ABSTRACT
INTRODUCTION: The COVID-19 pandemic triggered the unprecedented 'long COVID' crisis, with persistent symptoms beyond two months post-infection. This study explores the nexus between long COVID symptoms, patient demographics such as age, gender, and smoking, and clinical factors like vaccination, disease severity, and comorbidities. METHODS: A retrospective analysis of records was conducted between September 2021 and December 2022. The analysis covered adults with confirmed COVID-19 diagnoses. Data encompassed demographics, medical history, vaccination, disease severity, hospitalization, treatments, and post-COVID symptoms, analyzed using logistic regression. RESULTS: Among 289 participants, the average age was 51.51 years. Around 62.6% were females, and 93% received the COVID-19 vaccination, i.e., primarily the mRNA vaccine (48.4%) and the adenovirus vector-based vaccine (34.8%). Reinfections occurred in 11.76% of cases. Disease severity varied, with 75% having mild, 15% having moderate, and 10% having severe infections. Hospitalization rates were significant (25.6%), including 10.7% requiring intensive care. Thirteen distinct post-COVID symptoms were reported. Fatigue, shortness of breath upon exertion, and brain fog emerged as the most prevalent symptoms. Notably, females exhibited higher symptom prevalence. Significant correlations were established between higher BMI and smoking with augmented symptomatology. Conversely, a link between booster doses and symptom reduction was discerned. Using multinomial regression analysis, gender and smoking were identified as predictors of post-COVID-19 symptoms. CONCLUSION: The study underscores obesity, smoking, and the female gender's impact on long COVID symptoms; boosters show promise in alleviation. Respiratory pathology might underlie persistent symptoms in cases with radiological abnormalities and abnormal spirometry. Findings contribute to risk stratification, intervention strategies, and further research.
ABSTRACT
Introduction Adverse events related to Drug-Drug Interactions (DDIs) are among the few common reasons for hospitalization worldwide; however, they can be prevented with an efficient patient-centered system. Different mechanisms have successfully limited the prevalence of DDIs in developed countries. There are limited data regarding DDIs from limited-resource settings. Furthermore, there is no cost-effective system that has shown promising results in preventing them in this setting. This study aims to assess the frequency of potential DDIs in a low-resource setting and to check its association with different factors such as poly-pharmacy and demographics. Methods Through this cross-sectional study, drug charts of patients admitted to a medical unit in November 2019 were analyzed using a structured questionnaire. A list of drugs co-prescribed to each patient was entered into the Medscape Drug Interaction checker to calculate the frequency and severity of potential DDIs. Results The mean age of patients was 49 years, and on average, seven drugs were prescribed to each patient. Among 100 analyzed prescriptions, 400 potential DDIs were identified with a mean of 4±5.42 per patient. According to Medscape interaction checker classification, 2 DDIs were contraindicated, 28 were serious, 246 required close monitoring, and 124 were minor. The most frequently encountered drug interaction was "spironolactone with furosemide." There was a significant correlation of the occurrence of potential DDIs with increased numbers of prescribed drugs. Conclusion Our patient population was prescribed more drugs per patient than calculated in other settings. Poly-pharmacy is an independent risk factor for DDIs. Lastly, advancing age exposes patients to poly-pharmacy, and therefore, they are at a higher risk of developing DDIs.
