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.

Quality of life (QoL) is an important health measure and is widely used to assess the difference between treatments for Type 1 Diabetes Mellitus (T1DM) since the desirable glycemic control and the minimization of episodes of hypoglycemia are fundamental aspects for a better QoL. This study aims to identify the factors associated with QoL in patients with T1DM.

A cross-sectional study (approved by ethics committee) was carried out in the state of Minas Gerais with 401 T1DM patients who used insulin glargine (GLA) selected in March 2017, and 179 patients who used insulin-neutral protamine (NPH) selected between January and February 2014, and both groups were treated by Brazilian National Health System (SUS). A questionnaire with three blocks was used: A) sociodemographic data; B) clinical data and access to the service; and C) QoL by Euroqol (EQ-5D-3L). We used multiple linear regression model by the forward stepwise method to access the correlation between the utilities of the EQ-5D-3L and all the explanatory variables (blocks A and B). We adopted the significance level and confidence interval of 95 percent (95% CI).

Of the 580 patients evaluated, 54 percent were women, 47 percent were in the age group between 18–40 years, 53 percent reported to be non-black. The EQ-5D-3L analysis showed patients treated with insulin analogue GLA had an average utility of 0.849 and those treated with NPH insulin 0.722 (p < 0.000). Individuals young, very good/good health self-perception, having not been bedridden in the last 15 days, zero to three medical appointments in the last year, no hospitalization in the last year, regular physical activity in the last 15 days to practice physical exercise, having between zero and three comorbidities and no severe hypoglycemia in the last 30 days were explained 41.3 percent of QoL. The type of insulin therapy, GLA or NPH, did not enter into the final multiple regression model.

The findings of this study pointed to a lack of correlation between insulin therapy and QoL of patients with T1DM. Sociodemographic and clinical factors were more important to explain the QoL of diabetics. In addition, the evidence pointed to the importance of episodes of hypoglycemia for Qol. Of the 191 episodes of hypoglycemia (non-severe and severe) reported, 66 percent were from patients treated with GLA.