Search results for: clinical predictions

Authors: G. Ravindranath, S. Savitha

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This paper presents heat transfer analysis of single horizontal bare tube and heat transfer analysis of staggered arrangement of bare tube bundles bare tube bundles in gas-solid (air-solid) fluidized bed and predictions are done by using Artificial Neural Network (ANN) based on experimental data. Fluidized bed provide nearly isothermal environment with high heat transfer rate to submerged objects i.e. due to through mixing and large contact area between the gas and the particle, a fully fluidized bed has little temperature variation and gas leaves at a temperature which is close to that of the bed. Measurement of average heat transfer coefficient was made by local thermal simulation technique in a cold bubbling air-fluidized bed of size 0.305 m. x 0.305 m. Studies were conducted for single horizontal Bare Tube of length 305mm and 28.6mm outer diameter and for bare tube bundles of staggered arrangement using beds of large (average particle diameter greater than 1 mm) particle (raagi and mustard). Within the range of experimental conditions influence of bed particle diameter ( Dp), Fluidizing Velocity (U) were studied, which are significant parameters affecting heat transfer. Artificial Neural Networks (ANNs) have been receiving an increasing attention for simulating engineering systems due to some interesting characteristics such as learning capability, fault tolerance, and non-linearity. Here, feed-forward architecture and trained by back-propagation technique is adopted to predict heat transfer analysis found from experimental results. The ANN is designed to suit the present system which has 3 inputs and 2 out puts. The network predictions are found to be in very good agreement with the experimental observed values of bare heat transfer coefficient (hb) and nusselt number of bare tube (Nub).

Keywords: fluidized bed, large particles, particle diameter, ANN

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Authors: Caixiu Pu, Zhen Chen

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We present the rare case of umbilical arterial atresia, leading to a good outcome and provide clinical and pathological findings. A 27-year-old nulliparous first gravida with PGDM was found single umbilical artery(SUA) by routine ultrasound san at 30 weeeks of gestation. Fetal status was monitored weekly. A healthy male newborn was delivered by cesarean section at 39 weeks. The umbilical cord was overly twisted and no thrombus was found along the whole diseased vessel. The cause of umbilical arterial atresia was unclear, and the correct diagnosis was a challenge. Expected clinical management was recommended, in which sonographic diagnosis may play a very important part.

Keywords: pregnancy, single umbilical artery, umbilical arterial atresia, prenatal diagnosis

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Authors: Ilana Margalith, Yaron Niv

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One of the most important factors of professional health treatment is teamwork, in which each discipline contributes its expert knowledge, thus ensuring quality and a high standard of care as well as efficient communication (one of the International Patient Safety Goals). However, in most countries, students are educated separately by each health discipline. They are exposed to teamwork only during their clinical experience, which in some cases is short and skill-oriented. In addition, health organizations in most countries are hierarchical and although changes have occurred in the hierarchy of the medical system, there are still disciplines that underrate the unique contributions of other health professionals, thus, young graduates of health professions develop and base their perception of their peers from other disciplines on insufficient knowledge. In order to establish a wide-ranging perception among nursing students as to the contribution of different health professionals to the health of their patients, students at the Clalit Nursing Academy, Rabin Campus (Dina), Israel, participated in an interdisciplinary clinical discussion with students from several different professions, other than nursing, who were completing their clinical experience at Rabin Medical Center in medicine, health psychology, social work, audiology, physiotherapy and occupational therapy. The discussion was led by a medical-surgical nursing instructor. Their tutors received in advance, a case report enabling them to prepare the students as to how to present their professional theories and interventions regarding the case. Mutual stimulation and acknowledgment of the unique contribution of each part of the team enriched the nursing students' understanding as to how their own nursing interventions could be integrated into the entire process towards a safe and speedy recovery of the patient.

Keywords: health professions' students, interdisciplinary clinical discussion, nursing education, patient safety

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Authors: Siddharth Jain, Abhenil Mittal, Surendra Kumar Sharma

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Background: With its recent emergence and re-emergence, dengue has become a major international public health concern, imposing significant financial burden especially in developing countries. Despite aggressive control measures in place, India experienced one of its largest outbreaks in 2015 with Delhi being most severely affected. There is a lack of reliable predictors of disease severity and mortality in dengue. The present study was carried out to identify these predictors during the 2015 outbreak. Methods: This prospective observational study conducted at an apex tertiary care center in Delhi, India included confirmed adult dengue patients admitted between August-November 2015. Patient demographics, clinical details, and laboratory findings were recorded in a predesigned proforma. Appropriate statistical tests were used to summarize and compare the clinical and laboratory characteristics and derive predictors of mortality and severe disease, while developing a clinical risk score for mortality. Serotype analysis was also done for 75 representative samples to identify the dominant serotypes. Results: Data of 369 patients were analyzed (mean age 30.9 years; 67% males). Of these, 198 (54%) patients had dengue fever, 125 (34%) had dengue hemorrhagic fever (DHF Grade 1,2)and 46 (12%) developed dengue shock syndrome (DSS). Twenty two (6%) patients died. Late presentation to the hospital (≥5 days after onset) and dyspnoea at rest were identified as independent predictors of severe disease. Age ≥ 24 years, dyspnoea at rest and altered sensorium were identified as independent predictors of mortality. A clinical risk score was developed (12*age + 14*sensorium + 10*dyspnoea) which, if ≥ 22, predicted mortality with a high sensitivity (81.8%) and specificity (79.2%). The predominant serotypes in Delhi (2015) were DENV-2 and DENV-4. Conclusion: Age ≥ 24 years, dyspnoea at rest and altered sensorium were identified as independent predictors of mortality. Platelet counts did not determine the outcome in dengue patients. Timely referral/access to health care is important. Development and use of validated predictors of disease severity and simple clinical risk scores, which can be applied in all healthcare settings, can help minimize mortality and morbidity, especially in resource limited settings.

