Search results for: clinical deterioration prediction

Authors: Mohd N. Ahmad, Lariyah Mohd Sidek

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The study had shown that Sungai Penchala (urban) was experiencing localized rainfall and hazardous air pollution due to urbanization. The high rainfall that partly added by localized rain had been seen as a threat of causing the flash floods and water quality deterioration in the area. The air pollution that consisted of mainly particulate matter (PM10), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) gave an alarming air pollution index (API) to the surrounding area. Comparison among urban area (Sungai Penchala), sub-urban (Gombak), and green areas (Jerantut plus Temerloh) with respect to the rainfall parameters and air pollutants, it was found that the degree of intensities of the parameters was positively related with the urbanization. The air pollutants especially NO2, SO2, and CO were in tandem with the increase of the rainfall. Specifically, if the water catchment area is physically near to the urban area, then the authorities need to look into related urban development program by considering the management of emitted pollutants with respect to the ecological setting of the urban area.

Keywords: urbanization, green area localized rainfall, air pollution, sub-urban area

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Authors: Aschalew Cherie Workneh, K. S. Hari Prasad, Chandra Shekhar Prasad Ojha

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Due to the increase in water scarcity, the crop water stress index (CWSI) is receiving significant attention these days, especially in arid and semiarid regions, for quantifying water stress and effective irrigation scheduling. Nowadays, machine learning techniques such as neural networks are being widely used to determine CWSI. In the present study, the performance of two artificial neural networks, namely, Self-Organizing Maps (SOM) and Feed Forward-Back Propagation Artificial Neural Networks (FF-BP-ANN), are compared while determining the CWSI of rice crop. Irrigation field experiments with varying degrees of irrigation were conducted at the irrigation field laboratory of the Indian Institute of Technology, Roorkee, during the growing season of the rice crop. The CWSI of rice was computed empirically by measuring key meteorological variables (relative humidity, air temperature, wind speed, and canopy temperature) and crop parameters (crop height and root depth). The empirically computed CWSI was compared with SOM and FF-BP-ANN predicted CWSI. The upper and lower CWSI baselines are computed using multiple regression analysis. The regression analysis showed that the lower CWSI baseline for rice is a function of crop height (h), air vapor pressure deficit (AVPD), and wind speed (u), whereas the upper CWSI baseline is a function of crop height (h) and wind speed (u). The performance of SOM and FF-BP-ANN were compared by computing Nash-Sutcliffe efficiency (NSE), index of agreement (d), root mean squared error (RMSE), and coefficient of correlation (R²). It is found that FF-BP-ANN performs better than SOM while predicting the CWSI of rice crops.

Keywords: artificial neural networks; crop water stress index; canopy temperature, prediction capability

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Authors: Rashid S. Mohammad, Shicheng Zhang, Xinzhe Zhao

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In tight oil reservoirs, wettability alteration has generally been considered as an effective way to remove fracturing fluid retention on the surface of the fracture and consequently improved oil production. However, there is a lack of a reliable productivity prediction model to show the relationship between the wettability and oil production in tight oil well. In this paper, a new oil productivity prediction model of immiscible oil-water flow and miscible CO₂-oil flow accounting for wettability is developed. This mathematical model is established by considering two different length scales: nonporous network and propped fractures. CO₂ flow diffuses in the nonporous network and high velocity non-Darcy flow in propped fractures are considered by taking into account the effect of wettability alteration on capillary pressure and relative permeability. A laboratory experiment is also conducted here to validate this model. Laboratory experiments have been designed to compare the water saturation profiles for different contact angle, revealing the fluid retention in rock pores that affects capillary force and relative permeability. Four kinds of brines with different concentrations are selected here to create different contact angles. In water-wet porous media, as the system becomes more oil-wet, water saturation decreases. As a result, oil relative permeability increases. On the other hand, capillary pressure which is the resistance for the oil flow increases as well. The oil production change due to wettability alteration is the result of the comprehensive changes of oil relative permeability and capillary pressure. The results indicate that wettability is a key factor for fracturing fluid retention removal and oil enhancement in tight reservoirs. By incorporating laboratory test into a mathematical model, this work shows the relationship between wettability and oil production is not a simple linear pattern but a parabolic one. Additionally, it can be used for a better understanding of optimization design of fracturing fluids.

Keywords: wettability, relative permeability, fluid retention, oil production, unconventional and tight reservoirs

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Authors: Mitakshara Sharma, Sonal Sharma

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Vesiculobullous diseases are heterogeneous group of dermatological disorders with protean manifestations. The most important technique for the patients with vesiculobullous diseases is conventional histopathology and confirmatory tests like direct immunofluorescence (DIF) and indirect immunofluorescence (IIF). DIF has been used for decades to investigate pathophysiology and in the diagnosis. It detects molecules such as immunoglobulins and complement components. It is done on the perilesional skin. Diagnosis of DIF test depends on features like primary site of the immune deposits, class of immunoglobulin, number of immune deposits and deposition at other sites. The aim of the study is to correlate DIF with clinical and histopathological findings and to analyze the utility of DIF in the diagnosis of these disorders. It is a retrospective descriptive study conducted for 2 years from 2015 to 2017 in Department of Pathology, GTB Hospital on perilesional punch biopsies of vesiculobullous lesions. Biopsies were sent in Michael’s medium. The specimens were washed, frozen and incubated with fluorescein isothiocyanate (FITC) tagged antihuman antibodies IgA, IgG, IgM, C3 & F and were viewed under fluorescent microscope. Out of 401 skin biopsies submitted for DIF, 285 were vesiculobullous diseases, in which the most common was Pemphigus vulgaris (34%) followed by Bullous pemphigoid (21.5%), Dermatitis herpetiformis (16%), Pemphigus foliaceus (11.9%), Linear IgA disease (11.9%), Epidermolysisbullosa (2.39%) and Pemphigus herpetiformis (1.7%). We will be presenting the DIF findings in the all these vesiculobullous diseases. DIF in conjugation with histopathology gives the best diagnostic yield in these lesions. It also helps in the diagnosis whenever there is a clinical and histopathological overlap.

