Evidence map›Paper›PMID 34842835›Full record

ArticlePharmacy (Basel, Switzerland)2021

Potentially Inappropriate Medication Prescribing Detected by Computer Algorithm among Older Patients: Results from the MAPT Study.

Arnaud Pagès, Laure Rouch, Nadège Costa, Philippe Cestac, Philipe De Souto Barreto, Yves Rolland, Bruno Vellas, Laurent Molinier, Blandine Juillard-Condat, Mapt/Dsa Group

Open access · goldAbstract read
In one paragraph

Article in Pharmacy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Trial
  2. Article
  3. Observational
  4. Article
  5. Article
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 1 institution in 1 country.

Arnaud PagèsDepartment of Pharmacy, Toulouse University Hospital, 31000 Toulouse, France.ORCID 0000-0002-2337-8693
Laure RouchDepartment of Pharmacy, Toulouse University Hospital, 31000 Toulouse, France.
Nadège CostaCenter for Epidemiology and Research in POPulation Health (CERPOP), UMR 1295, Inserm, UPS Toulouse III University, 31000 Toulouse, France.
Philippe CestacDepartment of Pharmacy, Toulouse University Hospital, 31000 Toulouse, France.
Philipe De Souto BarretoInstitute of Aging, Gérontopôle, INSPIRE Project, Toulouse University Hospital, 31000 Toulouse, France.
Yves RollandInstitute of Aging, Gérontopôle, INSPIRE Project, Toulouse University Hospital, 31000 Toulouse, France.
Bruno VellasInstitute of Aging, Gérontopôle, INSPIRE Project, Toulouse University Hospital, 31000 Toulouse, France.
Laurent MolinierCenter for Epidemiology and Research in POPulation Health (CERPOP), UMR 1295, Inserm, UPS Toulouse III University, 31000 Toulouse, France.
Blandine Juillard-CondatDepartment of Pharmacy, Toulouse University Hospital, 31000 Toulouse, France.ORCID 0000-0002-0950-004X
Mapt/Dsa Group
Université Toulouse III - Paul Sabatier · FR

Funding

European Regional Development Fund MP0022856Région Occitanie Pyrénées-Méditerranée 1901175
6 · The paper itself

Abstract

(1) Background: Some medications may be dangerous for older patients. Potentially inappropriate medication prescribing (PIP) among older patients represents a significant cause of morbidity. The aim of this study was to create an algorithm to detect PIP in a geriatric database (Multidomain Alzheimer Preventive Trial (MAPT) study), and then to assess the algorithm construct validity by comparing the prevalence of PIP and associated factors with literature data. (2) Methods: An algorithm was constructed to detect PIP and was based on different explicit criteria among which the European list of potentially inappropriate medications (EU(7)-PIM), the STOPP and START version 2 tools. For construct validity assessment, logistic mixed-effects model repeated measures analyses were used to identify factors associated with PIP. (3) Results: Prevalence of PIP was 59.0% with the EU(7)-PIM list criteria, 43.2% with the STOPP criteria and 51.3% with the START criteria. Age, polypharmacy, and higher Charlson comorbidity index were associated with PIP. (4) Conclusions: Prevalence of PIP and associated factors are consistent with literature data, supporting the construct validity of our algorithm. This algorithm opens up interesting perspectives both in terms of analysis of very large databases and integration into e-prescribing or pharmaceutical validation software.

Indexed as

algorithmdatabaseelderlymedicationpotentially inappropriate medication prescribing

Identifiers

PMID34842835
PMCPMC8628967
OpenAlexW3215864987

What OpenQuestion holds

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LicenceCC BY
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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.