Predicting the course of depression is necessary for personalized treatment. Impaired glucose metabolism (IGM) was introduced as a promising depression biomarker, but no consensus was made. This study aimed to predict IGM at the time of depression diagnosis and examine the relationship between long-term prognosis and predicted results.

Clinical data were extracted from four electronic health records in South Korea. The study population included patients with depression, and the outcome was IGM within 1 year. One database was used to develop the model using three algorithms. External validation was performed using the best algorithm across the three databases. The area under the curve (AUC) was calculated to determine the model’s performance. Kaplan–Meier and Cox survival analyses of the risk of hospitalization for depression as the long-term outcome were performed. A meta-analysis of the long-term outcome was performed across the four databases.

A prediction model was developed using the data of 3,668 people, with an AUC of 0.781 with least absolute shrinkage and selection operator (LASSO) logistic regression. In the external validation, the AUCs were 0.643, 0.610, and 0.515. Through the predicted results, survival analysis and meta-analysis were performed; the hazard ratios of risk of hospitalization for depression in patients predicted to have IGM was 1.20 (95% confidence interval [CI] 1.02–1.41, p = 0.027) at a 3-year follow-up.

We developed prediction models for IGM occurrence within a year. The predicted results were related to the long-term prognosis of depression, presenting as a promising IGM biomarker related to the prognosis of depression.

We aimed to assess cancer risk in congenital heart defect patients, with and without Down's syndrome, compared with the general population.

We identified all patients born and diagnosed with congenital heart defects from 1977 to 2008 using the Danish National Registry of Patients, covering all Danish hospitals. We compared cancer incidence in the congenital heart defect cohort with that expected in the general population (∼5.5 million) using the Danish Cancer Registry, and computed age- and gender-standardised incidence ratios.

We identified 15,905 congenital heart defect patients, contributing a total of 151,172 person-years at risk; the maximum length of follow-up was 31 years (median 8 years). In all, 53 patients were diagnosed with cancer, including 30 female and 23 male patients (standardised incidence ratio = 1.63; 95% confidence interval: 1.22–2.13). Risks were increased for leukaemia, brain tumours, and basal cell carcinoma. After excluding 801 patients with Down's syndrome, the standardised incidence ratio was 1.19 (95% confidence interval: 0.84–1.64). In the subgroup of 5660 non-Down's syndrome patients undergoing cardiac surgery or catheter-based interventions, the standardised incidence ratio was 1.45 (95% confidence interval: 0.86–2.29).

The overall risk of cancer among congenital heart defect patients without Down's syndrome was not statistically significantly elevated. Cancer risk in the congenital heart defect cohort as a whole, including patients with Down's syndrome, was increased compared with the general population, although the absolute risk was low. Studies with longer follow-up and more information on radiation doses are needed to further examine a potential cancer risk associated with diagnostic radiation exposure.