Keywords: dengue, mortality, predictors, severity

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Authors: Vesile Unver, Tulay Basak, Hatice Ayhan, Ilknur Cinar, Emine Iyigun, Nuran Tosun

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The aim of this study is to analyze the effects of the hybrid simulation. In this simulation, types standardized patients and task trainers are employed simultaneously. For instance, in order to teach the IV activities standardized patients and IV arm models are used. The study was designed as a quasi-experimental research. Before the implementation an ethical permission was taken from the local ethical commission and administrative permission was granted from the nursing school. The universe of the study included second-grade nursing students (n=77). The participants were selected through simple random sample technique and total of 39 nursing students were included. The views of the participants were collected through a feedback form with 12 items. The form was developed by the authors and “Patient intervention self-confidence/competence scale”. Participants reported advantages of the hybrid simulation practice. Such advantages include the following: developing connections between the simulated scenario and real life situations in clinical conditions; recognition of the need for learning more about clinical practice. They all stated that the implementation was very useful for them. They also added three major gains; improvement of critical thinking skills (94.7%) and the skill of making decisions (97.3%); and feeling as if a nurse (92.1%). In regard to the mean scores of the participants in the patient intervention self-confidence/competence scale, it was found that the total mean score for the scale was 75.23±7.76. The findings obtained in the study suggest that the hybrid simulation has positive effects on the integration of theoretical and practical activities before clinical activities for the nursing students.

Keywords: hybrid simulation, clinical practice, nursing education, nursing students

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Authors: S. J. Yune, S. Y. Lee, S. J. Im, B. S. Kam, S. Y. Baek

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This study aimed to determine the reliability of clinical performance assessments, having been emphasized by ability-based education, and professors overall assessment methods. We addressed the following problems: First, we try to find out whether there is a difference in what we consider to be the main variables affecting the clinical performance test according to the evaluator’s working period and the number of evaluation experience. Second, we examined the relationship among the global rating score (G), analytic global rating score (Gc), and the sum of the analytical checklists (C). What are the main factors affecting clinical performance assessments in relation to the numbers of times the evaluator had administered evaluations and the length of their working period service? What is the relationship between overall assessment score and analytic checklist score? How does analytic global rating with 6 components in OSCE and 4 components in sub-domains (Gc) CPX: aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude overall assessment score and task-specific analytic checklist score sum (C) affect the professor’s overall global rating assessment score (G)? We studied 75 professors who attended a 2016 Bugyeoung Consortium clinical skills performances test evaluating third and fourth year medical students at the Pusan National University Medical school in South Korea (39 prof. in OSCE, 36 prof. in CPX; all consented to participate in our study). Each evaluator used 3 forms; a task-specific analytic checklist, subsequent analytic global rating scale with sub-6 domains, and overall global scale. After the evaluation, the professors responded to the questionnaire on the important factors of clinical performance assessment. The data were analyzed by frequency analysis, correlation analysis, and hierarchical regression analysis using SPSS 21.0. Their understanding of overall assessment was analyzed by dividing the subjects into groups based on experiences. As a result, they considered ‘precision’ most important in overall OSCE assessment, and ‘precise accuracy physical examination’, ‘systemic approaches to taking patient history’, and ‘diagnostic skill capability’ in overall CPX assessment. For OSCE, there was no clear difference of opinion about the main factors, but there was for CPX. Analytic global rating scale score, overall rating scale score, and analytic checklist score had meaningful mutual correlations. According to the regression analysis results, task-specific checklist score sum had the greatest effect on overall global rating. professors regarded task-specific analytic checklist total score sum as best reflecting overall OSCE test score, followed by aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude on a subsequent analytic global rating scale. For CPX, subsequent analytic global rating scale score, overall global rating scale score, and task-specific checklist score had meaningful mutual correlations. These findings support explanations for validity of professors’ global rating in clinical performance assessment.