Keywords: antibodies, direct immunofluorescence, pemphigus, vesiculobullous

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Authors: Ginger Egberts, Marianne Schaaphok, Fred Vermolen, Paul van Zuijlen

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A few years ago, a promising morphoelastic model was developed for the simulation of contraction formation after burn injuries. Contraction can lead to a serious reduction in physical mobility, like a reduction in the range-of-motion of joints. If this is the case in a healing burn wound, then this is referred to as a contracture that needs medical intervention. The morphoelastic model consists of a set of partial differential equations describing both a chemical part and a mechanical part in dermal wound healing. These equations are solved with the numerical finite element method (FEM). In this method, many calculations are required on each of the chosen elements. In general, the more elements, the more accurate the solution. However, the number of elements increases rapidly if simulations are performed in 2D and 3D. In that case, it not only takes longer before a prediction is available, the computation also becomes more expensive. It is therefore important to investigate alternative possibilities to generate the same results, based on the input parameters only. In this study, a surrogate neural network has been designed to mimic the results of the one-dimensional morphoelastic model. The neural network generates predictions quickly, is easy to implement, and there is freedom in the choice of input and output. Because a neural network requires extensive training and a data set, it is ideal that the one-dimensional FEM code generates output quickly. These feed-forward-type neural network results are very promising. Not only can the network give faster predictions, but it also has a performance of over 99%. It reports on the relative surface area of the wound/scar, the total strain energy density, and the evolutions of the densities of the chemicals and mechanics. It is, therefore, interesting to investigate the applicability of a neural network for the two- and three-dimensional morphoelastic model for contraction after burn injuries.

Keywords: biomechanics, burns, feasibility, feed-forward NN, morphoelasticity, neural network, relative surface area wound

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Authors: Parul Jindal, Shubhi Singh, Priya Ramakrishnan, Shailender Raghuvanshi

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Background: Knowledge of the influence of the age of the child on laryngeal dimensions is essential for all practitioners who are dealing with paediatric airway. Choosing the correct endotracheal tube (ETT) size is a crucial step in pediatric patients because a large-sized tube may cause complications like post-extubation stridor and subglottic stenosis. On the other hand with a smaller tube, there will be increased gas flow resistance, aspiration risk, poor ventilation, inaccurate monitoring of end-tidal gases and reintubation may also be required with a different size of the tracheal tube. Recent advancement in ultrasonography (USG) techniques should now allow for accurate and descriptive evaluation of pediatric airway. Aims and objectives: This study was planned to determine the accuracy of Ultrasonography (USG) to assess the appropriate ETT size and compare it with physical indices based formulae. Methods: After obtaining approval from Institute’s Ethical and Research committee, and parental written and informed consent, the study was conducted on 100 subjects of either sex between 12-60 months of age, undergoing various elective surgeries under general anesthesia requiring endotracheal intubation. The same experienced radiologist performed ultrasonography. The transverse diameter was measured at the level of cricoids cartilage by USG. After USG, general anesthesia was administered using standard techniques followed by the institute. An experienced anesthesiologist performed the endotracheal intubations with uncuffed endotracheal tube (Portex Tracheal Tube Smiths Medical India Pvt. Ltd.) with Murphy’s eye. He was unaware of the finding of the ultrasonography. The tracheal tube was considered best fit if air leak was satisfactory at 15-20 cm H₂O of airway pressure. The obtained values were compared with the values of endotracheal tube size calculated by ultrasonography, various age, height, weight-based formulas and diameter of right and left little finger. The correlation of the size of the endotracheal tube by different modalities was done and Pearson's correlation coefficient was obtained. The comparison of the mean size of the endotracheal tube by ultrasonography and by traditional formula was done by the Friedman’s test and Wilcoxon sign-rank test. Results: The predicted tube size was equal to best fit and best determined by ultrasonography (100%) followed by comparison to left little finger (98%) and right little finger (97%) and age-based formula (95%) followed by multivariate formula (83%) and body length (81%) formula. According to Pearson`s correlation, there was a moderate correlation of best fit endotracheal tube with endotracheal tube size by age-based formula (r=0.743), body length based formula (r=0.683), right little finger based formula (r=0.587), left little finger based formula (r=0.587) and multivariate formula (r=0.741). There was a strong correlation with ultrasonography (r=0.943). Ultrasonography was the most sensitive (100%) method of prediction followed by comparison to left (98%) and right (97%) little finger and age-based formula (95%), the multivariate formula had an even lesser sensitivity (83%) whereas body length based formula was least sensitive with a sensitivity of 78%. Conclusion: USG is a reliable method of estimation of subglottic diameter and for prediction of ETT size in children.

Keywords: endotracheal intubation, pediatric airway, subglottic diameter, traditional formulas, ultrasonography

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Authors: Jamboor K. Vishwanatha

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Among the potent anti-cancer agents, curcumin has been found to be very efficacious against various cancer cells. Despite multiple medicinal benefits of curcumin, poor water solubility, poor physiochemical properties and low bioavailability continue to pose major challenges in developing a formulation for clinical efficacy. To improve its potential application in the clinical area, we formulated poly lactic-co-glycolic acid (PLGA) nanoparticles. The PLGA nanoparticles were formulated using solid-oil/water emulsion solvent evaporation method and then characterized for percent yield, encapsulation efficiency, surface morphology, particle size, drug distribution within nanoparticles and drug polymer interaction. Our studies showed the successful formation of smooth and spherical curcumin loaded PLGA nanoparticles with a high percent yield of about 92.01±0.13% and an encapsulation efficiency of 90.88±0.14%. The mean particle size of the nanoparticles was found to be 145nm. The in vitro drug release profile showed 55-60% drug release from the nanoparticles over a period of 24 hours with continued sustained release over a period of 8 days. Exposure to curcumin loaded nanoparticles resulted in reduced cell viability of cancer cells compared to normal cells. We used a novel non-covalent insertion of a homo-bifunctional spacer for targeted delivery of curcumin to various cancer cells. Functionalized nanoparticles for antibody/targeting agent conjugation was prepared using a cross-linking ligand, bis(sulfosuccinimidyl) suberate (BS3), which has reactive carboxyl group to conjugate efficiently to the primary amino groups of the targeting agents. In our studies, we demonstrated successful conjugation of antibodies, Annexin A2 or prostate specific membrane antigen (PSMA), to curcumin loaded PLGA nanoparticles for targeting to prostate and breast cancer cells. The percent antibody attachment to PLGA nanoparticles was found to be 92.8%. Efficient intra-cellular uptake of the targeted nanoparticles was observed in the cancer cells. These results have emphasized the potential of our multifunctional curcumin nanoparticles to improve the clinical efficacy of curcumin therapy in patients with cancer.

