Evidence map›Paper›PMID 33982632›Full record

Observational studyThe European journal of general practice2021

Drug interactions detected by a computer-assisted prescription system in primary care patients in Spain: MULTIPAP study.

Eloísa Rogero-Blanco, Isabel Del-Cura-González, Mercedes Aza-Pascual-Salcedo, Francisca García de Blas González, Carmen Terrón-Rodas, Sergio Chimeno-Sánchez, Eva García-Domingo, Juan A López-Rodríguez, group MULTIPAP

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in The European journal of general practice, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 21% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 7 institutions in 7 countries.

Eloísa Rogero-BlancoPrimary Health Care Center General Ricardos, Madrid, Spain.ORCID https://orcid.org/0000-0002-8732-6120
Isabel Del-Cura-GonzálezHealth Services Research on Chronic Patients Network (REDISSEC), Madrid, Spain.ORCID https://orcid.org/0000-0002-3931-5304
Mercedes Aza-Pascual-SalcedoPrimary Care Direction, Sector Zaragoza III, Zaragoza, Spain.ORCID https://orcid.org/0000-0002-8937-5559
Francisca García de Blas GonzálezHealth Services Research on Chronic Patients Network (REDISSEC), Madrid, Spain.
Carmen Terrón-RodasLegazpi Health Center, Madrid, Spain.
Sergio Chimeno-SánchezFaculty of Health Sciences, URJC, Madrid, Spain.
Eva García-DomingoMultiprofessional Teaching Unit of Family and Community Medicine of the Málaga/Guadalhorce Healthcare District, Malaga, Spain.
Juan A López-RodríguezPrimary Health Care Center General Ricardos, Madrid, Spain.ORCID https://orcid.org/0000-0002-4985-2314
group MULTIPAP
Universidad Rey Juan Carlos · ESBJC HealthCare · USJapan Community Healthcare Organization · JPSpanish Clinical Research Network · ESUniversidad de Zaragoza · ESUniversity of Mary · USUniversity of Santo Tomas–Legazpi · PH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDrug interactions increase the risk of treatment failure, intoxication, hospital admissions, consultations and mortality. Computer-assisted prescription systems can help to detect interactions.

objectivesTo describe the drug-drug interaction (DDI) and drug-disease interaction (DdI) prevalence identified by a computer-assisted prescription system in patients with multimorbidity and polypharmacy. Factors associated with clinically relevant interactions were analysed.

methodsObservational, descriptive, cross-sectional study in primary health care centres was undertaken in Spain. The sample included 593 patients aged 65-74 years with multimorbidity and polypharmacy participating in the MULTIPAP Study, recruited from November 2016 to January 2017. Drug interactions were identified by a computer-assisted prescription system. Descriptive, bivariate, and multivariate analyses with logistic regression models and robust estimators were performed.

resultsHalf (50.1% (95% CI 46.1-54.1)) of the patients had at least one relevant DDI and 23.9% (95% CI 18.9-25.6) presented with a DdI. Non-opioid-central nervous system depressant drug combinations and benzodiazepine-opioid drug combinations were the two most common clinically relevant interactions (10.8% and 5.9%, respectively). Factors associated with DDI were the use of more than 10 drugs (OR 11.86; 95% CI 6.92-20.33) and having anxiety/depressive disorder (OR 1.98; 95% CI 1.31-2.98). Protective factors against DDI were hypertension (OR 0.62; 95% CI 0.41-0.94), diabetes (OR 0.57; 95% CI 0.40-0.82), and ischaemic heart disease (OR 0.43; 95% CI 0.25-0.74).

conclusionDrug interactions are prevalent in patients aged 65-74 years with multimorbidity and polypharmacy. The clinically relevant DDI frequency is low. The number of prescriptions taken is the most relevant factor associated with presenting a clinically relevant DDI.

Indexed as

PolypharmacyPrimary Health CareComputersCross-Sectional StudiesDrug InteractionsHumansPrescriptionsSpaincomputer-assistedDrug interactionsdrug therapymultimorbiditypolypharmacyprimary care

Identifiers

PMID33982632
PMCPMC8128212
OpenAlexW3160973040

What OpenQuestion holds

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Registered trials

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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.