Knowledge In Ophthalmology Research Articles

Large language models approach expert-level clinical knowledge and reasoning in ophthalmology: A head-to-head cross-sectional study.

Large language models (LLMs) underlie remarkable recent advanced in natural language processing, and they are beginning to be applied in clinical contexts. We aimed to evaluate the clinical potential of state-of-the-art LLMs in ophthalmology using a more robust benchmark than raw examination scores. We trialled GPT-3.5 and GPT-4 on 347 ophthalmology questions before GPT-3.5, GPT-4, PaLM 2, LLaMA, expert ophthalmologists, and doctors in training were trialled on a mock examination of 87 questions. Performance was analysed with respect to question subject and type (first order recall and higher order reasoning). Masked ophthalmologists graded the accuracy, relevance, and overall preference of GPT-3.5 and GPT-4 responses to the same questions. The performance of GPT-4 (69%) was superior to GPT-3.5 (48%), LLaMA (32%), and PaLM 2 (56%). GPT-4 compared favourably with expert ophthalmologists (median 76%, range 64-90%), ophthalmology trainees (median 59%, range 57-63%), and unspecialised junior doctors (median 43%, range 41-44%). Low agreement between LLMs and doctors reflected idiosyncratic differences in knowledge and reasoning with overall consistency across subjects and types (p>0.05). All ophthalmologists preferred GPT-4 responses over GPT-3.5 and rated the accuracy and relevance of GPT-4 as higher (p<0.05). LLMs are approaching expert-level knowledge and reasoning skills in ophthalmology. In view of the comparable or superior performance to trainee-grade ophthalmologists and unspecialised junior doctors, state-of-the-art LLMs such as GPT-4 may provide useful medical advice and assistance where access to expert ophthalmologists is limited. Clinical benchmarks provide useful assays of LLM capabilities in healthcare before clinical trials can be designed and conducted.

Google Gemini and Bard artificial intelligence chatbot performance in ophthalmology knowledge assessment.

With the popularization of ChatGPT (Open AI, San Francisco, California, United States) in recent months, understanding the potential of artificial intelligence (AI) chatbots in a medical context is important. Our study aims to evaluate Google Gemini and Bard's (Google, Mountain View, California, United States) knowledge in ophthalmology. In this study, we evaluated Google Gemini and Bard's performance on EyeQuiz, a platform containing ophthalmology board certification examination practice questions, when used from the United States (US). Accuracy, response length, response time, and provision of explanations were evaluated. Subspecialty-specific performance was noted. A secondary analysis was conducted using Bard from Vietnam, and Gemini from Vietnam, Brazil, and the Netherlands. Overall, Google Gemini and Bard both had accuracies of 71% across 150 text-based multiple-choice questions. The secondary analysis revealed an accuracy of 67% using Bard from Vietnam, with 32 questions (21%) answered differently than when using Bard from the US. Moreover, the Vietnam version of Gemini achieved an accuracy of 74%, with 23 (15%) answered differently than the US version of Gemini. While the Brazil (68%) and Netherlands (65%) versions of Gemini performed slightly worse than the US version, differences in performance across the various country-specific versions of Bard and Gemini were not statistically significant. Google Gemini and Bard had an acceptable performance in responding to ophthalmology board examination practice questions. Subtle variability was noted in the performance of the chatbots across different countries. The chatbots also tended to provide a confident explanation even when providing an incorrect answer.

An approach towards the detection of eye cancer using configured convolution neural network with sine cosine fitness gray wolf optimizer