Keywords: polymeric nanoparticles, cancer therapy, sustained release, curcumin

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: Danny Barash

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Riboswitches are RNA genetic control elements that were originally discovered in bacteria and provide a unique mechanism of gene regulation. They work without the participation of proteins and are believed to represent ancient regulatory systems in the evolutionary timescale. One of the biggest challenges in riboswitch research is that many are found in prokaryotes but only a small percentage of known riboswitches have been found in certain eukaryotic organisms. The few examples of eukaryotic riboswitches were identified using sequence-based bioinformatics search methods that include some slight structural considerations. These pattern-matching methods were the first ones to be applied for the purpose of riboswitch detection and they can also be programmed very efficiently using a data structure called affix arrays, making them suitable for genome-wide searches of riboswitch patterns. However, they are limited by their ability to detect harder to find riboswitches that deviate from the known patterns. Several methods have been developed since then to tackle this problem. The most commonly used by practitioners is Infernal that relies on Hidden Markov Models (HMMs) and Covariance Models (CMs). Profile Hidden Markov Models were also carried out in the pHMM Riboswitch Scanner web application, independently from Infernal. Other computational approaches that have been developed include RMDetect by the use of 3D structural modules and RNAbor that utilizes Boltzmann probability of structural neighbors. We have tried to incorporate more sophisticated secondary structure considerations based on RNA folding prediction using several strategies. The first idea was to utilize window-based methods in conjunction with folding predictions by energy minimization. The moving window approach is heavily geared towards secondary structure consideration relative to sequence that is treated as a constraint. However, the method cannot be used genome-wide due to its high cost because each folding prediction by energy minimization in the moving window is computationally expensive, enabling to scan only at the vicinity of genes of interest. The second idea was to remedy the inefficiency of the previous approach by constructing a pipeline that consists of inverse RNA folding considering RNA secondary structure, followed by a BLAST search that is sequence-based and highly efficient. This approach, which relies on inverse RNA folding in general and our own in-house fragment-based inverse RNA folding program called RNAfbinv in particular, shows capability to find attractive candidates that are missed by Infernal and other standard methods being used for riboswitch detection. We demonstrate attractive candidates found by both the moving-window approach and the inverse RNA folding approach performed together with BLAST. We conclude that structure-based methods like the two strategies outlined above hold considerable promise in detecting riboswitches and other conserved RNAs of functional importance in a variety of organisms.

Keywords: riboswitches, RNA folding prediction, RNA structure, structure-based methods

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Authors: Rajwanlop Kumpoopong, Sukit Yindeesuk, Pornchai Silarom

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Modeling cracks in concrete is complicated by its strain-softening behavior which requires the use of sophisticated energy criteria of fracture mechanics to assure stable and convergent solutions in the finite-element (FE) analysis particularly for relatively large structures. However, for small-scale structures such as beams and slabs, a simpler approach relies on retaining some shear stiffness in the cracking plane has been adopted in literature to model the strain-softening behavior of concrete under monotonically increased loading. According to the shear retaining approach, each element is assumed to be an isotropic material prior to cracking of concrete. Once an element is cracked, the isotropic element is replaced with an orthotropic element in which the new orthotropic stiffness matrix is formulated with respect to the crack orientation. The shear transfer factor of 0.5 is used in parallel to the crack plane. The shear retaining approach is adopted in this research to model cracks in RC bridge deck with some modifications to take into account the effect of repetitive moving truck wheel loads as they cause fatigue cracking of concrete. First modification is the introduction of fatigue tests of concrete and reinforcing steel and the Palmgren-Miner linear criterion of cumulative damage in the conventional FE analysis. For a certain loading, the number of cycles to failure of each concrete or RC element can be calculated from the fatigue or S-N curves of concrete and reinforcing steel. The elements with the minimum number of cycles to failure are the failed elements. For the elements that do not fail, the damage is accumulated according to Palmgren-Miner linear criterion of cumulative damage. The stiffness of the failed element is modified and the procedure is repeated until the deck slab fails. The total number of load cycles to failure of the deck slab can then be obtained from which the S-N curve of the deck slab can be simulated. Second modification is the modification in shear transfer factor. Moving loading causes continuous rubbing of crack interfaces which greatly reduces shear transfer mechanism. It is therefore conservatively assumed in this study that the analysis is conducted with shear transfer factor of zero for the case of moving loading. A customized FE program has been developed using the MATLAB software to accomodate such modifications. The developed procedure has been validated with the fatigue test of the 1/6.6-scale AASHTO bridge deck under the applications of both fixed-point repetitive loading and moving loading presented in the literature. Results are in good agreement both experimental vs. simulated S-N curves and observed vs. simulated crack patterns. Significant contribution of the developed procedure is a series of S-N relations which can now be simulated at any desired levels of cracking in addition to the experimentally derived S-N relation at the failure of the deck slab. This permits the systematic investigation of crack propagation or deterioration of RC bridge deck which is appeared to be useful information for highway agencies to prolong the life of their bridge decks.

Keywords: bridge deck, cracking, deterioration, fatigue, finite-element, moving truck, reinforced concrete

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Authors: Ayda Youssef, Tarek Rafaat, Iman zaky

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Purpose: Langerhans’ cell histiocytosis (LCH) is not uncommon pathology that implies aberrant proliferation of a specific dendritic (Langerhans) cell. These atypical but mature cells of monoclonal origin can infiltrate many sites of the body and may occur as localized lesions or as widespread systemic disease. Liver is one of the uncommon sites of affection. The twofold objective of this study is to illustrate the radiological presentation of this disease, and to compare these results with previously reported series. Methods and Materials: Between 2007 and 2012, 150 patients with biopsy-proven LCH were treated in our hospital, a paediatric cancer tertiary care center. A retrospective review of radiographic images and reports was performed. There were 33 patients with liver affection are stratified. All patients underwent imaging studies, mostly US and CT. A chart review was performed to obtain demographic, clinical and radiological data. They were analyzed and compared to other published series. Results: Retrospective assessment of 150 patients with LCH was performed, among them 33 patients were identified who had liver involvement. All these patients developed multisystemic disease; They were 12 females and 21 males with (n= 32), seven of them had marked hepatomegaly. Diffuse hypodense liver parenchyma was encountered in five cases, the periportal location has a certain predilection in cases of focal affection where three cases has a hypodense periportal soft tissue sheets, one of them associated with dilated biliary radicals, only one case has multiple focal lesions unrelated to portal tracts. On follow up of the patients, two cases show abnormal morphology of liver with bossy outline. Conclusion: LCH is a not infrequent disease. A high-index suspicion should be raised in the context of diagnosis of liver affection. A biopsy is recommended in the presence of radiological suspicion. Chemotherapy is the preferred therapeutic modality. Liver histiocytosis are not disease specific features but should be interpreted in conjunction with the clinical history and the results of biopsy. Clinical Relevance/Application: Radiologist should be aware of different patterns of hepatobiliary histiocytosis, Thus early diagnosis and proper management of patient can be conducted.

