ObjectivesCoronavirus disease 2019 (COVID-19) is an emerging viral infection without any approved treatment. Investigational therapies for COVID-19 may cause clinically important drug–drug interactions (DDIs). We aimed to study potential DDIs (pDDIs) and their risk factors in COVID-19 patients admitted to the hospital.MethodsWe conducted a cross-sectional study in a tertiary respiratory hospital dedicated to COVID-19 patients. The Lexi-Interact database was used to investigate clinically important pDDIs. The database output including interacting drug pairs, risk rating, reliability rating, mechanism, and management was evaluated. Associations between the occurrence of pDDIs and probable risk factors were assessed by logistic regression analysis.ResultsMedical charts of 227 patients were reviewed. About 38% of the patients had at least one clinically important pDDI. More than half of the interactions were between protease inhibitors (lopinavir/ritonavir) and regularly prescribed medications for the management of comorbidities or COVID-19 symptoms (e.g., atorvastatin, alprazolam, salmeterol, and tamsulosin). Ischemic heart disease, chronic respiratory diseases, and ICU admission were significantly associated with the occurrence of pDDIs.ConclusionsWe recommend considering the risk factors for the emergence of clinically important DDIs in the pharmacotherapy of COVID-19 patients. Using an alternative medication or dose adjustments may be required in high-risk patients.
Background
Hospitalized pediatric patients are at an increased risk of experiencing potential drug-drug interactions (pDDIs) due to polypharmacy and the unlicensed and off-label administration of drugs. The aim of this study is to characterize clinically significant pDDIs in pediatric patients hospitalized in a tertiary respiratory center.
Methods
A retrospective analysis of medications prescribed to pediatric patients admitted to the pediatric ward (PW) and pediatric intensive care unit (PICU) of a respiratory referral center was carried out over a six-month period. The pDDIs were identified using the Lexi-Interact database and considered as clinically relevant according to the severity rating as defined in the database. Frequency, drug classes, mechanisms, clinical managements, and risk factors were recorded for these potential interactions.
Results
Eight hundred and forty-five pDDIs were identified from the analysis of 176 prescriptions. Of the total pDDIs, 10.2% in PW and 14.6% in PICU were classified as clinically significant. Anti-infective agents and central nervous system drugs were the main drug classes involved in clinically significant pDDIs as object and/or precipitant drugs. A higher number of medications [odds ratio (OR): 4.8; 95% confidence interval (CI): 2.0–11.4; p < 0.001] and the existence of a nonrespiratory disease, which led to a respiratory disorder (OR: 3.8; 95% CI: 1.40–10.4; p < 0.05), were the main risk factors associated with an increased incidence of pDDIs.
Conclusions
A high and similar risk of pDDIs exists in pediatric patients with respiratory disorders hospitalized in PW and PICU. The patients prescribed a higher number of medications and presenting respiratory symptoms induced by a nonrespiratory disease require extra care and monitoring. Pediatricians should be educated about clinically significant DDIs for highly prescribed medications in their settings in order to take preventive measures and safeguard patient safety.
Breast cancer (BC) is the second most common cancer and cause of death in women. In recent years many studies investigated the association of long non-coding RNAs (lncRNAs), as novel genetic factors, on BC risk, survival, clinical and pathological features. Recent studies also investigated the roles of metformin treatment as the firstline treatment for type 2 diabetes (T2D) played in lncRNAs expression/regulation or BC incidence, outcome, mortality and survival, separately. This comprehensive study aimed to review lncRNAs associated with BC features and identify metformin-regulated lncRNAs and their mechanisms of action on BC or other types of cancers. Finally, metformin affects BC by regulating five BC-associated lncRNAs including GAS5, HOTAIR, MALAT1, and H19, by several molecular mechanisms have been described in this review. In addition, metformin action on other types of cancers by regulating ten lncRNAs including AC006160.1, Loc100506691, lncRNA-AF085935, SNHG7, HULC, UCA1, H19, MALAT1, AFAP1-AS1, AC026904.1 is described.
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