PURPOSE: Increasing technological advancements in processing and storage have made it easier to handle formerly difficult jobs like disease diagnosis or semantic segmentation. Eye cancer is a rare but deadly disorder that, if misdiagnosed, can cause blindness or even death. It is essential to find eye cancer early in order to successfully treat it and enhance patient outcomes. The usage of DL methods for medical image analysis, particularly the identification of eye cancer, has fascinated increasing consideration in current era. The demand for efficient tool to detect the eye cancer emphasize the need for reliable detection systems. Examining how explainable deep learning techniques, in which the model’s decision-making process can be understood and visualized, can increase confidence in and adoption of the deep learning-based approach for detecting eye cancer. Expert input is necessary to train machine learning algorithms properly. As it necessitates knowledge of ophthalmology, radiography, and pathology, this can be difficult for eye cancer identification. The main purpose of the study is to detect the eye cancer with at most accuracy with the utilization of Deep learning-based approach. METHODS: There are four steps involved to achieve the efficient detection system. They are pre-processing, segmentation, augmentation, feature extraction with classification. The Circle Hough Transform is applied to detect the edges in the image. The dataset size is increased by shifting, rotating and flipping augmentation techniques. Deep learning-based approach is suggested for the automatic detection of eye cancer. The two methods named 3XConPool and 10XCon5XPool were investigated using Python learning environment. The two techniques 3XConPool and 10XCon5XPool imply on the Sine Cosine Fitness Grey Wolf Optimization (SCFGWO) algorithm for the adjustment of the hyperparameters. The 3XConPool and 10XCon5XPool methods with SCFGWO are compared with each other and also with the other existing methods. RESULTS: As a comparison to the earlier techniques, the suggested configured Convolution Neural Network with SCFGWP exceeds with regard to high accuracy, recall and precision. The suggested 10XCon5XPool with SCFGWO obtains 98.01 as accuracy compared to other method 3XConPool which results 97.23% accuracy. CONCLUSION: The Proposed Method 1 and Proposed Method 2 is presented here, where Proposed Method 2 with 5 times convolution layer with pooling layer yields high accuracy compared to proposed method 1. The main contribution by the SCFGWO algorithm resulted in the achievement of accuracy. This study will open the door for further investigation and the creation of deep learning-based techniques with optimization for ophthalmic processing.

On the self-assessment of ocular status and of visual functions by senior students at Russian medical universities (anonymous survey results)

BACKGROUND: Visual impairment is a worldwide problem for the humanity in general, including students.&#x0D; AIM: to conduct a rough estimate of the visual system status in senior medical students at Russian universities taking a training according to General Medicine educational program 31.05.01 (specialty) and having completed the ophthalmology course.&#x0D; MATERIALS AND METHODS: an online anonymous survey of students from five universities in various cities of the country was conducted using an original interactive questionnaire. Answers were received from 549 respondents, predominantly women (n = 425, 77.4%), mean age 22.4 ± 0,06 years.&#x0D; RESULTS: Only 42.7% of students rated their vision as “excellent” or “good.” The most common refractive error according to the survey participants’ self-assessment was myopia, which was reported by 56.1% of them, while 21.9% of respondents reported that they did not know their clinical refraction; 25.5% of students confirmed the presence of astigmatism. 56.9% of respondents use optical correction, glasses being the most popular option. 76.7% of the respondents had their vision testing, and 64.5% visited an ophthalmologist within the last year. Any other concomitant ocular condition (refractive errors excluded) was reported by 4.9% of students (most frequently various types of vitreoretinal pathology, dry eye syndrome, and strabismus were mentioned). 57.9% of respondents believe their vision to have worsened over the past few years, and excessive visual stress was considered the leading cause, reported by 57.2% of the study participants. The respondents rated the importance of having a good vision at 9.25 ± 0.06 points on an arbitrary scale from 1 (minimum) to 10 (maximum) points.&#x0D; CONCLUSIONS: Senior students at Russian medical universities highly appreciate the importance of good vision, while more than half of respondents have visual impairments, use optical correction, and also believe that their vision continues to deteriorate. Insufficient awareness of some students about their vision and gaps in ophthalmological knowledge were revealed.

Hierarchical Knowledge Guided Learning for Real-World Retinal Disease Recognition.

