MATERIALS AND METHODS: Two hundred and ten students completed a validated questionnaire on SOC and SDLR. The percentage of marks obtained by these students in their year-end examination was used as their academic performance. The SOC scores were further divided into three hierarchical clusters using cluster analysis. The data were analyzed to determine the difference in the SDLR scores and academic performance among the three clusters. Furthermore, the relationship between SOC scores, SDLR scores, and academic performance was assessed.
RESULTS: The SDLR scores significantly increased from the low SOC cluster to the high SOC cluster (P = 0.026). However, there was no significant change in academic performance. A positive relationship was found between the SOC and the academic performance (R = +0.025; P > 0.05). The SDLR had a significant positive relationship with both SOC and academic performance (R = +0.27; P < 0.001).
CONCLUSION: Although SOC may not have a direct influence on academic performance, SDLR can play an intermediary role. Early identification and timely intervention in students with a weak SOC and low SDLR can have a beneficial influence on their academic life.
METHODS: The most important climatic factors that contribute to dengue outbreaks were identified in the current work. Correlation analyses were performed in order to determine these factors and these factors were used as input parameters for machine learning models. Top five machine learning classification models (Bayes network (BN) models, support vector machine (SVM), RBF tree, decision table and naive Bayes) were chosen based on past research. The models were then tested and evaluated on the basis of 4-year data (January 2010 to December 2013) collected in Malaysia.
RESULTS: This research has two major contributions. A new risk factor, called the TempeRain factor (TRF), was identified and used as an input parameter for the model of dengue outbreak prediction. Moreover, TRF was applied to demonstrate its strong impact on dengue outbreaks. Experimental results showed that the Bayes Network model with the new meteorological risk factor identified in this study increased accuracy to 92.35% for predicting dengue outbreaks.
CONCLUSIONS: This research explored the factors used in dengue outbreak prediction systems. The major contribution of this study is identifying new significant factors that contribute to dengue outbreak prediction. From the evaluation result, we obtained a significant improvement in the accuracy of a machine learning model for dengue outbreak prediction.
METHODS: A structured self-administered questionnaire was developed at Najran University and provided to the participants for data collection. The data collected included information on risk perception and incorporation of measures for protection against COVID-19 to gauge the attitude of dentists during this period. Also, clinical implementation of various protective measures was reviewed.
RESULTS: Of the n = 322 dentists that answered the questions, 50% were general dentists and 28.9% were dentists working at specialist clinics, while the remaining 21.1% of dentists were employed in academic institutions. Among the newer additions to the clinic, 36.3% of dentists answered that they had added atomizers to their practices, followed by 26.4% of dentists that had incorporated the use of UV lamps for sterilization. We found that 18.9% dentists were using HEPA filters in their clinics, while 9.9% of dentists were making use of fumigation devices to control the risk of infection. One-way ANOVA was also carried out to demonstrate that there was a statistically significant difference (p = 0.049) between groups of dentists utilizing HEPA filters, UV lamps, atomizers, and fumigation devices to prevent the spread of SARS-CoV2 across their workplaces.
CONCLUSION: Dentists are aware of recently updated knowledge about the modes of transmission of COVID-19 and the recommended infection control measures in dental settings. A better understanding of the situation and methods to prevent it will ensure that the dental community is able to provide healthcare services to patients during the pandemic.
OBJECTIVE: To assess knowledge and perceptions regarding PD in a large multiethnic urban Asian cohort of patients and caregivers.
METHODS: We conducted a survey at a university hospital neurology clinic, using a novel Knowledge and Perception of Parkinson's Disease Questionnaire (KPPDQ).
RESULTS: The KPPDQ had satisfactory psychometric properties among patients and caregivers. Five hundred subjects were recruited with a 97% response rate (211 patients, 273 caregivers). Non-motor symptoms such as urinary problems, visual hallucinations and pain were relatively poorly recognized. Many (≈ 50-80%) respondents incorrectly believed that all PD patients experience tremor, that PD is usually familial, and that there is a cure for PD. About one-half perceived PD to be caused by something the patient had done in the past, and that PD medications were likely to cause internal organ damage. Issues of stigma/shame were relevant to one-third of patients, and 70% of patients perceived themselves to be a burden to others. Two-thirds of participants felt that PD imposed a heavy financial toll. Participants were about equally divided as to whether they would consider treatment with deep brain stimulation, tube feeding or invasive ventilation. Over three-quarters of patients expressed a preference to die at home.
CONCLUSIONS: Important knowledge gaps, misperceptions and perspectives on PD were identified, highlighting the need for further efforts to raise awareness and provide accurate information regarding PD, and to address patient's and caregivers' needs and preferences.
