Exploring the usage of learning resources by medical students in the basic science stage and their effect on academic performance.

BACKGROUND: The United States Medical Licensing Examination (USMLE) step 1 is one of the two examinations written after completion of the first two years (basic science stage) of medical school to be eligible to apply for residency training in the USA. A huge number and types of study materials are available to prepare for the exam which might confuse students choosing a resource. We investigated learning resources being used by the third and fifth-semester medical students and their association with academic performance. We also compared learning resources and exam scores of high-performing and low-performing students. METHODS: Data collection was done using structured (quantitative study) and semi-structured (qualitative study) questionnaires during a face-to-face interview. This article is about the quantitative part which was designed as a correlational study. Single factor one-way analysis of variance (ANOVA), Pearson correlation coefficient test, T-test, and Fisher's exact test were used to analyze the data. RESULTS: About half of all students used three or more commercial resources dealing with the same content. A weak negative correlation was observed between the number of commercial resources and the exam scores, especially when the number of these resources was three or more (r = -0.26). The mean exam score of textbook users was statistically significantly higher than the mean score of textbook non-users (p = 0.01). The usage of textbooks was statistically significantly higher in the cohort of top performers in comparison to the rest of the students (p = 0.006). In addition to less usage of textbooks, the mean number of review books was higher in the group of weakest students (2.84 versus 3.7; p = 0.75). CONCLUSIONS: Most students did not use professional textbooks and about half used too many commercial review resources. While the former fact was significantly associated with poor academic performance, the later fact had weak negative correlation with exam score. Pedagogical interventions are urgently needed to make the right type of learning resources available by making professional textbooks more USMLE-oriented and helping the students choose the best and right number of resources for optimum academic performance. By fulfilling the observed needs of the students in this way, they might feel empowered because of self-determination which will motivate studies.

Four Transformer-Based Deep Learning Classifiers Embedded with an Attention U-Net-Based Lung Segmenter and Layer-Wise Relevance Propagation-Based Heatmaps for COVID-19 X-ray Scans.

Background: Diagnosing lung diseases accurately is crucial for proper treatment. Convolutional neural networks (CNNs) have advanced medical image processing, but challenges remain in their accurate explainability and reliability. This study combines U-Net with attention and Vision Transformers (ViTs) to enhance lung disease segmentation and classification. We hypothesize that Attention U-Net will enhance segmentation accuracy and that ViTs will improve classification performance. The explainability methodologies will shed light on model decision-making processes, aiding in clinical acceptance. Methodology: A comparative approach was used to evaluate deep learning models for segmenting and classifying lung illnesses using chest X-rays. The Attention U-Net model is used for segmentation, and architectures consisting of four CNNs and four ViTs were investigated for classification. Methods like Gradient-weighted Class Activation Mapping plus plus (Grad-CAM++) and Layer-wise Relevance Propagation (LRP) provide explainability by identifying crucial areas influencing model decisions. Results: The results support the conclusion that ViTs are outstanding in identifying lung disorders. Attention U-Net obtained a Dice Coefficient of 98.54% and a Jaccard Index of 97.12%. ViTs outperformed CNNs in classification tasks by 9.26%, reaching an accuracy of 98.52% with MobileViT. An 8.3% increase in accuracy was seen while moving from raw data classification to segmented image classification. Techniques like Grad-CAM++ and LRP provided insights into the decision-making processes of the models. Conclusions: This study highlights the benefits of integrating Attention U-Net and ViTs for analyzing lung diseases, demonstrating their importance in clinical settings. Emphasizing explainability clarifies deep learning processes, enhancing confidence in AI solutions and perhaps enhancing clinical acceptance for improved healthcare results.

COVLIAS 3.0: cloud-based quantized hybrid UNet3+ deep learning for COVID-19 lesion detection in lung computed tomography.