In the real world, medical datasets often exhibit a long-tailed data distribution (i.e., a few classes occupy the majority of the data, while most classes have only a limited number of samples), which results in a challenging long-tailed learning scenario. Some recently published datasets in ophthalmology AI consist of more than 40 kinds of retinal diseases with complex abnormalities and variable morbidity. Nevertheless, more than 30 conditions are rarely seen in global patient cohorts. From a modeling perspective, most deep learning models trained on these datasets may lack the ability to generalize to rare diseases where only a few available samples are presented for training. In addition, there may be more than one disease for the presence of the retina, resulting in a challenging label co-occurrence scenario, also known as multi-label, which can cause problems when some re-sampling strategies are applied during training. To address the above two major challenges, this paper presents a novel method that enables the deep neural network to learn from a long-tailed fundus database for various retinal disease recognition. Firstly, we exploit the prior knowledge in ophthalmology to improve the feature representation using a hierarchy-aware pre-training. Secondly, we adopt an instance-wise class-balanced sampling strategy to address the label co-occurrence issue under the long-tailed medical dataset scenario. Thirdly, we introduce a novel hybrid knowledge distillation to train a less biased representation and classifier. We conducted extensive experiments on four databases, including two public datasets and two in-house databases with more than one million fundus images. The experimental results demonstrate the superiority of our proposed methods with recognition accuracy outperforming the state-of-the-art competitors, especially for these rare diseases.

The Decline of Basic Ophthalmology in General Medical Education: A Scoping Review and Recommended Potential Solutions.

This literature review aims to explore research and conceptual pieces on the state of ophthalmology education and suggest potential ways to address current challenges. A search was conducted in PubMed, ERIC, Web of Science, and Google Scholar with combinations of the following search terms: "ophthalmology education," "undergraduate medical education," "medical student," "United States," and "Canada." Eliminating irrelevant articles yielded 47 articles. Three were excluded because of region and focus, leaving 44. After examining the citations, we generated an additional 22 texts for review, totaling 66 articles. Four primary themes were identified: (1) challenges to ophthalmological education in the U.S. and Canada, (2) potential remedies for optimizing ophthalmology curriculum, (3) technology in ophthalmology education, and (4) innovative ophthalmology teaching approaches. Major challenges included the lack of a standardized curriculum and inadequate clinical exposure and skills training. A number of remedies were proposed, such as standardizing curriculum and furthering faculty involvement, utilizing technology as time-effective learning aids, and employing innovative teaching approaches such as service learning. In light of challenges in ophthalmology education, curriculum designers should consider Cognitive Load Theory (CLT) to assist students to remember meaningful exposures to ophthalmology knowledge and techniques. Based on CLT, we suggest two potential approaches to incorporating ophthalmology curriculum. The first is to embrace interdisciplinary collaborations and place ophthalmology knowledge in varied contexts to facilitate schema construction. The second is to incorporate ophthalmology diagnostics requirements into OSCEs and utilize simulation models for students to gradually increase the fidelity of tasks and devote cognitive resources fully to learning.

Personalized Care in Eye Health: Exploring Opportunities, Challenges, and the Road Ahead for Chatbots.

In modern eye care, the adoption of ophthalmology chatbots stands out as a pivotal technological progression. These digital assistants present numerous benefits, such as better access to vital information, heightened patient interaction, and streamlined triaging. Recent evaluations have highlighted their performance in both the triage of ophthalmology conditions and ophthalmology knowledge assessment, underscoring their potential and areas for improvement. However, assimilating these chatbots into the prevailing healthcare infrastructures brings challenges. These encompass ethical dilemmas, legal compliance, seamless integration with electronic health records (EHR), and fostering effective dialogue with medical professionals. Addressing these challenges necessitates the creation of bespoke standards and protocols for ophthalmology chatbots. The horizon for these chatbots is illuminated by advancements and anticipated innovations, poised to redefine the delivery of eye care. The synergy of artificial intelligence (AI) and machine learning (ML) with chatbots amplifies their diagnostic prowess. Additionally, their capability to adapt linguistically and culturally ensures they can cater to a global patient demographic. In this article, we explore in detail the utilization of chatbots in ophthalmology, examining their accuracy, reliability, data protection, security, transparency, potential algorithmic biases, and ethical considerations. We provide a comprehensive review of their roles in the triage of ophthalmology conditions and knowledge assessment, emphasizing their significance and future potential in the field.