Keywords: global rating, clinical performance assessment, medical education, analytic checklist

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Authors: Ian McCulloh, Andrew Placona, Darren Stewart, Daniel Gause, Kevin Kiernan, Morgan Stuart, Christopher Zinner, Laura Cartwright

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An estimated 22-25% of viable deceased donor kidneys are discarded every year in the US, while waitlisted candidates are dying every day. As many as 85% of transplanted organs are refused at least once for a patient that scored higher on the match list. There are hundreds of clinical variables involved in making a clinical transplant decision and there is rarely an ideal match. Decision makers exhibit an optimism bias where they may refuse an organ offer assuming a better match is imminent. We propose a semi-parametric Cox proportional hazard model, augmented by an accelerated failure time model based on patient specific suitable organ supply and demand to estimate a time-to-next-offer. Performance is assessed with Cox-Snell residuals and decision curve analysis, demonstrating improved decision support for up to a 5-year outlook. Providing clinical decision makers with quantitative evidence of likely patient outcomes (e.g., time to next offer and the mortality associated with waiting) may improve decisions and reduce optimism bias, thus reducing discarded organs and matching more patients on the waitlist.

Keywords: decision science, KDPI, optimism bias, organ transplant

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Authors: Atitallah Sofien, Bouyahia Olfa, Hadj Salah Ibrahim, Ben Saleh Foued, Missaoui Nada, Ben Rabeh Rania, Yahyaoui Salem, Mazigh Sonia, Boukthir Samir

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Introduction: Carbon monoxide (CO) poisoning is a common pathology responsible for high morbidity and mortality worldwide. Aim: The purpose of this study was to determine the epidemiological profile of CO poisoning as well as its clinical, paraclinical, therapeutic, and evolutionary aspects. Methods: Our study included observations of CO poisoning in children hospitalized in the pediatric department C of the Children's Hospital in Tunis over a period of 3 years. Results: We have collected 199 cases of CO poisoning in children. The average age was 5.43 years, with a sex ratio of 0.98. The source of CO was inside the home in 73.2% of cases, and it was the gas bath heater in 68.8% of cases. The intoxication was collective in 93.5% of the cases, and it occurred during the month of January in 35.8% of the cases. The clinical manifestations were headaches in 69.5% of cases. The rate of carboxyhemoglobin was pathological in 73.9% of cases. All patients received normobaric oxygen therapy, and only 3.6% of patients had a hyperbaric oxygen therapy session. We did not deplore any case of death in our study. Conclusion: CO poisoning remains a public health problem in Tunisia with high morbidity. The risk of secondary complications, particularly neuropsychiatric, requires clinical and possibly neuroradiological monitoring of these victims.

Keywords: poisoning, carbon monoxide, children, hyperbaric oxygenation

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Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

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Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

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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: Shi-xia Xu, Zai-wen Zhang, Ru-xue Chen, Shan Zhou, Xiang-feng Tang

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Objective: The clinical influence of HLA-DPB1 mismatches on clinical outcome of HSCT is less clear. This is the first meta-analysis to study the HLA-DPB1 matching statues on clinical outcomes after unrelated donor HSCT. Methods: We searched the CIBMTR, Cochrane Central Register of Controlled Trials (CENTRAL) and related databases (1995.01–2017.06) for all relevant articles. Comparative studies were used to investigate the HLA-DPB1 loci mismatches on clinical outcomes after unrelated donor HSCT, such as the disease-free survival (DFS), overall survival, GVHD, relapse, and transplant-related mortality (TRM). We performed meta-analysis using Review Manager 5.2 software and funnel plot to assess the bias. Results: At first, 1246 articles were retrieved, and 18 studies totaling 26368 patients analyzed. Pooled comparisons of studies found that the HLA-DPB1 mismatched group had a lower rate of DFS than the DPB1-matched group, and lower OS in non-T cell depleted transplantation. The DPB1 mismatched group has a higher incidence of aGVHD and more severe ( ≥ III degree) aGvHD, lower rate of relapse and higher TRM. Moreover, compared with 1-antigen mismatch, 2-antigen mismatched led to a higher risk of TRM and lower relapse rate. Conclusions: This meta-analysis indicated HLA-DPB1 has important influence on survival and transplant-related complications during unrelated donor HSCT and HLA-DPB1 donor selection strategies have been proposed based on a personalized algorithm.

Keywords: human leukocyte antigen, DPB1, transplant, meta-analysis, outcome

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Authors: Jhe-Hao Huang, Kun-Da Wu, Wei-Cheng Shih, Jui-Pin Hung

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This study presented the investigation on the dynamic characteristics of a spindle tool system by experimental and finite element modeling approaches. As well known facts, the machining stability is greatly determined by the dynamic characteristics of the spindle tool system. Therefore, understanding the factors affecting dynamic behavior of a spindle tooling system is a prerequisite in dominating the final machining performance of machine tool system. To this purpose, a physical spindle unit was employed to assess the dynamic characteristics by vibration tests. Then, a three-dimensional finite element model of a high-speed spindle system integrated with tool holder was created to simulate the dynamic behaviors. For modeling the angular contact bearings, a series of spring elements were introduced between the inner and outer rings. The spring constant can be represented by the contact stiffness of the rolling bearing based on Hertz theory. The interface characteristic between spindle nose and tool holder taper can be quantified from the comparison of the measurements and predictions. According to the results obtained from experiments and finite element predictions, the vibration behavior of the spindle is dominated by the bending deformation of the spindle shaft in different modes, which is further determined by the stiffness of the bearings in spindle housing. Also, the spindle unit with tool holder shows a different dynamic behavior from that of spindle without tool holder. This indicates the interface property between tool holder and spindle nose plays an dominance on the dynamic characteristics the spindle tool system. Overall, the dynamic behaviors the spindle with and without tool holder can be successfully investigated through the finite element model proposed in this study. The prediction accuracy is determined by the modeling of the rolling interface of ball bearings in spindles and the interface characteristics between tool holder and spindle nose. Besides, identifications of the interface characteristics of a ball bearing and spindle tool holder are important for the refinement of the spindle tooling system to achieve the optimum machining performance.

