Evidence map›Paper›PMID 40679772›Full record

ArticleInternational journal of clinical pharmacy2025

Comparative effectiveness of the Beers Criteria (2023) versus the STOPP (v3) in detecting potentially inappropriate medications in older adults with heart failure: a retrospective cross-sectional study.

Suyan Zhu, Xiaomeng Zheng, Miao Fan, Yiyi Jin, Chunyan Chen, Mengjing Cheng

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in International journal of clinical pharmacy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Suyan ZhuDepartment of Pharmacy, The First Affiliated Hospital of Ningbo University, Ningbo First Hospital, Ningbo, 315010, China. suyan_chu@hotmail.com.
Xiaomeng ZhengDepartment of Pharmacy, The First Affiliated Hospital of Ningbo University, Ningbo First Hospital, Ningbo, 315010, China.
Miao FanDepartment of Pharmacy, The First Affiliated Hospital of Ningbo University, Ningbo First Hospital, Ningbo, 315010, China.
Yiyi JinDepartment of Pharmacy, The First Affiliated Hospital of Ningbo University, Ningbo First Hospital, Ningbo, 315010, China.
Chunyan ChenDepartment of Pharmacy, The First Affiliated Hospital of Ningbo University, Ningbo First Hospital, Ningbo, 315010, China.
Mengjing ChengDepartment of Pharmacy, The First Affiliated Hospital of Ningbo University, Ningbo First Hospital, Ningbo, 315010, China.

Funding

Medical Science and Technology Project of Zhejiang Province 2024KY329Natural Science Foundation of Ningbo Municipality 2022J220
6 · The paper itself

Abstract

introductionThe American Geriatrics Society (AGS) Beers Criteria and Screening Tool of Older Persons' Potentially Inappropriate Prescriptions (STOPP)/Screening Tool to Alert to Right Treatment (START) criteria are extensively utilized in identifying potentially inappropriate medications (PIMs) among older adults. Older adults with heart failure (HF) confront the dual challenge of polypharmacy and inadequate adherence to evidence-based medications, which further complicates their medication management and clinical outcomes.

aimTo assess the effectiveness of the AGS Beers (2023) Criteria and the STOPP (v3) criteria in identifying PIMs among older adults with HF and to analyze patterns of polypharmacy and evidence-based medications.

methodThis retrospective study was conducted at a tertiary academic medical center in China and involved 1578 outpatients aged ≥ 65 years with HF who received at least one outpatient prescription between January 1 and December 31, 2023. Data on demographics, comorbidities, and prescribed medications were extracted from the hospital's electronic medical record (EMR) system. PIMs were identified with the AGS Beers (2023) Criteria and the STOPP (v3) criteria. The data were analyzed using descriptive statistics in Microsoft Excel.

resultsPolypharmacy and hyperpolypharmacy were prevalent among the patients, affecting 65.3% and 15.7% of the cohort, respectively. PIMs were identified in 75.5% of patients (1192/1578), with a total of 2128 PIM cases observed according to the Beers Criteria, with the most common PIM being rivaroxaban (32.3%). The STOPP (v3) criteria identified PIMs in 28.9% of patients (n = 471), with the most frequent PIMs being statin use in frail patients aged ≥ 85 years (26.8%) and prolonged use of proton-pump inhibitors (16.6%). Among all patients in our study, 61.6% received either an angiotensin-converting enzyme inhibitor, angiotensin-II receptor blocker, or angiotensin receptor-neprilysin inhibitor (ACEI/ARB/ARNI); 57.0% were prescribed β-blockers; and 32.6% used a sodium-glucose cotransporter 2 inhibitor.

conclusionWhile the Beers Criteria identified a greater number of PIMs in this study, both tools have differing strengths in detecting medication-related risks. Their combined use may provide a more holistic assessment of prescribing appropriateness. The widespread use of PIMs in older adults with HF, coupled with the frequent underuse of beneficial therapies, calls for systematic interventions. Pharmacist-led interventions and electronic decision-support systems that integrate evidence-based prescribing, deprescribing, and regular medication reviews are crucial for optimizing therapeutic outcomes in older adults with HF.

Indexed as

Heart FailureInappropriate PrescribingPotentially Inappropriate Medication ListAgedAged, 80 and overChinaCross-Sectional StudiesFemaleHumansMalePolypharmacyRetrospective StudiesBeers criteriaHeart failurePolypharmacyPotentially inappropriate medicationSTOPP

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.