Predictors of Ophthalmology Resident Performance From Medical Student Application Materials

To determine whether elements in ophthalmology residency applications are predictors of future resident performance. This multi-institutional, cross-sectional, observational study retrospectively reviewed the residency application materials of ophthalmology residents who graduated from residency from 2006 through 2018. Resident performance was scored by 2 faculty reviewers in 4 domains (clinical, surgical, academic, and global performance). Correlation between specific elements of the residency application and resident performance was assessed by Spearman correlation coefficients (univariate) and linear regression (multivariate) for continuous variables and logistic regression (multivariate) for categorical variables. Seven ophthalmology residency programs in the US. Ophthalmology residents who graduated from their residency program. High-performing residents were a diverse group, in terms of sex, ethnicity, visa status, and educational background. Residents with United States Medical Licensing Examination Step 1 scores higher than the national average for that year had significantly higher scores in all 4 performance domains than those who scored at or below the mean (all domains P < 0.05). Residents who had honors in at least 4 core clerkships and who were members of Alpha Omega Alpha Medical Honor Society also had higher scores in all 4 performance domains (all domains P ≤ 0.04). Step 1 score (ρ=0.26, P < 0.001) and the difference between Step 1 score and the national average for that year (ρ=0.19, P = 0.009) positively correlated with total resident performance scores. Residents who passed the American Board of Ophthalmology Written Qualifying Examination or Oral Examination on their first attempt had significantly higher Step 1/2 scores (P ≤ 0.005), Ophthalmology Knowledge Assessment Program scores (P = 0.001), and resident performance scores (P ≤ 0.004). In this new landscape of increasing numbers of applicants to residency programs and changing of the Step 1 score to pass/fail, our findings may help guide selection committees as they holistically review applicants to select exceptional future residents in ophthalmology.

Assessment of Ophthalmology Teaching and its Impact on the Choice of Future Specialties Among Medical Students of Jazan University.

Ophthalmology is essential for primary and specialty care physicians, as eye complaints are common, accounting for a sizable proportion of general practice consultations and emergency department visits. Fundamental ophthalmology knowledge is also relevant to other specialty fields. Thus, medical schools must provide effective undergraduate curricula to teach students about salient points, visual examination skills, emergency recognition, and referral indications. The International Council of Ophthalmology (ICO) has set guidelines that medical students should imbibe to become proficient in ophthalmology. However, there have been no recent investigationsevaluating undergraduate ophthalmology education at Jazan University's Faculty of Medicine. Therefore, this study aimed to compare the curriculum at Jazan University to the ICO's requirements for undergraduate medical education. An observational cross-sectional study was conducted with both male and female student participantsenrolled in an ophthalmology course at Jazan University's Faculty of Medicine. Following IRB approval, the questionnaire was distributed on social media to assess if Jazan University's undergraduate ophthalmology curriculum complies with ICOstandards. The study included a diverse sample of 322 participants, predominantly consisting of female students (n=178, 55.3%). The participants' ages ranged from 22 to 36 years, with the majority falling within the 24-25 year age range (n=173, 53.7%). Regarding academic performance, (n=117, 36.3%) of participants had a GPA of less than 4, while 66 (20.5%) had a GPA between 4.76 and 5.00. Among the respondents, 31 (9.6%) indicated having no exposure to ophthalmology, while 117 (36.3%) felt they had insufficient exposure. A considerable percentage of participants expressed competence in various areas, such as obtaining ocular history (n=113, 35.1%), testing visual acuity (n=201, 62.4%), and examining extraocular motility (n=201, 62.4%). In total, 98participants (30.4%) expressed an interest in ophthalmology, while the majority (n=224, 69.6%) were not interested. Essential improvements include increasing hands-on clinical experience, small-group learning, exposure across academic years, and early mentorship. Developing competency-based curricula aligned with ICO guidelines could significantly strengthen education. Better training quality and exposure will equip students with the necessary skills, boost confidence, and potentially expand the ophthalmology workforce.

Evaluation of the Performance of a 3D-Printed Smartphone-Based Retinal Imaging Device as a Screening Tool for Retinal Pathology in Mozambique.

