Evidence map›Paper›PMID 29089750›Full record

SynthesisClinical interventions in aging2017

Inappropriate pharmacological treatment in older adults affected by cardiovascular disease and other chronic comorbidities: a systematic literature review to identify potentially inappropriate prescription indicators.

Ersilia Lucenteforte, Niccolò Lombardi, Davide Liborio Vetrano, Domenico La Carpia, Zuzana Mitrova, Ursula Kirchmayer, Giovanni Corrao, Francesco Lapi, Alessandro Mugelli, Alfredo Vannacci

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Clinical interventions in aging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-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

8 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
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  6. Galenic Preparations of TherapeuticFrontiers in pharmacology · 2018
    Article
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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 5 institutions in 2 countries.

Ersilia LucenteforteDepartment of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA), University of Florence, Florence, Italy.
Niccolò Lombardi *Department of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA), University of Florence, Florence, Italy.
Davide Liborio Vetrano *Department of Geriatrics Catholic University, Rome, Italy.
Domenico La Carpia *Department of Geriatrics Catholic University, Rome, Italy.
Zuzana MitrovaDepartment of Epidemiology, ASL 1 Rome, Italy.
Ursula KirchmayerDepartment of Epidemiology, ASL 1 Rome, Italy.
Giovanni CorraoDepartment of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy.
Francesco LapiEpidemiology Unit, ARS Toscana, Florence, Italy.
Alessandro MugelliDepartment of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA), University of Florence, Florence, Italy.
Alfredo VannacciDepartment of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA), University of Florence, Florence, Italy.
University of Florence · ITAzienda Sanitaria Locale Roma 3 · ITUniversità Cattolica del Sacro Cuore · ITAgenzia Regionale per la Protezione Ambientale della Toscana · ITUniversity of Milano-Bicocca · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Avoiding medications in which the risks outweigh the benefits in the elderly patient is a challenge for physicians, and different criteria to identify inappropriate prescription (IP) exist to aid prescribers. Definition of IP indicators in the Italian geriatric population affected by cardiovascular disease and chronic comorbidities could be extremely useful for prescribers and could offer advantages from a public health perspective. The purpose of the present study was to identify IP indicators by means of a systematic literature review coupled with consensus criteria. A systematic search of PubMed, EMBASE, and CENTRAL databases was conducted, with the search structured around four themes and combining each with the Boolean operator "and". The first regarded "prescriptions", the second "adverse events", the third "cardiovascular conditions", and the last was planned to identify studies on "older people". Two investigators independently reviewed titles, abstracts, full texts, and selected articles addressing IP in the elderly affected by cardiovascular condition using the following inclusion criteria: studies on people aged ≥65 years; studies on patients with no restriction on age but with data on subjects aged ≥65 years; and observational effectiveness studies. The database searches produced 5,742 citations. After removing duplicates, titles and abstracts of 3,880 records were reviewed, and 374 full texts were retrieved that met inclusion criteria. Thus, 49 studies reporting 32 potential IP indicators were included in the study. IP indicators regarded mainly drug-drug interactions, cardio- and cerebrovascular risk, bleeding risk, and gastrointestinal risk; among them, only 19 included at least one study that showed significant results, triggering a potential warning for a specific drug or class of drugs in a specific context. This systematic review demonstrates that both cardiovascular and non-cardiovascular drugs increase the risk of adverse drug reactions in older adults with cardiovascular diseases.

Indexed as

AgedCardiovascular AgentsCardiovascular DiseasesComorbidityDrug InteractionsHemorrhageHumansInappropriate PrescribingStrokeCardiovascular Agentscardiovascular diseaseschronic diseaseselderlyinappropriate prescriptionssystematic review

Identifiers

PMID29089750
PMCPMC5656349
OpenAlexW2765745054

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.