Keywords: langerhans’ cell histiocytosis, liver, medical and health sciences, radiology

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Authors: Ronak Mishra, Sachin Kale

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Background: The clinical outcome of a new fixation device (femoral neck system, FNS) for femoral neck fractures is not described properly. The main purpose of this study was to evaluate the functional outcome of the patients of femoral neck fractures treated with FNS. Methods: A retrospective study was done among patients aged 60 years or less. On the basis of inclusion and exclusion criteria a final sample size of 30 was considered. Blood loss, type of fracture internal fixation, and length of clinical follow-up were all acquired from patient records. The volume of blood loss was calculated. The mean and standard deviation of continuous variables were reported (with range). Harris Hip score (HHS) And Post op xrays at intervals(6 weeks, 6 months ,12 months ) we used to clinically asses the patient. Results: Out of all 60% were females and 40% were males. The mean age of the patients was. 44.12(+-) years The comparison of functional outcomes of the patients treated with FNS using Harris Hip Score. It showed a highly significant comparison between the patients at post operatively , 6 weeks and 3 months and 12 months . There were no postoperative complications seen among the patients. Conclusion: FNS offers superior biomechanical qualities and greatly improved overall build stability. It allows for a significant reduction in operation time, potentially lowering risks and consequences associated with surgery.

Keywords: FNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Umamaheswari Shanmugam, Silvia Ronchi, Radu Vornicu

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that are able to use the large amount and variety of data generated during healthcare services every day. As we read the news, over 500 machine learning or other artificial intelligence medical devices have now received FDA clearance or approval, the first ones even preceding the year 2000. One of the big advantages of these new technologies is the ability to get experience and knowledge from real-world use and to continuously improve their performance. Healthcare systems and institutions can have a great benefit because the use of advanced technologies improves the same time efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and also to protect patients’ safety. The evolution and the continuous improvement of software used in healthcare must take into consideration the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device approval, but they are necessary to ensure performance, quality, and safety, and at the same time, they can be a business opportunity if the manufacturer is able to define in advance the appropriate regulatory strategy. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems.

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Authors: Lucas Derks, Christine Beenhakker, Michiel Brandt, Gert Arts, Ruud van Langeveld

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Background: The method Depression in Awareness Space (DAS) is a psychotherapeutic intervention technique based on the principles of spatial cognition and imagination therapy with spatial components. The basic assumptions are: mental space is the primary organizing principle in the mind, and all psychological issues can be treated by first locating and by next relocating the conceptualizations involved. The most clinical experience was gathered over the last 20 years in the area of social issues (with the social panorama model). The latter work led to the conclusion that a mental object (image) gains emotional impact when it is placed more central, closer and higher in the visual field – and vice versa. Changing the locations of mental objects in space thus alters the (socio-) emotional meaning of the relationships. The experience of depression seems always associated with darkness. Psychologists tend to see the link between depression and darkness as a metaphor. However, clinical practice hints to the existence of more literal forms of darkness. Aims: The aim of the method Depression in Awareness Space is to reduce the distress of clients with depression in the clinical counseling practice, as a reliable alternative method of psychological therapy for the treatment of depression. The method Depression in Awareness Space aims at making dark areas smaller, lighter and more transparent in order to identify the problem or the cause of the depression which lies behind the darkness. It was hypothesized that the darkness is a subjective side-effect of the neurological process of repression. After reducing the dark clouds the real problem behind the depression becomes more visible, allowing the client to work on it and in that way reduce their feelings of depression. This makes repression of the issue obsolete. Results: Clients could easily get into their 'sadness' when asked to do so and finding the location of the dark zones proved pretty easy as well. In a recent pilot study with five participants with mild depressive symptoms (measured on two different scales and tested against an untreated control group with similar symptoms), the first results were also very promising. If the mental spatial approach to depression can be proven to be really effective, this would be very good news. The Society of Mental Space Psychology is now looking for sponsoring of an up scaled experiment. Conclusions: For spatial cognition and the research into spatial psychological phenomena, the discovery of dark areas can be a step forward. Beside out of pure scientific interest, it is great to know that this discovery has a clinical implication: when darkness can be connected to depression. Also, darkness seems to be more than metaphorical expression. Progress can be monitored over measurement tools that quantify the level of depressive symptoms and by reviewing the areas of darkness.

Keywords: depression, spatial cognition, spatial imagery, social panorama

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Authors: Madeline Foster

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Since the COVID-19 pandemic, telehealth usage for the delivery of psychotherapy has surged. The evidence base evaluating the success of telehealth interventions continues to grow, with both benefits as well as potential risks identified. This study compared two recent randomized clinical trials (RCTs) from Sweden that looked at the effectiveness of Cognitive Behavioral Therapy (CBT) delivered via telehealth (TH) versus face-to-face (FTF) for individuals with Obsessive Compulsive Disorder (OCD). The papers had mixed results. The first paper by Aspvall and colleagues compared the effect of a therapist-supported, internet-delivered stepped-care CBT program for children and adolescents aged 7 to 17 with face-to-face CBT (2021). In Aspvall’s study, the control scored a mean Y-BOCS of 10.57 and the TH intervention group scored a mean Y-BOCS of 11.57. The mean difference (0.91) met the criteria for noninferiority (p = 0.03). The second study by Lundström and colleagues also compared therapist-supported, internet-based CBT with FTF CBT for the treatment of those with DSM-5-diagnosed OCD. Conversely, while Lundström’s study reported improved symptoms across all groups, at follow up the difference in symptom severity between FTF and TH was clinically significant, with 77% of FTF participants responding to treatment compared to only 45% of TH participants. Due to the methodological limitations of Lundström’s study, it was concluded that Aspvall’s paper made a stronger scientific argument.

Keywords: telehealth, Sweden, RCT, cognitive-behavioral therapy, obsessive-compulsive disorder

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Authors: Pamela Ventola, Laurel Bales, Sara Florczyk

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Background: Fully remote or hybrid administration of clinical outcome measures in rare neurodevelopmental disorders trials is increasing due to the ongoing pandemic and recognition that remote assessments reduce the burden on families. Many assessments in rare neurodevelopmental disorders trials are complex; however, remote/hybrid trials readily allow for the use of centralized raters to administer and score the scales. The use of centralized raters has many benefits, including reducing site burden; however, a specific impact on data quality has not yet been determined. Purpose: The current study has two aims: a) evaluate differences in data quality between administration of a standardized clinical interview completed by centralized raters compared to those completed by site raters and b) evaluate improvement in accuracy of scoring standardized developmental assessments when scored centrally compared to when scored by site raters. Methods: For aim 1, the Vineland-3, a widely used measure of adaptive functioning, was administered by site raters (n= 52) participating in one of four rare disease trials. The measure was also administered as part of two additional trials that utilized central raters (n=7). Each rater completed a comprehensive training program on the assessment. Following completion of the training, each clinician completed a Vineland-3 with a mock caregiver. Administrations were recorded and reviewed by a neuropsychologist for administration and scoring accuracy. Raters were able to certify for the trials after demonstrating an accurate administration of the scale. For site raters, 25% of each rater’s in-study administrations were reviewed by a neuropsychologist for accuracy of administration and scoring. For central raters, the first two administrations and every 10th administration were reviewed. Aim 2 evaluated the added benefit of centralized scoring on the accuracy of scoring of the Bayley-3, a comprehensive developmental assessment widely used in rare neurodevelopmental disorders trials. Bayley-3 administrations across four rare disease trials were centrally scored. For all administrations, the site rater who administered the Bayley-3 scored the scale, and a centralized rater reviewed the video recordings of the administrations and also scored the scales to confirm accuracy. Results: For aim 1, site raters completed 138 Vineland-3 administrations. Of the138 administrations, 53 administrations were reviewed by a neuropsychologist. Four of the administrations had errors that compromised the validity of the assessment. The central raters completed 180 Vineland-3 administrations, 38 administrations were reviewed, and none had significant errors. For aim 2, 68 administrations of the Bayley-3 were reviewed and scored by both a site rater and a centralized rater. Of these administrations, 25 had errors in scoring that were corrected by the central rater. Conclusion: In rare neurodevelopmental disorders trials, sample sizes are often small, so data quality is critical. The use of central raters inherently decreases site burden, but it also decreases rater variance, as illustrated by the small team of central raters (n=7) needed to conduct all of the assessments (n=180) in these trials compared to the number of site raters (n=53) required for even fewer assessments (n=138). In addition, the use of central raters dramatically improves the quality of scoring the assessments.

