Search results for: probability-driven health outcome predictions

Authors: Rajnish Gourh, Nitesh Sharma, Nikhil Patil

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Introduction: Adequate nutrition is essential for improving pregnancy and its outcomes. Failure to comply with the required daily intake of nutrition can lead to complications threatening both mother and child survival. Objectives: To provide access to nutritious diet to mothers in antenatal and post-natal stage for supporting a healthy progressive pregnancy, positive delivery outcome, and lactation and to promote regular consumption of the foods by the mothers and help overcome the dietary gap by nutrition education during pregnancy time. Methodology: Total of 95 ANC mothers were identified from Malvada PHC area, in Palghar district of Maharashtra. This short-term cohort intended for the proposed supplementation and education was targeted for follow-up until birth and six-months of post-natal period. In month of May 2016 to June 2017. Results: Average weight of women was observed 40.01kg, (SD- 5.024) at registered for ANC at Centre in the first month. In same month, average Haemoglobin level of women was observed 9.13gm/dl. Average increase in weight of women during pregnancy in month October 2016 was 48.83kg. Birth weight of 14 babies was less than 2 kgs. 13 babies with birth weight in range of 2.1kgs to 2.4kgs. 68 babies with birth weight in range of 2.5kg to 3kg and above. Conclusion: Importance of consumption of food, improving levels of nutrient intake and outcome of delivery was excellent.

Keywords: delivery status, nutrition, pregnancy, education

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Authors: Mohamed Abo El Nasr, Mohamed Shoeib, Abdelhamid Abdelkhalik, Amro Serag

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Background: Early assessment of severity of chest trauma, either blunt or penetrating is of critical importance in prediction of patient outcome. Different trauma scoring systems are widely available and are based on anatomical or physiological parameters to expect patient morbidity or mortality. Up till now, there is no ideal, universally accepted trauma score that could be applied in all trauma centers and is suitable for assessment of severity of chest trauma patients. Aim: Our aim was to compare various trauma scoring systems regarding their predictability of morbidity and mortality in chest trauma patients. Patients and Methods: This study was a prospective study including 400 patients with chest trauma who were managed at Tanta University Emergency Hospital, Egypt during a period of 2 years (March 2014 until March 2016). The patients were divided into 2 groups according to the mode of trauma: blunt or penetrating. The collected data included age, sex, hemodynamic status on admission, intrathoracic injuries, and associated extra-thoracic injuries. The patients outcome including mortality, need of thoracotomy, need for ICU admission, need for mechanical ventilation, length of hospital stay and the development of acute respiratory distress syndrome were also recorded. The relevant data were used to calculate the following trauma scores: 1. Anatomical scores including abbreviated injury scale (AIS), Injury severity score (ISS), New injury severity score (NISS) and Chest wall injury scale (CWIS). 2. Physiological scores including revised trauma score (RTS), Acute physiology and chronic health evaluation II (APACHE II) score. 3. Combined score including Trauma and injury severity score (TRISS ) and 4. Chest-Specific score Thoracic trauma severity score (TTSS). All these scores were analyzed statistically to detect their sensitivity, specificity and compared regarding their predictive power of mortality and morbidity in blunt and penetrating chest trauma patients. Results: The incidence of mortality was 3.75% (15/400). Eleven patients (11/230) died in blunt chest trauma group, while (4/170) patients died in penetrating trauma group. The mortality rate increased more than three folds to reach 13% (13/100) in patients with severe chest trauma (ISS of >16). The physiological scores APACHE II and RTS had the highest predictive value for mortality in both blunt and penetrating chest injuries. The physiological score APACHE II followed by the combined score TRISS were more predictive for intensive care admission in penetrating injuries while RTS was more predictive in blunt trauma. Also, RTS had a higher predictive value for expectation of need for mechanical ventilation followed by the combined score TRISS. APACHE II score was more predictive for the need of thoracotomy in penetrating injuries and the Chest-Specific score TTSS was higher in blunt injuries. The anatomical score ISS and TTSS score were more predictive for prolonged hospital stay in penetrating and blunt injuries respectively. Conclusion: Trauma scores including physiological parameters have a higher predictive power for mortality in both blunt and penetrating chest trauma. They are more suitable for assessment of injury severity and prediction of patients outcome.

Keywords: chest trauma, trauma scores, blunt injuries, penetrating injuries

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Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: Redouane Larbi Boufeniza, Jing-Jia Luo

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This study assesses the suitability of deep learning (DL) for downscaling sea surface temperature (SST) over the Mediterranean Sea in the context of seasonal forecasting. We design a set of experiments that compare different DL configurations and deploy the best-performing architecture to downscale one-month lead forecasts of June–September (JJAS) SST from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for the period of 1982–2020. We have also introduced predictors over a larger area to include information about the main large-scale circulations that drive SST over the Mediterranean Sea region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results showed that the convolutional neural network (CNN)-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme SST spatial patterns. Besides, the CNN-based downscaling yields a much more accurate forecast of extreme SST and spell indicators and reduces the significant relevant biases exhibited by the raw model predictions. Moreover, our results show that the CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of the Mediterranean Sea. The results demonstrate the potential usefulness of CNN in downscaling seasonal SST predictions over the Mediterranean Sea, particularly in providing improved forecast products.

