De la Hoz Juan F, Arias Alejandro, Service Susan K, Castaño Mauricio, Díaz-Zuluaga Ana M, Song Janet, Gallego Cristian, Ruiz-Sánchez Sergio, Escobar Javier I, Bui Alex A T, Bearden Carrie E, Reus Victor, López-Jaramillo Carlos, Freimer Nelson B, Olde Loohuis Loes M
Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Department of Mental Health and Human Behavior, University of Caldas, Manizales, Colombia.
Br J Psychiatry. 2025 Jun 23:1-8. doi: 10.1192/bjp.2025.107.
Electronic health records (EHRs), increasingly available in low- and middle-income countries (LMICs), provide an opportunity to study transdiagnostic features of serious mental illness (SMI) and its trajectories.
Characterise transdiagnostic features and diagnostic trajectories of SMI using an EHR database in an LMIC institution.
We conducted a retrospective cohort study using EHRs from 2005-2022 at Clínica San Juan de Dios Manizales, a specialised mental health facility in Colombia, including 22 447 patients with schizophrenia (SCZ), bipolar disorder (BPD) or severe/recurrent major depressive disorder (MDD). Using diagnostic codes and clinical notes, we analysed the frequency of suicidality and psychosis across diagnoses, patterns of diagnostic switching and the accumulation of comorbidities. Mixed-effect logistic regression was used to identify factors influencing diagnostic stability.
High frequencies of suicidality and psychosis were observed across diagnoses of SCZ, BPD and MDD. Most patients (64%) received multiple diagnoses over time, including switches between primary SMI diagnoses (19%), diagnostic comorbidities (30%) or both (15%). Predictors of diagnostic switching included mentions of delusions (odds ratio = 1.47, 95% CI 1.34-1.61), prior diagnostic switching (odds ratio = 4.01, 95% CI 3.7-4.34) and time in treatment, independent of age (log of visit number; odds ratio = 0.57, 95% CI 0.54-0.61). Over 80% of patients reached diagnostic stability within 6 years of their first record.
Integrating structured and unstructured EHR data reveals transdiagnostic patterns in SMI and predictors of disease trajectories, highlighting the potential of EHR-based tools for research and precision psychiatry in LMICs.
电子健康记录（EHRs）在低收入和中等收入国家（LMICs）越来越普及，为研究严重精神疾病（SMI）的跨诊断特征及其病程提供了机会。
利用LMIC机构的EHR数据库，描述SMI的跨诊断特征和诊断病程。
我们在哥伦比亚马尼萨莱斯的一家专业心理健康机构圣胡安·迪奥斯诊所进行了一项回顾性队列研究，使用了2005年至2022年的EHRs，纳入了22447例精神分裂症（SCZ）、双相情感障碍（BPD）或重度/复发性重度抑郁症（MDD）患者。通过诊断编码和临床记录，我们分析了自杀倾向和精神病在不同诊断中的发生率、诊断转换模式以及共病的累积情况。采用混合效应逻辑回归来确定影响诊断稳定性的因素。
在SCZ、BPD和MDD的诊断中均观察到较高的自杀倾向和精神病发生率。大多数患者（64%）随着时间推移接受了多种诊断，包括主要SMI诊断之间的转换（19%）、诊断共病（30%）或两者兼有（15%）。诊断转换的预测因素包括妄想的提及（优势比 = 1.47，95%置信区间1.34 - 1.61）、先前的诊断转换（优势比 = 4.01，95%置信区间3.7 - 4.34）以及治疗时间，与年龄无关（就诊次数的对数；优势比 = 0.57，95%置信区间0.54 - 0.61）。超过80%的患者在首次记录后的6年内达到诊断稳定。
整合结构化和非结构化的EHR数据揭示了SMI的跨诊断模式和疾病病程的预测因素，凸显了基于EHR的工具在LMICs研究和精准精神病学中的潜力。
