Evidence map›Paper›PMID 42381224›Full record

ArticleBipolar disorders2026

Psychotropic Prescribing Patterns Among Bipolar-I Patients Prior to Established Bipolar-I Disorder Diagnosis.

Filmon Haile, Clayton English, Kyueun Lee

Abstract read
In one paragraph

Article in Bipolar disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

3 authors.

Filmon HaileDepartment of Pharmacy, CHOICE Institute, University of Washington, School of Pharmacy, Seattle, WA, USA.ORCID 0009-0005-9890-7827
Clayton EnglishDepartment of Pharmacy, CHOICE Institute, University of Washington, School of Pharmacy, Seattle, WA, USA.ORCID 0000-0001-7999-5191
Kyueun LeeDepartment of Pharmacy, CHOICE Institute, University of Washington, School of Pharmacy, Seattle, WA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveBipolar I Disorder (BP-I) is frequently misdiagnosed as Major Depressive Disorder (MDD), delaying appropriate treatment. This study aimed to examine treatment patterns among BP-I patients misdiagnosed with MDD and assess the impact of these regimens on the time until BP-I diagnosis.

methodsA retrospective cohort study was conducted using the MarketScan Commercial Claims and Encounters database, analyzing 21,771 BP-I patients initially misdiagnosed with MDD and 50,667 correctly diagnosed BP-I patients. Treatment patterns and their influence on time to BP-I diagnosis were assessed using multinomial logistic regression and Cox proportional hazards models.

resultsAmong the misdiagnosed cohort, 25.1% were initially started on antidepressant monotherapy, with 8.7% continuing this regimen after BP-I diagnosis. In contrast, 7.6% of the initially BP-I diagnosed cohort received antidepressant monotherapy. The time to BP-I conversion was shortest for those on mood stabilizer monotherapy (HR: 1.26, 95% CI: 1.19-1.34, p < 0.001), compared to those on antidepressant monotherapy. After BP-I diagnosis, patients originally misdiagnosed with MDD had different prescribing patterns, exhibiting lower rates of guideline-consistent treatments. Specifically, patients initially diagnosed with BP-I were more likely to receive mood stabilizing therapy, either as monotherapy (OR = 2.63, p < 0.001) or in combination with an antidepressant (OR = 1.84, p < 0.001).

conclusionMisdiagnosis of BP-I as MDD leads to significant delays in accurate diagnosis and inappropriate treatment regimens, highlighting the critical need for improved diagnostic accuracy at initial presentation. Prompt and accurate BP-I diagnosis can optimize treatment approaches and improve patient outcomes.

Indexed as

Bipolar DisorderPractice Patterns, Physicians'Psychotropic DrugsAdultAntidepressive AgentsCohort StudiesDiagnostic ErrorsFemaleHumansMajor Depressive DisorderMaleMiddle AgedRetrospective StudiesYoung AdultAntidepressive AgentsPsychotropic Drugs

Identifiers

PMID42381224
PMCPMC13320148

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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.