Summary What is known and objective In the last decades, many lists have been developed to screen for inappropriate prescribing. However, information on which potentially inappropriate medications (PIMs) could increase the cardiovascular risk in the elderly is not objectively presented. This review aimed to identify and quantify those PIMs by extracting information from published PIM‐lists. Methods In accordance with the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses Statement (PRISMA), a systematic review of PIM‐lists was conducted. The search strategy was run in PubMed, MEDLINE and Google Scholar (1991‐09/2017). All PIMs described in those lists were extracted and stratified by their potential cardiovascular risk (including major adverse cardiovascular events—MACE). The number of times each PIM was reported on those lists was also assessed. Results and discussion We identified 724 papers, and 24 were retained. From those, a total of 17 PIMs to be avoided by the elderly and 21 drug‐disease interactions were retrieved. The reporting of PIMs with risk of cardiovascular adverse events was 15.3%, whereas the reporting of those with MACE risk was 7.2%. PIMs most frequently described were tricyclic antidepressants (TCAs; 12/24), centrally acting antiadrenergic agents (11/24), NSAIDs (7/24), antiarrhythmics (Class I and III; 6/24), peripherally acting antiadrenergic agents (6/24) and antithrombotic agents (5/24). Most frequently described PIMs with MACE risk were NSAIDs (7/24), antiarrhythmics (Class I and III) (7/24), selective calcium channel blockers with vascular effects (6/24) and antipsychotics (4/24). What is new and conclusion Data suggest that PIM‐lists focus mainly on common adverse events and often poorly describe the potential consequence for MACE occurrence. This systematic review could help healthcare professionals in the identification and deprescribing of these medicines in older patients with high cardiovascular risk during medication review.

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Background Pharmaceutical Interventions (PI) are part of pharmaceutical care process and aim to reduce drug-related negative results through early detection of drug related problems (DRP). They are mainly focused on renal/hepatic adjustment of drugs, and supervision of medicines with narrow therapeutic windows and unconventional regimen features. Purpose Evaluation of PI in separate departments during the first semester of 2011. This will allow a consistent and uniform record and classification of PI, aiming to raise doctors' awareness for the most frequent prescription-related DRPs. Materials and methods PI's were recorded on a database (Excel 2007) and classified according to the DÁDER method (Third Revision 2005-University of Granada), accepted as a tool to identify DRPs. DRPs are classified according to: Need: DRP1-Need of additional treatment and DRP2-Unnecessary drug; Efficacy: DRP3-Non-quantitative lack of efficacy and DRP4-Quantitative lack of efficacy; Safety: DRP5-Non-quantitative insecurity and DRP6-Quantitative insecurity. Results From a total of 1835 PI, 82% were accepted (AC). The DRP's distribution was: DRP1-17, 4%, DRP2-25, 4%, DRP3-2%, DRP4-16, 1%, DRP5-5, 1%, DRP6-33, 5%. Departments were analysed separately because of different specifications. The medicine department had a total of 795 PI, with an acceptance of 80, 4%. The most frequent DRP's were DRP6 (38%), DRP1 (20%) and DRP2 (19%). The surgical department had 470 PI, with an acceptance of 95, 5%. The most frequent DRP's were DRP2 (42,2%), DRP6 (19,9%), DRP1 (18,6%) and DRP4 (17,2%). Intensive care units had a total of 149 PI with 89, 3% accepted, the most frequent being DRP6 (40,4%) and DRP4 (31, 5%). The emergency department had a total of 421 PI with 67% accepted. The most frequent DRP's were DRP6 (37%) and DRP2 (24%). Conclusions This analysis showed that: The pharmaceutical interventions had high rates of acceptance (≥80%) The most frequent DRP were related to quantitative insecurity (DRP6), followed by the prescription of unnecessary drug (DRP2), despite some differences between different departments.