Evidence map›Paper›PMID 24262287›Full record

ArticleThe American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry2014

Age as a predictor of cognitive decline in bipolar disorder.

Kathryn E Lewandowski, Sarah H Sperry, Mary C Malloy, Brent P Forester

Open access · greenAbstract read
In one paragraph

Article in The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
0.6field-weighted citation impact, top 33% 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Interactive relationships of Type 2 diabetes and bipolar disorder with cognition: evidence of putative premature cognitive ageing in the UK Biobank Cohort.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2023
    Article
  7. Article
  8. Article
  9. Steeper Slope of Age-Related Changes in White Matter Microstructure and Processing Speed in Bipolar Disorder.The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry · 2017
    Article
  10. Bipolar Patients with Vascular Risk Display a Steeper Age-Related Negative Slope in Inhibitory Performance but Not Processing Speed: A Preliminary Study.The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry · 2017
    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

4 authors at 2 institutions in 1 country.

Kathryn E LewandowskiSchizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, MA; Department of Psychiatry, Harvard Medical School, Boston, MA. Electronic address: klewandowski@mclean.harvard.edu.
Sarah H SperrySchizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, MA.
Mary C MalloyGeriatric Mood Disorders Research Program, McLean Hospital, Belmont, MA.
Brent P ForesterGeriatric Mood Disorders Research Program, McLean Hospital, Belmont, MA; Department of Psychiatry, Harvard Medical School, Boston, MA.
McLean Hospital · USHarvard University · US

Funding

Cerebral Energy Metabolism in Geriatric Bipolar DepressionK23MH077287 · NIMH · MCLEAN HOSPITAL · PI FORESTER, BRENT PETER · 2009 to 2013
$897k
Efficacy of a Cognitive Remediation Treatment Program for Bipolar DisorderK23MH091210 · NIMH · MCLEAN HOSPITAL · PI LEWANDOWSKI, KATHRYN EVE · 2011 to 2015
$749k
NIMH NIH HHS K23 MH091210
6 · The paper itself

Abstract

objectiveCognitive dysfunction is a core feature of bipolar disorder (BD) in both adult and geriatric patients. However, little is known about whether cognitive functioning declines at a faster rate in patients with BD, and there are conflicting reports regarding the relationship between age and cognitive functioning in this population. This cross-sectional study examined the relationship between age and cognitive functioning in patients with BD.

methodsPatients with BD I (N = 113) and healthy adults (N = 64) ages 18-87 completed measures of processing speed, attention, executive functioning, verbal fluency, and clinical symptomatology. Groupwise comparisons were used to examine differences between patients and the comparison group and adult and geriatric BD cohorts. A series of linear regressions was conducted to examine the relationship of age and cognitive functioning and clinical variables and cognition.

resultsPatients performed significantly worse than the comparison group on all neuropsychological measures. Age was a significant predictor of Trails A scores with older age associated with worse performance.

conclusionsOlder age was associated with poorer performance on Trails A in patients with BD but not healthy adults. These results are suggestive of greater dysfunction in processing speed with older age in patients with BD compared with a healthy comparison group. Because cognitive functioning is associated with community outcomes, these findings suggest a need for treatments targeting cognitive symptoms across the life span. Future research exploring neurobiologic evidence for neurodegenerative processes in BD will pave the way for potential therapeutic interventions.

Indexed as

Disease ProgressionAdolescentAdultAgedAge FactorsAgingBipolar DisorderCognition DisordersFemaleHumansMaleMiddle AgedYoung AdultagingBipolarcognitivelife span

Identifiers

PMID24262287
PMCPMC3977013
OpenAlexW2009501827

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.