Keywords: neurodevelopmental disorders, clinical trials, rare disease, central raters, remote trials, decentralized trials

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Authors: Florence Roselle Adalin, Misha Louise Delariarte, Fabbette Laire Lagas, Sarah Emanuelle Mejia, Lika Mizukoshi, Irish Paullen Palomeno, Gibrianne Alistaire Ramos, Danica Pauline Ramos, Josefina Tuazon, Jo Leah Flores

Abstract:

Pain, often a missed and undertreated symptom, affects the quality of life of individuals. Nurses are key players in providing effective pain management to decrease morbidity and mortality of patients in pain. Nurses’ knowledge and attitude on pain greatly affect their ability on assessment and management. The Pain Society of the Philippines recognized the inadequacy and inaccessibility of data on the knowledge, skills, and attitude of nurses on pain management in the country. This study may be the first of its kind in the county, giving it the potential to contribute greatly to nursing education and practice through providing valuable baseline data. Objectives: This study aims to describe the level of knowledge and attitude, and current practices of nurses on pain assessment and management; and determine the relationship of nurses’ knowledge and attitude with years of experience, training on pain management and clinical area of practice. Methodology: A survey research design was employed. Four hospitals were selected through purposive sampling. A total of 235 Medical-Surgical Unit and Intensive Care Unit (ICU) nurses participated in the study. The tool used is a combination of demographic survey, Nurses’ Knowledge and Attitude Survey Regarding Pain (NKASRP), Acute Pain Evidence Based Practice Questionnaire (APEBPQ) with self-report questions on non-pharmacologic pain management. The data obtained was analysed using descriptive statistics, two sample T-tests for clinical areas and training; and Pearson product correlation to identify relationship of level of knowledge and attitude with years of experience. Results and Analysis: The mean knowledge and attitude score of the nurses was 47.14%. Majority answered ‘most of the time’ or ‘all the time’ on 84.12% of practice items on pain assessment, implementation of non-pharmacologic interventions, evaluation and documentation. Three of 19 practice items describing morphine and opioid administration in special populations were only done ‘a little of the time’. Most utilized non-pharmacologic interventions were deep breathing exercises (79.66%), massage therapy (27.54%), and ice therapy (26.69%). There was no significant relationship between knowledge scores and years of clinical experience (p = 0.05, r= -0.09). Moreover, there was not enough evidence to show difference in nurses’ knowledge and attitude scores in relation to presence of training (p = 0.41) or areas (Medical-Surgical or ICU) of clinical practice (p = 0.53). Conclusion and Recommendations: Findings of the study showed that the level of knowledge and attitude of nurses on pain assessment and management is suboptimal; and no relationship between nurses’ knowledge and attitude and years of experience. It is recommended that further studies look into the nursing curriculum on pain education, culture-specific pain management protocols and evidence-based practices in the country.

Keywords: knowledge and attitude, nurses, pain management, practices on pain management

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Authors: Junfeng Yan, Wenkui Hou

Abstract:

Prognostics and Health Management (PHM) is a technology to monitor the equipment status and predict impending faults. It is used to predict the potential fault and provide fault information and track trends of system degradation by capturing characteristics signals. So how to detect characteristics signals is very important. The select of test point plays a very important role in detecting characteristics signal. Traditionally, we use dependency model to select the test point containing the most detecting information. But, facing the large complicated system, the dependency model is not built so easily sometimes and the greater trouble is how to calculate the matrix. Rely on this premise, the paper provide a highly effective method to select test point without dependency model. Because signal flow model is a diagnosis model based on failure mode, which focuses on system’s failure mode and the dependency relationship between the test points and faults. In the signal flow model, a fault information can flow from the beginning to the end. According to the signal flow model, we can find out location and structure information of every test point and module. We break the signal flow model up into serial and parallel parts to obtain the final relationship function between the system’s testability or prediction metrics and test points. Further, through the partial derivatives operation, we can obtain every test point’s importance degree in determining the testability metrics, such as undetected rate, false alarm rate, untrusted rate. This contributes to installing the test point according to the real requirement and also provides a solid foundation for the Prognostics and Health Management. According to the real effect of the practical engineering application, the method is very efficient.

Keywords: false alarm rate, importance degree, signal flow model, undetected rate, untrusted rate

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Authors: V. Jayanthi

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Urbanization and pace of urbanization have increased tremendously in last few decades. More towns are now getting converted into cities. Urbanization trend is seen all over the world but is becoming most dominant in Asia. Today, the scale of urbanization in India is so huge that Indian cities are among the fastest-growing in the world, including Bangalore, Hyderabad, Pune, Chennai, Delhi, and Mumbai. Urbanization remains a single predominant factor that is continuously linked to the destruction of urban green spaces. With reference to Chennai as a case study, which is suffering from rapid deterioration of its green spaces, this paper sought to fill this gap by exploring key factors aside urbanization that is responsible for the destruction of green spaces. The paper relied on a research approach and triangulated data collection techniques such as interviews, focus group discussion, personal observation and retrieval of archival data. It was observed that apart from urbanization, problem of ownership of green space lands, low priority to green spaces, poor maintenance, enforcement of development controls, wastage of underpass spaces, and uncooperative attitudes of the general public, play a critical role in the destruction of urban green spaces. Therefore the paper narrows down to a point, that for a city to have a proper sustainable urban green space, broader city development plans are essential. Though rapid urbanization is an indicator of positive development, it is also accompanied by a host of challenges. Chennai lost a lot of greenery, as the city urbanized rapidly that led to a steep fall in vegetation cover. Environmental deterioration will be the big price we pay if Chennai continues to grow at the expense of greenery. Soaring skyscrapers, multistoried complexes, gated communities, and villas, frame the iconic skyline of today’s Chennai city which reveals that we overlook the importance of our green cover, which is important to balance our urban and lung spaces. Chennai, with a clumped landscape at the center of the city, is predicted to convert 36% of its total area into urban areas by 2026. One major issue is that a city designed and planned in isolation creates underused spaces all around the cities which are of negligence. These urban voids are dead, underused, unused spaces in the cities that are formed due to inefficient decision making, poor land management, and poor coordination. Urban voids have huge potential of creating a stronger urban fabric, exploited as public gathering spaces, pocket parks or plazas or just enhance public realm, rather than dumping of debris and encroachments. Flyovers need to justify their existence themselves by being more than just traffic and transport solutions. The vast, unused space below the Kathipara flyover is a case in point. This flyover connects three major routes: Tambaram, Koyambedu, and Adyar. This research will focus on the concept of urban voids, how these voids under the flyovers, can be used for place making process, how this space beneath flyovers which are neglected, can be a part of the urban realm through urban design and landscaping.

