Antimicrobial resistance (AMR) poses a significant global health threat by diminishing the effectiveness of once-powerful antimicrobial agents, leading to higher rates of illness and death, along with escalating healthcare costs. While bacterial resistance is a primary concern, resistance is also increasing against antifungal, antiparasitic, and antiviral drugs. Many of the last-resort drugs are becoming less effective due to AMR. Projections indicate that by 2050, AMR could cause up to 10 million deaths annually, making it the leading cause of death worldwide, a situation that could result in a post-antibiotic era with substantially increased morbidity and mortality. This review aims to raise awareness about the dangers of AMR and its potential to become a silent global pandemic. It begins by examining antimicrobial drugs, followed by a discussion on AMR, focusing on resistance to antibacterial, antifungal, antimalarial, and antiviral drugs, along with its effects on health, and the economy, and prioritized global pathogens. Finally, it explores preventive measures and innovative strategies to combat AMR.

Background: Ecopharmacology, as a form of drug management for the environment, focuses on the impact of drugs on the environment. Pharmacists, and by extension pharmacy students, are expected to play an important role in ecopharmacology. Therefore, this study was conducted to determine the knowledge and attitude towards ecopharmacology and the practice of disposal of leftover or expired medicines among pharmacy students. Methods: This was a descriptive cross-sectional study among pharmacy students in Northwestern Ethiopia. The study took place from May 1 to June 15, 2023. A self-administered questionnaire was used for data collection. Results: Four hundred and forty-five students were included in the study. Only 91 (20%) of the students were aware of the term ecopharmacology, 27% knew that excretion from the human or animal body is the major route by which pharmaceutical agents enter the environment, and 42% were aware of the risk of increased antimicrobial resistance due to antibiotic residues in the environment. In addition, only 27% of respondents reported receiving information about the disposal of pharmaceuticals. The most common method of disposing of medications was throwing them away in household trash (61.8%). Conclusion: Our results suggest that while most pharmacy students in Ethiopia have a positive attitude toward ecopharmacology, they do not know enough about ecopharmacology and dispose of their medicines poorly. More uniform education in ecopharmacology and pharmaceutical pollution might be warranted in the pharmacy curriculum.

Background: Chemotherapy-induced anemia (CIA) is a hematologic complication that frequently affects patients with cancer undergoing chemotherapy. It is associated with worse treatment outcomes, higher rates of morbidity and mortality, worse quality of life, and higher healthcare costs. The incidence and predictors of CIA in Ethiopia, particularly in Northwest Ethiopian oncology centers, are poorly understood. This study was conducted at Northwest Ethiopian oncology centers to evaluate the incidence and determinants of chemotherapy-induced anemia in adult patients with cancer undergoing chemotherapy.Methods: This 3-year hospital-based retrospective follow-up study included adult patients with cancer receiving chemotherapy between 2019 and 2021 at two oncology centers in Northwest Ethiopia. Data were collected from October to December 2021. A binary logistic regression model was used to select variables and determine the Crude Odds Ratio (COR). Variables with P-value < 0.2 were entered into the multivariable logistic regression and Adjusted odds ratio (AOR) with 95% Confidence intervals (CI) for variables with P-value < 0.05 were estimated to show determinants of chemotherapy-induced anemia among cancer patients who received chemotherapy.Results: A total of 402 patients were included in the final analysis. The overall incidence of CIA was 75.4% (95% CI 70.7, 79.8). Older age [AOR = 1.8, 95% CI (1.4–3.5); P = 0.043], hematologic cancer [AOR = 3.7, 95% CI (3.2–5.7), P = 0.021], obesity [AOR = 3.4, 95% CI (2.3–6.9); P = 0.028], ≥6 chemotherapy cycles [AOR = 3.8, 95% CI (3.2–5.1), P = 0.019], cancer metastasis to bone [AOR = 2.9, 95% CI (1.2–4.7), P = 0.025] were statistically significant predictors of chemotherapy-induced anemia.Conclusion: Chemotherapy-induced anemia persisted in a significant percentage of cancer patients. Chemotherapy-induced anemia developed in three-quarters of patients undergoing chemotherapy. Chemotherapy-induced anemia was significantly associated with older age, hematologic malignancy, obesity, a greater number of chemotherapy cycles, and cancer metastasis to bone. To lower the risk of morbidity related to anemia, patients with chemotherapy-induced anemia should be regularly evaluated and treated with appropriate treatment.

