Evidence map›Paper›PMID 40883976›Full record

ArticleBritish journal of clinical pharmacology2025

Enhancing patient stratification methods for medication review during acute admissions.

Louise Westberg Strejby Christensen, Helle Gybel Juul-Larsen, Line Jee Hartmann Rasmussen, Esben Iversen, Kim Peder Dalhoff, Ove Andersen, Morten Baltzer Houlind

Abstract read
In one paragraph

Article in British journal of clinical pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

7 authors.

Louise Westberg Strejby ChristensenDepartment of Clinical Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark.ORCID https://orcid.org/0009-0006-8954-2675
Helle Gybel Juul-LarsenDepartment of Clinical Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark.ORCID https://orcid.org/0000-0002-8543-9201
Line Jee Hartmann RasmussenDepartment of Clinical Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark.ORCID https://orcid.org/0000-0001-6613-2469
Esben IversenDepartment of Clinical Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark.ORCID https://orcid.org/0000-0002-7558-9257
Kim Peder DalhoffDepartment of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.ORCID https://orcid.org/0000-0002-5548-6381
Ove AndersenDepartment of Clinical Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark.ORCID https://orcid.org/0000-0002-2274-548X
Morten Baltzer HoulindDepartment of Clinical Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark.ORCID https://orcid.org/0000-0003-4058-3012

Funding

Beckett Foundation 24-2-13742Capital Region of Denmark's Research FundsCapital Region's Fund for Transitional Research, Denmark U-0081Danish Research Unit for Hospital Pharmacy, AMGROS I/S, DenmarkIndependent Research Fund DenmarkResearch Foundation of Amager and Hvidovre Hospital, DenmarkROCKWOOL Foundation
6 · The paper itself

Abstract

Medication review in the hospital is an effective tool for identifying inappropriate prescribing, but not every patient can receive one due to resource constraints. Thus, it is important to identify patients who stand to benefit most from medication review. Patients are typically identified for medication review based on number of medications and age, but this may not be the most efficient strategy for identifying patients at high risk of future adverse clinical outcomes. In this exploratory study of 27 873 acutely admitted medical patients (≥18 years) at Copenhagen University Hospital Hvidovre, Denmark, we investigated whether other clinical factors could improve the prediction of adverse clinical outcomes and, therefore, be incorporated into patient stratification for medication review. The outcomes of interest were acute readmission or mortality within 90 days post-discharge. Medication risk score (MERIS), renal function and anticholinergic cognitive burden did not improve prediction of adverse clinical outcomes compared to number of medications and age. However, addition of a frailty index based on routine biomarkers (FI-OutRef) or plasma soluble urokinase plasminogen activator receptor (suPAR) did improve prediction of outcomes. Use of these practical proxies of disease burden may improve the identification of acutely hospitalized patients who would benefit most from a medication review.

Indexed as

Inappropriate PrescribingMedication ReconciliationAdultAgedAged, 80 and overBiomarkersDenmarkFemaleHospitalizationHumansMaleMiddle AgedPatient AdmissionPatient ReadmissionRisk AssessmentBiomarkersadverse clinical outcomesdisease burdenmedication burdenpredictionrisk stratification

Identifiers

PMID40883976
PMCPMC12569553

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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.