Evidence map›Paper›PMID 32785232›Full record

Observational studyPloS one2020

Potentially inappropriate prescriptions according to explicit and implicit criteria in patients with multimorbidity and polypharmacy. MULTIPAP: A cross-sectional study.

Juan A Lopez-Rodriguez, Eloísa Rogero-Blanco, Mercedes Aza-Pascual-Salcedo, Fernando Lopez-Verde, Victoria Pico-Soler, Francisca Leiva-Fernandez, J Daniel Prados-Torres, Alexandra Prados-Torres, Isabel Cura-González, MULTIPAP group

Open access · goldAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 4 pooled it
4.7field-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

37 citing papers in PubMed, 4 syntheses or guidelines pooled it, 66 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

10 authors at 3 institutions in 1 country.

Juan A Lopez-RodriguezPrimary Healthcare Center General Ricardos, Madrid, Spain.
Eloísa Rogero-BlancoPrimary Healthcare Center General Ricardos, Madrid, Spain.ORCID 0000-0002-8732-6120
Mercedes Aza-Pascual-SalcedoPrimary Care Direction, Sector Zaragoza III, Zaragoza, Spain.
Fernando Lopez-VerdeUnidad Docente Multiprofesional de Atención Familiar y Comunitaria Distrito Málaga/Guadalhorce, Málaga, Spain.ORCID 0000-0001-7870-0793
Victoria Pico-SolerHealth Services Research on Chronic Patients Network (REDISSEC), Madrid, Spain.
Francisca Leiva-FernandezUnidad Docente Multiprofesional de Atención Familiar y Comunitaria Distrito Málaga/Guadalhorce, Málaga, Spain.ORCID 0000-0001-6919-4817
J Daniel Prados-TorresHealth Services Research on Chronic Patients Network (REDISSEC), Madrid, Spain.ORCID 0000-0001-5204-7781
Alexandra Prados-TorresHealth Services Research on Chronic Patients Network (REDISSEC), Madrid, Spain.
Isabel Cura-GonzálezMedical Specialties and Public Health Department, School of Health Sciences, University Rey Juan Carlos Alcorcón, Madrid, Spain.
MULTIPAP group
Spanish Clinical Research Network · ESUniversidad Rey Juan Carlos · ESInstituto de Investigación Biomédica de Málaga · ES

Funding

Department of Health PI15/00276Department of Health PI15/00572Department of Health PI15/00996Department of Health RD16/0001/0004Department of Health RD16/0001/0005Department of Health RD16/0001/0006
6 · The paper itself

Abstract

backgroundMultimorbidity is a global health challenge that is associated with polypharmacy, increasing the risk of potentially inappropriate prescribing (PIP). There are tools to improve prescription, such as implicit and explicit criteria.

objectiveTo estimate the prevalence of PIP in a population aged 65 to 74 years with multimorbidity and polypharmacy, according to American Geriatrics Society Beers Criteria® (2015, 2019), the Screening Tool of Older Person's Prescription -STOPP- criteria (2008, 2014), and the Medication Appropriateness Index -MAI- criteria in primary care.

methodsThis was an observational, descriptive, cross-sectional study. The sample included 593 community-dwelling elderly aged 65 to 74 years, with multimorbidity and polypharmacy, who participated in the MULTIPAP trial. Socio-demographic, clinical, professional, and pharmacological-treatment variables were recorded. Potentially inappropriate prescribing was detected by computerized prescription assistance system, and family doctors evaluated the MAI. The MAI-associated factors were analysed using a logistic regression model.

resultsA total of 4,386 prescriptions were evaluated. The mean number of drugs was 7.4 (2.4 SD). A total of 94.1% of the patients in the study had at least one criterion for drug inappropriateness according to the MAI. Potentially inappropriate prescribing was detected in 57.7%, 43.6%, 68.8% and 71% of 50 patients according to the explicit criteria STOPP 2014, STOPP 2008, Beers 2019 and Beers 2015 respectively. For every new drug taken by a patient, the MAI score increased by 2.41 (95% CI 1.46; 3.35) points. Diabetes, ischaemic heart disease and asthma were independently associated with lower summated MAI scores.

conclusionsThe prevalence of potentially inappropriate prescribing detected in the sample was high and in agreement with previous literature for populations with multimorbidity and polypharmacy. The MAI criteria detected greater inappropriateness than did the explicit criteria, but their application was more complex and difficult to automate.

Indexed as

MultimorbidityPolypharmacyPotentially Inappropriate Medication ListAgedCross-Sectional StudiesFemaleGeriatricsHumansInappropriate PrescribingIndependent LivingMalePrevalencePrimary Health CareRiskSpain

Identifiers

PMID32785232
PMCPMC7423095
OpenAlexW3048664408

What OpenQuestion holds

Textmetadata
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.