Keywords: Mediterranean Sea, sea surface temperature, seasonal forecasting, downscaling, deep learning

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Authors: Sarika Gupta, Harshika Khanna, Ajay K Verma, Surya Kant

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Background: Drug-resistant tuberculosis (DR-TB) is a growing health challenge to global TB control efforts. Pediatric DR-TB is one of the neglected infectious diseases. In our previously published report, we have notified an increased prevalence of DR-TB in the pediatric population at a tertiary health care centre in North India which was estimated as 17.4%, 15.1%, 18.4%, and 20.3% in (%) in the year 2018, 2019, 2020, and 2021. Limited evidence exists about a pattern of drug resistance, side effect profile and programmatic outcomes of Paediatric DR-TB treatment. Therefore, this study was done to find out the pattern of resistance, side effect profile and treatment outcome. Methodology: This was a prospective cohort study conducted at the nodal drug-resistant tuberculosis centre of a tertiary care hospital in North India from January 2021 to December 2022. Subjects included children aged between 0-18 years of age with a diagnosis of DR-TB, on the basis of GeneXpert (rifampicin [RIF] resistance detected), line probe assay and drug sensitivity testing (DST) of M. tuberculosis (MTB) grown on a culture of body fluids. Children were classified as monoresistant TB, polyresistant TB (resistance to more than 1 first-line anti-TB drug, other than both INH and RIF), MDR-TB, pre-XDR-TB and XDR-TB, as per the WHO classification. All the patients were prescribed DR TB treatment as per the standard guidelines, either shorter oral DR-TB regimen or a longer all-oral MDR/XDR-TB regimen (age below five years needed modification). All the patients were followed up for side effects of treatment once per month. The patient outcomes were categorized as good outcomes if they had completed treatment and cured or were improving during the course of treatment, while bad outcomes included death or not improving during the course of treatment. Results: Of the 50 pediatric patients included in the study, 34 were females (66.7%) and 16 were male (31.4%). Around 33 patients (64.7%) were suffering from pulmonary TB, while 17 (33.3%) were suffering from extrapulmonary TB. The proportions of monoresistant TB, polyresistant TB, MDR-TB, pre-XDR-TB and XDR-TB were 2.0%, 0%, 50.0%, 30.0% and 18.0%, respectively. Good outcome was reported in 40 patients (80.0%). The 10 bad outcomes were 7 deaths (14%) and 3 (6.0%) children who were not improving. Adverse events (single or multiple) were reported in all the patients, most of which were mild in nature. The most common adverse events were metallic taste 16(31.4%), rash and allergic reaction 15(29.4%), nausea and vomiting 13(26.0%), arthralgia 11 (21.6%) and alopecia 11 (21.6%). Serious adverse event of QTc prolongation was reported in 4 cases (7.8%), but neither arrhythmias nor symptomatic cardiac side effects occurred. Vestibular toxicity was reported in 2(3.9%), and psychotic symptoms in 4(7.8%). Hepatotoxicity, hypothyroidism, peripheral neuropathy, gynaecomastia, and amenorrhea were reported in 2 (4.0%), 4 (7.8%), 2 (3.9%), 1(2.0%), and 2 (3.9%) respectively. None of the drugs needed to be withdrawn due to uncontrolled adverse events. Conclusion: Paediatric DR TB treatment achieved favorable outcomes in a large proportion of children. DR TB treatment regimen drugs were overall well tolerated in this cohort.

Keywords: pediatric, drug-resistant, tuberculosis, adverse events, treatment

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Authors: Rekha S., S. J. Nalini, S. Bhuvana, S. Kanmani, Vidhya Venugopal

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Introduction: Pregnant women's occupational heat exposure has been linked to foetal abnormalities and pregnancy complications. The presence of heat in the workplace is expected to lead to Adverse Pregnancy Outcomes (APO), especially in tropical countries where temperatures are rising and workplace cooling interventions are minimal. For effective interventions, in-depth understanding and evidence about occupational heat stress and APO are required. Methodology: Approximately 800 pregnant women in and around Chennai who were employed in jobs requiring moderate to hard labour participated in the cohort research. During the study period (2014-2019), environmental heat exposures were measured using a Questemp WBGT monitor, and heat strain markers, such as Core Body Temperature (CBT) and Urine Specific Gravity (USG), were evaluated using an Infrared Thermometer and a refractometer, respectively. Using a valid HOTHAPS questionnaire, self-reported health symptoms were collected. In addition, a postpartum follow-up with the mothers was done to collect APO-related data. Major findings of the study: Approximately 47.3% of pregnant workers have workplace WBGTs over the safe manual work threshold value for moderate/heavy employment (Average WBGT of 26.6°C±1.0°C). About 12.5% of the workers had CBT levels above the usual range, and 24.8% had USG levels above 1.020, both of which suggested mild dehydration. Miscarriages (3%), stillbirths/preterm births (3.5%), and low birth weights (8.8%) were the most common unfavorable outcomes among pregnant employees. In addition, WBGT exposures above TLVs during all trimesters were associated with a 2.3-fold increased risk of adverse fetal/maternal outcomes (95% CI: 1.4-3.8), after adjusting for potential confounding variables including age, education, socioeconomic status, abortion history, stillbirth, preterm, LBW, and BMI. The study determined that WBGTs in the workplace had direct short- and long-term effects on the health of both the mother and the foetus. Despite the study's limited scope, the findings provided valuable insights and highlighted the need for future comprehensive cohort studies and extensive data in order to establish effective policies to protect vulnerable pregnant women from the dangers of heat stress and to promote reproductive health.

Keywords: adverse outcome, heat stress, interventions, physiological strain, pregnant women

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Authors: Bundit Pungnirund

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The purposes of this research were to develop and to monitor the antecedent factors which directly affected the success rate of new product development. This was a case study of the leather industry in Bangkok, Thailand. A total of 350 leather factories were used as a sample group. The findings revealed that the new product development model was harmonized with the empirical data at the acceptable level, the statistic values are: x^2=6.45, df= 7, p-value = .48856; RMSEA = .000; RMR = .0029; AGFI = .98; GFI = 1.00. The independent variable that directly influenced the dependent variable at the highest level was marketing outcome which had a influence coefficient at 0.32 and the independent variables that indirectly influenced the dependent variables at the highest level was a clear organization policy which had a influence coefficient at 0.17, whereas, all independent variables can predict the model at 48 percent.