Keywords: contact stiffness, dynamic characteristics, spindle, tool holder interface

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Authors: P. Sathyathas, H. M. I. S. W. Herath, T. Amalraj, U. J. M. A. L. Jayasinghe

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Over two thirds of medical radiation can now be attributed to Computed Tomography (CT). There is little information on amount of radiation received from multiphase CT scan of abdomen- pelvic region in clinical practice. We sought to estimate the radiation dose and associated exposure parameters in the multiphase abdomen - pelvic scan of Multideteror Computed Tomography (MDCT) studies in clinical practice. This was a retrospective cross sectional studies describing radiation dose associated with main exposure parameters in diagnostic multiphase abdomen - pelvic scans performed on 152 consecutive patients by two different sixteen slice CT scanners. Patient information, exposure parameters of CTDI (volume), DLP, kVp, mAs and pitch were recorded for every phases of abdomen- a pelvic study from dose report of MDCT scanners (MDCTs). Age of patients range from 14 years to 87 years in both MDCT scanners. Overall CTDI (volume) median was 63.8 (±10.4) mGy for a multiphase abdominal-pelvic scan with scanner A while it was 35.4 (±15.6) mGy for scanner B. Patients' effective dose for multiphase abdomen - pelvic CT scan range from 8.2 mSv to 58 mSv. Median effective dose for patients, who underwent multiphase abdomen- pelvis scan with scanner A and B were 38.5 (± 8.2) mSv and 21.3 (± 8.6) mSv respectively. Median value of exposure parameters of mAs, kVp and pitch, were 150 (±29.7), 130 (±15.3) and 1.3 (±0.1) respectively in scanner A. In scanner B; they were 60 (±14.5), 120 and 1. The median effective dose for patients between multiphase abdomen-pelvic scan of both MDCT, a significant different (P<0.05) was observed. Multiphase abdomen – pelvic scan of clinical study shows significant different of effective dose with reference level of phantom studies (8-14mSv) and it depends on the type of vendors.

Keywords: abdomen-pelvic region, computed tomography, exposure parameters, radiation dose

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Authors: Eddy K. Mukadi

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This work is a documentary and descriptive study devoted to the epidemiological, clinical, histopathological and therapeutic profile of breast cancer deals with the department of gynecology and obstetrics of the university clinics of Kinshasa during the period from 1 January 2014 to 31 December 2014. We have identified 56 cases of breast cancer. These cancers accounted for 45.2% of gynecological mammary cancers. The youngest in our series was 18 years old while the oldest was 74 years old; And the mean age of these patients was 43.4 years and mostly multiparous (35.7%). Brides (60.7%) and bachelors (26.8%) were the most affected by breast cancer. The reasons for consultation were dominated by nodules in the breast (48.2%) followed by pain (35.7%) and nipple discharge (14.3%). In 89.2% of the cases, it was the advanced clinical stage (stage 3 and 4) and the infiltrating ductal carcinoma was the most frequent histological type (75%) The malignant tumor was mainly in the left breast (55.3%), and chemotherapy with hormone therapy and patey was the most convenient treatment (42.8%), while patey mastectomy was performed in 12.5% of patients. Because of the high incidence of breast cancer identified in our study, some preventive measures must be taken into account to address this public health problem, including breast autopalpation once a month, Early detection system development of a national breast cancer policy and the implementation of a national breast cancer control program.

Keywords: breast cancer, histopathological profile, epidemiological profile, Kinshasa

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Authors: Aliakbar Hafezi, Jalal Taherian, Mahsa Elahi, Jamshid Abedi

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Background: Patients with breast cancer with different molecular subtypes may have different pathological responses to neoadjuvant chemotherapy (NAC). The aim of this study was to evaluate the pathological response to NAC in patients with locally advanced breast cancer based on molecular subtypes. Method: In this retrospective cohort study, 210 female patients with breast cancer candidate for NAC referred to the radiation oncology departments in southern Iran between August 2019 and September 2024 were evaluated in terms of pathologic complete response (pCR) based on immunohistochemical molecular markers (estrogen and progesterone receptors, Her-2/neu and Ki-67), overall survival (OS) and disease-free survival (DFS). Results: The mean age of the patients was 38.22 ± 10.34 years, and 68 patients (32.4%) had a positive family history of breast cancer. The pCR rate was 17.6% (37 patients), which in the subtypes of luminal A, luminal B, Her-2/neu positive and triple negative was 7.7%, 16.9%, 26.5% and 21.05%, respectively. Patients with pCR had significantly better OS (78.4% vs. 49.1%, P = 0.014) and DFS (83.8% vs. 51.4%, P = 0.020) than patients with partial/no pathological response. Conclusion: It seems that the molecular subtype plays a decisive role in the clinical outcome and the pathological response to NAC in patients with locally advanced breast cancer.

