Objectives: This study aimed to assess the efficacy of Oseltamivir-Azithromycin combination therapy for prevention of Influenza-A(H1)pdm09 infection associated complications and early relief of influenza symptoms. Methods: In a retrospective observational cohort study, Influenza-A(H1)pdm09 infection hospitalized patients were identified and divided into two groups based on the initial therapy. Group-AV patients were initiated on Oseltamivir without any antibiotic in treatment regimen while Group-AV+AZ patients were initiated on Oseltamivir and Azithromycin combination therapy for at least 3-5 days. Patients were evaluated for different clinical outcomes. Results: A total of 227 and 102 patients were identified for Group-AV and Group-AV+AZ respectively. The identified patients of both groups were mostly unvaccinated. Multivariate regression analysis showed that incidences of secondary bacterial infections were significantly less frequent (23.4% vs 10.4%; P-value=0.019) in Group-AV+AZ patients. Group-AV+AZ patients were associated with shorter length of hospitalization (6.58 vs 5.09 days; P-value=<0.0001) and less frequent incidences of respiratory support (38.3% vs 17.6%; P-value=0.016). Overall influenza symptom severity score was statistically significant less for Group-AV+AZ patients on Day-5 (10.68±2.09; P-value=0.001) of hospitalization. Conclusion: Oseltamivir-Azithromycin combination therapy was found to be more efficacious as compared to Oseltamivir alone in rapid recovery and prevention of Influenza associated complications especially in high risk patients.

Each year, the number of cases of strokes and deaths due to this is increasing around the world. This could be due to work stress, lifestyles, unhealthy food habits, and several other reasons. Currently, there are several traditional methods like thrombolysis and mechanical thrombectomy for managing strokes. The current approach has several limitations, like delayed diagnosis, limited therapeutic delivery, and risks of secondary injuries. So, there is a need for some effective and reliable methods for the management of strokes, which could help in early diagnosis followed by the treatment of strokes. Nanotechnology has played an immense role in managing strokes, and recently, it has emerged as a transformative solution offering innovative diagnostic tools and therapeutic strategies. Nanoparticles (NPs) belonging to several classes, including metallic (metallic and metal oxide), organic (lipids, liposome), and carbon, can cross the blood–brain barrier and may exhibit immense potential for managing various strokes. Moreover, these NPs have exhibited promise in improving imaging specificity and therapeutic delivery by precise drug delivery and real-time monitoring of treatment efficacy. Nanomaterials like cerium oxide (CeO₂) and liposome-encapsulated agents have neuroprotective properties that reduce oxidative stress and promote neuroregeneration. In the present article, the authors have emphasized the significant advancements in the nanomedicine management of stroke, including NPs-based drug delivery systems, neuroprotective and neuroregenerative therapies, and multimodal imaging advancements.

Objective: The study aimed to evaluate the novel coronavirus disease 2019 (COVID-19) vaccination acceptance and reluctance among staff working in Saudi healthcare facilities.Methods: A cross-sectional study was conducted during April – May 2021, among healthcare workers in five public hospitals under the National Guards Health Association located in Alahsa, Dammam, Jeddah, Madinah, and Riyadh. The study used a questionnaire in English language, which was distributed through official email communication among healthcare staff currently working at study venues. The data was analyzed using IBM SPSS v23. An ethical approval was obtained.Results: A total of 1,031 responses were recorded. Most of the staff had both doses of COVID-19 vaccine (89%). The mean score for vaccine acceptance on a scale of 1 (strongly disagree) to 5 (strongly agree) was 3.55 ± 1.6. The mean score for vaccine reluctance on the same scale was 2.71 ± 1.05. Most participants mentioned safety (76.9%) and efficacy (56.3%) as vaccine concerns and believed that COVID-19 vaccine may not be effective because of changes in virus strain (55.5%). The variables of gender and nationality significantly affected vaccine acceptance, while age, gender, nationality, and profession significantly affected vaccine reluctance (p< 0.05).Conclusion: Most healthcare staff were vaccinated, and a high acceptance for COVID-19 vaccination was reported. Several demographic factors affected the vaccine acceptance and reluctance.