Low-income countries carry approximately 90% of the global burden of visual impairment, and up to 80% of this could be prevented or cured. However, there are only a few studies on the prevalence of retinal disease in these countries. Easier access to retinal information would allow differential diagnosis and promote strategies to improve eye health, which are currently scarce. This pilot study aims to evaluate the functionality and usability of a tele-retinography system for the detection of retinal pathology, based on a low-cost portable retinal scanner, manufactured with 3D printing and controlled by a mobile phone with an application designed ad hoc. The study was conducted at the Manhiça Rural Hospital in Mozambique. General practitioners, with no specific knowledge of ophthalmology or previous use of retinography, performed digital retinographies on 104 hospitalized patients. The retinographies were acquired in video format, uploaded to a web platform, and reviewed centrally by two ophthalmologists, analyzing the image quality and the presence of retinal lesions. In our sample there was a high proportion of exudates and hemorrhages-8% and 4%, respectively. In addition, the presence of lesions was studied in patients with known underlying risk factors for retinal disease, such as HIV, diabetes, and/or hypertension. Our tele-retinography system based on a smartphone coupled with a simple and low-cost 3D printed device is easy to use by healthcare personnel without specialized ophthalmological knowledge and could be applied for the screening and initial diagnosis of retinal pathology.

Success of ChatGPT, an AI language model, in taking the French language version of the European Board of Ophthalmology examination: A novel approach to medical knowledge assessment

The purpose of this study was to evaluate the performance of ChatGPT, a cutting-edge artificial intelligence (AI) language model developed by OpenAI, in successfully completing the French language version of the European Board of Ophthalmology (EBO) examination and to assess its potential role in medical education and knowledge assessment. ChatGPT, based on the GPT-4 architecture, was exposed to a series of EBO examination questions in French, covering various aspects of ophthalmology. The AI's performance was evaluated by comparing its responses with the correct answers provided by ophthalmology experts. Additionally, the study assessed the time taken by ChatGPT to answer each question as a measure of efficiency. ChatGPT achieved a 91% success rate on the EBO examination, demonstrating a high level of competency in ophthalmology knowledge and application. The AI provided correct answers across all question categories, indicating a strong understanding of basic sciences, clinical knowledge, and clinical management. The AI model also answered the questions rapidly, taking only a fraction of the time needed by human test-takers. ChatGPT's performance on the French language version of the EBO examination demonstrates its potential to be a valuable tool in medical education and knowledge assessment. Further research is needed to explore optimal ways to implement AI language models in medical education and to address the associated ethical and practical concerns.

An Ophthalmology Virtual Externship during the COVID-19 Pandemic: A Pilot Study.

Background The evolution of medical school curricula, characterized by truncated preclinical periods and reduced emphasis on ophthalmology, presents formidable obstacles to early exposure for aspiring medical students. The constraints imposed by the coronavirus disease 2019 pandemic further exacerbated the limitations on opportunities, compelling the implementation of innovative initiatives aimed at augmenting students' ophthalmology education through virtual means. Purpose This article assesses the impact of an Ophthalmology Virtual Externship (OVE) on medical students' knowledge, interest, confidence, and seeking mentorship in ophthalmology. Materials and Methods A total of 76 students voluntarily participated in the program. The OVE encompassed four virtual sessions, facilitated by 4th year medical students employing a near-peer mentorship framework. The initiative was tailored for 2nd and 3rd year medical students and was conducted under the supervision of a faculty member. All participating students completed both pre- and postexternship surveys utilizing a 7-point Likert scale to gauge their levels of interest, confidence, and inclination toward mentorship opportunities in the field of ophthalmology. Furthermore, assessments of ophthalmology knowledge were administered prior to and subsequent to the externship participation. The degree of satisfaction derived from the OVE experience was also evaluated. Results Participation in the OVE significantly elevated confidence in knowledge ( p < 0.001) and mentorship interest ( p = 0.029). Ophthalmology knowledge test scores also notably improved post-OVE across all participants, irrespective of prior experience ( p < 0.001), with the most significant increase observed among 2nd and 3rd year students ( p < 0.0001). After OVE participation, 73% of students expressed intent to pursue ophthalmology opportunities, including mentorship or research. The OVE received an average Likert score of 6.35 out of 7 for student satisfaction. Conclusion The OVE serves as a virtual learning instrument beneficial for 2nd and 3rd year students with a proclivity for ophthalmology, offering a means to circumvent curriculum-related constraints. Moreover, given the decline in formal ophthalmic education, our study contributes to future research assessing the effectiveness of an OVE in addressing ophthalmic knowledge gaps among all medical students.