Keywords: landscape design, flyovers, public spaces, reclaiming lost spaces, urban voids

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Authors: Abu S. Mustafa, Mohammad W. Khan, Faraz Shaheed Khan, Nazima Habibi

Abstract:

Brucellosis is a zoonotic disease of worldwide prevalence. There are at least four species and several strains of Brucella that cause human disease. Brucella genomes have very limited variation across strains, which hinder strain identification using classical molecular techniques, including PCR and 16 S rDNA sequencing. The aim of this study was to perform whole genome sequencing of clinical isolates of Brucella and perform bioinformatics and comparative genomics analyses to determine the existence of genetic differences across the isolates of a single Brucella species and strain. The draft sequence data were generated from 15 clinical isolates of Brucella melitensis (biovar 2 strain 63/9) using MiSeq next generation sequencing platform. The generated reads were used for further assembly and analysis. All the analysis was performed using Bioinformatics work station (8 core i7 processor, 8GB RAM with Bio-Linux operating system). FastQC was used to determine the quality of reads and low quality reads were trimmed or eliminated using Fastx_trimmer. Assembly was done by using Velvet and ABySS softwares. The ordering of assembled contigs was performed by Mauve. An online server RAST was employed to annotate the contigs assembly. Annotated genomes were compared using Mauve and ACT tools. The QC score for DNA sequence data, generated by MiSeq, was higher than 30 for 80% of reads with more than 100x coverage, which suggested that data could be utilized for further analysis. However when analyzed by FastQC, quality of four reads was not good enough for creating a complete genome draft so remaining 11 samples were used for further analysis. The comparative genome analyses showed that despite sharing same gene sets, single nucleotide polymorphisms and insertions/deletions existed across different genomes, which provided a variable extent of diversity to these bacteria. In conclusion, the next generation sequencing, bioinformatics, and comparative genome analysis can be utilized to find variations (point mutations, insertions and deletions) across different genomes of Brucella within a single strain. This information could be useful in surveillance and epidemiological studies supported by Kuwait University Research Sector grants MI04/15 and SRUL02/13.

Keywords: brucella, bioinformatics, comparative genomics, whole genome sequencing

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Authors: Sedigheh Samimian, Sadra Ashrafi, Tahereh Khaleghdoost Mohammadi, Mohammad Reza Yeganeh, Ali Ashraf, Hamideh Hakimi, Maryam Dehghani

Abstract:

Introduction: The recommended position for measuring Intra-Abdominal Pressure (IAP) is the supine position. However, patients put in this position are prone to Ventilator-associated pneumonia. This study was done to evaluate the relationship between bed head angle and IAP measurements of intubated patients in the intensive care unit. Methods: In this clinical trial, seventy-six critically ill patients under mechanical ventilation were enrolled. IAP measurement was performed every 8 hours for 24 hours using the KORN method in three different degrees of the head of bed (HOB) elevation (0°, 15°, and 30°). Bland-Altman analysis was performed to identify the bias and limits of agreement among the three HOBs. According to World Society of the Abdominal Compartment Syndrome (WSACS), we can consider two IAP techniques equivalent if a bias of <1 mmHg and limits of agreement of - 4 to +4 were found between them. Data were analyzed using SPSS statistical software (v. 19), and the significance level was considered as 0.05. Results: The prevalence of intra-abdominal hypertension was 18.42%. Mean ± standard deviation (SD) of IAP were 8.44 ± 4.02 mmHg for HOB angle 0°, 9.58 ± 4.52 for HOB angle 15°, and 11.10 ± 4.73 for HOB angle 30o (p = 0.0001). The IAP measurement bias between HOB angle 0◦ and HOB angle 15° was 1.13 mmHg. This bias was 2.66 mmHg between HOB angle 0° and HOB angle 30°. Conclusion: Elevation of HOB angle from 0 to 30 degree significantly increases IAP. It seems that the measurement of IAP at HOB angle 15° was more reliable than 30°.

Keywords: pressure, intra-abdominal hypertension, head of bed, critical care, compartment syndrome, supine position

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Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Siti Khairunniza Bejo

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Conventional methods for nutrient soil mapping are based on laboratory tests of samples that are obtained from surveys. The time and cost involved in gathering and analyzing soil samples are the reasons that researchers use Predictive Soil Mapping (PSM). PSM can be defined as the development of a numerical or statistical model of the relationship among environmental variables and soil properties, which is then applied to a geographic database to create a predictive map. Kriging is a group of geostatistical techniques to spatially interpolate point values at an unobserved location from observations of values at nearby locations. The main problem with using kriging as an interpolator is that it is excessively data-dependent and requires a large number of closely spaced data points. Hence, there is a need to minimize the number of data points without sacrificing the accuracy of the results. In this paper, an Artificial Neural Networks (ANN) scheme was used to predict macronutrient values at un-sampled points. ANN has become a popular tool for prediction as it eliminates certain difficulties in soil property prediction, such as non-linear relationships and non-normality. Back-propagation multilayer feed-forward network structures were used to predict nitrogen, phosphorous and potassium values in the soil of the study area. A limited number of samples were used in the training, validation and testing phases of ANN (pattern reconstruction structures) to classify soil properties and the trained network was used for prediction. The soil analysis results of samples collected from the soil survey of block C of Sawah Sempadan, Tanjung Karang rice irrigation project at Selangor of Malaysia were used. Soil maps were produced by the Kriging method using 236 samples (or values) that were a combination of actual values (obtained from real samples) and virtual values (neural network predicted values). For each macronutrient element, three types of maps were generated with 118 actual and 118 virtual values, 59 actual and 177 virtual values, and 30 actual and 206 virtual values, respectively. To evaluate the performance of the proposed method, for each macronutrient element, a base map using 236 actual samples and test maps using 118, 59 and 30 actual samples respectively produced by the Kriging method. A set of parameters was defined to measure the similarity of the maps that were generated with the proposed method, termed the sample reduction method. The results show that the maps that were generated through the sample reduction method were more accurate than the corresponding base maps produced through a smaller number of real samples. For example, nitrogen maps that were produced from 118, 59 and 30 real samples have 78%, 62%, 41% similarity, respectively with the base map (236 samples) and the sample reduction method increased similarity to 87%, 77%, 71%, respectively. Hence, this method can reduce the number of real samples and substitute ANN predictive samples to achieve the specified level of accuracy.