Keywords: locally advanced breast cancer, neoadjuvant chemotherapy, pathologic complete response, clinical outcomes

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Authors: Hamza Ikhlaq, Stephen Franks

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Background: Polycystic ovarian syndrome (PCOS) is one of the most common endocrine disorders affecting women of reproductive age. The aetiology behind PCOS is poorly understood but influencing ethnic, environmental, and genetic factors have been recognised. However, literature examining the impact of ethnicity is scarce. We hypothesised Body Mass Index (BMI) and ethnicity influence the clinical, metabolic, and biochemical presentations of PCOS, with an interaction between these factors. Methods: A database of 1081 women with PCOS and a control group of 72 women were analysed. BMIs were grouped using the World Health Organisation classification into normal weight, overweight and obese groups. Ethnicities were classified into European, South Asian, and Afro-Caribbean groups. Biochemical and clinical presentations were compared amongst these groups, and statistical analyses were performed to assess significance. Results: This study revealed ethnicity significantly influences biochemical and clinical presentations of PCOS. A greater proportion of South Asian women are impacted by menstrual cycle disturbances and hirsutism than European and Afro-Caribbean women. South Asian and Afro-Caribbean women show greater measures of insulin resistance and weight gain when compared to their European peers. Women with increased BMI are shown to have an increased prevalence of PCOS phenotypes alongside increased levels of insulin resistance and testosterone. Furthermore, significantly different relationships between the waist-hip ratio and measures of insulin and glucose control for Afro-Caribbean women were identified compared to other ethnic groups. Conclusions: The findings of this study show ethnicity significantly influence the phenotypic and biochemical presentations of PCOS, with an interaction between body habitus and ethnicity found. Furthermore, we provide further data on the influences of BMI on the manifestations of PCOS. Therefore, we highlight the need to consider these factors when reviewing diagnostic criteria and delivering clinical care for these groups.

Keywords: PCOS, ethnicity, BMI, clinical

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Authors: Swati Kishor Zode, Rahul Ambekar

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Data mining is the extraction of fascinating examples on the other hand information from enormous measure of information and choice is made as indicated by the applicable information extracted. As of late, with the dangerous advancement in internet, stockpiling of information and handling procedures, privacy preservation has been one of the major (higher) concerns in data mining. Various techniques and methods have been produced for protection saving data mining. In the situation of Clinical Decision Support System, the choice is to be made on the premise of the data separated from the remote servers by means of Internet to diagnose the patient. In this paper, the fundamental thought is to build the precision of Decision Support System for multiple diseases for different maladies and in addition protect persistent information while correspondence between Clinician side (Client side) also, the Server side. A privacy preserving protocol for clinical decision support network is proposed so that patients information dependably stay scrambled amid diagnose prepare by looking after the accuracy. To enhance the precision of Decision Support System for various malady C5.0 classifiers and to save security, a Homomorphism encryption algorithm Paillier cryptosystem is being utilized.

Keywords: classification, homomorphic encryption, clinical decision support, privacy

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Authors: Mehmet Bulent Ozdemir, Sultan Çagirici, Sahika Pinar Akyer, Fikri Turk

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Neuroanatomical appearance can be correlated with clinical or other characteristics of illness. With the introduction of diagnostic imaging machines, producing 3D images of anatomic structures, calculating the correlation between subjects and pattern of the structures have become possible. The aim of this study is to examine the 3D structure of hippocampus in cases with Alzheimer disease in different dementia severity. For this purpose, 62 female and 38 male- 68 patients’s (age range between 52 and 88) MR scanning were imported to the computer. 3D model of each right and left hippocampus were developed by a computer aided propramme-Surf Driver 3.5. Every reconstruction was taken by the same investigator. There were different apperance of hippocampus from normal to abnormal. In conclusion, These results might improve the understanding of the correlation between the morphological changes in hippocampus and clinical staging in Alzheimer disease.