Nurse Practitioner Students' Knowledge Assessment and Perceived Preparedness to Triage Ophthalmology Complaints in a Primary Care Setting: An Educational Intervention.

Purpose In this proof-of-concept pilot study, we aimed to increase nurse practitioner (NP) student knowledge of ophthalmology to prepare NPs for encounters in primary care settings. The Association of University Professors of Ophthalmology (AUPO) and the American Academy of Ophthalmology (AAO) endorse core knowledge that medical students should achieve. We assess the effectiveness of an innovative ophthalmologist-led curriculum based on these competencies tailored to issues NPs encounter in primary care. Methods Johns Hopkins University NP students enrolled in a pre-post-cohort study and educational intervention. The didactic program was developed according to AUPO and AAO core ophthalmology content for medical students and was taught in-person by an ophthalmologist. Pre-post-assessments evaluated students' perceived readiness to encounter ophthalmic issues in the clinic and baseline knowledge of core competencies of ophthalmology. Results A total of 42 NP students were included in the analysis. NP students improved in core knowledge and readiness to encounter ophthalmology issues. After the educational event, there was a statistically significant improvement in students' ratings of preparedness to obtain a focused history, exam, perform initial management and decide the urgency of a referral for acute painless vision loss ( p < 0.001), chronic vision loss ( p < 0.001), or a patient with a red/painful eye ( p < 0.001). Students showed a statistically significant improvement in postdidactic event core ophthalmology knowledge assessment scores ( p = 0.002). Conclusion Primary care NPs are increasingly the initial point of contact for patients with ophthalmic complaints, and thus, high-quality and thorough education regarding ophthalmology triage and referral for NPs is necessary. NP student comfort with and knowledge of ophthalmic complaints and triage may be improved by a brief educational intervention taught by an ophthalmologist early in the NP curriculum.

Improved Performance of ChatGPT-4 on the OKAP Examination: A Comparative Study with ChatGPT-3.5.

Introduction: This study aims to evaluate the performance of ChatGPT-4, an advanced artificial intelligence (AI) language model, on the Ophthalmology Knowledge Assessment Program (OKAP) examination compared to its predecessor, ChatGPT-3.5. Methods: Both models were tested on 180 OKAP practice questions covering various ophthalmology subject categories. Results: ChatGPT-4 significantly outperformed ChatGPT-3.5 (81% vs. 57%; p <0.001), indicating improvements in medical knowledge assessment. Discussion: The superior performance of ChatGPT-4 suggests potential applicability in ophthalmologic education and clinical decision support systems. Future research should focus on refining AI models, ensuring a balanced representation of fundamental and specialized knowledge, and determining the optimal method of integrating AI into medical education and practice.

Consultations in Eye Pathology: Experience at the Ophthalmology Specialty Hospital.

Ophthalmic pathology is a discipline that relies heavily on a knowledge of clinical ophthalmology. The diagnosis of ocular and periocular lesions can be challenging because some lesions and diseases are unique to this region, whereas others may demonstrate site-specific differences from nonocular counterparts. Because of these challenges, ocular and periocular biopsies are frequently referred to specialized ophthalmic pathology centers for second opinion diagnoses. To analyze the referral patterns, diagnostic challenges, and diagnostic discrepancies for second opinion referrals at a dedicated ophthalmic pathology laboratory with an emphasis on lesions of special interest in ophthalmic pathology. Data sources included the pathology records of all slides and blocks received in consultation at the referral eye pathology center between December 1, 2015, and December 1, 2022, the personal experience of senior authors, and published peer-reviewed literature. Corneal, intraocular, and conjunctival biopsies are the most common types of cases received in consultation without the referring pathologist's diagnosis, likely reflecting diagnostic challenges. Degenerative intraocular processes occasionally raise concern for a neoplasm. Conjunctival melanocytic lesions are the most common conjunctival biopsies referred for second opinion diagnosis and require careful tissue sampling and clinical-pathologic correlation. Careful clinical-pathologic correlation, a high level of suspicion, and adequate sampling also are required for the accurate diagnosis of periocular sebaceous carcinoma. The diagnostic discrepancies involving uveal, retinal, conjunctival, eyelid, and temporal artery biopsies are most likely to adversely influence patient management and possible outcome. Such specimens may benefit from referral to specialized ophthalmic pathology laboratories.

