Evidence map›Paper›PMID 29265170›Full record

SynthesisJournal of the American Geriatrics Society2018

Meta-analysis of Interventions to Reduce Adverse Drug Reactions in Older Adults.

Shelly L Gray, Laura A Hart, Subashan Perera, Todd P Semla, Kenneth E Schmader, Joseph T Hanlon

Abstract readMeta-Analysis
In one paragraph

Synthesis in Journal of the American Geriatrics Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 1 pooled it
–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

38 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  15. Deprescribing trials: A focus on adverse drug withdrawal events.Journal of the American Geriatrics Society · 2022
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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

6 authors.

Shelly L GrayDepartment of Pharmacy, School of Pharmacy, University of Washington, Seattle, Washington.
Laura A HartDepartment of Pharmacy, School of Pharmacy, University of Washington, Seattle, Washington.
Subashan PereraDivision of Geriatrics, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
Todd P SemlaPharmacy Benefits Management, Department of Veterans Affairs, Hines, Illinois.
Kenneth E SchmaderDivision of Geriatrics, Department of Medicine, School of Medicine, Duke University, Durham, North Carolina.
Joseph T HanlonDivision of Geriatrics, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.

Funding

Furthering scientific understanding of mechanisms underlying resilience to the effects of AD pathology by incorporating state of the art quantification of gliosis, inflammation, & synaptic toxicityU01AG006781 · NIA · UNIVERSITY OF WASHINGTON · PI CRANE, PAUL K, LARSON, ERIC B · 1986 to 2020
$39.3M
VARIABILITY, STABILITY & SMOOTHNESS OF WALKINGP30AG024827 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Caterina Rosano · 2004 to 2026
$28.6M
Resource Core 3 - Metabolomics CoreP30AG028716 · NIA · DUKE UNIVERSITY · PI Sarah B. Peskoe · 2006 to 2026
$24.6M
Advancing Geriatrics Infrastructure & Network Growth - Admin Supplement: Designing and Testing an Informatics Tool to Aid Prescribers in Reducing Anticholinergic Burden in Older AdultsR24AG045050 · NIA · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI GURWITZ, JERRY H · 2014 to 2017
$3.6M
Improving Outcomes of UTI in LTC Facilities: The IOU StudyR18HS023779 · AHRQ · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI NACE, DAVID A. · 2015 to 2017
$1.4M
Integration of Geriatrics Principles into the Care of Older Adults with CardiovasU13AG047008 · NIA · AMERICAN COLLEGE OF CARDIOLOGY · PI RICH, MICHAEL W · 2014 to 2018
$210k
AHRQ HHS R18 HS023779NIA NIH HHS P30 AG024827NIA NIH HHS P30 AG028716NIA NIH HHS R24 AG045050NIA NIH HHS U01 AG006781NIA NIH HHS U13 AG047008
6 · The paper itself

Abstract

objectivesTo examine the effect of interventions to optimize medication use on adverse drug reactions (ADRs) in older adults.

designSystematic review and meta-analysis. EMBASE, PubMed, OVID, Cochrane Library, Clinicaltrials.gov, and Google Scholar were searched through April 30, 2017.

settingRandomized controlled trials.

participantsOlder adults (mean age ≥65) taking medications. MEASUREMENTS: Two authors independently extracted relevant information and assessed studies for risk of bias. Discrepancies were resolved in consensus meetings. The outcomes were any and serious ADRs. Random-effects models were used to combine the results of multiple studies and create summary estimates.

resultsThirteen randomized controlled trials involving 6,198 older adults were included. The studies employed a number of different interventions that were categorized as pharmacist-led interventions (8 studies), other health professional-led interventions (3 studies), a brief educational session (1 study), and a technology intervention (1 study). The intervention group was 21% less likely than the control group to experience any ADR (odds ratio (OR) = 0.79, 95% confidence interval (CI) = 0.62-0.99). In the six studies that examined serious ADRs, the intervention group was 36% less likely than the control group to experience a serious ADR (OR = 0.64, 95% CI = 0.42-0.98).

conclusionInterventions designed to optimize medication use reduced the risk of any and serious ADRs in older adults. Implementation of these successful interventions in healthcare systems may improve medication safety in older adults.

Indexed as

PharmacistsAgedDrug-Related Side Effects and Adverse ReactionsHumansMedical InformaticsRandomized Controlled Trials as Topicadverse drug reactionagedmeta-analysisrandomized controlled trials

Identifiers

PMID29265170
PMCPMC5809283

What OpenQuestion holds

Textmetadata
LicenceTDM
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.