Keywords: Alzheimer disease, hippocampus, computer-assisted anatomy, 3D

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Authors: Marlin Mubarak

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Background: Endometriosis is a complex disabling disease affecting young females in the reproductive period mainly. The aim of this project is to generate a diagnostic model to predict severity and stage of endometriosis prior to Laparoscopic surgery. This will help to improve the pre-operative diagnostic accuracy of stage 3 & 4 endometriosis and as a result, refer relevant women to a specialist centre for complex Laparoscopic surgery. The model is based on the British Society of Gynaecological Endoscopy (BSGE) pain questionnaire, clinical examination and ultrasound scan. Design: This is a prospective, observational, study, in which women completed the BSGE pain questionnaire, a BSGE requirement. Also, as part of the routine preoperative assessment patient had a routine ultrasound scan and when recto-vaginal and deep infiltrating endometriosis was suspected an MRI was performed. Setting: Luton & Dunstable University Hospital. Patients: Symptomatic women (n = 56) scheduled for laparoscopy due to pelvic pain. The age ranged between 17 – 52 years of age (mean 33.8 years, SD 8.7 years). Interventions: None outside the recognised and established endometriosis centre protocol set up by BSGE. Main Outcome Measure(s): Sensitivity and specificity of endometriosis diagnosis predicted by symptoms based on BSGE pain questionnaire, clinical examinations and imaging. Findings: The prevalence of diagnosed endometriosis was calculated to be 76.8% and the prevalence of advanced stage was 55.4%. Deep infiltrating endometriosis in various locations was diagnosed in 32/56 women (57.1%) and some had DIE involving several locations. Logistic regression analysis was performed on 36 clinical variables to create a simple clinical prediction model. After creating the scoring system using variables with P < 0.05, the model was applied to the whole dataset. The sensitivity was 83.87% and specificity 96%. The positive likelihood ratio was 20.97 and the negative likelihood ratio was 0.17, indicating that the model has a good predictive value and could be useful in predicting advanced stage endometriosis. Conclusions: This is a hypothesis-generating project with one operator, but future proposed research would provide validation of the model and establish its usefulness in the general setting. Predictive tools based on such model could help organise the appropriate investigation in clinical practice, reduce risks associated with surgery and improve outcome. It could be of value for future research to standardise the assessment of women presenting with pelvic pain. The model needs further testing in a general setting to assess if the initial results are reproducible.

Keywords: deep endometriosis, endometriosis, minimally invasive, MRI, ultrasound.

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Authors: Michelangelo Sofo, Giuseppe Labianca

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In recent years, the scientific community's interest in the exploratory analysis of biomedical data has increased exponentially. Considering the field of research of nutritional biologists, the curative process, based on the analysis of clinical data, is a very delicate operation due to the fact that there are multiple solutions for the management of pathologies in the food sector (for example can recall intolerances and allergies, management of cholesterol metabolism, diabetic pathologies, arterial hypertension, up to obesity and breathing and sleep problems). In this regard, in this research work a system was created capable of evaluating various dietary regimes for specific patient pathologies. The system is founded on a mathematical-numerical model and has been created tailored for the real working needs of an expert in human nutrition using the human-centered design (ISO 9241-210), therefore it is in step with continuous scientific progress in the field and evolves through the experience of managed clinical cases (machine learning process). DietAdhoc® is a decision support system nutrition specialists for patients of both sexes (from 18 years of age) developed with an agile methodology. Its task consists in drawing up the biomedical and clinical profile of the specific patient by applying two algorithmic optimization approaches on nutritional data and a symbolic solution, obtained by transforming the relational database underlying the system into a deductive database. For all three solution approaches, particular emphasis has been given to the explainability of the suggested clinical decisions through flexible and customizable user interfaces. Furthermore, the system has multiple software modules based on time series and visual analytics techniques that allow to evaluate the complete picture of the situation and the evolution of the diet assigned for specific pathologies.

Keywords: medical decision support, physiological data extraction, data driven diagnosis, human centered AI, symbiotic AI paradigm

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Authors: Paria Baharvand, Mohammad Reza Abbasi, Soha Namazi

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Introduction: Uremic pruritus (UP) is one of the major complaints in hemodialysis patients. The aim of this randomized clinical trial study was the evaluation of the anti-pruritus effect of Melatonin on hemodialysis patients with UP. Methods: This multi-centered double, blinded randomized clinical trial study was conducted on hemodialysis patients with UP that referred to the dialysis department of Imam Khomeini Hospital, Labbafinezhad Hospital and Ghiasi Hospital in Tehran, Iran, in 2018. Forty participants were enrolled and block randomization was performed by using a randomized list and divided into 2 groups of twenty patients. Evaluation of the 12-Item Pruritus Severity Scale (12-PSS), Visual analog scale (VAS), and Calculation of the affected body surface area for pruritus extent (BSA %) was performed every week. The Melatonin group received a 10 mg soft gel capsule, and the placebo group received a soft gel capsule placebo after dinner. For statistical analysis used by SPSS version 21(IRCT20180714040462N1). Results: 38 hemodialysis patients enrolled in this study. The mean age in the placebo group and in the Melatonin group was 55.88 ± 11.70 and 54.52 ± 13.00 years (p> 0.05). Also, 46% of all participants were female. Aspartate transaminase, alanine transaminase and C-reactive protein have significant differences between the two groups (p< 0.05). VAS score reduction in the two groups had a statistically significant (CI 95% = -1.71, P= 0.015(.The results of BSA% showed Melatonin had a significant effect on the decrease of the pruritus extent compared to placebo (CI 95% = -22.82, P= 0.001(. Conclusion: According to the results of this study and the preliminary effects of Melatonin on uremic pruritus, we suggest performing advanced clinical trials studies.