AIM: The general objective of this study is to find out the description of community first responder in providing pre-hospital first aid to head injuries.
METHODS: This study uses qualitative descriptive method.
RESULTS: Most of the respondents have variety of educational backgrounds and do not have sufficient knowledge and skills to provide first aid. The average respondents provided help by performing initial assessment, managing effective airway and controlling bleeding. Limited pre-hospital facilities become one of the reasons for respondent not getting help so the efforts provided are not maximal. Respondents prefer to send patients directly to health facilities.
CONCLUSION: Regular education and training programs for the community first responders should be initiated so that the number of death and disability can be minimized.
METHODS: An electronic literature search was done till March 2020 to include studies with comparative cohorts of IH versus OOH. Primary outcomes were 30-day mortality, stroke, and reoperation for bleeding; secondary outcomes were acute kidney injury, total hospital stay, and intensive care unit stay.
RESULTS: Six articles with a total of 3744 patients met the inclusion criteria. Mean age was similar, 60 ± 12 versus 60 ± 13 in IH versus OOH (p = .25). Aortic root and total arch replacement were similar in both cohorts, 22% in IH versus 25% in OOH (risk ratio [RR], 1.10; 95% confidence interval [CI: 0.78, 1.55]; p = .58) and 29% in IH versus 32% in OOH (RR, 0.96; 95% CI [0.89, 1.04], p = .37) respectively. Reoperation for bleeding and stroke rate were similar, with 18% in IH versus 23% in OOH (RR, 0.89; 95% CI [0.73, 1.08]; p = .24), and 12% in IH versus 13% in OOH (RR, 0.83; 95% CI [0.66, 1.03]; p = .09) respectively. Thirty-day mortality was significantly lower in IH (RR, 0.81; 95% CI [0.72, 0.90]; p = .0001).
CONCLUSION: There was higher 30-day mortality rate during OOH surgery, yet this difference diminished following sensitivity analysis. There were no significant differences in major postoperative outcomes. Therefore, operating on such cases should be decided on clinical priority without delay.
METHODS: In this paper, we analyze four wide-spread deep learning models designed for the segmentation of three retinal fluids outputting dense predictions in the RETOUCH challenge data. We aim to demonstrate how a patch-based approach could push the performance for each method. Besides, we also evaluate the methods using the OPTIMA challenge dataset for generalizing network performance. The analysis is driven into two sections: the comparison between the four approaches and the significance of patching the images.
RESULTS: The performance of networks trained on the RETOUCH dataset is higher than human performance. The analysis further generalized the performance of the best network obtained by fine-tuning it and achieved a mean Dice similarity coefficient (DSC) of 0.85. Out of the three types of fluids, intraretinal fluid (IRF) is more recognized, and the highest DSC value of 0.922 is achieved using Spectralis dataset. Additionally, the highest average DSC score is 0.84, which is achieved by PaDeeplabv3+ model using Cirrus dataset.
CONCLUSIONS: The proposed method segments the three fluids in the retina with high DSC value. Fine-tuning the networks trained on the RETOUCH dataset makes the network perform better and faster than training from scratch. Enriching the networks with inputting a variety of shapes by extracting patches helped to segment the fluids better than using a full image.
METHODS: A retrospective review of all cases of computed tomography-confirmed acute diverticulitis from November 2015 to April 2018 was performed. Data collated included basic demographics, computed tomography scan results (uncomplicated versus complicated diverticulitis), treatment modality (conservative versus intervention), outcomes and follow-up colonoscopy results within 12 months of presentation. The patients were divided into no adenoma (A) and adenoma (B) groups. Visceral fat area (VFA), subcutaneous fat area (SFA) and VFA/SFA ratio (V/S) were measured at L4/L5 level. Statistical analysis was performed to evaluation the association of VFA, SFA, V/S and different thresholds with the risk of adenoma formation.
RESULTS: A total of 169 patients were included in this study (A:B = 123:46). The mean ± standard deviation for VFA was higher in group B (201 ± 87 cm2 versus 176 ± 79 cm2 ) with a trend towards statistical significance (P = 0.08). There was no difference in SFA and V/S in both groups. When the VFA >200 cm2 was analysed, it was associated with a threefold risk of adenoma formation (odds ratio 2.7, 95% confidence interval 1.35-5.50, P = 0.006). Subgroup analysis of gender with VFA, SFA and V/S found that males have a significantly higher VFA in group B (220.0 ± 95.2 cm2 versus 187.3 ± 69.2 cm2 ; P = 0.05).
CONCLUSIONS: The radiological measurement of visceral adiposity is a useful tool for opportunistic assessment of risk of colorectal adenoma.