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Type 2 Diabetes Mellitus (T2DM) patients are exposed to a 7.5 times higher risk of hypoglycemia while fasting during Ramadan. Relevant diabetes guidelines prioritize the use of SGLT2 inhibitors over other classes. There is a great need to enrich data on their safe and effective use by fasting patients at greater risk of hypoglycemia. Therefore, this study aims to assess the safety and tolerability of Empagliflozin in T2DM Muslim patients during Ramadan. A prospective cohort study was conducted for adult Muslim T2DM patients. Patients who met the inclusion criteria were categorized into two sub-cohorts based on Empagliflozin use during Ramadan (Control versus Empagliflozin). The primary outcomes were the incidence of hypoglycemia symptoms and confirmed hypoglycemia. Other outcomes were secondary. All patients were followed up to eight weeks post-Ramadan. A propensity score (PS) matching and Risk Ratio (RR) were used to report the outcomes. Among 1104 patients with T2DM who were screened, 220 patients were included, and Empagliflozin was given to 89 patients as an add-on to OHDs. After matching with PS (1:1 ratio), the two groups were comparable. The use of other OHDs, such as sulfonylurea, DPP4 inhibitors, and Biguanides, was not statistically different between the two groups. The risk of hypoglycemia symptoms during Ramadan was lower in patients who received Empagliflozin than in the control group (RR 0.48 CI 0.26, 0.89; p-value = 0.02). Additionally, the risk of confirmed hypoglycemia was not statistically significant between the two groups (RR 1.09 CI 0.37, 3.22; p-value = 0.89). Empagliflozin use during Ramadan fasting was associated with a lower risk of hypoglycemia symptoms and higher tolerability. Further randomized control trials are required to confirm these findings. [ABSTRACT FROM AUTHOR]

Background and Aim: The availability of concise and valid instruments for measuring vaccination attitudes across different countries or populations is limited. The 12-item four-subscale Vaccination Attitudes Examination (VAX) scale designed to assess vaccination hesitancy has been validated in more than 15 languages. This study aimed to validate the Arabic translation of VAX., Methods: VAX was translated from Danish to Arabic following the Principles of Good Practice for the Translation and Cultural Adaptation Process for Patient-Reported Outcome Measures. The translated VAX was distributed to the citizens of Saudi Arabia in March 2023 through an online survey system and the authors' networks. Internal consistency reliability was assessed with Cronbach's α. Factorial structure was examined using confirmatory factor analysis (CFA). Known-group validity was assessed based on COVID-19 vaccination status., Results: Responses from 164 participants who fully answered the questionnaire were analyzed. The mean age was 40 years, 77 % were females, and 90 % were fully vaccinated against COVID-19, with one-third receiving booster doses. CFA confirmed a well-fit four-factor structure. All items loaded well with their factors: standardized regression weight values ranged from 0.69 to 0.96. Correlations between the four factors ranged from 0.47 to 0.79. Cronbach α ranged from 0.874 to 0.930. As expected, the mean scores of all subscales were higher in those unvaccinated compared to those who were fully vaccinated as well as those fully vaccinated with a booster dose (p < 0.05)., Conclusion: The Arabic translation of the VAX exhibited a well-defined factorial structure with good internal consistency reliability and known-group validity. It is a valuable tool for measuring vaccination hesitancy in Arabic-speaking countries or populations, enabling the comparison of vaccine hesitancy across different countries and cultures., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. This research received no specific grant from any funding agency in the public, commercial or not-for-profit sections., (Copyright © 2024. Published by Elsevier Ltd.)

Background: The current study sets out to develop and validate a robust machine-learning model utilizing electronic health records (EHR) to forecast the risk of hypoglycemia among ICU patients in Jordan., Research Design and Methods: The present study drew upon a substantial cohort of 13,567 patients admitted 26,248 times to the intensive care unit (ICU) over 10 years from July 2012 to July 2022. The primary outcome of interest was the occurrence of any hypoglycemic episode during the patient's ICU stay. Developing and testing predictor models was conducted using Python machine-learning libraries., Results: A total of 1,896 were eligible to participate in the study, 206 experienced at least one hypoglycemic episode. Eight machine-learning models were trained to predict hypoglycemia. All models showed predicting power with a range of 74.53-99.69 for AUROC. Except for Naive Bayes, the six remaining models performed distinctly better than the basic logistic regression usually used for prediction in epidemiological studies. CatBoost model was consistently the best performer with the highest AUROC (0.99), accuracy and precision, sensitivity and specificity, and recall., Conclusions: We used machine learning to anticipate the likelihood of hypoglycemia, which can significantly decrease hypoglycemia incidents and enhance patient outcomes.

While several studies have explored the barriers to accessing community pharmacies for individuals with physical, hearing, visual, and learning disabilities, most have focused on the perspectives of disabled individuals. Therefore, this study aimed to examine the barriers faced by community pharmacists when serving individuals with physical, visual, and hearing disabilities in Saudi Arabia, with the goal of recommending ways to enhance future healthcare provisions., Methods: A mixed-methods cross-sectional phenomenological study was conducted among community pharmacists in Saudi Arabia between March and April 2022. Both closed- and open-ended questions were utilized to identify themes related to community pharmacists' barriers and experiences when providing care to individuals with disabilities., Results: A total of 40 community pharmacists participated in this study. Among them, 57.5% reported encountering difficulties when caring for patients with disabilities, with 65% indicating a lack of specialized services at their respective community pharmacies. Three major themes emerged from the findings: the need for pharmacist training and awareness, technology-guided methods for overcoming communication barriers, and improving overall pharmacy accessibility., Conclusion: This study reveals a significant gap in the provision of services for patients with disabilities in Saudi Arabia. Addressing physical accessibility, providing targeted training, and leveraging technology can enhance care delivery and promote inclusivity. Further research is warranted to assess the effectiveness of technological solutions and the integration of artificial intelligence in improving communication and patient-centered care for individuals with disabilities.