Keywords: antecedent, new product development, leather industry, Thailand

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Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

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Accurate estimation of RUL provides a basis for effective predictive maintenance, reducing unexpected downtime for industrial equipment. However, while models such as the Random Forest have effective predictive capabilities, they are the so-called ‘black box’ models, where interpretability is at a threshold to make critical diagnostic decisions involved in industries related to aviation. The purpose of this work is to present a prognostic framework that embeds Explainable Artificial Intelligence (XAI) techniques in order to provide essential transparency in Machine Learning methods' decision-making mechanisms based on sensor data, with the objective of procuring actionable insights for the aviation industry. Sensor readings have been gathered from critical equipment such as turbofan jet engine and landing gear, and the prediction of the RUL is done by a Random Forest model. It involves steps such as data gathering, feature engineering, model training, and evaluation. These critical components’ datasets are independently trained and evaluated by the models. While suitable predictions are served, their performance metrics are reasonably good; such complex models, however obscure reasoning for the predictions made by them and may even undermine the confidence of the decision-maker or the maintenance teams. This is followed by global explanations using SHAP and local explanations using LIME in the second phase to bridge the gap in reliability within industrial contexts. These tools analyze model decisions, highlighting feature importance and explaining how each input variable affects the output. This dual approach offers a general comprehension of the overall model behavior and detailed insight into specific predictions. The proposed framework, in its third component, incorporates the techniques of causal analysis in the form of Granger causality tests in order to move beyond correlation toward causation. This will not only allow the model to predict failures but also present reasons, from the key sensor features linked to possible failure mechanisms to relevant personnel. The causality between sensor behaviors and equipment failures creates much value for maintenance teams due to better root cause identification and effective preventive measures. This step contributes to the system being more explainable. Surrogate Several simple models, including Decision Trees and Linear Models, can be used in yet another stage to approximately represent the complex Random Forest model. These simpler models act as backups, replicating important jobs of the original model's behavior. If the feature explanations obtained from the surrogate model are cross-validated with the primary model, the insights derived would be more reliable and provide an intuitive sense of how the input variables affect the predictions. We then create an iterative explainable feedback loop, where the knowledge learned from the explainability methods feeds back into the training of the models. This feeds into a cycle of continuous improvement both in model accuracy and interpretability over time. By systematically integrating new findings, the model is expected to adapt to changed conditions and further develop its prognosis capability. These components are then presented to the decision-makers through the development of a fully transparent condition monitoring and alert system. The system provides a holistic tool for maintenance operations by leveraging RUL predictions, feature importance scores, persistent sensor threshold values, and autonomous alert mechanisms. Since the system will provide explanations for the predictions given, along with active alerts, the maintenance personnel can make informed decisions on their end regarding correct interventions to extend the life of the critical machinery.

Keywords: predictive maintenance, explainable artificial intelligence, prognostic, RUL, machine learning, turbofan engines, C-MAPSS dataset

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Authors: Lauren McGillivray, Michelle Torok, Alison Calear

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Suicide is the leading cause of death for Australians aged 15-24 years, with rates increasing over the past decade. As young people can be particularly vulnerable to mental health problems and suicidal behavior, they are an essential and obvious target for suicide prevention efforts. This study investigates the effectiveness of the universal mental health promotion and suicide prevention program, Youth Aware of Mental Health (YAM), to reduce suicidal ideation and attempts and increase help-seeking in young people. This trial took place in Australian schools across four regions in New South Wales that form part of LifeSpan, a larger multilevel suicide prevention research trial. The YAM program was delivered to Year 9 students in up to 78 schools over two years (from January 2017 to December 2019). All schools were invited to participate in YAM's evaluation, which included completing a student questionnaire at three time-points: baseline, 3-month post-intervention, and 6-month follow-up. The primary outcome is suicidal ideation severity. Secondary outcomes are new reports of suicide attempts, stigma towards suicide, knowledge about suicide, help-seeking intentions and behaviors, and depressive symptoms. Results from pre-post and follow-up data will be presented. These research findings are promising and will contribute to the evidence-based for YAM and suicide prevention programs in Australian schools. These findings are also expected to promote YAM's value and sustainability to be more widely delivered in Australian secondary schools.

Keywords: adolescent mental health, suicidal ideation, suicide prevention, universal program

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Authors: Estelle Abrahams, Tania Pretorius

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A joint media statement by the South African Reserve Bank, the Banking Association of South Africa, the Financial Sector Conduct Authority, and the Payments Association of South Africa was recently published, stating that the receipt or acceptance of cheques will terminate effectively on 31 December 2020. All stakeholders are urged to cease accepting or issuing cheques as a payment method. The purpose of the study is to examine the effect that the discontinuation of the usage of cheques has on bank reconciliations for the subject: economic and management sciences. A literature study was performed to gain insight into the bank reconciliation process to be able to draw conclusions on the outcome of the discontinuation of cheques on the bank reconciliation. The study found that the teaching of the bank reconciliation process will change to introduce new replacement source documents for digital payments, and this impacts the teaching of reconciling differences.

Keywords: bank reconciliation, internal control, accounting education, source documents

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Authors: Vibha Kriti

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Background: Polycystic ovary syndrome (PCOS) is a common endocrine disorder generally found in reproductive women. It is associated with significant reproductive, metabolic, cosmetic, and psychological consequences. Objective: There is a high prevalence of PCOS found among reproductive-age women, therefore, the major objective of the present study is to identify the illness perception of PCOS women and to explore the relationship between illness perception and health-related quality of life (HRQoL). Material and Method: A cross-sectional study was conducted in a university tertiary-care center, Sir Sunder Lal Hospital, Banaras Hindu University (B.H.U). Tools used for data collection were self-structured, which included socio-demographic status, illness perception questionnaire (revised version), and short-form 36 for assessing illness perception and health-related quality of life, respectively. Statistical analysis was done by SPSS version ‘24’. Results: The results of correlation analyses indicated that there is a strong relationship between strong illness perception and HRQoL. Stepwise regression indicated that illness identity, long illness duration, and severe consequences were associated with the worse outcome on emotional functioning and on social functioning. A high score on the controllability of the disease and seeking social support was significantly related to better functioning. Conclusion: Illness perception is an important factor in self-care behaviors in PCOS females and has a strong association with health-related quality of life and has a profound effect on it.