Background: Inappropriate complementary feeding during the first two years of life significantly impacts children’s health, increasing risks of malnutrition and illness. Methods: This study investigates factors influencing early feeding patterns among 600 mothers of children aged 9–23 months in selected hospitals in Punjab, Pakistan. Using a structured questionnaire, data were collected and analyzed, with associations measured by odds ratios (ORs) and 95% confidence intervals (CIs). Results: The results showed the key indicators of inappropriate complementary feeding among young children, including timely complementary feeding, minimum meal frequency, dietary diversity, and acceptable diet. The rates for these factors were found to be 60.3%, 32.7%, 24.6%, and 48.5%, respectively. The study identified several significant factors influencing these practices. Key predictors of inappropriate feeding included the order of birth, the mother’s employment status, parental education, the number of children, household income, maternal knowledge, and maternal health. Conclusion: The findings underscore that maternal education, employment, and health significantly influence complementary feeding. Targeted interventions and education programs are essential to support healthy feeding behaviors, especially for mothers facing challenges related to education, work, or health conditions. Addressing these practices can improve child health outcomes, contributing to economic growth and a healthier future for Pakistan’s youngest population.

Background: This study systematically evaluates and compares the performance of ChatGPT 3. 5, Google Bard (Gemini), Perplexity AI, Microsoft Copilot, and Meta AI in responding to infectious disease-related multiple-choice questions (MCQs).Methods: A systematic comparative study was conducted using 20 infectious disease case studies sourced from Infectious Diseases: A Case Study Approach by Jonathan C. Cho. Each case study included 7–10 MCQs, resulting in a total of 160 questions. AI platforms were provided with standardized prompts containing the case study text and MCQs without additional context. Their responses were evaluated against a reference answer key from the textbook. Accuracy was measured by the percentage of correct responses, and consistency was assessed by submitting identical prompts 24 h apart.Results: ChatGPT 3.5 achieved the highest numerical accuracy (65.6%), followed by Perplexity AI (63.2%), Microsoft Copilot (60.9%), Meta AI (60.8%), and Google Bard (58.8%). AI models performed best in symptom identification (76.5%) and worst in therapy-related questions (57.1%). ChatGPT 3.5 demonstrated strong diagnostic accuracy (79.1%) but had a significant drop in antimicrobial treatment recommendations (56.6%). Google Bard performed inconsistently in microorganism identification (61.9%) and preventive therapy (62.5%). Microsoft Copilot exhibited the most stable responses across repeated testing, while ChatGPT 3.5 showed a 7.5% accuracy decline. Perplexity AI and Meta AI struggled with individualized treatment recommendations, showing variability in drug selection and dosing adjustments. AI-generated responses were found to change over time, with some models giving different antimicrobial recommendations for the same case scenario upon repeated testing.Conclusion: AI platforms offer potential in infectious disease education but demonstrate limitations in pharmacotherapy decision-making, particularly in antimicrobial selection and dosing accuracy. ChatGPT 3.5 performed best but lacked response stability, while Microsoft Copilot showed greater consistency but lacked nuanced therapeutic reasoning. Further research is needed to improve AI-driven decision support systems for medical education and clinical applications through clinical trials, evaluation of real-world patient data, and assessment of long-term stability.

This paper aims to compare the efficacy of antiviral drug alone and antiviral-antibiotic combination in prevention of complications associated with Influenza B hospitalized patients. Laboratory confirmed Influenza B hospitalized patients who presented in emergency room after 48 hours of symptoms onset were identified and divided into two groups; Group-1 patients were initiated on Antiviral drug (oseltamivir) while Group-2 patients were initiated on Antiviral drug (oseltamivir) in combination with Antibiotic for at least 3 days. Patients were evaluated for different clinical outcomes among both treatment group patients. A total of 153 and 131 patients were identified for Group-1 and Group-2 respectively. Clinical outcomes such as secondary bacterial infections (20.9%-vs-9.1%; P= 0.031), need of respiratory support (28.7%-vs-12.9%; P= 0.002), length of hospitalization stay (6.57-vs-4.95 days; P= <0.001), incidences of ICU admission (15.7%-vs-7.6%; P= 0.036), early clinical failure (32.6%-vs-16.1%; P= 0.01) and time to clinical stability (4.83-vs-4.1 days;P= 0.001) were found to be statistically less significant (P-value <0.05) for Group-2 patients. Early initiation of antibiotic therapy in combination with oseltamivir was found to be more efficacious than oseltamivir alone in prevention of Influenza B associated complications especially in high risk patients.