Evidence map›Paper›PMID 25505672›Full record

ArticleInternational journal of bipolar disorders2013

Drug treatment patterns in bipolar disorder: analysis of long-term self-reported data.

Michael Bauer, Tasha Glenn, Martin Alda, Kemal Sagduyu, Wendy Marsh, Paul Grof, Rodrigo Munoz, Emanuel Severus, Philipp Ritter, Peter C Whybrow

Open access · goldAbstract read
In one paragraph

Article in International journal of bipolar disorders, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
2.7field-weighted citation impact, top 10% 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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 41 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  5. Review
  6. Article
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  11. Article
  12. Article
  13. Electronic monitoring of self-reported mood: the return of the subjective?International journal of bipolar disorders · 2016
    Review
  14. Big data for bipolar disorder.International journal of bipolar disorders · 2016
    Review
  15. Observational
  16. Review
  17. Big data are coming to psychiatry: a general introduction.International journal of bipolar disorders · 2015
    Article
  18. Article
  19. Review
  20. 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

10 authors at 7 institutions in 3 countries.

Michael BauerDepartment of Psychiatry and Psychotherapy, Universitätsklinikum Carl Gustav Carus, Technische Universität Dresden, Fetscherstr. 74, Dresden, 01307 Germany.
Tasha GlennChronoRecord Association Inc., Fullerton, CA 92834 USA.
Martin AldaDepartment of Psychiatry, Dalhousie University, Halifax, NS B3H 4R2 Canada.
Kemal SagduyuDepartment of Psychiatry, University of Missouri Kansas City School of Medicine, Kansas City, MO 64110 USA.
Wendy MarshDepartment of Psychiatry, University of Massachusetts, 55 Lake Avenue North, Worcester, MA 01655 USA.
Paul GrofDepartment of Psychiatry, University of Toronto, Toronto, Ontario M5S 1A1 Canada ; Mood Disorders Centre of Ottawa, Ottawa, Ontario K1G 4G3 Canada.
Rodrigo MunozDepartment of Psychiatry, University of California San Diego, San Diego, CA 92093 USA.
Emanuel SeverusDepartment of Psychiatry and Psychotherapy, Universitätsklinikum Carl Gustav Carus, Technische Universität Dresden, Fetscherstr. 74, Dresden, 01307 Germany.
Philipp RitterDepartment of Psychiatry and Psychotherapy, Universitätsklinikum Carl Gustav Carus, Technische Universität Dresden, Fetscherstr. 74, Dresden, 01307 Germany.
Peter C WhybrowDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior University of California Los Angeles (UCLA), 300 UCLA Medical Plaza, Los Angeles, CA 90095 USA.
Klinik und Poliklinik für Psychotherapie und Psychosomatik · DEDalhousie University · CAUniversity of California, Los Angeles · USUniversity of California, San Diego · USUniversity of Massachusetts Chan Medical School · USUniversity of Missouri–Kansas City · USUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe objective of this study is to investigate drug treatment patterns in bipolar disorder using daily data from patients who received treatment as usual.

methodsPatients self-reported the drugs taken daily for about 6 months. Daily drug use and drug combinations were determined for each patient, both by the specific drugs and by medication class. The drug load was calculated for all drugs taken within a medication class. RESULTS AND DISCUSSION: Four hundred fifty patients returned a total of 99,895 days of data (mean 222.0 days). The most frequently taken drugs were mood stabilizers. Of the 450 patients, 353 (78.4%) took a stable drug combination for ≥50% of days. The majority of patients were taking polypharmacy, including 75% of those with a stable combination. Only a small number of drugs were commonly taken within each medication class, but there were a large number of unique drug combinations: 52 by medication class and 231 by specific drugs. Eighty percent of patients with a stable combination were taking three or less drugs daily. Patients without a stable combination took drugs but made frequent changes. Taking more than one drug within a medication class greatly increased the drug load. To summarize, (1) patients were more likely to take a mood stabilizer than any other drug; (2) although most patients were taking polypharmacy, there were no predominant drug regimens even among those taking a stable combination; and (3) most patients with a stable combination take a relatively small number of drugs daily. The wide variation in drug regimens and numerous possible drug combinations suggest that more evidence is needed to optimize treatment of bipolar disorder.

Indexed as

Bipolar disorderDrug loadDrug treatment patternsPolypharmacy

Identifiers

PMID25505672
PMCPMC4230449
OpenAlexW2123735858

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.