Keywords: artificial neural network, kriging, macro nutrient, pattern recognition, precision farming, soil mapping

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Authors: S. Mousavian, F. Mousavian, V. Nikkhah Rashidabad

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Cubic equations of state like Redlich–Kwong (RK) EOS have been proved to be very reliable tools in the prediction of phase behavior. Despite their good performance in compositional calculations, they usually suffer from weaknesses in the predictions of saturated liquid density. In this research, RK equation was modified. The result of this study shows that modified equation has good agreement with experimental data.

Keywords: equation of state, modification, ammonia, genetic algorithm

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Authors: Melissa Dorsey

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Moral distress and compassion fatigue plague nurses in the Cardiothoracic Intensive Care Unit (CTICU) and cause an unnecessary level of turnover. Dueling Burnout describes an initiative that was implemented in the CTICU to reduce the level of burnout the nurses endure by encouraging dual roles with collaborating departments. Purpose: Critical care nurses are plagued by burnout, moral distress, and compassion fatigue due to the intensity of care provided. The purpose of the dual role program was to decrease these issues by providing relief from the intensity of the critical care environment while maintaining full-time employment. Relevance/Significance: Burnout, moral distress, and compassion fatigue are leading causes of Cardiothoracic Critical Care (CTCU) turnover. A contributing factor to burnout is the workload related to serving as a preceptor for a constant influx of new nurses (RN). As a result of these factors, the CTICU averages 17% nursing turnover/year. The cost, unit disruption, and, most importantly, distress of the clinical nurses required an innovative approach to create an improved work environment and experience. Strategies/Implementation/Methods: In May 2018, a dual role pilot was initiated for nurses. The dual role constitutes .6 full-time equivalent hours (FTE) worked in CTICU in combination with .3 FTE worked in the Emergency Department (ED). ED nurses who expressed an interest in cross-training to CTICU were also offered the dual role opportunity. The initial hypothesis was that full-time employees would benefit from a change in clinical setting leading to increased engagement and job satisfaction. The dual role also presents an opportunity for professional development through the expansion of clinical skills in another specialty. Success of the pilot led to extending the dual role to areas beyond the ED. Evaluation/Outcomes/Results: The number of dual role clinical nurses has grown to 22. From the dual role cohort, only one has transferred out of CTICU. This is a 5% turnover rate for this group of nurses as compared to the average turnover rate of 17%. A role satisfaction survey conducted with the dual role cohort found that because of working in a dual role, 76.5% decreased their intent to leave, 100% decreased their level of burnout, and 100% reported an increase in overall job satisfaction. Nurses reported the ability to develop skills that are transferable between departments. Respondents emphasized the appreciation gained from working in multiple environments; the dual role served to transform their care. Conclusions/Implications: Dual role is an effective strategy to retain experienced nurses, decrease burnout and turnover, improve collaboration, and provide flexibility to meet staffing needs. The dual role offers RNs an expansion of skills, relief from high acuity and orientee demands, while improving job satisfaction.

Keywords: nursing retention, burnout, pandemic, strategic staffing, leadership

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Authors: Selim M. Khan, Aaron A. Goodarzi, Joshua M. Taron, Tryggve Rönnqvist

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Indoor air quality, a prime determinant of health, is strongly influenced by the presence of hazardous radon gas within the built environment. As a health issue, dangerously high indoor radon arose within the 20th century to become the 2nd leading cause of lung cancer. While the 21st century building metrics and human behaviors have captured, contained, and concentrated radon to yet higher and more hazardous levels, the issue is rapidly worsening in Canada. It is established that Canadians in the Prairies are the 2nd highest radon-exposed population in the world, with 1 in 6 residences experiencing 0.2-6.5 millisieverts (mSv) radiation per week, whereas the Canadian Nuclear Safety Commission sets maximum 5-year occupational limits for atomic workplace exposure at only 20 mSv. This situation is also deteriorating over time within newer housing stocks containing higher levels of radon. Deep machine learning (LSTM) algorithms were applied to analyze multiple quantitative and qualitative features, determine the most important contributory factors, and predicted radon levels in the known past (1990-2020) and projected future (2021-2050). The findings showed gradual downwards patterns in Sweden, whereas it would continue to go from high to higher levels in Canada over time. The contributory factors found to be the basement porosity, roof insulation depthness, R-factor, and air dynamics of the indoor environment related to human window opening behaviour. Building codes must consider including these factors to ensure adequate indoor ventilation and healthy living that can prevent lung cancer in non-smokers.

Keywords: radon, building metrics, deep learning, LSTM prediction model, lung cancer, canada, sweden

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Authors: Muhamad Aris Burhanudin, Angga Firmansyas, Bagus Jaya Santosa

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Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction.

Keywords: earthquake, fuzzy TOPSIS, neural network, tsunami

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Authors: Itsuo Yokoyama, Rika Kikuti, Naoko Watabe

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Introduction: It has been known that chronic kidney disease (CKD) patients can benefit from physical exercise during dialysis therapy improving aerobic capacity, muscle function, cardiovascular function, and overall health-related quality of life. This study aimed to evaluate the effectiveness of dialysis rehabilitation. Materials and Methods: A total of 55 patients underwent two-hour resistance exercise training during each hemodialysis session for three consecutive months. Various routine clinical data were collected, including the calculation of the planar dimension of the muscle area in both upper legs at the level of the ischial bone. This area calculation was possible in 26 patients who had yearly plain abdominal computed tomography (CT) scans. DICOM files from the CT scans were used with 3D Slicer software for area calculation. An age and sex-matched group of 26 patients without dialysis rehabilitation also had yearly CT scans during the study period for comparison. Clinical data were compared between the two groups: Group A (rehabilitation) and Group B (non-rehabilitation). Results: There were no differences in basic laboratory data between the two groups. The average muscle area before and after rehabilitation in Group A was 212 cm² and 216 cm², respectively. In Group B, the average areas were 230.0 cm² and 225.8 cm². While there was no significant difference in absolute values, the average percentage increase in muscle area was +1.2% (ranging from -7.6% to 6.54%) for Group A and -2.0% (ranging from -12.1% to 4.9%) for Group B, which was statistically significant. In Group A, 9 of 26 were diabetic (DM), and 13 of 26 in Group B were non-DM. The increase in muscle area for DM patients was 4.9% compared to -0.7% for non-DM patients, which was significantly different. There were no significant differences between the two groups in terms of nutritional assessment, Kt/V, or incidence of clinical complications such as cardiovascular events. Considerations: Dialysis rehabilitation has been reported to prevent muscle atrophy by increasing muscle fibers and capillaries. This study demonstrated that muscle volume increased after dialysis exercise, as evidenced by the increased muscle area in the thighs. Notably, diabetic patients seemed to benefit more from dialysis exercise than non-diabetics. Although this study is preliminary due to its relatively small sample size, it suggests that intradialytic physical training may improve insulin utilization in muscle fiber cells, particularly in type II diabetic patients where insulin receptor function and signaling are altered. Further studies are needed to investigate the detailed mechanisms underlying the muscle hypertrophic effects of dialysis exercise.