Keywords: polycystic ovary syndrome, illness perception, quality of life, young females, mental health

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Authors: Kevin Syam, Devendra K. Chauhan, Mandeep Singh Dhillon

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Background: The posterior horn of medial meniscus (PHMM) is a secondary stabilizer against anterior translation of tibia. Cadaveric studies have revealed increased strain on the ACL graft and greater instrumented laxity in Posterior horn deficient knees. Clinical studies have shown higher prevalence of radiological OA after ACL reconstruction combined with menisectomy. However, functional outcomes in ACL reconstructed knee in the absence of Posterior horn is less discussed, and specific role of posterior horn is ill-documented. This study evaluated functional and radiological outcomes in posterior horn preserved and posterior horn sacrificed ACL reconstructed knees. Materials: Of the 457 patients who had ACL reconstruction done over a 6 year period, 77 cases with minimum follow up of 18 months were included in the study after strict exclusion criteria (associated lateral meniscus injury, other ligamentous injuries, significant cartilage degeneration, repeat injury and contralateral knee injuries were excluded). 41 patients with intact menisci were compared with 36 patients with absent posterior horn of medial meniscus. Radiological and clinical tests for instability were conducted, and knees were evaluated using subjective International Knee Documentation Committee (IKDC) score and the Orthopadische Arbeitsgruppe Knie score (OAK). Results: We found a trend towards significantly better overall outcome (OAK) in cases with intact PHMM at average follow-up of 43.03 months (p value 0.082). Cases with intact PHMM had significantly better objective stability (p value 0.004). No significant differences were noted in the subjective IKDC score (p value 0.526) and the functional OAK outcome (category D) (p value 0.363). More cases with absent posterior horn had evidence of radiological OA (p value 0.022) even at mid-term follow-up. Conclusion: Even though the overall OAK and subjective IKDC scores did not show significant difference between the two subsets, the poorer outcomes in terms of objective stability and radiological OA noted in the absence of PHMM, indicates the importance of preserving this important part of the meniscus.

Keywords: ACL, functional outcome, knee, posterior of medial meniscus

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Authors: Nji Clement Bang, Rosemary Shafack M., Kum Henry Asei, Yaro Loveline Y

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Scholars perceive learner-centered teaching-learning reform as roles and resources in teacher education (TE) and professional outcome with transformative learning (TL) continuum dimensions. But, teaching-learning reform is fast proliferating amidst debilitating stakeholder systemic dichotomies, resources, commitment, resistance and poor quality outcome that necessitate stronger TE and professional continuums. Scholars keep seeking greater understanding of themes in teaching-learning reform, TE and professional outcome as continuums and how policymakers, student-teachers, teacher trainers and local communities concerned with initial TE can promote continuous holistic quality performance. To sustain the debate continuum and answer the overarching question, we use mixed-methods research-design with diverse literature and 409 sample-data. Onset text, interview and questionnaire analyses reveal debilitating teaching-learning reform in TE continuums that need TL revival. Follow-up focus group discussion and teaching considering TL insights reinforce holistic teaching-learning in TE. Therefore, significant increase in diverse prior-experience articulation1; critical reflection-discourse engagement2; teaching-practice interaction3; complex-activity constrain control4 and formative outcome- reintegration5 reinforce teaching-learning in learning-to-teach role-resource pathways and outcomes. Themes reiterate complex teaching-learning in TE programs that suits TL journeys and student-teachers and students cum teachers, workers/citizens become akin, transformative-learners who evolve personal and collective roles-resources towards holistic-lifelong-learning outcomes. The article could assist debate about quality teaching-learning reform through TL dimensions as TE and professional role-resource continuums.

Keywords: transformative learning perspectives, teacher education, initial teacher education, learner-centered pedagogical reform, life-long learning

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Authors: Mohammed Seid, Aklilu Azazh, Fikre Enquselassie, Engida Yisma

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Background: Road traffic injuries are the eighth leading cause of death globally, and the leading cause of death for young people. More than a million people die each year on the world’s roads, and the risk of dying as a result of a road traffic injury is highest in the Africa. Methods: A prospective hospital-based study was undertaken to assess injury characteristics and outcome of road traffic accident among victims at Adult Emergency Department of Tikur Anbesa specialized hospital, Addis Ababa, Ethiopia. A structured pre-tested questionnaire was used to gather the required data. The collected data were analyzed using SPSS version 16.0. Results: A total of 230 road traffic accident victims were studied. The majority of the study subjects were men 165 (71.7%) and the male/female ratio was 2.6:1. The victims’ ages ranged from 14 to 80 years with the mean and standard deviations of 32.15 and ± 14.38 years respectively. Daily laborers (95 (41.3%)) and students (28 (12.2%)) were the majority of road traffic accident victims. Long-distance travelling Minibus (16.5%) was responsible for the majority of road traffic crash followed by followed by Taxi (14.8%) and pedestrians (62.6%) accounted for the majority of road traffic accident. Head (50.4%) and musculoskeletal (extremities) (47.0%) were the most common body region injured. Fractures (78.0%) and open wounds (56.5%) were the most common type of injuries sustained. Treatment of fracture was the most common procedure performed in 57.7 % of the victims. The overall length of hospital stay (LOS) ranged from 1 day to 61 days with mean (± standard deviation) of 7.12 ± 10.5 days and the mortality rate was 7.4 %. A significant higher proportion of victims aged 14-55 years were had less likelihood of death compared to those victims aged more than 55 years of age [Adjusted OR = 0.1 (95% CI: 0.01, 0.82)]. Conclusions: This study showed diverse injury characteristics and high morbidity and mortality among the victims attending Adult Emergency Department of Tikur Anbesa specialized hospital, Addis Ababa, Ethiopia. The findings reflect that road traffic accident is a major public health problem. Urgent road traffic accident preventive measures and prompt treatment of the victims are warranted in order to reduce morbidity and mortality among the victims.