Background and novelty: When RT-PCR is ineffective in early diagnosis and understanding of COVID-19 severity, Computed Tomography (CT) scans are needed for COVID diagnosis, especially in patients having high ground-glass opacities, consolidations, and crazy paving. Radiologists find the manual method for lesion detection in CT very challenging and tedious. Previously solo deep learning (SDL) was tried but they had low to moderate-level performance. This study presents two new cloud-based quantized deep learning UNet3+ hybrid (HDL) models, which incorporated full-scale skip connections to enhance and improve the detections. Methodology: Annotations from expert radiologists were used to train one SDL (UNet3+), and two HDL models, namely, VGG-UNet3+ and ResNet-UNet3+. For accuracy, 5-fold cross-validation protocols, training on 3,500 CT scans, and testing on unseen 500 CT scans were adopted in the cloud framework. Two kinds of loss functions were used: Dice Similarity (DS) and binary cross-entropy (BCE). Performance was evaluated using (i) Area error, (ii) DS, (iii) Jaccard Index, (iii) Bland-Altman, and (iv) Correlation plots. Results: Among the two HDL models, ResNet-UNet3+ was superior to UNet3+ by 17 and 10% for Dice and BCE loss. The models were further compressed using quantization showing a percentage size reduction of 66.76, 36.64, and 46.23%, respectively, for UNet3+, VGG-UNet3+, and ResNet-UNet3+. Its stability and reliability were proved by statistical tests such as the Mann-Whitney, Paired t-Test, Wilcoxon test, and Friedman test all of which had a p < 0.001. Conclusion: Full-scale skip connections of UNet3+ with VGG and ResNet in HDL framework proved the hypothesis showing powerful results improving the detection accuracy of COVID-19.

Morphological Study of Hashimoto Thyroiditis in Fine Needle Aspiration Cytology Specimens.

Background: Hashimoto thyroiditis is an autoimmune disease which is diagnosed based on well-defined clinical and cytological criteria. Purpose: The objective of this research is to study cytomorphological features in patients of Hashimoto thyroiditis and compare the findings with other studies. Literature on morphology of multinucleated giant cells was found to be lacking, and this study has focused on the number and morphology of these cells in this study. Material and Methods: FNAC was done in patients who met the clinical diagnostic criteria of Hashimoto thyroiditis formulated by "Japan Thyroid Association" and smears were analyzed by light microscopy. Data analysis was done by XLSTAT in Microsoft Excel 2010. The Wilcoxon Signed Rank Test was done to analyze the data on multinucleated giant cells. The null hypothesis was that the median of the population of differences between the paired data of small and large giant cells is zero. Results: A total of 26 patients were included in a period of one year. Contrary to observations in other studies, multinucleated giant cells were found in most participants. The Wilcoxon Signed Rank Test proved that small multinucleated giant cells were significantly more common than large multinucleated giant cells in Hashimoto thyroiditis; P value (two-tailed) being <0.0001 at significance alpha of 0.05. This study has also revealed that a few patients with Hashimoto thyroiditis can have large and very large multinucleated giant cells in a small number. Data on other cytomorphological features were no different than in other studies. Conclusion: The presence of multinucleated giant cells in 92.3% of patients in this study is far higher than in other studies which can have important diagnostic implications. Few large multinucleated giant cells can be present in a small number in a few patients as in Hashimoto thyroiditis.

Photocatalytic oxygenation of sulfide using solar light and ingenious GQDs@AQ catalyst: Mechanistic and synthetic investigations.

The combination of excellent electronic properties and thermal stability positions orange-derived graphene quantum dots (GQDs) as promising materials for solar light-based applications. Researchers are actively exploring their potential in fields such as photovoltaics, photocatalysis, optoelectronics, and energy storage. Their abundance, cost-effectiveness, and eco-friendly nature further contribute to their growing relevance in cutting-edge scientific research. Furthermore, only GQDs are not much more effective in the UV-visible region, therefore, required band gap engineering in GQDs material. In this context, we designed GQDs-based light harvesting materials, which is active in UV-visible region. Herein we synthesized GQDs coupled with 2,6-diaminoanthrquninone (AQ), that is, GQDs@AQ light harvesting photocatalyst the first time for the oxidation of sulfide to sulfoxide under visible light. For the integrating reactions of sulfide in aerobic conditions under visible light by GQDs@AQ photocatalyst exhibit utmost higher photocatalytic activity than simple GQDs due to low molar extinction coefficient and slow recombination charges. The use of GQDs@AQ light harvesting photocatalyst, showed the excellent organic transformation efficiency of sulfide to sulfoxide with excellent yield (94%). The high efficiency and excellent yield of 94% indicate the effectiveness of GQDs@AQ as a photocatalyst for these specific organic transformations.

