Background This study aimed to evaluate the efficacy of ChatGPT, an advanced natural language processing model, in adapting and synthesizing clinical guidelines for diabetic ketoacidosis (DKA) by comparing and contrasting different guideline sources. Methodology We employed a comprehensive comparison approach and examined three reputable guideline sources: Diabetes Canada Clinical Practice Guidelines Expert Committee (2018), Emergency Management of Hyperglycaemia in Primary Care, and Joint British Diabetes Societies (JBDS) 02 The Management of Diabetic Ketoacidosis in Adults. Data extraction focused on diagnostic criteria, risk factors, signs and symptoms, investigations, and treatment recommendations. We compared the synthesized guidelines generated by ChatGPT and identified any misreporting or non-reporting errors. Results ChatGPT was capable of generating a comprehensive table comparing the guidelines. However, multiple recurrent errors, including misreporting and non-reporting errors, were identified, rendering the results unreliable. Additionally, inconsistencies were observed in the repeated reporting of data. The study highlights the limitations of using ChatGPT for the adaptation of clinical guidelines without expert human intervention. Conclusions Although ChatGPT demonstrates the potential for the synthesis of clinical guidelines, the presence of multiple recurrent errors and inconsistencies underscores the need for expert human intervention and validation. Future research should focus on improving the accuracy and reliability of ChatGPT, as well as exploring its potential applications in other areas of clinical practice and guideline development.

This cross-sectional study examines knowledge, attitudes, and practices surrounding breast cancer awareness and screening among women residents in Qatar. Females, >18 years old, registered with the Primary Health Care Corporation were invited to complete an Arabic or English online survey using a modified version of the Breast Cancer Awareness Module. Of the 9008 participants, 69% report awareness of breast cancer warning signs, but the results did not substantiate these claims. There remains a disconnect between participants’ perceived awareness of their ability to detect breast cancer and their actual recognition of individual signs and symptoms. Nearly half (45.4%) report rarely or never checking their breasts for abnormalities (44.6%). Breast self-examination (BSE) and Breast Cancer Screening (BCS) uptake is low and many are unaware of the starting age for invitation to Qatar’s BCS program. While only 18% of women report receiving an invitation, 94% attended, indicating that the BCS invitation is a remarkably effective means of improving screening uptake. Policymakers should capitalize on early recognition, which is possible in the youthful population. Broadening awareness campaigns and interventions targeting a broader audience including males, community and religious leaders and healthcare professionals may prove more effective in Arab communities.

Introduction This case study aimed to enhance the traceability and retrieval accuracy of ChatGPT-4 in medical text by employing a step-by-step systematic approach. The focus was on retrieving clinical answers from three international guidelines on diabetic ketoacidosis (DKA). Methods A systematic methodology was developed to guide the retrieval process. One question was asked per guideline to ensure accuracy and maintain referencing. ChatGPT-4 was utilized to retrieve answers, and the 'Link Reader' plug-in was integrated to facilitate direct access to webpages containing the guidelines. Subsequently, ChatGPT-4 was employed to compile answers while providing citations to the sources. This process was iterated 30 times per question to ensure consistency. In this report, we present our observations regarding the retrieval accuracy, consistency of responses, and the challenges encountered during the process. Results Integrating ChatGPT-4 with the 'Link Reader' plug-in demonstrated notable traceability and retrieval accuracy benefits. The AI model successfully provided relevant and accurate clinical answers based on the analyzed guidelines. Despite occasional challenges with webpage access and minor memory drift, the overall performance of the integrated system was promising. The compilation of the answers was also impressive and held significant promise for further trials. Conclusion The findings of this case study contribute to the utilization of AI text-generation models as valuable tools for medical professionals and researchers. The systematic approach employed in this case study and the integration of the 'Link Reader' plug-in offer a framework for automating medical text synthesis, asking one question at a time before compilation from different sources, which has led to improving AI models' traceability and retrieval accuracy. Further advancements and refinement of AI models and integration with other software utilities hold promise for enhancing the utility and applicability of AI-generated recommendations in medicine and scientific academia. These advancements have the potential to drive significant improvements in everyday medical practice.

Background: Vitamin D deficiency is highly prevalent worldwide among pregnant women. Although vitamin D supplementation is effective in improving vitamin D status, the safety and optimal dosing of vitamin D supplementation during pregnancy remain less well understood. Objective: This study aimed to investigate the prevalence of vitamin D deficiency among pregnant women and evaluate the effectiveness of vitamin D supplementation in improving vitamin D status during pregnancy. Design: This prospective cohort study assessed the impact of a 16-week daily vitamin D supplementation 1000 IU regimen on vitamin D status among pregnant women. Methods: A total of 365 pregnant women were recruited, and their baseline total circulating 25-hydroxy vitamin D concentrations were measured. Of these, 249 participants completed the study, which involved oral daily supplementation with 1000 IU of vitamin D and a repeat of total circulating 25-hydroxy vitamin D concentrations after 16 weeks. Results: The study found that 57.7% of the participants had vitamin D deficiency, consistent with the rates reported in other studies. However, vitamin D supplementation at a dose of 1000 IU had a small effect size and was not clinically significant. However, 67% of participants with vitamin D deficiency remained deficient; among participants initially with vitamin D insufficiency, 30% became deficient. Moreover, 26.5% of individuals with sufficient vitamin D status at 12 weeks showed insufficient levels by 28 weeks. Conclusion: Vitamin D deficiency is widespread among pregnant women, and vitamin D supplementation at a daily dose of 1000 IU may not adequately address this problem. Although the study has limitations, its results align with previous research and may apply to other populations with a high prevalence of vitamin D deficiency during pregnancy. Further research is necessary to determine the most effective approach for addressing prenatal vitamin D deficiency.