Evidence map›Paper›PMID 38637816›Full record

ArticleBMC medicine2024

Prevalence and differences in the co-administration of drugs known to interact: an analysis of three distinct and large populations.

Jon Sánchez-Valle, Rion Brattig Correia, Marta Camacho-Artacho, Rosalba Lepore, Mauro M Mattos, Luis M Rocha, Alfonso Valencia

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
4.8field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 14 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 6 institutions in 5 countries.

Jon Sánchez-Valle *Life Sciences Department, Barcelona Supercomputing Center, 08034, Barcelona, Spain. jon.sanchez@bsc.es.ORCID 0000-0001-7959-6326
Rion Brattig Correia *Instituto Gulbenkian de Ciência, 2780-156, Street, Oeiras, Portugal. rionbr@gmail.com.
Marta Camacho-ArtachoAgencia Española de Medicamentos y Productos Sanitarios, Madrid, Spain.
Rosalba LeporeLife Sciences Department, Barcelona Supercomputing Center, 08034, Barcelona, Spain.
Mauro M MattosUniversidade Regional de Blumenau, Blumenau, 89030-903, Brazil.
Luis M RochaInstituto Gulbenkian de Ciência, 2780-156, Street, Oeiras, Portugal. rocha@binghamton.edu.
Alfonso ValenciaLife Sciences Department, Barcelona Supercomputing Center, 08034, Barcelona, Spain. alfonso.valencia@bsc.es.
Barcelona Supercomputing Center · ESAgencia Española de Medicamentos y Productos Sanitarios · ESBinghamton University · USInstitució Catalana de Recerca i Estudis Avançats · ESInstituto Gulbenkian de Ciência · PTUniversidade Regional de Blumenau · BR

Funding

Evidence-based Drug-Interaction Discovery: In-Vivo, In-Vitro and ClinicalR01LM011945 · NLM · INDIANA UNIVERSITY INDIANAPOLIS · PI LI, LANG, ROCHA, LUIS M · 2014 to 2017
$1.8M
myAURA: Personalized Web Service for Epilepsy ManagementR01LM012832 · NLM · TRUSTEES OF INDIANA UNIVERSITY · PI BORNER, KATY, MILLER, WENDY RENEE · 2018 to 2021
$1.3M
NLM NIH HHS R01 LM011945NLM NIH HHS R01 LM012832
6 · The paper itself

Abstract

backgroundThe co-administration of drugs known to interact greatly impacts morbidity, mortality, and health economics. This study aims to examine the drug-drug interaction (DDI) phenomenon with a large-scale longitudinal analysis of age and gender differences found in drug administration data from three distinct healthcare systems.

methodsThis study analyzes drug administrations from population-wide electronic health records in Blumenau (Brazil; 133 K individuals), Catalonia (Spain; 5.5 M individuals), and Indianapolis (USA; 264 K individuals). The stratified prevalences of DDI for multiple severity levels per patient gender and age at the time of administration are computed, and null models are used to estimate the expected impact of polypharmacy on DDI prevalence. Finally, to study actionable strategies to reduce DDI prevalence, alternative polypharmacy regimens using drugs with fewer known interactions are simulated.

resultsA large prevalence of co-administration of drugs known to interact is found in all populations, affecting 12.51%, 12.12%, and 10.06% of individuals in Blumenau, Indianapolis, and Catalonia, respectively. Despite very different healthcare systems and drug availability, the increasing prevalence of DDI as patients age is very similar across all three populations and is not explained solely by higher co-administration rates in the elderly. In general, the prevalence of DDI is significantly higher in women - with the exception of men over 50 years old in Indianapolis. Finally, we show that using proton pump inhibitor alternatives to omeprazole (the drug involved in more co-administrations in Catalonia and Blumenau), the proportion of patients that are administered known DDI can be reduced by up to 21% in both Blumenau and Catalonia and 2% in Indianapolis.

conclusionsDDI administration has a high incidence in society, regardless of geographic, population, and healthcare management differences. Although DDI prevalence increases with age, our analysis points to a complex phenomenon that is much more prevalent than expected, suggesting comorbidities as key drivers of the increase. Furthermore, the gender differences observed in most age groups across populations are concerning in regard to gender equity in healthcare. Finally, our study exemplifies how electronic health records' analysis can lead to actionable interventions that significantly reduce the administration of known DDI and its associated human and economic costs.

Indexed as

PolypharmacyAgedComorbidityDrug InteractionsFemaleHumansMaleMiddle AgedPharmaceutical PreparationsPrevalencePharmaceutical PreparationsDrug–drug interactionsElectronic health recordsMultimorbidityPolypharmacy

Identifiers

PMID38637816
PMCPMC11027217
OpenAlexW4394960833

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.