Keywords: road traffic accident, injury characteristics, outcome, Tikur Anbesa specialized hospital, Addis Ababa, Ethiopia

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Authors: Ferissa B. Ablola

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The two learning theories which were evidently used in medical education include cognitive and sociocultural frameworks. The interplay of different learning theories in education is vital since most of the existing theories have specific focus of development. In addition, a certain theory is best fit with a particular learning outcome and audience profile. The application of learning theories is education is said to be dynamic and becomes more complex with increasing educational level. This systematic review aims to describe the possible shift from integration of cognitive learning theory to employment of socio-cultural approach in medical and health-allied education over the years among students, educators and the learning institution through systematic review following the PRISMA guidelines. In addition, the changes in teaching modality and individual acceptance of the shift of learning framework among cognitive constructivist and social constructivist will also be documented. This present review may serve as baseline information on the connection of two widely used theories in medical education in different year levels. Further, this study emphasizes the significance of the alignment of different learning theories and combination of insights from several educational frameworks, would permit the creation of a teaching/learning design with real theoretical depth. A more inclusive systematic review is necessary to involve more related studies, and exploration of interaction among other learning theories in health and other fields of study is encouraged.

Keywords: learning theory, cognitive, sociocultural, medical education

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Authors: Soheila Zhaeentan, Anders Von Heijne, Elisabet Hagert, André Stark, Björn Salomonsson

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Recommended treatment for traumatic rotator cuff tear (TRCT) is surgery within a few weeks after injury if the diagnosis is made early, especially if a functional impairment of the shoulder exists. This may lead to the assumption that a poor outcome then can be expected in delayed surgical treatment, when the patient is diagnosed at a later stage. The aim of this study was to investigate if a surgical repair later than three months after injury may result in successful outcomes and patient satisfaction. There is evidence in literature that good results of treatment can be expected up to three months after the injury, but little is known of later treatment with cuff repair. 73 patients (75 shoulders), 58 males/17 females, mean age 59 (range 34-­‐72), who had undergone surgical intervention for TRCT between January 1999 to December 2011 at our clinic, were included in this study. Patients were assessed by MRI investigation, clinical examination, Western Ontario Rotator Cuff index (WORC), Oxford Shoulder Score, Constant-­‐Murley Score, EQ-­‐5D and patient subjective satisfaction at follow-­‐up. The patients treated surgically within three months ( < 12 weeks) after injury (39 cases) were compared with patients treated more than three months ( ≥ 12 weeks) after injury (36 cases). WORC was used as the primary outcome measure and the other variables as secondary. A senior consultant radiologist, blinded to patient category and clinical outcome, evaluated all MRI-­‐images. Rotator cuff integrity, presence of arthritis, fatty degeneration and muscle atrophy was evaluated in all cases. The average follow-­‐up time was 56 months (range 14-­‐149) and the average time from injury to repair was 16 weeks (range 3-­‐104). No statistically significant differences were found for any of the assessed parameters or scores between the two groups. The mean WORC score was 77 (early group, range 25-­‐ 100 and late group, range 27-­‐100) for both groups (p= 0.86), Constant-­‐Murley Score (p= 0.91), Oxford Shoulder Score (p= 0.79), EQ-­‐5D index (p= 0.86). Re-­‐tear frequency was 24% for both groups, and the patients with re-­‐tear reported less satisfaction with outcome. Discussion and conclusion: This study shows that surgical repair of TRCT performed later than three months after injury may result in good functional outcomes and patient satisfaction. However, this does not motivate an intentional delay in surgery when there is an indication for surgical repair as that delay may adversely affect the possibility to perform a repair. Our results show that surgeons may safely consider surgical repair even if a delay in diagnosis has occurred. A retrospective cohort study on 75 shoulders shows good functional result after traumatic rotator cuff tear (TRCT) treated surgically up to one year after the injury.

Keywords: traumatic rotator cuff injury, time to surgery, surgical outcome, retrospective cohort study

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Authors: Rupesh K. Chaudhary, Narinder P. Jain, Rajesh Mahajan, Rajat Manchanda

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Introduction: Delirium is a complex, multifactorial neuropsychiatric syndrome comprising a broad range of cognitive and neurobehavioral symptoms. In critically ill patients, it may develop secondary to multiple predisposing factors. Although it can be transient and irreversible but if left untreated may lead to long term cognitive dysfunction. Early identification and assessment of risk factors usually help in appropriate management of delirium which in turn leads to decreased hospital stay, cost of therapy and mortality. Aim and Objective: Aim of the present study was to estimate the incidence of delirium using a validated scale in medical ICU patients and to determine the associated risk factors and outcomes. Material and Method: A prospective study in an 18-bed medical-intensive care unit (ICU) was undertaken. A total of 357 consecutive patients admitted to ICU for more than 24 hours were assessed. These patients were screened with the help of Confusion Assessment Method for Intensive Care Unit -CAM-ICU, Richmond Agitation and Sedation Scale, Screening Checklist for delirium and APACHE II. Appropiate statistical analysis was done to evaluate the risk factors influencing mortality in delirium. Results: Delirium occurred in 54.6% of 194 patients. Risk of delirium was independently associated with a history of hypertension, diabetes but not with severity of illness APACHE II score. Delirium was linked to longer ICU stay 13.08 ± 9.6 ver 7.07 ± 4.98 days, higher ICU mortality (35.8% % vs. 17.0%). Conclusion: Our study concluded that delirium poses a great risk factor in the outcome of the patient and carries high mortality, so a timely intervention helps in addressing these issues.

Keywords: delirium, risk factors, outcome, intervention

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Authors: Laila Vivas

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Fossil Health is proposed as a value-concept to describe the hegemonic health paradigms that underpin health enactment. Such representation is justified by Foucaldian and related ideas on biopower and biosocialities, calling for the politicization of health and signalling the importance of narratives. This approach, hence, enables contemplating health paradigms as reflexive or co-constitutive of health itself or, in other words, conceiving health as a verb. Fossil health is a symbolic representation, influenced by Andreas Malm’s concept of fossil capitalism, that integrates environment and health as non-dichotomic areas. Fossil Health sustains that current notions of human and non-human health revolve around fossil fuel dependencies. Moreover, addressing disequilibria from established health ideals involves fossil-fixes. Fossil Health, therefore, represents causes and consequences of a health conception that has the agency to contribute to the functioning of a particular structural eco-social model. Moreover, within current capitalist relations, Fossil Health expands its meaning to cover not only fossil implications but also other dominant paradigms of the capitalist system that are (re)produced through health paradigms, such as the burgeoning of technoscience and biomedicalization, privatization of health, expertization of health, or the imposing of standards of uniformity. Overall, Fossil Health is a comprehensive approach to environment and health, where understanding hegemonic health paradigms means understanding our (human-non-human) nature paradigms and the structuring effect these narratives convey.