DermAI 1.0: A Robust, Generalized, and Novel Attention-Enabled Ensemble-Based Transfer Learning Paradigm for Multiclass Classification of Skin Lesion Images.

Skin lesion classification plays a crucial role in dermatology, aiding in the early detection, diagnosis, and management of life-threatening malignant lesions. However, standalone transfer learning (TL) models failed to deliver optimal performance. In this study, we present an attention-enabled ensemble-based deep learning technique, a powerful, novel, and generalized method for extracting features for the classification of skin lesions. This technique holds significant promise in enhancing diagnostic accuracy by using seven pre-trained TL models for classification. Six ensemble-based DL (EBDL) models were created using stacking, softmax voting, and weighted average techniques. Furthermore, we investigated the attention mechanism as an effective paradigm and created seven attention-enabled transfer learning (aeTL) models before branching out to construct three attention-enabled ensemble-based DL (aeEBDL) models to create a reliable, adaptive, and generalized paradigm. The mean accuracy of the TL models is 95.30%, and the use of an ensemble-based paradigm increased it by 4.22%, to 99.52%. The aeTL models' performance was superior to the TL models in accuracy by 3.01%, and aeEBDL models outperformed aeTL models by 1.29%. Statistical tests show significant p-value and Kappa coefficient along with a 99.6% reliability index for the aeEBDL models. The approach is highly effective and generalized for the classification of skin lesions.

Ensemble Deep Learning Derived from Transfer Learning for Classification of COVID-19 Patients on Hybrid Deep-Learning-Based Lung Segmentation: A Data Augmentation and Balancing Framework.

BACKGROUND AND MOTIVATION: Lung computed tomography (CT) techniques are high-resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease control classification. Most artificial intelligence (AI) systems do not undergo generalization and are typically overfitted. Such trained AI systems are not practical for clinical settings and therefore do not give accurate results when executed on unseen data sets. We hypothesize that ensemble deep learning (EDL) is superior to deep transfer learning (TL) in both non-augmented and augmented frameworks. METHODOLOGY: The system consists of a cascade of quality control, ResNet-UNet-based hybrid deep learning for lung segmentation, and seven models using TL-based classification followed by five types of EDL's. To prove our hypothesis, five different kinds of data combinations (DC) were designed using a combination of two multicenter cohorts-Croatia (80 COVID) and Italy (72 COVID and 30 controls)-leading to 12,000 CT slices. As part of generalization, the system was tested on unseen data and statistically tested for reliability/stability. RESULTS: Using the K5 (80:20) cross-validation protocol on the balanced and augmented dataset, the five DC datasets improved TL mean accuracy by 3.32%, 6.56%, 12.96%, 47.1%, and 2.78%, respectively. The five EDL systems showed improvements in accuracy of 2.12%, 5.78%, 6.72%, 32.05%, and 2.40%, thus validating our hypothesis. All statistical tests proved positive for reliability and stability. CONCLUSION: EDL showed superior performance to TL systems for both (a) unbalanced and unaugmented and (b) balanced and augmented datasets for both (i) seen and (ii) unseen paradigms, validating both our hypotheses.

Spatial and temporal variation of the ambient noise environment of the Sikkim Himalaya.

Ambient noise characteristics are perused to assess the station performance of 27 newly constructed broadband seismic stations across Sikkim Himalaya and adjoining Himalayan foreland basin, installed to study the seismogenesis and subsurface structure of the region. Power spectral densities obtained at each station, compared against the global noise limits, reveal that observed vertical component noise levels are within the defined global limits. However, the horizontal components marginally overshoot the limits due to the tilt effect. Ambient noise conditions significantly vary with different installation techniques, analysis revealing that seismic sensors buried directly in the ground have reduced long-period noise in comparison to pier installations. Tectonic settings and anthropogenic activities are also noted to cause a significant rise across short-period and microseism noise spectrum, varying spatially and temporally across the region. Day-time records higher cultural noise than night-time, while the microseism noise dominates during the monsoonal season. An assessment of the effect of the nationwide lockdown imposed due to COVID-19 pandemic revealed a significant decrease in the short-period noise levels at stations installed across the foreland basin marked with higher anthropogenic activity. Our study summarizes the overall ambient noise patterns, validating the stability and performance of the seismic stations across the Sikkim Himalayas.

