(1) Objectives: Clinical pharmacists are now playing a significant role in hospitals aiming to reduce medication errors, adverse drug reactions, and healthcare costs. Therefore, the main objective of this study was to assess the interventions provided by a clinical pharmacist in the intensive care unit at the King Faisal Hospital in Taif city. (2) Methods: For this single-center retrospective study, patients were included from December 2021 to May 2022. In the present study, all the interventions of clinical pharmacists made over six months were included. The Intensive care unit (ICU) ward was covered by three clinical pharmacists, and the interventions made were categorized into four groups: (1) interventions related to indications; (2) interventions regarding safety; (3) interventions regarding dosing, and (4) miscellaneous. Descriptive statistics was applied to evaluate the results in the form of frequencies and percentages. Analysis was performed using the statistical package SPSS 20.0. (3) Results: Overall, a total of 404 interventions were recommended for 165 patients during the six- month period of study. Among them, 370 interventions (91.5%) were accepted by physicians. Among all the interventions, the majority were suggested regarding ‘indication’ (45.7%), including the addition of drugs, drugs with no indications, and duplication. The acceptance rate of clinical pharmacist intervention was 98.5%. (4) Conclusions: This retrospective study shows that clinical pharmacists played a critical role in optimizing drug therapy which could subsequently help to prevent drug-related issues and lower drug costs. More research is needed to do a thorough cost-benefit analysis.

Glioblastoma (GBM) is a highly aggressive primary malignant brain tumor with a dismal prognosis despite current treatment strategies. Inflammation plays an essential role in GBM pathophysiology, contributing to tumor growth, invasion, immunosuppression, and angiogenesis. As a result, pharmacological intervention with anti-inflammatory drugs has been used as a potential approach for the management of GBM. To provide an overview of the current understanding of GBM pathophysiology, potential therapeutic applications of anti-inflammatory drugs in GBM, conventional treatments of glioblastoma and emerging therapeutic approaches currently under investigation. A narrative review was carried out, scanning publications from 2000 to 2023 on PubMed and Google Scholar. The search was not guided by a set research question or a specific search method but rather focused on the area of interest. Conventional treatments such as surgery, radiotherapy, and chemotherapy have shown some benefits, but their effectiveness is limited by various factors such as tumor heterogeneity and resistance.

Autism is one of the most pressing issues facing the international community in recent years, particularly in Middle Eastern countries. Risperidone is a selective serotonin type 2 and dopamine type 2 receptor antagonist. It is the most administered antipsychotic medication in children with autism-related behavioral disorders. Therapeutic monitoring of risperidone may improve safety and efficacy in autistic individuals. The main objective of this work was to develop a highly sensitive green fitted method for the determination of risperidone in the plasma matrix and pharmaceutical dosage forms. Novel water-soluble N–carbon quantum dots were synthesized from guava fruit, a natural green precursor, and used for determination of risperidone based on quenching fluorescence spectroscopy phenomena. The synthesized dots were characterized by transmission electron microscopy and Fourier transform infrared spectroscopy. The synthesized N–carbon quantum dots exhibited aquantum yield of 26.12% and showed a strong emission fluorescence peak at 475 nm when excited at 380 nm. The fluorescence intensity of the N–carbon quantum dots decreased with increasing risperidone concentration, indicating that the fluorescence quenching was concentration dependent. The presented method was carefully optimized and validated according to the guidelines of ICH, and it demonstrated good linearity in a concentration range of 5–150 ng mL⁻¹. With a LOD of 1.379 ng mL⁻¹ and a LOQ of 4.108 ng mL⁻¹, the technique was extremely sensitive. Due to the high sensitivity of the proposed method, it could be effectively used for the determination of risperidone in the plasma matrix. The proposed method was compared with the previously reported HPLC method in terms of sensitivity and green chemistry metrics. The proposed method proved to be more sensitive and compatible with the principles of green analytical chemistry.

