47 resultados para Medical and biological imaging
Resumo:
Objectives Medical and dental students experience poor psychological well-being relative to their peers. This study aimed to assess the psychological well-being among medical and dental students in Saudi Arabia, identify the high-risk groups and assess the association between the psychological well-being and the academic performance. Methods In this cross-sectional study, 422 preclinical medical and dental students at Umm Al-Qura University, Saudi Arabia, were recruited to assess their depression, anxiety, stress, self-efficacy and satisfaction with life levels using 21-items Depression Anxiety Stress Scale (DASS-21), General Self-Efficacy (GSE) scale and Satisfaction With Life Scale (SWLS). Students’ academic weighted grades were obtained later. Descriptive statistics and univariate general linear model were used to analyse data. Results High levels of depression (69.9%), anxiety (66.4%) and stress (70.9%) were indicated, whereas self-efficacy (mean = 27.22, sd = 4.85) and life satisfaction (mean = 23.60, sd = 6.37) were within the normal range. Female medical students had higher psychological distress in contrast to dental students. In general, third-year students were more depressed and stressed in comparison with second-year students, except for stress among dental students. Moreover, all females had higher self-efficacy than males. Life satisfaction was higher within the second-year and high family income students. Depression was the only psychological variable correlated with the academic performance. Conclusion High levels of psychological distress were found. Female medical students had higher psychological distress than males, whereas male dental students had higher distress than female. Medical students at third year were more depressed and stressed. Dental students were more depressed in the third year, but more stressed in the second year. Attention should be directed towards reducing the alarming levels of depression, anxiety and stress among medical and dental students.
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Dorsiflexion (DF) of the foot plays an essential role in both controlling balance and human gait. Electromyography and Sonomyography can provide information on several aspects of muscle function. The aim was to describe a new method for real-time monitoring of muscular activity, as measured using EMG, muscular architecture, as measured using SMG, force, as measured using dynamometry, and kinematic parameters, as measured using IS during isometric and isotonic contractions of the foot DF. The present methodology may be clinically relevant because it involves a reproducible procedure which allows the function and structure of the foot DF to be monitored.
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Study Design Cross-sectional study. Objectives To compare erector spinae (ES) muscle fatigue between chronic non-specific lower back pain (CNLBP) sufferers and healthy subjects from a biomechanical perspective during fatiguing isometric lumbar extensions. Background Paraspinal muscle maximal contraction and fatigue are used as a functional predictor for disabilities. The simplest method to determine muscle fatigue is by evaluating the evolution during specific contractions, such as isometric contractions. There are no studies that evaluate the evolution of the ES muscle during fatiguing isometric lumbar extensions and analyse functional and architectural variables. Methods In a pre-calibrated system, participants performed a maximal isometric extension of the lumbar spine for 5 and 30 seconds. Functional variables (torque and muscle activation) and architecture (pennation angle and muscle thickness) were measured using a load cell, surface electromyography and ultrasound, respectively. The results were normalised and a reliability study of the ultrasound measurement was made. Results: The ultrasound measurements were highly reliable, with Cronbach’s alpha values ranging from 0.951 0.981. All measured variables shown significant differences before and after fatiguing isometric lumbar extension. Conclusion During a lumbar isometric extension test, architecture and functional variables of the ES muscle could be analised using ultrasound, surface EMG and load cell. In adition, during an endurance test, ES muscle suffers an acute effect on architectural and functional variables.
Resumo:
Background Psychological distress is well-documented worldwide among medical and dental students. Few studies have assessed the impact of self-development coaching programs on the students’ psychological health. The aim of the study was to evaluate the effect of a self-development coaching programme on the psychological health and academic performance of preclinical medical and dental students at Umm Al-Qura University, Saudi Arabia. Methods Four-hundred and twenty-two participants (n = 422, 20–22 years) fulfilled the study requirements and were invited into a parallel-randomised controlled trial that was partially blinded. Participants were stratified by faculty, gender, and academic year, and then randomised. A total of 156 students participated in the intervention group (IG) and 163 students participated in the control group (CG). The IG received the selfdevelopment programme, involving skills and strategies aimed to improve students’ psychological health and academic performance, through a two-day workshop. Meanwhile, the CG attended an active placebo programme focussing on theoretical information that was delivered through a five-hour workshop. Both programmes were conducted by the same presenter during Week 1 of the second semester of the 2012–2013 academic year. Data were gathered immediately before (T1), one week after (T2) and five weeks (T3) after the intervention. Psychological health was measured using the Depression Anxiety Stress Scale (DASS-21), the General Self-Efficacy (GSE), and the Satisfaction With Life Scale (SWLS). Academic performance was measured using students’ academic weighted grades (WG). Student cognitive and emotional perceptions of the intervention were measured using the Credibility/Expectancy Questionnaire (CEQ). Results Data from 317 students, who completed the follow ups, were analysed across the three time periods (IG, n = 155; CG, n = 162). The baseline variables and demographic data of the IG and CG were not significantly different. The IG showed short-term significant reductions in depression and anxiety in compared to CG from T1 to T2. The short-term changes in stress, GSE and SWLS of the IG were not significantly different from those of the CG. While both groups showed a significant change on most of the psychological variables from T1 to T3, no significant differences were found between the groups in this period. In addition, no significant difference was found in WG between the IG and CG after the intervention. No harms relevant to the intervention were reported. Conclusion The investigated self-development coaching programme showed only a short-term improvement on depression and anxiety compared with an active control. There was no effect of the intervention on academic performance.
