Evidence map›Paper›PMID 37695395›Full record

ArticleDrugs & aging2023

Secular Trends in Central Nervous System-Active Polypharmacy Among Serial Cross-Sections of US Adults, 2009-2020.

Samuel W Terman, Joshua D Niznik, Matthew E Growdon, Lauren B Gerlach, James F Burke

Abstract read
In one paragraph

Article in Drugs & aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Trends in central nervous system-active polypharmacy among people with multiple sclerosis.Multiple sclerosis (Houndmills, Basingstoke, England) · 2024
    Article
  6. Article
  7. 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

5 authors.

Samuel W TermanDepartment of Neurology, University of Michigan, Taubman 1st Floor, Reception C, 1500 E Medical Center Dr, SPC 5316, Ann Arbor, MI, 48109, USA. sterman@umich.edu.ORCID 0000-0001-6179-9467
Joshua D NiznikDivision of Geriatric Medicine, Center for Aging and Health, School of Medicine, University of North Carolina At Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0003-1466-5751
Matthew E GrowdonDivision of Geriatrics, University of California San Francisco, San Francisco, CA, USA.ORCID 0000-0001-5997-4406
Lauren B GerlachDepartment of Psychiatry, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0003-1943-0150
James F BurkeDepartment of Neurology, The Ohio State University, Columbus, OH, USA.

Funding

Michigan Institute for Clinical and Health Research (MICHR)UL1TR002240 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LUMENG, JULIE C, MASHOUR, GEORGE ALEXANDER · 2017 to 2022
$54.9M
Michigan Institute for Clinical and Health Research (MICHR)UM1TR004404 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Julie C Lumeng · 2023 to 2026
$39.8M
U.S. Deprescribing Research NetworkR24AG064025 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI BOYD, CYNTHIA MELINDA, STEINMAN, MICHAEL A. · 2019 to 2023
$9.9M
Medicating distress: Use of psychotropic medications among patients with dementia receiving hospice careK23AG066864 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GERLACH, LAUREN BETH · 2021 to 2025
$1.0M
Deprescribing Bisphosphonates in Older Nursing Home Residents with DementiaK08AG071794 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI NIZNIK, JOSHUA DAVID · 2021 to 2025
$724k
Medication risks and challenges among people with dementia who live aloneR03AG078804 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GROWDON, MATTHEW EVAN · 2022 to 2023
$323k
AHRQ HHS K12 HS026383NCATS NIH HHS UL1 TR002240NCATS NIH HHS UM1 TR004404NIA NIH HHS K08 AG071794NIA NIH HHS K23 AG066864NIA NIH HHS R03 AG078804NIA NIH HHS R24 AG064025
6 · The paper itself

Abstract

backgroundData comprehensively examining trends in central nervous system (CNS)-active polypharmacy are limited. The objective of this cross-sectional study was to characterize the composition of and trends in CNS-active medication use in US adults.

methodsWe included all participants ≥ 18 years old in the National Health and Nutrition Examination Study (NHANES), 2009-2020. The primary outcome was the percent of adults with CNS-active polypharmacy. This was defined as ≥ 3 medications among antidepressants [tricyclic, selective and serotonin-norepinephrine reuptake inhibitors (SSRIs and SNRIs), opioids, antiepileptics, antipsychotics, benzodiazepines, and nonbenzodiazepine receptor agonists ("Z-drugs")]. Secondary outcomes included prevalence of any CNS-active medication and specific medications and classes over time, and their indications. Percentages were weighted according to NHANES's nationally representative sampling frame. log binomial regressions evaluated the relative risk (RR) for each outcome, comparing the last (2017-2020) versus the first (2010-2011) survey cycle.

resultsWe included 34,189 adults (18.8% at least 65 years old) from five serial cross-sections (survey cycles). The prevalence of CNS-active polypharmacy was 2.1% in 2009-2010 and 2.6% in 2017-2020 [RR 1.18, 95% confidence interval (CI) 0.94-1.47]. The prevalence of CNS-active polypharmacy did not significantly change within any specific age group (e.g., age at least 65 years: RR 1.29, CI 0.74-2.24). The prevalence of any CNS-active medication was 21.0% in 2009 and 24.6% in 2017-2020 (RR] 1.12, 95% CI 1.02-1.25). A substantial increase occurred for antiepileptics (5.1-8.3%), specifically among participants aged 65 years and older (8.3-13.7%). This was largely driven by increasing gabapentin prevalence (1.4-3.6% overall; 3.3-7.9% age 65 years and older). Anticholinergic, SSRIs/SNRIs, antiepileptics, and benzodiazepines were elevated in most cycles for participants at least 65 years old compared with participants less than 65 years, and opioid use was increased in several cycles for older participants as well. Alprazolam was the most common benzodiazepine and third most common medication for anxiety/depression. Gabapentin was the most common CNS-active medication (3.6% of all participants in 2017-2020), followed by sertraline, citalopram, and acetaminophen-hydrocodone (each ~2%). The most common categories were antidepressants (13.7% in 2017-2020), followed by opioids (5.1% in 2017-2020).

conclusionsCNS-active medications are increasingly common, particularly gabapentin, and use of any CNS-active medication increased by 12%. Numerous CNS-active classes also increased in older adults throughout the years. Increasing suboptimal medication use highlight the need for further investigation into causes for potentially inappropriate prescribing, particularly for older adults.

Indexed as

PolypharmacySerotonin and Noradrenaline Reuptake InhibitorsAgedAnalgesics, OpioidAnticonvulsantsBenzodiazepinesCentral Nervous SystemCross-Sectional StudiesGabapentinHumansNutrition SurveysSelective Serotonin Reuptake InhibitorsAnalgesics, OpioidAnticonvulsantsBenzodiazepinesGabapentinSelective Serotonin Reuptake InhibitorsSerotonin and Noradrenaline Reuptake Inhibitors

Identifiers

PMID37695395
PMCPMC10629698

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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.