Evidence map›Paper›PMID 38319492›Full record

ArticleDrugs & aging2024

Development and Pilot Testing of an Algorithm-Based Approach to Anticholinergic Deprescribing in Older Patients.

Tanja Wehran, Annette Eidam, David Czock, Jürgen Kopitz, Konstanze Plaschke, Margarete Mattern, Walter Emil Haefeli, Jürgen Martin Bauer, Hanna Marita Seidling

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Drugs & aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 18% 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, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. [Frailty and pharmacotherapy].Innere Medizin (Heidelberg, Germany) · 2025
    Review
  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

9 authors at 1 institution in 1 country.

Tanja Wehran *Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University, Medical Faculty Heidelberg / Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany.
Annette Eidam *Center for Geriatric Medicine, Heidelberg University Hospital, Agaplesion Bethanien Hospital, Rohrbacher Straße 149, 69126, Heidelberg, Germany.
David CzockDepartment of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University, Medical Faculty Heidelberg / Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany.
Jürgen KopitzInstitute of Pathology, Heidelberg University, Im Neuenheimer Feld 224, 69120, Heidelberg, Germany.
Konstanze PlaschkeDepartment of Anaesthesiology, Heidelberg University Hospital, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany.
Margarete MatternDepartment of General Psychiatry, Heidelberg University Hospital, Voßstraße 4, 69115, Heidelberg, Germany.
Walter Emil HaefeliDepartment of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University, Medical Faculty Heidelberg / Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany.
Jürgen Martin BauerCenter for Geriatric Medicine, Heidelberg University Hospital, Agaplesion Bethanien Hospital, Rohrbacher Straße 149, 69126, Heidelberg, Germany.
Hanna Marita SeidlingDepartment of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University, Medical Faculty Heidelberg / Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany. hanna.seidling@med.uni-heidelberg.de.ORCID 0000-0002-1215-634X
Heidelberg University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdverse anticholinergic drug reactions are common, yet evidence on how to reduce exposure to anticholinergic activity and reliably measure successful deprescribing is still scant. This study proposes an algorithm-based approach to evaluate and reduce anticholinergic load, and reports the results of its pilot testing.

methodsBased on published evidence and expert opinion, a list of 85 anticholinergic drugs and 21 algorithms for reducing anticholinergic load, e.g., by recommending alternative drugs with lower risk, were developed. An accompanying test battery was assembled by focusing on instruments that sensitively reflect anticholinergic load and may be sensitive to depict changes (Neuropsychological Assessment Battery to measure memory and attention, validated assessments for constipation, urinary symptoms, and xerostomia, as well as blood biomarkers). The approach was pilot-tested in a geriatric rehabilitation unit, with clinician feedback as the primary outcome and characterization of anticholinergic symptoms as the secondary outcome. The intervention was delivered by a pharmacist and a clinical pharmacologist who used the algorithms to generate personalized recommendation letters.

resultsWe included a total of 20 patients, 13 with anticholinergic drugs and 7 without. Recommendations were made for 22 drugs in nine patients from the intervention group, of which seven letters (78%) were considered helpful and 8/22 (36%) anticholinergic drugs were discontinued, reducing anticholinergic load in seven patients. In contrast to patients without drug change, memory assessment in patients with reduced anticholinergic load improved significantly after 2 weeks (6 ± 3 vs. -1 ± 6 points).

conclusionsThe approach was well received by the participating physicians and might support standardized anticholinergic deprescribing.

Indexed as

DeprescriptionsPhysiciansAgedCholinergic AntagonistsConstipationHumansPatientsCholinergic Antagonists

Identifiers

PMID38319492
PMCPMC10869417
OpenAlexW4391562250

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.