Deep Learning Approaches for Automatic Localization in Medical Images.

Recent revolutionary advances in deep learning (DL) have fueled several breakthrough achievements in various complicated computer vision tasks. The remarkable successes and achievements started in 2012 when deep learning neural networks (DNNs) outperformed the shallow machine learning models on a number of significant benchmarks. Significant advances were made in computer vision by conducting very complex image interpretation tasks with outstanding accuracy. These achievements have shown great promise in a wide variety of fields, especially in medical image analysis by creating opportunities to diagnose and treat diseases earlier. In recent years, the application of the DNN for object localization has gained the attention of researchers due to its success over conventional methods, especially in object localization. As this has become a very broad and rapidly growing field, this study presents a short review of DNN implementation for medical images and validates its efficacy on benchmarks. This study presents the first review that focuses on object localization using the DNN in medical images. The key aim of this study was to summarize the recent studies based on the DNN for medical image localization and to highlight the research gaps that can provide worthwhile ideas to shape future research related to object localization tasks. It starts with an overview on the importance of medical image analysis and existing technology in this space. The discussion then proceeds to the dominant DNN utilized in the current literature. Finally, we conclude by discussing the challenges associated with the application of the DNN for medical image localization which can drive further studies in identifying potential future developments in the relevant field of study.

Emerging Pharmaceutical Treatments of Novel COVID-19: A Review.

As a new decade began, COVID-19 quickly gained importance as it became the cause of the current global pandemic. Research has been focusing on studying the structure of SARS-CoV-2 and investigates possible pharmaceutical approaches. With the number of cases increasing every day, globally, multiple drugs are being researched as possible candidates. Although multiple drugs show promise in the treatment of COVID-19 via either inhibiting viral replication or preventing fusion of the virus to the ACE2 receptors, further investigation is still warranted and necessary before the admission of any type of pharmaceutical agent. Furthermore, several supplements have also been documented in being utilized as treatment of COVID-19. The exact mechanism and efficacy of current candidate drugs are still being explored through clinical trials. Despite the advancements in current research with emerging treatments, social distancing and engaging in preventative measures remains crucial to attempt to prevent the occurrence of more cases and deaths, worldwide. This review explores various drugs and their mechanism of action which are either currently being used in clinical trials or may be used in the future for the treatment of COVID-19.

Role of Zinc in Mucosal Health and Disease: A Review of Physiological, Biochemical, and Molecular Processes.

Zinc is an essential trace element of all highly proliferating cells in the human body. It is essential to the development and growth of all organisms. Zinc plays a critical role in modulating resistance to infectious agents and reduces the duration, severity, and risk of diarrheal disease via improved regeneration of intestinal epithelium, improved absorption of water and electrolytes, increased levels of brush border enzymes, and, possibly, an enhancement in the immune response allowing better clearance of pathogens. On the cellular level, zinc finger motifs play various roles including diverse functions that involve specific gene expression for ion channels throughout the body. It maintains the function and the structure of the membrane barrier by contributing to host defense, which is particularly crucial in the intestines due to the continuous exposure to noxious agents and pathogens. Zinc deficiency is characterized by impaired immune function, loss of appetite, and growth retardation. More severe cases cause diarrhea, delayed sexual maturation, hair loss, eye and skin lesions, impotence and hypogonadism in males, as well as weight loss, taste abnormalities, delayed healing of wounds, and mental lethargy. The objective of this study is a critical review of the molecular and genetic regulation of zinc in various cellular processes and organs, the association between zinc and diarrheal disease, the recommended dietary zinc intake, and the effects of zinc deficiency on the human body.

Comparing Standard Setting Methods for Objective Structured Clinical Examinations in a Caribbean Medical School.

