Key Points Question Is it possible to assess adverse events associated with drug-drug interactions (DDIs) by drug interaction checkers in patients with COVID-19? Findings The DDIs identified in this systematic review involved 46 different drugs, with 575 DDIs for 58 drug pairs (305 associated with at least 1 adverse drug reaction) reported. Drug interaction checkers could have identified such events, including severe and life-threatening ones. Meaning Notwithstanding the emergency context of the COVID-19 pandemic, DDI-related adverse events should never be overlooked to customize the most effective and safest therapy.

Heart Failure (HF) is a syndrome, which implies the existence of different phenotypes. The new categorization includes patients with preserved ejection fraction (HFpEF), mid-range EF (HFmrEF), and reduced EF (HFrEF) but the molecular mechanisms involved in these HF phenotypes have not yet been exhaustively investigated. Sirt1 plays a crucial role in biological processes strongly related to HF. This study aimed to evaluate whether Sirt1 activity was correlated with EF and other parameters in HFpEF, HFmrEF, and HFrEF. Seventy patients, HFpEF (n = 23), HFmrEF (n = 23) and HFrEF (n = 24), were enrolled at the Cardiology Unit of the University Hospital of Salerno. Sirt1 activity was measured in peripheral blood mononuclear cells (PBMCs). Angiotensin-Converting Enzyme 2 (ACE2) activity, Tumor Necrosis Factor-alpha (TNF-α) and Brain Natriuretic Peptide (BNP) levels were quantified in plasma. HFpEF showed lower Sirt1 and ACE2 activities than both HFmrEF and HFrEF (p < 0.0001), without difference compared to No HF controls. In HFmrEF and HFrEF a very strong correlation was found between Sirt1 activity and EF (r2 = 0.899 and r2 = 0.909, respectively), and between ACE2 activity and Sirt1 (r2 = 0.801 and r2 = 0.802, respectively). HFrEF showed the highest TNF-α levels without reaching statistical significance. Significant differences in BNP were found among the groups, with the highest levels in the HFrEF. Determining Sirt1 activity in PBMCs is useful to distinguish the HF patients’ phenotypes from each other, especially HFmrEF/HFrEF from HFpEF.

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Fluoropyrimidines (FP) are mainly metabolised by dihydropyrimidine dehydrogenase (DPD), encoded by the DPYD gene. FP pharmacogenetics, including four DPYD polymorphisms (DPYD-PGx), is recommended to tailor the FP-based chemotherapy. These polymorphisms increase the risk of severe toxicity; thus, the DPYD-PGx should be performed prior to starting FP. Other factors influence FP safety, therefore phenotyping methods, such as the measurement of 5-fluorouracil (5-FU) clearance and DPD activity, could complement the DPYD-PGx. We describe a case series of patients in whom we performed DPYD-PGx (by real-time PCR), 5-FU clearance and a dihydrouracil/uracil ratio (as the phenotyping analysis) and a continuous clinical monitoring. Patients who had already experienced severe toxicity were then identified as carriers of DPYD variants. The plasmatic dihydrouracil/uracil ratio (by high-performance liquid chromatography (HPLC)) ranged between 1.77 and 7.38. 5-FU clearance (by ultra-HPLC with tandem mass spectrometry) was measured in 3/11 patients. In one of them, it reduced after the 5-FU dosage was halved; in the other case, it remained high despite a drastic dosage reduction. Moreover, we performed a systematic review on genotyping/phenotyping combinations used as predictive factors of FP safety. Measuring the plasmatic 5-FU clearance and/or dihydrouracil/uracil (UH2/U) ratio could improve the predictive potential of DPYD-PGx. The upfront DPYD-PGx combined with clinical monitoring and feasible phenotyping method is essential to optimising FP-based chemotherapy.