Keywords: Melatonin, Uremic Pruritus, hemodialysis, anti-pruritus

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Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

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Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

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Authors: Zahra Salehi Shahrbabaki, Zahra Chavoshzadeh, Fahimeh Abdollahimajd, Samin Sharafian, Tolue Mahdavi, Mahnaz Jamee

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Background: Inborn errors of immunity (IEIs) are monogenic diseases of the immune the system with broad clinical manifestations. Despite the increasing genetic advancements, the diagnosis of IEIs still leans on clinical diagnosis. Dermatologic manifestations are observed in a large number of IEI patients and can lead to proper approach, prompt intervention and improved prognosis. Methods: This cross-sectional study was carried out between 2018 and 2020 on IEIs at a Children's tertiary care center in Tehran, Iran. Demographic details (including age, sex, and parental consanguinity), age at onset of symptoms and family history of IEI with were recorded. Results :212 patients were included. Cutaneous findings were reported in (95 ,44.8%) patients. and 61 of 95 (64.2%) reported skin lesions as the first clinical presentation. Skin infection (69, 72.6%) was the most frequent cutaneous manifestation, followed by an eczematous rash (24, 25 %). Conclusions: Skin manifestations are common feature in IEI patients and can be readily recognizable by healthcare providers. This study tried to provide information on prognostic consequences.

Keywords: primary immuno deficiency, inborn errror of metabolism, skin manifestation, skin infection

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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: Guy Rubin, Ravit Shay, Nimrod Rozen

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The accuracy of a diagnostic test used to classify a patient as having disease or being disease-free is a valuable piece of information to be used by the physician when making treatment decisions. Finger laceration, suspected to have nerve injury is a challenging decision for the treating surgeon. The purpose of this study was to evaluate the sensitivity, specificity and predictive values of six clinical tests in the diagnosis of digital nerve injury. The six clinical tests included light touch, pin prick, static and dynamic 2-point discrimination, Semmes Weinstein monofilament and wrinkle test. Data comparing pre-surgery examination with post-surgery results of 42 patients with 52 digital nerve injury was evaluated. The subjective examinations, light touch, pin prick, static and dynamic 2-point discrimination and Semmes-Weinstein monofilament were not sensitive (57.6, 69.7, 42.4, 40 and 66.8% respectively) and specific (36.8, 36.8, 47.4, 42.1 and 31.6% respectively). Wrinkle test, the only objective examination, was the most sensitive (78.1%) and specific (55.6%). This result gives no pre-operative examination the ability to predict the result of explorative surgery.

Keywords: digital nerve, injury, nerve examination, Semmes-Weinstein monofilamen, sensitivity, specificity, two point discrimination, wrinkle test

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Authors: Qin-Min Ge, Shu-Ming Pan

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Emergency clinicians usually get teaching qualification after graduating from medical universities without special faculty training in China mainland. Emergency departments are overcrowded places, with large numbers of patients suffering undifferentiated illness. In the field of emergency medicine (EM), improving the faculty competencies and developing the teaching skills are important for medical education, they could enhance learners outcomes and hence affect the patients prognosis indirectly. This article highlights the necessities of faculty training in EM, illustrates the qualities a good clinical educator should qualify, advances the skills as educators in an academic setting and discusses the ways to be good clinical teachers.

Keywords: emergency education, competence, faculty training, teaching, emergency medicine

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Authors: Nizar Ghali, Bernard Fortin, Guy Lacroix

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In Quebec, colonoscopies volumes have continued to rise in recent years in the absence of effective monitoring mechanism for the appropriateness and the quality of these exams. In 2010, November, Quebec Government introduced the colorectal cancer-screening program in the objective to control for volume and cost imperfection. This program is based on clinical standards and was initiated for first group of institutions. One year later, Government adds financial incentives for participants institutions. In this analysis, we want to assess for the causal effect of the two components of this program: clinical pathways and financial incentives. Especially we assess for the reform effect on healthcare quality and population health in the context that medical remuneration is not directly dependent on this additional funding offered by the program. We have data on admissions episodes and deaths for 8 years. We use multistate model analog to difference in difference approach to estimate reform effect on the transition probability between different states for each patient. Our results show that the reform reduced length of stay without deterioration in hospital mortality or readmission rate. In the other hand, the program contributed to decrease the hospitalization rate and a less invasive treatment approach for colorectal surgeries. This is a sign of healthcare quality and population health improvement. We demonstrate in this analysis that physicians’ behavior can be affected by both clinical standards and financial incentives even if offered to facilities.