BACKGROUND: OSCE are widely used for assessing clinical skills training in medical schools. Use of traditional pass fail cut off yields wide variations in the results of different cohorts of students. This has led to a growing emphasis on the application of standard setting procedures in OSCEs. PURPOSE/AIM: The purpose of the study was comparing the utility, feasibility and appropriateness of 4 different standard setting methods with OSCEs at XUSOM. METHODS: A 15-station OSCE was administered to 173 students over 6 months. Five stations were conducted for each organ system (Respiratory, Gastrointestinal and Cardiovascular). Students were assessed for their clinical skills in 15 stations. Four different standard setting methods were applied and compared with a control (Traditional method) to establish cut off scores for pass/fail decisions. RESULTS: OSCE checklist scores revealed a Cronbach's alpha of 0.711, demonstrating acceptable level of internal consistency. About 13 of 15 OSCE stations performed well with "Alpha if deleted values" lower that 0.711 emphasizing the reliability of OSCE stations. The traditional standard setting method (cut off score of 70) resulted in highest failure rate. The Modified Angoff Method and Relative methods yielded the lowest failure rates, which were typically less than 10% for each system. Failure rates for the Borderline methods ranged from 28% to 57% across systems. CONCLUSIONS: In our study, Modified Angoff method and Borderline regression method have shown to be consistently reliable and practically suitable to provide acceptable cut-off score across different organ system. Therefore, an average of Modified Angoff Method and Borderline Regression Method appeared to provide an acceptable cutoff score in OSCE. Further studies, in high-stake clinical examinations, utilizing larger number of judges and OSCE stations are recommended to reinforce the validity of combining multiple methods for standard setting.

Reading habits and attitude toward medical humanities of basic science students in a medical college in Western Nepal.

BACKGROUND: The Manipal College of Medical Sciences, Pokhara, Nepal, admits students from Nepal, India, Sri Lanka, and other countries to the undergraduate medical course. PURPOSES: The present study sought to describe and explore reading habits of medical students during the first three semesters and obtain their views regarding inclusion of medical humanities in the course. METHODS: The authors introduced a voluntary module in medical humanities to the fifth- and sixth-semester students. Gender, semester, and nationality of respondents were noted. Commonly read noncourse books (fiction and nonfiction) were noted. Student attitudes toward medical humanities were studied using a set of nine statements. A total of 165 of the 220 students (75%) participated. Indians followed by Nepalese were the most common nationalities. RESULTS: Romantic fiction and biography were most commonly read. The Alchemist and The Da Vinci Code were commonly read books. Students were in favor of inclusion of medical humanities in the curriculum. The median total score was 30 (maximum possible score = 45). CONCLUSIONS: Students read widely beyond their course. The possibility of introducing medical humanities in the curriculum should be explored.

Fluoroquinolone utilization among inpatients in a teaching hospital in western Nepal.

OBJECTIVE: To obtain information on the prescribing patterns of fluoroquinolones among hospitalized patients, other antibiotics and drugs co-prescribed, calculate fluoroquinolone utilization using defined daily dose (DDD), calculate mean cost of drugs and detail the sensitivity patterns of isolated microorganisms. METHODS: The study was carried out over a five-month period (1st November 2003 to 31st March 2004) at the Manipal Teaching Hospital, Pokhara, Nepal. Demographic details and duration of hospitalization was noted. The percentage of patients prescribed parenteral antibiotics and fluoroquinolones were recorded. The cost of drugs was determined using the price list supplied by the pharmacy. Fluoroquinolone utilization was measured in DDD/100 bed-days. RESULTS: Fluoroquinolones were prescribed to 263 patients during the study period; 160 females and 103 males. Mean +/- SD number of drugs prescribed and duration of hospitalization were 6.5 +/- 3.3 and 6.2 +/- 5.4 days respectively. Fluoroquinolone utilization was 7.76 DDD/100 bed-days. Ciprofloxacin was the most commonly prescribed drug (6.83 DDD/100 bed-days). Fluoroquinolones were used for prophylaxis in 110 patients (41.8%). Other indications were urinary tract infections and acute gastroenteritis. E.coli, S.aureus and P. aeruginosa were common organisms isolated. The mean cost of drugs was 13.1 U.S. $ and fluoroquinolones contributed to 36.7% of the total drug costs. CONCLUSION: The use of fluoroquinolones was high compared to that reported previously.

Science attitudes and knowledge among preclinical medical students in Pokhara, Nepal.