Assessment of skills and knowledge in clinical ophthalmology: A survey among undergraduate medical students during internship in SKNMC and GH, Pune

Internship is the last year of undergraduate medical training wherein a graduate is exposed to actual patients, conduct varied tasks and acquire skills under supervision of a faculty so that medical student becomes capable of performing clinical skills independently. In India interns have a compulsory 15 days posting in the subject of Ophthalmology. In this study we assessed the clinical skills and knowledge of undergraduate students using a structured questionnaire. A detailed questionnaire based study was conducted which had four parts: (1) clinical skills (2) diagnosis of anterior segment diseases (3) diagnosis of posterior segment diseases and (4) ocular emergencies and sight threatening diseases. Interns were asked to fill this questionnaire before and after completion of 15 days training. : A statistically significant improvement was found i assessment of clinical skills, anterior segment eye diseases and ocular emergencies; whereas assessment of posterior segment diseases showed no statistically significant improvement. The undergraduate teaching program in Ophthalmology seems to be adequate in diagnosis of anterior segment eye diseases and ocular emergencies; though more focus is required in training of diagnosis of posterior segment diseases and certain ocular emergencies. There is a need of change in the structure of training programs of undergraduate students in order to improve their clinical skills and knowledge of appropriate referral after graduation during their independent practice.

Avaliação do conhecimento dos pediatras e neonatologistas sobre afecções oculares na infância

Objective: The aim was to evaluate the level of knowledge of pediatricians and neonatologists about eye problems in children, their diagnosis and management, using a standardized questionnaire. Methods: A questionnaire with demographic data and questions about ophthalmological knowledge was applied among pediatricians, through the transmission line of the pediatric service of the HC FMRP/USP from January to June 2021. A cross-sectional study was carried out, whose responses were tabulated, and statistical analysis was performed using the Krukal Wallis Test and Fishers Exact Test for comparison between the pre-established groups (pediatric residents, 4 to 9 years, and more than 10 years of practice in pediatrics). Sampling was by convenience. Results: The structured questionnaire was sent to 277 pediatricians. Ninety pediatricians answered the questionnaire and 81.11% were female. As for the time of pediatric practice, 42.22% had more than 10 years. From the 17 questions about ophthalmologic knowledge, correct answers ranged from 6 to 14, and the average score was 58.52%. The questions with the highest error rate were about the management of newborns with ocular discharge and congenital tear obstruction and when a premature child should be evaluated by an ophthalmologist. However, no significant differences were found when comparing the correct answers between the groups (p=0.425) Conclusion: The results suggest a deficiency in ophthalmologic knowledge among the pediatricians interviewed; therefore, continuing education and collaboration programs between ophthalmology and pediatrics disciplines should be developed and reinforced to deepen knowledge on these topics.

AVALIAÇÃO DO CONHECIMENTO DOS PEDIATRAS E NEONATOLOGISTAS SOBRE AFECÇÕES OCULARES NA INFÂNCIA.

Objective: The aim was to evaluate the level of knowledge of pediatricians and neonatologists about eye problems in children, their diagnosis and management, using a standardized questionnaire. Methods: A questionnaire with demographic data and questions about ophthalmological knowledge was applied among pediatricians, through the transmission line of the pediatric service of the HC FMRP/USP from January to June 2021. A cross-sectional study was carried out, whose responses were tabulated, and statistical analysis was performed using the Krukal Wallis Test and Fishers Exact Test for comparison between the pre-established groups (pediatric residents, 4 to 9 years, and more than 10 years of practice in pediatrics). Sampling was by convenience. Results: The structured questionnaire was sent to 277 pediatricians. Ninety pediatricians answered the questionnaire and 81.11% were female. As for the time of pediatric practice, 42.22% had more than 10 years. From the 17 questions about ophthalmologic knowledge, correct answers ranged from 6 to 14, and the average score was 58.52%. The questions with the highest error rate were about the management of newborns with ocular discharge and congenital tear obstruction and when a premature child should be evaluated by an ophthalmologist. However, no significant differences were found when comparing the correct answers between the groups (p=0.425) Conclusion: The results suggest a deficiency in ophthalmologic knowledge among the pediatricians interviewed; therefore, continuing education and collaboration programs between ophthalmology and pediatrics disciplines should be developed and reinforced to deepen knowledge on these topics.