(1) Background: Outpatient parenteral antibiotic therapy (OPAT) is a well-established and cost-effective measure that improves the efficient use of healthcare resources and increases bed availability. Only limited published data is available to illustrate OPAT implementation and outcomes in Saudi Arabia. The main objective of this study was to evaluate the effectiveness of OPAT in a tertiary center in Saudi Arabia. (2) Methods: In this retrospective study, clinical charts of enrolled patients were reviewed in a tertiary care center from the initial month of November 2017 to March 2020. All admitted patients with a central line and who enrolled in the OPAT of the hospital during this study period were included. The primary outcome was the 30-days readmission rate of OPAT patients. Secondary outcomes were factors associated with OPAT failure. Descriptive analysis of the data was used to express the results. (3) Results: We enrolled 90 patients; 54 (60%) were male; the mean age was 55.16 (±17.7) years old. The mean duration of the antimicrobial treatment was 21.9 (+24.6) days. All patients completed the intended course of therapy. Ertapenem was the most frequently used antimicrobial (43%), followed by vancomycin (11.2%). Urinary tract infections (UTIs) are some of the most common bacterial infections in 25 patients (26.9%), followed by osteomyelitis in 16 patients (17.2%). Extended-spectrum beta-lactamase E.coli was the highest common isolated microorganism (44.9%), followed by methicillin-resistant Staphylococcus aureus MRSA (16.9%). The readmission to the hospital during therapy was required for 12 patients (13.3%). Shifting from hospital care to OPAT care resulted in cost savings of 18 million SAR in the overall assessment period and avoided a total of 1984 patient days of hospitalization. (4) Conclusion: The findings have shown that OPAT therapy was effective with minimum hospital readmissions and therapy complications. OPAT programs can reduce healthcare costs and should be integrated into practice.

The protective and therapeutic anti-inflammatory and antioxidant potency of Malapterurus electricus (F. Malapteruridae) skin fish methanolic extract (FE) (300 mg/kg.b.wt/day for 7 days, orally) was tested in monosodium urate(MSU)-induced arthritic Wistar albino male rats’ joints. Serum uric acid, TNF-α, IL-1β, NF-𝜅B, MDA, GSH, catalase, SOD, and glutathione reductase levels were all measured. According to the findings, FE significantly reduced uric acid levels and ankle swelling in both protective and therapeutic groups. Furthermore, it has anti-inflammatory effects by downregulating inflammatory cytokines, primarily through decreased oxidative stress and increased antioxidant status. All the aforementioned lesions were significantly improved in protected and treated rats with FE, according to histopathological findings. iNOS immunostaining revealed that protected and treated arthritic rats with FE had weak positive immune-reactive cells. Phytochemical analysis revealed that FE was high in fatty and amino acids. The most abundant compounds were vaccenic (24.52%), 9-octadecenoic (11.66%), palmitic (34.66%), stearic acids (14.63%), glycine (0.813 mg/100 mg), and alanine (1.645 mg/100 mg). Extensive molecular modelling and dynamics simulation experiments revealed that compound 4 has the potential to target and inhibit COX isoforms with a higher affinity for COX-2. As a result, we contend that FE could be a promising protective and therapeutic option for arthritis, aiding in the prevention and progression of this chronic inflammatory disease.

The use of artificial intelligence (AI) and the Internet of Things (IoT), which is a developing technology in medical applications that assists physicians in making more informed decisions regarding patients’ courses of treatment, has become increasingly widespread in recent years in the field of healthcare. On the other hand, the number of PET scans that are being performed is rising, and radiologists are getting significantly overworked as a result. As a direct result of this, a novel approach that goes by the name “computer-aided diagnostics” is now being investigated as a potential method for reducing the tremendous workloads. A Smart Lung Tumor Detector and Stage Classifier (SLD-SC) is presented in this study as a hybrid technique for PET scans. This detector can identify the stage of a lung tumour. Following the development of the modified LSTM for the detection of lung tumours, the proposed SLD-SC went on to develop a Multilayer Convolutional Neural Network (M-CNN) for the classification of the various stages of lung cancer. This network was then modelled and validated utilising standard benchmark images. The suggested SLD-SC is now being evaluated on lung cancer pictures taken from patients with the disease. We observed that our recommended method gave good results when compared to other tactics that are currently being used in the literature. These findings were outstanding in terms of the performance metrics accuracy, recall, and precision that were assessed. As can be shown by the much better outcomes that were achieved with each of the test images that were used, our proposed method excels its rivals in a variety of respects. In addition to this, it achieves an average accuracy of 97 percent in the categorization of lung tumours, which is much higher than the accuracy achieved by the other approaches.