Knowledge of science and the scientific method are important in learning about and using evidence-based medicine in practice. Courses in research methodology have been introduced for both medical students and practicing doctors. In Pokhara, the basic science subjects are taught in an integrated manner during the first four semesters of the undergraduate medical course. Studies on students' attitudes towards and knowledge of science are lacking in medical colleges in Nepal. Hence the study was carried out to obtain information on students' attitude towards and knowledge of science and scientific methodology among preclinical medical students and note the association, if any, of students' attitudes and their demographic characteristics. The study was carried out in March 2005 among the students of the first four semesters at the Manipal College of Medical Sciences, Pokhara, Nepal using a questionnaire developed by Hren and coworkers. Two hundred and twenty students (overall response rate 73.3%) successfully completed the questionnaire. Seventy-five respondents were Nepalese, 115 were Indians, 27 were Sri Lankans and 3 belonged to other nationalities. The X +/- SD total attitude score was 147.4 +/- 10.8 (neutral score 135). The X +/- SD scores on the subscales, value of science to humanity, value of scientific methodology and value of science to medicine were 51.3 +/- 5.4, 39.6 +/- 3.7 and 58.5 +/- 5.9 (neutral scores were 36, 51 and 48 respectively). The knowledge score measured using a set of 8 multiple choice questions was 3.3 +/- 1.4. The attitude scores were lower and the knowledge score was comparable to that reported previously in a study in Croatia but higher than that reported from Southeast Europe.

Introduction to medication errors and the error prevention initiatives in a teaching hospital in Western Nepal.

Pharmacotherapy is a complex process and involves interaction of the patient and the healthcare professionals at various levels. Prevention of medication errors is important however, errors may occur even in a carefully monitored healthcare setup. The out comes of the errors may range from mild inconvenience to the patient to even fatal toxic reactions. There are several predisposing factors for the occurrence of errors starting from improper drug selection to errors in administration technique by the healthcare providers' and patients. Several methods can be employed to detect the occurrence of errors. At the Manipal Teaching Hospital, Pokhara, Nepal, the Department of Hospital and Clinical Pharmacy has taken the initiative in identifying the error prone situations and has taken remedial measures including educational and managerial interventions to minimize the occurrence of errors.

Assessment of knowledge and perceptions toward generic medicines among basic science undergraduate medical students at Aruba.

OBJECTIVE: Use of generic medicines is important to reduce rising health-care costs. Proper knowledge and perception of medical students and doctors toward generic medicines are important. Xavier University School of Medicine in Aruba admits students from the United States, Canada, and other countries to the undergraduate medical (MD) program. The present study was conducted to study the knowledge and perception about generic medicines among basic science MD students. MATERIALS AND METHODS: The cross-sectional study was conducted among first to fifth semester students during February 2015. A previously developed instrument was used. Basic demographic information was collected. Respondent's agreement with a set of statements was noted using a Likert-type scale. The calculated total score was compared among subgroups of respondents. One sample Kolmogorov-Smirnov test was used to study the normality of distribution, Independent samples t-test to compare the total score for dichotomous variables, and analysis of variance for others were used for statistical analysis. RESULTS: Fifty-six of the 85 students (65.8%) participated. Around 55% of respondents were between 20 and 25 years of age and of American nationality. Only three respondents (5.3%) provided the correct value of the regulatory bioequivalence limits. The mean total score was 43.41 (maximum 60). There was no significant difference in scores among subgroups. CONCLUSIONS: There was a significant knowledge gap with regard to the regulatory bioequivalence limits for generic medicines. Respondents' level of knowledge about other aspects of generic medicines was good but could be improved. Studies among clinical students in the institution and in other Caribbean medical schools are required. Deficiencies were noted and we have strengthened learning about generic medicines during the basic science years.

Intraoperative and Immediate Postoperative Outcomes of Cataract Surgery using Phacoemulsification in Eyes with and without Pseudoexfoliation Syndrome.