Avaliação do conhecimento dos pediatras e neonatologistas sobre afecções oculares na infância

OBJECTIVE: The aim was to evaluate the level of knowledge of pediatricians and neonatologists about eye problems in children, their diagnosis and management, using a standardized questionnaire. METHODS: A questionnaire with demographic data and questions about ophthalmological knowledge was applied among pediatricians, through the transmission line of the pediatric service of the HC FMRP/USP from January to June 2021. A cross-sectional study was carried out, whose responses were tabulated, and statistical analysis was performed using the Krukal Wallis Test and Fishers Exact Test for comparison between the pre-established groups (pediatric residents, 4 to 9 years, and more than 10 years of practice in pediatrics). Sampling was by convenience. RESULTS: The structured questionnaire was sent to 277 pediatricians. Ninety pediatricians answered the questionnaire and 81.11% were female. As for the time of pediatric practice, 42.22% had more than 10 years. From the 17 questions about ophthalmologic knowledge, correct answers ranged from 6 to 14, and the average score was 58.52%. The questions with the highest error rate were about the management of newborns with ocular discharge and congenital tear obstruction and when a premature child should be evaluated by an ophthalmologist. However, no significant differences were found when comparing the correct answers between the groups (p=0.425) CONCLUSION: The results suggest a deficiency in ophthalmologic knowledge among the pediatricians interviewed; therefore, continuing education and collaboration programs between ophthalmology and pediatrics disciplines should be developed and reinforced to deepen knowledge on these topics.

Virtual Ophthalmology Rotation for Visiting Medical Students: An Opportunity to Enhance Diversity in the Workforce.

Introduction We created a virtual rotation to facilitate the exposure of ophthalmology to medical students and serve as a pilot program to help attract students from under-represented in medicine (URM) backgrounds. In addition to the rotation eliminating the financial burdens associated with in-person away rotations, we offered a not-for-credit (i.e., drop-in) option that included sessions outside the typical clinic hours. This option reduced scheduling conflicts as a barrier to enrollment and allowed junior medical students and postgraduates to participate and hopefully further develop an interest in ophthalmology. Methods Before the rotation, participants completed a pre-test and a survey to collect data on learners' backgrounds and interest in applying for ophthalmology residency. The rotation included live lectures, case-based discussions, chart reviews, and guided self-study. Following the rotation, participants completed a post-test and a survey to query applicants on the online rotation's utility and delivery. Results Eleven learners enrolled in the course and completed the prerotation survey and test. Approximately one-third (4/11; 36%) were URM students and two-thirds (7/11; 64%) were female. All responded they were planning to apply for ophthalmology residency. All responded they strongly agreed that the rotation increased their general knowledge in ophthalmology, and 89% (9/11) strongly agreed that it improved their ability to diagnose and manage actual patients. Nearly all (7/8; 87.5%) strongly agreed the rotation provided the opportunity to seek support for the residency application process, and all found the online platform reliable and easy to access. Exam scores improved significantly from pre- to post-tests (60 vs. 79%; p < 0.01). Conclusions The rotation attracted a substantial proportion of URM students. Learners reported that the virtual rotation effectively taught and supported their endeavors to become ophthalmologists. Virtual rotations for visiting students can reduce barriers such as travel, financial costs, and time constraints that might otherwise hinder exposure to specialty training that is not offered or is underrepresented at students' home institutions. Increasing exposure and offering mentorship through this novel platform deserves further study to enhance diversity and inclusion in medicine.