi-square, positive semi-definite, area under the curve

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Authors: Beng Yew Low, Cher Liang Cha, Cheng Yong Teoh

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Due to a lack of continual assessment or grade related data, identifying first-year engineering students in a polytechnic education at risk of failing is challenging. Our experience over the years tells us that there is no strong correlation between having good entry grades in Mathematics and the Sciences and excelling in hardcore engineering subjects. Hence, identifying students at risk of failure cannot be on the basis of entry grades in Mathematics and the Sciences alone. These factors compound the difficulty of early identification and intervention. This paper describes the development of a predictive analytics model in the early detection of students at risk of failing and evaluates its effectiveness. Data from continual assessments conducted in term one, supplemented by data of student psychological profiles such as interests and study habits, were used. Three classification techniques, namely Logistic Regression, K Nearest Neighbour, and Random Forest, were used in our predictive model. Based on our findings, Random Forest was determined to be the strongest predictor with an Area Under the Curve (AUC) value of 0.994. Correspondingly, the Accuracy, Precision, Recall, and F-Score were also highest among these three classifiers. Using this Random Forest Classification technique, students at risk of failure could be identified at the end of term one. They could then be assigned to a Learning Support Programme at the beginning of term two. This paper gathers the results of our findings. It also proposes further improvements that can be made to the model.

Keywords: continual assessment, predictive analytics, random forest, student psychological profile

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Authors: Mohammed El-Arbi Khalfallah, Mohamed Lakhdar Hadji

Abstract:

Managing and controlling risk is a topic research in the world of finance. Before a risky situation, the stakeholders need to do comparison according to the positions and actions, and financial institutions must take measures of a particular market risk and credit. In this work, we study a model of risk measure in finance: Value at Risk (VaR), which is a new tool for measuring an entity's exposure risk. We explain the concept of value at risk, your average, tail, and describe the three methods for computing: Parametric method, Historical method, and numerical method of Monte Carlo. Finally, we briefly describe advantages and disadvantages of the three methods for computing value at risk.

Keywords: average value at risk, conditional value at risk, tail value at risk, value at risk

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Authors: Ruqayya Naheed Khan, Awais Amjad Malik, Awais Naeem, Amina Khan, Asad Parvaiz

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Introduction: Axillary nodal status in breast cancer patients is a paramount prognosticator, next to primary tumor size and grade. It has been well established that patients with negative sentinel lymph node biopsy can safely avoid axillary lymph node dissection. A positive sentinel lymph node has traditionally required subsequent axillary dissection. According to ACOSOG Z11 trial, patients who underwent axillary dissection with 3 or more positive sentinel nodes or opted for observation in case of negative sentinel lymph node, did not find any difference in Overall Survival (OS) and Disease Free Survival (DFS). The Z11 trial included patients who underwent breast conserving surgery and excluded patients with mastectomies. The purpose of this study is to determine whether Z0011 can be applied to mastectomy patients as well in 1-3 positive sentinel lymph nodes and avoid unnecessary ALND. Methods: A retrospective review was conducted at Shaukat Khanam Memorial Cancer Hospital Pakistan from Jan 2015 to Dec 2017 including patients who were treated for invasive breast cancer and required upfront mastectomy. They were clinically node negative, so sentinel lymph node biopsy was performed. Patients underwent ALND with positive sentinel lymph node. A total of 156 breast cancer patients with mastectomies were reviewed. Results: 95% of the patients were female while 3% were male. Average age was 44 years. There was no difference in race, comorbidities, histology, T stage, N stage, and overall stage, use of adjuvant chemotherapy and radiation therapy. 64 patients underwent ALND for positive lymph node while 92 patients were spared of axillary dissection due to negative sentinel lymph node biopsy. Out of 64 patients, 38 patients (59%) had only 1 lymph node positive which was the sentinel node. 18 patients (28%) had 2 lymph nodes positive including the sentinel node while only 8 patients (13%) had 3 or more positive nodes. Conclusion: Keeping in mind the complications related to ALND, above results clearly show that ALND could have been avoided in 87% of patients in the setting of adjuvant radiation, possibly avoiding the morbidity associated with axillary lymphadenectomy although a prospective randomized trial needs to confirm these results.

Keywords: mastectomy, sentinel lymph node biopsy, axillary lymph node dissection, breast cancer

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Authors: Kenan Morani, Esra Kaya Ayana

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This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.

Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation

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Authors: Tharwat Ibrahim Rushdy, Warda Youssef Mohammed Morsy, Hanaa Ali Ahmed Elfeky

Abstract:

Background: Intra-aortic balloon pump (IABP) is the first and the most commonly used mechanical circulatory support for patients with acute coronary syndromes and cardiogenic shock. Therefore, critical care nurses not only have to know how to monitor and operate the IABP, but also to provide interventions for preventing possible complications. Aim of the study: To assess nurses' knowledge and practices regarding care of patients connected to IABP at the ICUs of Cairo University Hospitals. Research design: A descriptive exploratory design was utilized. Sample: Convenience samples of 40 nurses were included in the current study. Setting: This study was carried out at the Intensive Care Units of Cairo University Hospitals. Tools of data collection: Three tools were developed, tested for clarity, and feasibility: a- Nurses' personal background sheet, b- IABP nurses' knowledge self-administered questionnaire, and c- IABP Nurses' practice observational checklist. Results: The majority of the studied sample had unsatisfactory knowledge and practice level (88% & 95%) respectively with a mean of 9.45+2.94 and 30.5+8.7, respectively. Unsatisfactory knowledge was found regarding description and physiological effects, nursing care, indications, contraindications, complications, weaning, and removal of IABP in percentage of 95%, 90%, 72.5%, and 57.5%, respectively, with a mean total knowledge score of 9.45 +2.94. In addition, unsatisfactory practice was found regarding about preparation and initiation of IABP therapy, nursing practice during therapy, weaning, and removal of IABP in percentages of (97.5%, 97.5%, and 90%), respectively. Finally, knowledge level was found to differ significantly in relation to gender (t = 2.46 at P ≤ 0.018). However, gender didn't play a role in relation to practice (t = 0.086 at P≤ 0.932). Conclusion: In spite of having vital role in assessment and management of critically ill patients, critical care nurses in the current study had in general unsatisfactory knowledge and practice regarding care of patients connected to IABP. Recommendation: updating knowledge and practice of ICU nurses through carrying out continuing educational programs about IABP; strict observation of nurses' practice when caring for patients connected to IABP and provision of guidance to correct of poor practices and replication of this study on larger probability sample selected from different geographical locations.

Keywords: knowledge, practice, intra-aortic balloon pump (IABP), ICU nurses, intensive care unit (ICU), introduction

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Authors: Jennifer Reese, Josh Biber, Howard Weeks, Rachel Hess

Abstract:

Aim: The Edinburgh Postnatal Depression Screen (EPDS) is a mental health screening for pregnant women that has been widely used over the last 30 years. This screen is typically given in clinic on paper to patients throughout pregnancy and postpartum. The screen helps identify patients who may be at risk for pregnancy related depression or postpartum depression. In early 2016, University of Utah Health implemented an electronic version of the EPDS as well as the PROMIS Depression v1.0 instrument for all pregnant and postpartum patients. We asked patients both instruments to understand coverage of patients identified as at risk for each instrument. Methods: The EPDS is currently administered as part of our PRO template for pregnant and postpartum women. We also administer the PROMIS Depression as part of a standard PRO assessment to all patients. Patients are asked to complete an assessment no more often than every eight weeks. PRO assessments are either completed at home or in clinic with a tablet computer. Patients with a PROMIS score of ≥ 65 or a EPDS score of ≥ 10 were identified as at risk for depression Results: From April 2016 to April 2017, 1,330 unique patients were screened at University of Utah Health in OBGYN clinics with both the EPDS and PROMIS depression instrument on the same day. There were 28 (2.1%) patients were identified as at risk for depression using the PROMIS depression screen, while 262 (19.7%) patients were identified as at risk for postpartum depression using the EPDS screen. Overall, 27 (2%) patients were identified as at risk on both instruments. Conclusion: The EPDS identified a higher percent (19.7%) of patients at risk for depression when compared to the PROMIS depression (2.1%). Ninety-six percent of patients who screened positive on the PROMIS depression screen also screened positive on the EPDS screen. Mental health is an important component to a patient’s overall wellbeing. We want to ensure all patients, particularly pregnant or post-partum women, receive screening and treatment when necessary. A combination of screenings may be necessary to provide the overall best care for patients and to identify the highest percentage of patients at risk.

Keywords: patient reported outcomes, mental health, maternal, depression

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