Evidence map›Paper›PMID 38844392›Full record

ArticleBMJ open2024

New data-driven method to predict the therapeutic indication of redeemed prescriptions in secondary data sources: a case study on antiseizure medications users aged ≥65 identified in Danish registries.

Israa Mahmoud, Vera Battini, Carla Carnovale, Emilio Clementi, Kristian Kragholm, Maurizio Sessa

Abstract read
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Israa MahmoudDepartment of Drug Design and Pharmacology, University of Copenhagen, Kobenhavn, Denmark.
Vera BattiniDepartment of Drug Design and Pharmacology, University of Copenhagen, Kobenhavn, Denmark.ORCID 0000-0002-3513-9593
Carla CarnovaleUniversità degli Studi di Milano, Milano, Italy.
Emilio ClementiUniversità degli Studi di Milano, Milano, Italy.
Kristian KragholmUnit of Epidemiology and Biostatistics, Aalborg Universitetshospital, Aalborg, Denmark.
Maurizio SessaDepartment of Drug Design and Pharmacology, University of Copenhagen, Kobenhavn, Denmark maurizio.sessa@sund.ku.dk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesWe aimed to develop a new data-driven method to predict the therapeutic indication of redeemed prescriptions in secondary data sources using antiepileptic drugs among individuals aged ≥65 identified in Danish registries.

designThis was an incident new-user register-based cohort study using Danish registers.

settingThe study setting was Denmark and the study period was 2005-2017.

participantsParticipants included antiepileptic drug users in Denmark aged ≥65 with a confirmed diagnosis of epilepsy. PRIMARY AND SECONDARY OUTCOME MEASURES: Sensitivity served as the performance measure of the algorithm.

resultsThe study population comprised 8609 incident new users of antiepileptic drugs. The sensitivity of the algorithm in correctly predicting the therapeutic indication of antiepileptic drugs in the study population was 65.3% (95% CI 64.4 to 66.2).

conclusionsThe algorithm demonstrated promising properties in terms of overall sensitivity for predicting the therapeutic indication of redeemed antiepileptic drugs by older individuals with epilepsy, correctly identifying the therapeutic indication for 6 out of 10 individuals using antiepileptic drugs for epilepsy.

Indexed as

AlgorithmsAnticonvulsantsEpilepsyRegistriesAgedAged, 80 and overCohort StudiesDenmarkDrug PrescriptionsFemaleHumansInformation SourcesMaleAnticonvulsantsagedepidemiologyepilepsy

Identifiers

PMID38844392
PMCPMC11163620

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