Author Correction:Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models

In the version of this article initially published, Cristina Leal Rodríguez (Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark) was omitted from the author list. The error has been corrected in the HTML and PDF versions of the article</p

Drug interactions in hospital prescriptions in Denmark:Prevalence and associations with adverse outcomes

PURPOSE: While the beneficial effects of medications are numerous, drug–drug interactions may lead to adverse drug reactions that are preventable causes of morbidity and mortality. Our goal was to quantify the prevalence of potential drug–drug interactions in drug prescriptions at Danish hospitals, estimate the risk of adverse outcomes associated with discouraged drug combinations, and highlight the patient types (defined by the primary diagnosis of the admission) that appear to be more affected. METHODS: This cross‐sectional (descriptive part) and cohort study (adverse outcomes part) used hospital electronic health records from two Danish regions (~2.5 million people) from January 2008 through June 2016. We included all inpatients receiving two or more medications during their admission and considered concomitant prescriptions of potentially interacting drugs as per the Danish Drug Interaction Database. We measured the prevalence of potential drug–drug interactions in general and discouraged drug pairs in particular during admissions and associations with adverse outcomes: post‐discharge all‐cause mortality rate, readmission rate and length‐of‐stay. RESULTS: Among 2 886 227 hospital admissions (945 475 patients; median age 62 years [IQR: 41–74]; 54% female; median number of drugs 7 [IQR: 4–11]), patients in 1 836 170 admissions were exposed to at least one potential drug–drug interaction (659 525 patients; median age 65 years [IQR: 49–77]; 54% female; median number of drugs 9 [IQR: 6–13]) and in 27 605 admissions to a discouraged drug pair (18 192 patients; median age 68 years [IQR: 58–77]; female 46%; median number of drugs 16 [IQR: 11–22]). Meropenem‐valproic acid (HR: 1.5, 95% CI: 1.1–1.9), domperidone‐fluconazole (HR: 2.5, 95% CI: 2.1–3.1), imipramine‐terbinafine (HR: 3.8, 95% CI: 1.2–12), agomelatine‐ciprofloxacin (HR: 2.6, 95% CI: 1.3–5.5), clarithromycin‐quetiapine (HR: 1.7, 95% CI: 1.1–2.7) and piroxicam‐warfarin (HR: 3.4, 95% CI: 1–11.4) were associated with elevated mortality. Confidence interval bounds of pairs associated with readmission were close to 1; length‐of‐stay results were inconclusive. CONCLUSIONS: Well‐described potential drug–drug interactions are still missed and alerts at point of prescription may reduce the risk of harming patients; prescribing clinicians should be alert when using strong inhibitor/inducer drugs (i.e. clarithromycin, valproic acid, terbinafine) and prevalent anticoagulants (i.e. warfarin and non‐steroidal anti‐inflammatory drugs ‐ NSAIDs) due to their great potential for dangerous interactions. The most prominent CYP isoenzyme involved in mortality and readmission rates was 3A4

Drug dosage modifications in 24 million in-patient prescriptions covering eight years: A Danish population-wide study of polypharmacy.

Polypharmacy has generally been assessed by raw counts of different drugs administered concomitantly to the same patients; not with respect to the likelihood of dosage-adjustments. To address this aspect of polypharmacy, the objective of the present study was to identify co-medications associated with more frequent dosage adjustments. The data foundation was electronic health records from 3.2 million inpatient admissions at Danish hospitals (2008-2016). The likelihood of dosage-adjustments when two drugs were administered concomitantly were computed using Bayesian logistic regressions. We identified 3,993 co-medication pairs that associate significantly with dosage changes when administered together. Of these pairs, 2,412 (60%) did associate with readmission, mortality or longer stays, while 308 (8%) associated with reduced kidney function. In comparison to co-medications pairs that were previously classified as drug-drug interactions, pairs not classified as drug-drug interactions had higher odds ratios of dosage modifications than drug pairs with an established interaction. Drug pairs not corresponding to known drug-drug interactions while still being associated significantly with dosage changes were prescribed to fewer patients and mentioned more rarely together in the literature. We hypothesize that some of these pairs could be associated with yet to be discovered interactions as they may be harder to identify in smaller-scale studies