Keywords: fossil health, environment, paradigm, capitalism

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Authors: Abdullahi Jibril, Rod Burgass, Antonin Chapoy

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Carbon dioxide (CO₂) is widely used in reservoirs to enhance oil and gas production, mixing with natural gas and other impurities in the process. However, hydrate formation frequently hinders the efficiency of CO₂-based enhanced oil recovery, causing pipeline blockages and pressure build-ups. Current hydrate prediction methods are primarily designed for gas mixtures with low CO₂ content and struggle to accurately predict hydrate formation in CO₂-rich streams in equilibrium with salt solutions. Given that oil and gas reservoirs are saline, experimental data for CO₂-rich streams in equilibrium with salt solutions are essential to improve these predictive models. This study investigates the inhibition of hydrate formation in a CO₂-rich gas mixture (CO₂, CH₄, N₂, H₂ at 84.73/15/0.19/0.08 mol.%) using multicomponent salt solutions at concentrations of 2.4 wt.%, 13.65 wt.%, and 27.3 wt.%. The setup, test fluids, methodology, and results for hydrates formed in equilibrium with varying salt solution concentrations are presented. Measurements were conducted using an isochoric pressure-search method at pressures up to 45 MPa. Experimental data were compared with predictions from a thermodynamic model based on the Cubic-Plus-Association equation of state (EoS), while hydrate-forming conditions were modeled using the van der Waals and Platteeuw solid solution theory. Water activity was evaluated based on hydrate suppression temperature to assess consistency in the inhibited systems. Results indicate that hydrate stability is significantly influenced by inhibitor concentration, offering valuable guidelines for the design and operation of pipeline systems involved in offshore gas transport of CO₂-rich streams.

Keywords: CO₂-rich streams, hydrates, monoethylene glycol, phase equilibria

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Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

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Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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Authors: Juzhong Tan, William Kerr

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Conching is one critical procedure in chocolate processing, where special flavors are developed, and smooth mouse feel the texture of the chocolate is developed due to particle size reduction of cocoa mass and other additives. Therefore, determination of the particle size and volatile compounds profile of cocoa bean is important for chocolate manufacturers to ensure the quality of chocolate products. Currently, precise particle size measurement is usually done by laser scattering which is expensive and inaccessible to small/medium size chocolate manufacturers. Also, some other alternatives, such as micrometer and microscopy, can’t provide good measurements and provide little information. Volatile compounds analysis of cocoa during conching, has similar problems due to its high cost and limited accessibility. In this study, a self-made electronic nose system consists of gas sensors (TGS 800 and 2000 series) was inserted to a conching machine and was used to monitoring the volatile compound profile of chocolate during the conching. A model correlated volatile compounds profiles along with factors including the content of cocoa, sugar, and the temperature during the conching to particle size of chocolate particles by genetic programming was established. The model was used to predict the particle size reduction of chocolates with different cocoa mass to sugar ratio (1:2, 1:1, 1.5:1, 2:1) at 8 conching time (15min, 30min, 1h, 1.5h, 2h, 4h, 8h, and 24h). And the predictions were compared to laser scattering measurements of the same chocolate samples. 91.3% of the predictions were within the range of later scatting measurement ± 5% deviation. 99.3% were within the range of later scatting measurement ± 10% deviation.

Keywords: cocoa bean, conching, electronic nose, genetic programming

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Authors: Mayank, Navneet Kaur, Narinder Singh

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The V599 mutations in the BRAF protein are extremely oncogenic, responsible for countless of malignant conditions. Along with wild type, V599E, V599D, and V599R are the important mutated variants of the BRAF proteins. The BRAF inhibitory anticancer agents are continuously developing, and sorafenib is a BRAF inhibitor that is under clinical use. The crystal structure of sorafenib bounded to wild type, and V599 is known, showing a similar interaction pattern in both the case. The mutated 599th residue, in both the case, is also found not interacting directly with the co-crystallized sorafenib molecule. However, the IC50 value of sorafenib was found extremely different in both the case, i.e., 22 nmol/L for wild and 38 nmol/L for V599E protein. Molecular docking study and MMGBSA binding energy results also revealed a significant difference in the binding pattern of sorafenib in both the case. Therefore, to explore the role of distinctively situated 599th residue, we have further conducted comprehensive computational studies. The molecular dynamics simulation, residue interaction network (RIN) analysis, and residue correlation study results revealed the importance of the 599th residue on the therapeutic outcome and overall dynamic of the BRAF protein. Therefore, although the position of 599th residue is very much distinctive from the ligand-binding cavity of BRAF, still it has exceptional control over the overall functional outcome of the protein. The insight obtained here may seem extremely important and guide us while designing ideal BRAF inhibitory anticancer molecules.

Keywords: BRAF, oncogenic, sorafenib, computational studies

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Authors: Nilanchali Singh, Alka Kriplani, Reeta Mahey, Garima Kachhawa

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Objective: Resection of larger uterine septa does improve obstetric performance but whether smaller septa need resection and their impact on obstetric outcome is not clear. We wanted to evaluate the role of septal resection of septa of various sizes in obstetric performance. Methods: This retrospective cohort study comprised of 107 patients with uterine septum. The patients were categorized on the basis of extent of uterine septum into four groups: a) Subsepta (< 1/3rd), b) Septum > 1/3 to ½, c) Septum>1/2 to whole uterine cervix, d) Septum traversing whole of uterine cavity and cervix. Out of these 107 patients, 74 could be contacted telephonically and outcomes recorded. Sensitivity and specificity of investigative modalities were calculated. Results: Infertility was seen in maximum number of cases in complete septa (100%), whereas abortions were seen more commonly, in subsepta (18%). MRI had maximum sensitivity and positive predictive value, followed by hysteron-salpingography. Tubal block, fibroid, endometriosis, pelvic adhesions, ovarian pathologies were seen in some but no definite association of these pathologies was seen with any subgroup of septa. Almost five-year follow-up was recorded in all the subgroups. Significant reduction in infertility was seen in all septal subgroup (p=0.046, 0.032 & 0.05) patients except in subsepta (< 1/3rd uterine cavity) after septum resection. Abortions were significantly reduced (p=0.048) in third subgroup (i.e. septum > ½ to upto internal os) after hysteroscopic septum resection. Take home baby rate was 33% in subsepta and around 50% in the remaining subgroups of septa. Conclusions: Septal resection improves obstetric performance in patients with uterine septa of various sizes. Whether septal resection improves obstetric performance in patients with subsepta or very small septa, is controversial. Larger studies addressing this issue need to be planned.