Objective: Drug–drug interactions are of major concern due to links to untoward drug effects, hospitalizations, and serious health impacts. Elderly patients are more predisposed to drug interactions than younger patients. The present study aimed to find out the prevalence of drug–drug interactions at North West Ethiopian compressive specialized hospitals’ Internal Medicine wards. Methods: From 30 April to 30 July 2021 GC, a multicenter prospective observational study was conducted at north Ethiopian specialized hospitals. Data was collected by using a structured questionnaire adapted from different literature and medical records at the North West Ethiopian Comprehensive Specialized Hospitals’ Internal Medicine wards during the study period. Thereafter checked the completeness of the collected data was checked drug–drug interactions by using Medscape. Epi data version 4.6.2 software was used as data clearance and STATA version 14.1 was used for further data analysis. Result: A total of 389 subjects participated in the study of which more than half (55.53%) of them were female with a mean (SD) age of 68.9 ± 7.46 years. A total of 641 drug–drug interactions were detected in this investigation of which, 225(35.1%) were major, 299(46.6%) were significant interactions, and 117(18.3%) were minor interactions. Hospital stay (AOR = 5.95 CI: 3.49–10.12), retire (AOR = 6.71 CI: 1.26–35.78), 5–9 drugs (AOR = 5.30 CI: 2.91–9.67) and more than 10 drugs (AOR = 8.03 CI: 2.47–26.07) were important risk factors for drug–drug interactions. Conclusion: The findings of this study suggest that drug–drug interactions were high among hospitalized elderly patients. The presence of polypharmacy, to be retired, and hospital stayed were all found to be strongly linked with drug–drug interactions.

Diabetes self-care activities are essential for achieving optimal glycemic control. However, little investigation has been conducted in Ethiopia to evaluate the relationship between the rate glycemic controland self-care activities among patients with type 2 diabetes mellitus (T2DM). Therefore, this study was conducted to assess self -care activities and their association with glycemic control among patients with T2DM in Northwest Ethiopia general hospitals. This multicenter cross-sectional study was conducted in Northwest Ethiopia general hospitals diabetic clinics. Diabetes self-care activities were measured using the Amharic version of the Summary of Diabetes Self-Care Activities (SDSCA-Amharic). Glycated hemoglobin (HbA1c) were used to assess the rate of glycemic control. A linear regression model was used to identify predictors of self-care activities and glycemic control. P-value of < 0.05 at 95% confidence interval (CI) was considerd as statistically significant. Of 413 participants included in the final analysis, two-thirds (66.3%) had poor glycemic control, with a mean HbA1c of 7.94% (SD = 1.75). Blood glucose testing was the most important self-care activity domain for predicting better glycemic control [β=-0.36, 95% CI (-0.48, -0.24); P = 0.0001] followed by diet [β=-0.29, 95% CI (-0.39, -0.083); P = 0.0001], foot-care [β=-0.28, 95% CI (-0.3, -0.061); P = 0.003], and physical activity [β=-0.27, 95% CI (-0.29, -0.056); P = 0.004], respectively. Moreover, unable to read and write [β = 0.72, 95% CI (0.57, 3.8); P = 0.037], overweight [β = 0.32, 95% CI (0.011, 0.62); P = 0.042], obesity [β = 0.67, 95% CI (0.39, 0.94); P = 0.0001], and low level of medication adherence [β = 0.7, 95% CI (0.39, 1.1); P = 0.0001] were significant predictors of poor glycemic control. Previous diabetes education [β=-0.88, 95% CI (-1.2, -0.57); P=0.0001] was a significant predictor of good glycemic control. The prevalence of poor glycemic control and poor self-care activities were high among patients with T2DM. Self-care activities were independent predictors of glycemic control among patients with T2DM. Therefore, management interventions for patients with T2DM should focus on improving self-care activities and other predictor variables.

Objective The study was conducted to assess potential drug–drug interactions (PDDIs) and its determinants among patients with cancer receiving chemotherapy. Design and setting An institutional-based cross-sectional study was used. This study was conducted from 1 June 2021 to 15 December 2021, in Northwest Ethiopia oncology centres. Participants All eligible patients with cancer received a combination of chemotherapy. Outcomes The prevalence and severity of PDDIs were evaluated using three drug interaction databases. Characteristics of participants were presented, arranged and summarised using descriptive statistics. The predictors and outcome variables were examined using logistic regression. The cut-off point was a p value of 0.05. Results Of 422 patients included in the study, 304 patients were exposed to at least one PDDI with a prevalence of 72.1% (95 % CI: 68% to 76%) using three drug interaction databases. There were varied reports of the severity of PDDI among databases, but the test agreement using the kappa index was 0.57 (95% CI: 0.52 to 0.62, p=0.0001) which is interpreted as a moderate agreement among three databases. Patients aged ≥50 years old had the risk to be exposed to PDDI by odds of 3.1 times (adjusted OR (AOR)=3.1, 95% CI (1.8 to 5.3); p=0.001) as compared with patients <50 years old. Similarly, patients with polypharmacy and comorbidity were more likely to be exposed to PDDI than their counterparts (AOR=2.4, 95% CI (1.4 to 4.1); p=0.002 and AOR=1.9, 95% CI (1.1 to 3.4); p=0.02, respectively). Conclusion The main finding of this study is the high prevalence of PDDI, signifying the need for strict patient monitoring for PDDIs among patients with cancer receiving chemotherapy. We suggest the use of at least three drug databases for quality screening. Patients with an age ≥50 years old, polypharmacy and comorbidity were significantly associated with PDDIs. The establishment of oncology clinical pharmacists and computerised reminder mechanisms for PDDIs through drug utilisation review is suggested.