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Systematic reviews and meta-analyses are used to combine results across studies to determine an overall effect. Meta-analysis is especially useful for combining evidence to inform social policy, but meta-analyses of applied social science research may encounter practical issues arising from the nature of the research domain. The current paper identifies potential resolutions to four issues that may be encountered in systematic reviews and meta-analyses in social research. The four issues are: scoping and targeting research questions appropriate for meta-analysis; selecting eligibility criteria where primary studies vary in research design and choice of outcome measures; dealing with inconsistent reporting in primary studies; and identifying sources of heterogeneity with multiple confounded moderators. The paper presents an overview of each issue with a review of potential resolutions, identified from similar issues encountered in meta-analysis in medical and biological sciences. The discussion aims to share and improve methodology in systematic reviews and meta-analysis by promoting cross-disciplinary communication, that is, to encourage 'viewing through different lenses'.
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Atherosclerosis plaque rupture has been considered to be a mechanical failure of the thin fibrous cap, resulted from extreme plaque stress. Plaque stress was affected by many factors from morphological features to biological abnormalities. In this study, geometrical factors (curvedness, fibrous cap thickness) were studied on assessing plaque vulnerability in comparison with stress analysis results obtained by fluid structure interaction from 20 human carotid atherosclerosis plaques. The results show that plaque surface curvedness could contribute to extreme stress level, especially in plaque shoulder region. General plaque stress distribution could be predicted by fibrous cap thickness and curvedness with multi-regression model. With more features included in the regression model, plaque stress could be easily calculated and used to assess plaque vulnerability.
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Purpose This study evaluated the impact of a daily and weekly image-guided radiotherapy protocols in reducing setup errors and setting of appropriate margins in head and neck cancer patients. Materials and methods Interfraction and systematic shifts for the hypothetical day 1–3 plus weekly imaging were extrapolated from daily imaging data from 31 patients (964 cone beam computed tomography (CBCT) scans). In addition, residual setup errors were calculated by taking the average shifts in each direction for each patient based on the first three shifts and were presumed to represent systematic setup error. The clinical target volume (CTV) to planning target volume (PTV) margins were calculated using van Herk formula and analysed for each protocol. Results The mean interfraction shifts for daily imaging were 0·8, 0·3 and 0·5 mm in the S-I (superior-inferior), L-R (left-right) and A-P (anterior-posterior) direction, respectively. On the other hand the mean shifts for day 1–3 plus weekly imaging were 0·9, 1·8 and 0·5 mm in the S-I, L-R and A-P direction, respectively. The mean day 1–3 residual shifts were 1·5, 2·1 and 0·7 mm in the S-I, L-R and A-P direction, respectively. No significant difference was found in the mean setup error for the daily and hypothetical day 1–3 plus weekly protocol. However, the calculated CTV to PTV margins for the daily interfraction imaging data were 1·6, 3·8 and 1·4 mm in the S-I, L-R and A-P directions, respectively. Hypothetical day 1–3 plus weekly resulted in CTV–PTV margins of 5, 4·2 and 5 mm in the S-I, L-R and A-P direction. Conclusions The results of this study show that a daily CBCT protocol reduces setup errors and allows setup margin reduction in head and neck radiotherapy compared to a weekly imaging protocol.
Resumo:
Observational studies have shown that medical and dental students have poor psychological health worldwide; however, few interventional studies have been used to test approaches to help students. This thesis used a randomised control trial study design to evaluate the effect of a self-development coaching program on psychological health and the academic performance among medical and dental students in Saudi Arabia. The outcomes indicated that these medical and dental students in Saudi Arabia experienced high levels of depression, anxiety and stress, and that the self-development coaching program was a promising intervention to improve students' psychological health.
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Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder that has a major impact on the ability to function effectively in daily life. PTSD may develop as a response to exposure to an event or events perceived as potentially harmful or life-threatening. It has high prevalence rates in the community, especially among vulnerable groups such as military personnel or those in emergency services. Despite extensive research in this field, the underlying mechanisms of the disorder remain largely unknown. The identification of risk factors for PTSD has posed a particular challenge as there can be delays in onset of the disorder, and most people who are exposed to traumatic events will not meet diagnostic criteria for PTSD. With the advent of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM V), the classification for PTSD has changed from an anxiety disorder into the category of stress- and trauma-related disorders. This has the potential to refocus PTSD research on the nature of stress and the stress response relationship. This review focuses on some of the important findings from psychological and biological research based on early models of stress and resilience. Improving our understanding of PTSD by investigating both genetic and psychological risk and coping factors that influence stress response, as well as their interaction, may provide a basis for more effective and earlier intervention.
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Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated approximately 2,000, approximately 3,700 and approximately 9,500 SNPs explained approximately 21%, approximately 24% and approximately 29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
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Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
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Owing to the successful use of non-invasive vibration analysis to monitor the progression of dental implant healing and stabilization, it is now being considered as a method to monitor femoral implants in transfemoral amputees. This study uses composite femur-implant physical models to investigate the ability of modal analysis to detect changes at the interface between the implant and bone simulating those that occur during osseointegration. Using electromagnetic shaker excitation, differences were detected in the resonant frequencies and mode shapes of the model when the implant fit in the bone was altered to simulate the two interface cases considered: firm and loose fixation. The study showed that it is beneficial to examine higher resonant frequencies and their mode shapes (rather than the fundamental frequency only) when assessing fixation. The influence of the model boundary conditions on the modal parameters was also demonstrated. Further work is required to more accurately model the mechanical changes occurring at the bone-implant interface in vivo, as well as further refinement of the model boundary conditions to appropriately represent the in vivo conditions. Nevertheless, the ability to detect changes in the model dynamic properties demonstrates the potential of modal analysis in this application and warrants further investigation.
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Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.