Keywords: septal resection, obstetric outcome, infertility, septum size

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Authors: Sarah E. Nelson, Casey Weiner, Alexander Sigmon, Jun Hua, Haris I. Sair, Jose I. Suarez, Robert D. Stevens

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Graph-theoretical information from structural connectomes indicated significant connectivity changes and improved acute prognostication in a Random Forest (RF) model in aneurysmal subarachnoid hemorrhage (aSAH), which can lead to significant morbidity and mortality and has traditionally been fraught by poor methods to predict outcome. This study’s hypothesis was that structural connectivity changes occur in canonical brain networks of acute aSAH patients, and that these changes are associated with functional outcome at six months. In a prospective cohort of patients admitted to a single institution for management of acute aSAH, patients underwent diffusion tensor imaging (DTI) as part of a multimodal MRI scan. A weighted undirected structural connectome was created of each patient’s images using Constant Solid Angle (CSA) tractography, with 176 regions of interest (ROIs) defined by the Johns Hopkins Eve atlas. ROIs were sorted into four networks: Default Mode Network, Executive Control Network, Salience Network, and Whole Brain. The resulting nodes and edges were characterized using graph-theoretic features, including Node Strength (NS), Betweenness Centrality (BC), Network Degree (ND), and Connectedness (C). Clinical (including demographics and World Federation of Neurologic Surgeons scale) and graph features were used separately and in combination to train RF and Logistic Regression classifiers to predict two outcomes: dichotomized modified Rankin Score (mRS) at discharge and at six months after discharge (favorable outcome mRS 0-2, unfavorable outcome mRS 3-6). A total of 56 aSAH patients underwent DTI a median (IQR) of 7 (IQR=8.5) days after admission. The best performing model (RF) combining clinical and DTI graph features had a mean Area Under the Receiver Operator Characteristic Curve (AUROC) of 0.88 ± 0.00 and Area Under the Precision Recall Curve (AUPRC) of 0.95 ± 0.00 over 500 trials. The combined model performed better than the clinical model alone (AUROC 0.81 ± 0.01, AUPRC 0.91 ± 0.00). The highest-ranked graph features for prediction were NS, BC, and ND. These results indicate reorganization of the connectome early after aSAH. The performance of clinical prognostic models was increased significantly by the inclusion of DTI-derived graph connectivity metrics. This methodology could significantly improve prognostication of aSAH.

Keywords: connectomics, diffusion tensor imaging, graph theory, machine learning, subarachnoid hemorrhage

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Authors: Pongsakorn Komutpol, Pravej Serichetaphongse, Soontra Panmekiate, Atiphan Pimkhaokham

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Statement of Problem: The important parameter of esthetic assessment in anterior maxillary implant include pink esthetic of gingiva and white esthetic of restoration. While the 3 dimensional (3D) implant position are recently concerned as a key for succeeding in implant treatment. However, to our knowledge, the authors did not come across any publication that demonstrated the relations of esthetic outcome and 3D implant position. Objectives: To investigate the correlation between positional accuracy of single-tooth implant restoration (STIR) in all 3 dimensions and their esthetic outcomes. Materials and Methods: 17 patients’ data who had a STIR at central incisor with pristine contralateral tooth were included in this study. Intraoral photographs, dental models, and cone beam computed tomography (CBCT) images were retrieved. The esthetic outcome was assessed in accordance with pink esthetic score and white esthetic score (PES/WES). While the number of correct position in each dimension (mesiodistal, labiolingual, apicocoronal) of the implant were evaluated and defined as 'right' or 'wrong' according to ITI consensus conference by one investigator using CBCT data. The different mean score between right and wrong position in all dimensions was analyzed by Mann-Whitney U test with 0.05 was the significant level of the study. Results: The average score of PES/WES was 15.88 ± 1.65 which was considered as clinically acceptable. The average PES/WES score in 1, 2 and 3 right dimension of the implant position were 16.71, 15.75 and 15.17 respectively. None of the implants placed wrongly in all three dimensions. Statistically significant difference of the PES/WES score was found between the implants that placed right in 3 dimensions and 1 dimension (p = 0.041). Conclusion: This study supported the principle of 3D position of implant. The more properly implant was placed, the higher esthetic outcome was found.

Keywords: accuracy, dental implant, esthetic, 3D implant position

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Authors: T. Pradhan, P. Rijal, M. C. Regmi