Keywords: dialysis, excercise, muscle, hypertrophy, diabetes, insulin

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Authors: Sanela Slavkovic, Congor Nad, Spela Golubovic

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Background: The diagnosis of multiple sclerosis (MS) is a major life challenge and has repercussions on all aspects of the daily functioning of those attained by it – personal activities, social participation, and quality of life. Regular follow-up of only the neurological status is not informative enough so that it could provide data on the sort of support and rehabilitation that is required. Objective: The aim of this study was to establish the current level of functioning of persons attained by MS and the factors that influence it. Methods: The study was conducted in Serbia, on a sample of 108 persons with relapse-remitting form of MS, aged 20 to 53 (mean 39.86 years; SD 8.20 years). All participants were fully ambulatory. Methods applied in the study include Expanded Disability Status Scale-EDSS and World Health Organization Disability Assessment Schedule, WHODAS 2.0 (36-item version, self-administered). Results: Participants were found to experience the most problems in the domains of Participation, Mobility, Life activities and Cognition. The least difficulties were found in the domain of Self-care. Symptom duration was the only control variable with a significant partial contribution to the prediction of the WHODAS scale score (β=0.30, p < 0.05). The total EDSS score correlated with the total WHODAS 2.0 score (r=0.34, p=0.00). Statistically significant differences in the domain of EDSS 0-5.5 were found within categories (0-1.5; 2-3.5; 4-5.5). The more pronounced a participant’s EDSS score was, although not indicative of large changes in the neurological status, the more apparent the changes in the functional domain, i.e. in all areas covered by WHODAS 2.0. Pyramidal (β=0.34, p < 0.05) and Bowel and bladder (β=0.24, p < 0.05) functional systems were found to have a significant partial contribution to the prediction of the WHODAS score. Conclusion: Measuring functioning and disability is important in the follow-up of persons suffering from MS in order to plan rehabilitation and define areas in which additional support is needed.

Keywords: disability, functionality, multiple sclerosis, rehabilitation

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Authors: Ryotaro Ishikawa

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INTRODUCTION: Post-traumatic stress disorder (PTSD) is a psychiatric label for a collection of psychological symptoms following a traumatic event. PTSD is as a result of a traumatic experience such as rape or sexual assault. A victim may have PTSD if she/he has experienced the following symptoms for at least a month: a) Stressor, b) Intrusion symptoms, c) Avoidance, d) Negative alterations in cognitions and mood, e) Alterations in arousal and reactivity. Studies on the cognitive theory of PTSD emphasized the roles of (a) negative appraisals of trauma memories in maintaining the symptomatology of PTSD, and (b) disorganized trauma memories in the development of PTSD. Mental contamination is primarily caused by experiences involving humans (e.g. violators or perpetrators) as opposed to substances (e.g. dirt or bodily fluids). Feelings of mental contamination may evoke following experiences of ill-treatment, sexual assault, domination, degradation, manipulation, betrayal, or humiliation. Some studies have demonstrated that traumatic thoughts related to sexual assault are particularly strong predictors of mental contamination. Treatment protocols based on cognitive-behavioral therapy appear to be beneficial in reducing the severity of PTSD and mental contamination. Studies on the cognitive theory of PTSD emphasized the roles of (A) negative appraisals of trauma memories in maintaining the symptomatology of PTSD, and (B) disorganized trauma memories in the development of PTSD. We will demonstrate a feasibility study of individual CBT for PTSD and mental contamination in Japanese clinical settings. METHOD: The single-arm trial is a group setting CBT intervention. The primary outcome is the self-rated Posttraumatic Stress Diagnostic Scale, with secondary measurements of depressive severity and mental pollution questionnaire. Assessments are conducted at baseline, after a waiting period before CBT, during CBT, and after CBT. RESULTS: Participants are eligible for the study and complete the outcome measures at all assessment points. In our hypothesis, receiving CBT would lead to improvements in primary and secondary PTSD severity. CONCLUSION: We will demonstrate a feasibility study of individual CBT for PTSD and mental contamination in Japanese clinical settings. Our treatment would achieve favorable treatment outcomes for PTSD with mental contamination in Japanese clinical settings.

Keywords: CBT, cognitive theory, PTSD, mental pollution

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Authors: Fatema Salman, Ridha Hammam, Fatima Khairallah, Fatima Aradi, Nafeesa Abdulla, Mohammed Alsafar

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Purpose: This study aims at measuring the extent of nurses’ knowledge and attitudes toward the use of physical restraints in different hospital wards at Salmaniya Medical Complex (SMC). Background: The habitual use of physical restraint is a widespread practice among nurses working in the clinical settings. Restraints inflict many deleterious consequences on patients physically and psychologically which in turn increases their morbidity and mortality risk and jeopardizes care quality. Nurses’ knowledge and attitudes toward physical restraints are crucial determinants of the persistence of this practice. Literature review: the evidence of lack of knowledge among nurses regarding the use of physical restraints is overwhelming in various clinical settings, especially in two main areas which are the negative consequences and the available alternatives to physical restraints. Studies explored nurses’ attitudes toward physical restraints yielded inconsistent findings. Equally comparable, some studies found that nurses hold positive attitudes toward the use of physical restraints while some others reported just the opposite. Methods: Self-administered knowledge and attitudes scales to 106 nurses working in the SMC. Findings: nurses hold the moderate level of knowledge about restraints (M=58%) with weak negative attitudes (M = -20%) toward using it. Significant moderately-strong negative correlation (r= -0.57, r2= 0.32, p= 0.000) was uncovered between nurses knowledge and their attitudes which provided an empirical explanation of this phenomenon (use of physical restraints). Recommendations: Induction of awareness program that especially focuses on the negative consequences and encourages the use of alternatives is an evident need. This effort necessarily should be adjoined with policy and procedure adjustments.

Keywords: attitudes, knowledge, nurses, restraints

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