Evidence map›Paper›PMID 39666719›Full record

ArticleBipolar disorders2025

Predicting Diagnostic Conversion From Major Depressive Disorder to Bipolar Disorder: An EHR Based Study From Colombia.

Susan K Service, Juan F De La Hoz, Ana M Diaz-Zuluaga, Alejandro Arias, Aditya Pimplaskar, Chuc Luu, Laura Mena, Johanna Valencia-Echeverry, Mauricio Castaño Ramírez, Carrie E Bearden and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bipolar disorders, 2025. 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. Characterisation of serious mental illness trajectories through transdiagnostic clinical features.The British journal of psychiatry : the journal of mental science · 2026
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  3. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Susan K ServiceCenter for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Juan F De La HozCenter for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.ORCID 0000-0002-5584-7511
Ana M Diaz-ZuluagaCenter for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Alejandro AriasResearch Group in Psychiatry (GIPSI), Institute of Medical Research, Department of Psychiatry, Faculty of Medicine, University of Antioquia, Medellín, Colombia.
Aditya PimplaskarCenter for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Chuc LuuCenter for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Laura MenaCenter for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Johanna Valencia-EcheverryResearch Group in Psychiatry (GIPSI), Institute of Medical Research, Department of Psychiatry, Faculty of Medicine, University of Antioquia, Medellín, Colombia.
Mauricio Castaño RamírezDepartment of Mental Health and Human Behavior, University of Caldas, Manizales, Colombia.
Carrie E BeardenCenter for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Chiara SabattiDepartment of Biomedical Data Science, Stanford University, Stanford, California, USA.
Victor I ReusDepartment of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, California, USA.
Carlos López-JaramilloResearch Group in Psychiatry (GIPSI), Institute of Medical Research, Department of Psychiatry, Faculty of Medicine, University of Antioquia, Medellín, Colombia.
Nelson B FreimerCenter for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Loes M Olde LoohuisCenter for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.ORCID 0000-0002-3327-7837

Funding

A Latin American biobank for large-scale genetics research on severe mental illnessR01MH123157 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI FREIMER, NELSON B., LOPEZ JARAMILLO, CARLOS · 2020 to 2025
$10.6M
Genetics of Severe Mental IllnessR01MH113078 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BEARDEN, CARRIE E, FREIMER, NELSON B. · 2017 to 2021
$5.8M
Neurodevelopment and Psychosis in the 22q11.2 Copy Number VariantsR37MH085953 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CARRIE E BEARDEN · 2023 to 2026
$2.9M
Accelerating the Diagnosis of Bipolar Disorder Using Genetic and Phenotypic SignaturesR00MH116115 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI OLDE LOOHUIS, LOES MARLEIN · 2020 to 2022
$747k
Accelerating the diagnosis of bipolar disorder using genetic and phenotypic signaturesK99MH116115 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI OLDE LOOHUIS, LOES MARLEIN · 2018 to 2019
$257k
Fulbright-MincienciasNIMH NIH HHS K99 MH116115NIMH NIH HHS R00 MH116115NIMH NIH HHS R01 MH113078NIMH NIH HHS R01 MH123157NIMH NIH HHS R37 MH085953
6 · The paper itself

Abstract

objectivesMost bipolar disorder (BD) patients initially present with depressive symptoms, resulting in a delayed diagnosis of BD and poor clinical outcomes. This study aims to identify features predictive of the conversion from Major Depressive Disorder (MDD) to BD by leveraging electronic health record (EHR) data from the Clínica San Juan de Dios Manizales in Colombia.

methodsWe employed a multivariable Cox regression model to identify important predictors of conversion from MDD to BD.

resultsAnalyzing 15 years of EHR data from 13,607 patients diagnosed with MDD, a total of 1610 (11.8%) transitioned to BD. Predictive features of the conversion to BD included severity of the initial MDD episode, presence of psychosis and hospitalization at first episode, family history of BD, and female gender. Additionally, we observed associations with medication classes (positive associations with prescriptions of mood stabilizers, antipsychotics, and negative associations with antidepressants) and a positive association with suicidality, a feature derived from natural language processing (NLP) of clinical notes. Together, these risk factors predicted BD conversion within 5 years of the initial MDD diagnosis, with a recall of 72% and a precision of 38%.

conclusionsOur study confirms previously identified risk factors identified through registry-based studies (female gender and psychotic depression at the index MDD episode) and identifies novel ones (suicidality extracted from clinical notes). These results simultaneously demonstrate the validity of using EHR data for predicting BD conversion and underscore its potential for the identification of novel risk factors, thereby improving early diagnosis.

Indexed as

Bipolar DisorderElectronic Health RecordsMajor Depressive DisorderAdultAntidepressive AgentsColombiaDisease ProgressionFemaleHumansMaleMiddle AgedRisk FactorsYoung AdultAntidepressive Agentsbipolar disorderdiagnostic conversionEHRmajor depressive disorder

Identifiers

PMID39666719
PMCPMC11848012

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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 OpenQuestion graph.