Antimicrobial Stewardship Intervention for the Family Caregiver Attending Primary Health Care Setting: A Quasi-Experimental Study.

Antimicrobial resistance (AMR) has been identified as one of the top ten public health threats facing humanity. The purpose of this study was to assess the effect of an antimicrobial stewardship educational intervention on family caregivers' knowledge and practices in primary healthcare settings in Egypt. A quasi-experimental, one-group pretest-posttest design involving a sample of 300 family caregivers attending family health centers.

Approach to death and dying patients and its relation with death anxiety among medical interns: a multicenter cross-sectional study.

Background: Dealing with death and dying patients is one of the most challenging aspects of medical practice. The purpose of this study was to assess the attitude of medical interns toward death and dying patients as well as their level of death anxiety.

Methods: This cross-sectional study was conducted on medical interns across three countries-Egypt, Jordan, and Palestine-using an online survey created with Google Forms.

Optimizing Probiotic Low-Fat Yogurt: The Benefits of Incorporating Defatted Rice Bran for Enhanced Quality and Functionality.

This study investigated the effects of incorporating defatted rice bran (DRB) at different concentrations (0.5%, 1%, 1.5%, and 2%) on the quality, microbiological, and sensory characteristics of probiotic low-fat yogurt (LFY) during a 21-day storage period at 4°C.

Impact of skin closure with staples vs sutures on perioperative outcomes following lower extremity bypass surgery.

Objective: Wound complications are one of the major sources of morbidity after open vascular procedures, especially lower extremity bypass (LEB). The preferred skin closure method is based on surgeon preference. Because no data clearly demonstrates the superiority of one method over the other, we aimed to compare outcomes of staples vs sutures for skin closure after LEB.

External validation and performance analysis of a deep learning-based model for the detection of intracranial hemorrhage.

Purpose: We aimed to investigate the external validation and performance of an FDA-approved deep learning model in labeling intracranial hemorrhage (ICH) cases on a real-world heterogeneous clinical dataset. Furthermore, we delved deeper into evaluating how patients' risk factors influenced the model's performance and gathered feedback on satisfaction from radiologists of varying ranks.

Methods: This prospective IRB approved study included 5600 non-contrast CT scans of the head in various clinical settings, that is, emergency, inpatient, and outpatient units.