Evidence map›Paper›PMID 41193022›Full record

ArticleThe western journal of emergency medicine2025

Pharmacogenomic Drug-Gene Interactions in Geriatric Emergency Department Patients Who Sustained Falls: A Pilot Study.

Richard D Shih, Gabriella Engstrom, Abhijit S Pandya, Gregg B Fields, Borivoje Furht, Ali A Danesh, Scott M Alter, Humberto Munoz, Lisa M Clayton, Joshua J Solano and 4 more

Abstract read
In one paragraph

Article in The western journal of emergency medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Richard D ShihFlorida Atlantic University, Charles E. Schmidt College of Medicine, Department of Emergency Medicine, Boca Raton, Florida.
Gabriella EngstromFlorida Atlantic University, Charles E. Schmidt College of Medicine, Department of Emergency Medicine, Boca Raton, Florida.
Abhijit S PandyaFlorida Atlantic University, College of Engineering and Computer Science, Department of Electrical Engineering and Computer Science, Boca Raton, Florida.
Gregg B FieldsFlorida Atlantic University, Charles E. Schmidt College of Science, Department of Chemistry and Biochemistry, Boca Raton, Florida.
Borivoje FurhtFlorida Atlantic University, College of Engineering and Computer Science, Department of Electrical Engineering and Computer Science, Boca Raton, Florida.
Ali A DaneshFlorida Atlantic University, College of Education, Department of Communication Sciences and Disorders, Boca Raton, Florida.
Scott M AlterFlorida Atlantic University, Charles E. Schmidt College of Medicine, Department of Emergency Medicine, Boca Raton, Florida.
Humberto MunozDelray Medical Center, Department of Emergency Medicine, Delray Beach, Florida.
Lisa M ClaytonFlorida Atlantic University, Charles E. Schmidt College of Medicine, Department of Emergency Medicine, Boca Raton, Florida.
Joshua J SolanoFlorida Atlantic University, Charles E. Schmidt College of Medicine, Department of Emergency Medicine, Boca Raton, Florida.
Timothy BuckleyFlorida Atlantic University, Charles E. Schmidt College of Medicine, Department of Emergency Medicine, Boca Raton, Florida.
Olivia HungFlorida Atlantic University, Charles E. Schmidt College of Medicine, Department of Emergency Medicine, Boca Raton, Florida.
Alexander FaragFlorida Atlantic University, Charles E. Schmidt College of Medicine, Department of Emergency Medicine, Boca Raton, Florida.
Mike WellsFlorida Atlantic University, Charles E. Schmidt College of Medicine, Department of Emergency Medicine, Boca Raton, Florida.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPharmacogenomic-assisted prescribing of medications uses individual genetic information to identify drug-gene interactions. We aimed to assess potential pharmacogenomic drug-gene interactions in geriatric emergency department (ED) patients who sustained a fall.

methodsThis was a prospective study involving 25 older adult ED patients with fall-related injury. Data collected included current medications, demographics, and mechanism of injury. All patients provided a DNA sample, which underwent pharmacogenomic testing by an accredited genetics lab, Each patient's medications were reviewed against their pharmacogenomic report and categorized as Green (continue to use), Yellow (use with caution) or Red (stop use) based on their genetic information and published interactions by the Clinical Pharmacogenetics Implementation Consortium, Dutch Pharmacogenetics Working Group, and US Food and Drug Administration-approved drug label information. The main study outcome was pharmacogenomic drug-gene interactions.

resultsOf the 25 patients enrolled (median age, 81 years, IQR 76-85), 68% were female. Patients were taking a median of eight medications (IQR 5-11). The most common types were antihypertensives, statins, anticoagulants, and anti-platelet medications. Significant drug-gene interactions (Yellow or Red) were identified in 14/25 patients (56%; 95% CI 35-76%). Further, 6/25 (24%; 95% CI 9-45%) had one or more potentially serious (Red) interactions identified.

conclusionWe found that in geriatric ED patients with a fall-related injury, most had a significant pharmacogenomic drug-gene interaction. DNA testing identifies these interactions and can assist with pharmacogenomic-guided medication prescribing, which may decrease adverse drug events and improve clinical outcomes.

Indexed as

Accidental FallsEmergency Service, HospitalPharmacogeneticsAgedAged, 80 and overDrug InteractionsFemaleHumansMalePharmacogenomic TestingPilot ProjectsProspective Studies

Identifiers

PMID41193022
PMCPMC12591660

What Socratic holds

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LicenceCC BY
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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 Socratic graph.