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Background: Eclampsia is a multisystem disorder that involves vital organs and failure of these may lead to deterioration of maternal condition and hypoxia and acidosis of fetus resulting in high maternal and perinatal mortality and morbidity. Thus, evaluation of the contributing factors for this condition and its complications leading to maternal deaths should be the priority. Formulating the plan and protocol to decrease these losses should be our goal. Aims and Objectives: To evaluate the risk factors associated with adverse maternal and fetal outcome in patients with eclampsia and to correlate the risk factors associated with maternal and fetal morbidity and mortality. Methods: All patients with eclampsia admitted in Department of Obstetrics and Gynecology, B. P. Koirala Institute of Health Sciences were enrolled after informed consent from February 2013 to February 2014. Questions as per per-forma were asked to patients, and attendants like Antenatal clinic visits, parity, number of episodes of seizures, duration from onset of seizure to magnesium sulfate and the patients were followed as per the hospital protocol, the mode of delivery, outcome of baby, post partum maternal condition like maternal Intensive Care Unit admission, neurological impairment and mortality were noted before discharge. Statistical analysis was done using Statistical Package for the Social Sciences (SPSS 11). Mean and percentage were calculated for demographic variables. Pearson’s correlation test and chi-square test were applied to find the relation between the risk factors and the outcomes. P value less than 0.05 was considered significant. Results: There were 10,000 antenatal deliveries during the study period. Fifty-two patients with eclampsia were admitted. All of the patients were unbooked for our institute. Thirty-nine patients were antepartum eclampsia. Thirty-one patients required mechanical ventilator support. Twenty-four patients were delivered by emergency c-section and 21 babies were Low Birth Weight and there were 9 stillbirths. There was one maternal mortality and 45 patients were discharged with improvement but 3 patients had neurological impairment. Mortality was significantly related with number of seizure episodes and time interval between seizure onset and administration of magnesium sulphate. Conclusion: Early detection and management of hypertensive complicating pregnancy during antenatal clinic check up. Early hospitalization and management with magnesium sulphate for eclampsia can help to minimize the maternal and fetal adverse outcomes.

Keywords: eclampsia, maternal mortality, perinatal mortality, risk factors

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Authors: Anna Guitart Atienza, Ana Fernández del Río, Madhav Nekkar, Jelena Ljubicic, África Periáñez, Eura Shin, Lauren Bellhouse

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The use of digital devices in healthcare or mobile health (mHealth) has increased in recent years due to the advances in digital technology, making it possible to nudge healthy behaviors through individual interventions. In addition, mHealth is becoming essential in poor-resource settings due to the widespread use of smartphones in areas where access to professional healthcare is limited. In this work, we evaluate mHealth interventions in low-income countries with a focus on causal inference. Counterfactuals estimation and other causal computations are key to determining intervention success and assisting in empirical decision-making. Our main purpose is to personalize treatment recommendations and triage patients at the individual level in order to maximize the entire intervention's impact on the desired outcome. For this study, collected data includes mHealth individual logs from front-line healthcare workers, electronic health records (EHR), and external variables data such as environmental, demographic, and geolocation information.

Keywords: causal inference, mHealth, intervention, personalization

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Authors: Elaheh Ezami, Behzad Mohammadian, Elham Aznab

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Health service design will need to change due to bringing in new digital health tools. This highlights the importance of innovation in adopting Health Information Technology (HIT). It can be argued that innovation in the health sector correlates with entrepreneurship. Various reasons exist for health entrepreneurs to advocate increased investment in HIT to compensate for shortcomings in the health sector and improve the quality of healthcare. Furthermore, every innovative program presents challenges and motivations for entrepreneurs that may distract or encourage the adoption of technology. Our study used a systematic literature review to identify relevant articles that defined the frustrations and promotions of using health information technology in organizations or enterprises. A meta-analysis of the articles was conducted to identify the factors driving or pulling entrepreneurs to use HIT.

Keywords: health information technology, health entrepreneurship, health enterprise, health entrepreneurs' innovation

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Authors: Mohammad Didar Hossain

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Background/Purpose: The purpose of this study was to examine the associations between productive engagements and the psychological well-being of older adults in the U.S by analyzing cross-sectional data from a secondary dataset. Specifically, this paper analyzed the associations of 4 different types of productive engagements, including current work status, caregiving to the family members, volunteering and religious strengths with the psychological well-being as an outcome variable. Methods: Data and sample: The study used the data from the Health and Retirement Study (HRS). The HRS is a nationally representative prospective longitudinal cohort study that has been conducting biennial surveys since 1992 to community-dwelling individuals 50 years of age or older on diverse issues. This analysis was based on the 2016 wave (cross-sectional) of the HRS dataset and the data collection period was April 2016 through August 2017. The samples were recruited from a multistage, national area-clustered probability sampling frame. Measures: Four different variables were considered as the predicting variables in this analysis. Firstly, current working status was a binary variable that measured by 0=Yes and 1= No. The second and third variables were respectively caregiving and volunteering, and both of them were measured by; 0=Regularly, 1= Irregularly. Finally, find in strength was measured by 0= Agree and 1= Disagree. Outcome (Wellbeing) variable was measured by 0= High level of well-being, 1= Low level of well-being. Control variables including age were measured in years, education in the categories of 0=Low level of education, 1= Higher level of education and sex r in the categories 0=male, 1= female. Analysis and Results: Besides the descriptive statistics, binary logistic regression analyses were applied to examine the association between independent and dependent variables. The results showed that among the four independent variables, three of them including working status (OR: .392, p<.001), volunteering (OR: .471, p<.003) and strengths in religion (OR .588, p<.003), were significantly associated with psychological well-being while controlling for age, gender and education factors. Also, no significant association was found between the caregiving engagement of older adults and their psychological well-being outcome. Conclusions and Implications: The findings of this study are mostly consistent with the previous studies except for the caregiving engagements and their impact on older adults’ well-being outcomes. Therefore, the findings support the proactive initiatives from different micro to macro levels to facilitate opportunities for productive engagements for the older adults, and all of these may ultimately benefit their psychological well-being and life satisfaction in later life.

Keywords: productive engagements, older adults, psychological wellbeing, productive aging

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Authors: Catherine Equey Balzli

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Old age retirement pensions are an important concern among the Swiss but estimating one’s income after retirement is difficult due to the Swiss insurance system’s complexity. This project’s aim is to prepare for developing a digital platform that will allow individuals to plan for retirement in a simplified manner. The main objective of the platform will be to give individuals the tools to check that their savings and retirement benefits will allow them to continue the lifestyle to which they are accustomed once they are retired. The research results from qualitative (focus group) and quantitative (survey) methodologies, recommend the scope and functionalities for a digital platform to be developed. A main outcome is the need to limit the platform’s scope to old-age pension only (excluding survivors’ or disability pensions, for instance). Furthermore, an outcome regarding the functionalities is the proposition of scenarios such as early retirement, changes to income, or modifications to personal status. The development of the digital platform will be a subsequent project.

Keywords: benefit statement, digital platform, retirement financial planning, social insurance

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