BACKGROUND: To compare the intraoperative and immediate postoperative behavior and complications in eyes with pseudoexfoliation (PEX) syndrome with eyes having senile cataract without PEX during cataract surgery using phacoemulsification (PKE). MATERIALS AND METHODS: In this prospective study, 68 eyes of 68 patients were divided into two groups: Group 1 (test) comprised 34 eyes with immature senile cataract with PEX and Group 2 (control) included 34 eyes with immature senile cataract without PEX and any coexisting ocular pathology. Phacoemulsification (modern cataract surgery) was performed on both groups through stop and chop technique and comparative analysis of the incidence of intraoperative and immediate postoperative complications was made. RESULTS: There was no significant difference in rates of intraoperative complications between PEX (2.9%) and Control (0%) group. The mean pupil diameter was significantly smaller in Group 1 (p<0.001). No eye in either group had phacodonesis. 58.8% of eyes in Group 1 and 29.4% in Group 2 had a harder cataract (nuclear sclerosis) ≥ grade 3 (p=0.017). PKE was performed in all eyes with cataract in both groups. Intraoperative complication (zonular dialysis (dehiscence) was encountered in only 2.9% (1 case) of eyes with PEX. PC (posterior capsule) tear (rent) with vitreous loss was seen in 2.9% eyes of Group 1 and none in Group 2. Postoperatively, IOP (intraocular pressure) and aqueous flare response were comparable between the groups. Significantly higher inflammatory cell response was observed in Group 1 (p=0.014). BCVA (best corrected visual acuity) using Snellen chart with pinhole on postoperative day1 was significantly better in the control group compared to the group with PEX (p=0.027). CONCLUSION: Phacoemulsification can be safely performed by experienced hands in cataractous eyes with PEX. The incidence of intraoperative and immediate post-operative complications in eyes with PEX was not significantly different compared to eyes without PEX in our study. Further studies among a larger population are required.

Student perception about working in rural United States/Canada after graduation: a study in an offshore Caribbean medical school.

INTRODUCTION: Rural residents of the United States (US) and Canada face problems in accessing healthcare. International medical graduates (IMGs) play an important role in delivering rural healthcare. IMGs from Caribbean medical schools have the highest proportion of physicians in primary care.  Xavier University School of Medicines admits students from the US, Canada and other countries to the undergraduate medical (MD) course and also offers a premedical program. The present study was conducted to obtain student perception about working in rural US/Canada after graduation.   METHODS: The study was conducted among premedical and preclinical undergraduate medical (MD) students during October 2014. The questionnaire used was modified from a previous study. Semester of study, gender, nationality, place of residence and occupation of parents were noted. Information about whether students plan to work in rural US/Canada after graduation, possible reasons why doctors are reluctant to work in rural areas, how the government can encourage rural practice, possible problems respondents anticipate while working in rural areas were among the topics studied. RESULTS: Ninety nine of the 108 students (91.7%) participated. Forty respondents were in favor of working in rural US/Canada after graduation. Respondents mentioned good housing, regular electricity, water supply, telecommunication facilities, and schools for education of children as important conditions to be fulfilled. The government should provide higher salaries to rural doctors, help with loan repayment, and provide opportunities for professional growth.  Potential problems mentioned were difficulty in being accepted by the rural community, problems in convincing patients to follow medical advice, lack of exposure to rural life among the respondents, and cultural issues. CONCLUSIONS: About 40% of respondents would consider working in rural US/Canada. Conditions required to be fulfilled have been mentioned above. Graduates from Caribbean medical schools have a role in addressing rural physician shortage. Similar studies in other offshore Caribbean medical schools are required as Caribbean IMGs make an important contribution to the rural US and Canadian health workforce.

Students' perception of the learning environment at Xavier University School of Medicine, Aruba.

PURPOSE: The learning environment at Xavier University School of Medicine (XUSOM), Aruba has not been previously studied. Hence, the present study was carried out using the Dundee Ready Education Environment Measure (DREEM) to obtain student perceptions about the learning environment and compare the same among different subgroups of respondents. METHODS: The questionnaire was administered to undergraduate medical students in their first to fifth semester during the first two weeks of June 2013. The students' perceptions were evaluated by noting their degree of agreement with a set of 50 statements using a Likert-type scale. The mean overall score and the scores of subcategory were calculated and compared among different respondents (P<0.05). RESULTS: Seventy-three of the 86 students (84.9%) completed the questionnaire. The overall mean±SD score was 131.79±22.86 (maximum score 200). The mean±SD score for students' perception of teaching/learning was 31.99±6.23 (maximum score, 48), while the score for students' perceptions of teachers was 30.05±5.54 (maximum score, 44). The mean±SD scores for students' academic self-perception, students' perception of the atmosphere, and students' social self-perception were 21.88±5.11 (maximum score, 32), 30.92±8.59 (maximum score, 48), and 16.96±4.71 (maximum score, 28), respectively. There were no differences in scores according to the respondents' personal characteristics. CONCLUSION: The student responses about the learning environment at the institution were positive. We plan to obtain regular student feedback as the curriculum becomes progressively more student-centered and integrated.