Keywords: multi-state and multi-episode transition model, healthcare quality, length of stay, transition probability, difference in difference

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Authors: Jose Daniel Hoyos Giraldo, Jesus Hernan Jimenez Giraldo, Juan Pablo Alvarado Perilla

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Range and endurance are the main limitations of electric aircraft due to the nature of its source of power. The improvement of efficiency on this kind of systems is extremely meaningful to encourage the aircraft operation with less environmental impact. The propeller efficiency highly affects the overall efficiency of the propulsion system; hence its optimization can have an outstanding effect on the aircraft performance. An optimization method is applied to an aircraft propeller in order to maximize its range and endurance by estimating the best combination of geometrical parameters such as diameter and airfoil, chord and pitch distribution for a specific aircraft design at a certain cruise speed, then the rotational speed at which the propeller operates at minimum current consumption is estimated. The optimization is based on the Blade Element Momentum (BEM) method, additionally corrected to account for tip and hub losses, Mach number and rotational effects; furthermore an airfoil lift and drag coefficients approximation is implemented from Computational Fluid Dynamics (CFD) simulations supported by preliminary studies of grid independence and suitability of different turbulence models, to feed the BEM method, with the aim of achieve more reliable results. Additionally, Vortex Theory is employed to find the optimum pitch and chord distribution to achieve a minimum induced loss propeller design. Moreover, the optimization takes into account the well-known brushless motor model, thrust constraints for take-off runway limitations, maximum allowable propeller diameter due to aircraft height and maximum motor power. The BEM-CFD method is validated by comparing its predictions for a known APC propeller with both available experimental tests and APC reported performance curves which are based on Vortex Theory fed with the NASA Transonic Airfoil code, showing a adequate fitting with experimental data even more than reported APC data. Optimal propeller predictions are validated by wind tunnel tests, CFD propeller simulations and a study of how the propeller will perform if it replaces the one of on known aircraft. Some tendency charts relating a wide range of parameters such as diameter, voltage, pitch, rotational speed, current, propeller and electric efficiencies are obtained and discussed. The implementation of CFD tools shows an improvement in the accuracy of BEM predictions. Results also showed how a propeller has higher efficiency peaks when it operates at high rotational speed due to the higher Reynolds at which airfoils present lower drag. On the other hand, the behavior of the current consumption related to the propulsive efficiency shows counterintuitive results, the best range and endurance is not necessary achieved in an efficiency peak.

Keywords: BEM, blade design, CFD, electric aircraft, endurance, optimization, range

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Authors: Sanjay Saraf

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The oral cavity can be the site for early manifestations of mucocutaneous disorders (MD) or the only site for occurrence of these disorders. It can also exhibit oral lesions with simultaneous associated skin lesions. The MD involving the oral mucosa commonly presents with signs such as ulcers, vesicles and bullae. The unique environment of the oral cavity may modify these signs of the disease, thereby making the clinical diagnosis an arduous task. In addition to the unique environment of oral cavity, the overlapping of the signs of various mucocutaneous disorders, also makes the clinical diagnosis more intricate. The aim of this review is to present the oral signs of dermatological disorders having common oral involvement and emphasize their importance in early detection of the systemic disorders. The aim is also to highlight the necessity of oral examination by a dermatologist while examining the skin lesions. Prior to the oral examination, it must be imperative for the dermatologists and the dental clinicians to have the knowledge of oral anatomy. It is also important to know the impact of various diseases on oral mucosa, and the characteristic features of various oral mucocutaneous lesions. An initial clinical oral examination is may help in the early diagnosis of the MD. Failure to identify the oral manifestations may reduce the likelihood of early treatment and lead to more serious problems. This paper reviews the oral manifestations of immune mediated dermatological disorders with common oral manifestations.

Keywords: dermatological investigations, genodermatosis, histological features, oral examination

Procedia PDF Downloads 357

Authors: Nabil A. A. Mohamed, Alaa A. A. Balbaa, Khaled E. Ayad

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Osteoarthritis (OA) of the knee is the most common form of arthritis and leads to more activity limitations (e.g., disability in walking and stair climbing) than any other disease, especially in the elderly. Recently, impaired proprioceptive accuracy of the knee has been proposed as a local factor in the onset and progression of radiographic knee OA (ROA). Purpose: To compare the clinical and radiological findings in healthy with that of knee OA. Also, to determine if there is a correlation between the clinical and radiological findings in patients with knee OA. Subjects: Fifty one patients diagnosed as unilateral or bilateral knee OA with age ranged between 35-70 years, from both gender without any previous history of knee trauma or surgery, and twenty one normal subjects with age ranged from 35 - 68 years. METHODS: peak torque/body weight (PT/BW) was recorded from knee extensors at isokinetic isometric mode at angle of 45 degree. Also, the Absolute Angular Error was recorded at 45O and 30O to measure joint position sense (JPS). They made anteroposterior (AP) plain X-rays from standing semiflexed knee position and their average score of Timed Up and Go test(TUG) and WOMAC were recorded as a measure of knee pain, stiffness and function. Comparison between the mean values of different variables in the two groups was performed using unpaired student t test. The P value less or equal to 0.05 was considered significant. Results: There were significant differences between the studied variables between the experimental and control groups except the values of AAE at 30O. Also, there were no significant correlation between the clinical findings (pain, function, muscle strength and proprioception) and the severity of arthritic changes in X-rays. CONCLUSION: From the finding of the current study we can conclude that there were a significant difference between the both groups in all studied parameters (the WOMAC, functional level, quadriceps muscle strength and the joint proprioception). Also this study did not support the dependency on radiological findings in management of knee OA as the radiological features did not necessarily indicate the level of structural damage of patients with knee OA and we should consider the clinical features in our treatment plan.

Keywords: joint position sense, peak torque, proprioception, radiological knee osteoarthritis

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