Coronary artery bypass grafting (CABG) remains one of the most commonly performed cardiac surgeries worldwide. Despite surgical advancements, a significant proportion of patients experience psychological distress following surgery, with depression being particularly common. Current evidence regarding the effectiveness of preoperative psychological interventions in improving postoperative mental health outcomes remains inconclusive. There is a critical need for predictive models that can identify patients at risk of developing clinically significant depressive symptoms (CSDSs) and related psychological conditions after CABG. This multicentre observational study aims to develop and validate prognostic models for predicting CSDSs and other psychological outcomes, including anxiety, post-traumatic stress symptoms and quality of life, 6 weeks after elective CABG surgery.

The study will recruit 300 adult patients undergoing elective CABG (with or without valve intervention) across two Swiss hospitals. Data collected will include demographic, clinical, psychometric, inflammation-related and interoceptive variables. A training set (n=200) will be used to develop predictive models using machine learning, while a held-out test set (n=100) will be used for model validation. The primary outcome prediction will focus on CSDSs, assessed using the Patient Health Questionnaire-9 (PHQ-9), with analyses conducted both categorically (PHQ-9 total score ≥10) and continuously as complementary approaches. Secondary models will address anxiety, using the General Anxiety Disorder Scale-7, post-traumatic stress, using the post-traumatic stress disorder checklist for Diagnostic and Statistical Manual of Mental Disorders-5 and health-related quality of life, using the 12-item Short Form Survey. A simplified ‘light solution’ model with fewer predictors will also be developed for broader applicability. This study will address an important gap in perioperative mental healthcare by identifying key predictors of psychological morbidity following CABG, particularly CSDSs. The resulting models may inform future screening and preventive strategies and improve postsurgical outcomes through early identification and intervention in high-risk individuals.

The responsible ethics committee has reviewed and approved this project (Kantonale Ethikkommission Zürich, BASEC number: 2023-02040). The study minimises participant burden by integrating brief validated instruments and limiting psychiatric interviews to relevant outcomes, while ensuring ethical safeguards and respect for participant rights (including written consent). Results will be shared through peer-reviewed publications, conference presentations and stakeholder meetings involving clinicians and mental health professionals. Findings will also be communicated to participating centres and patient communities in accessible formats.

To assess the effects of age, birth cohort, and period on comorbidity rates as well as project their future trends over the next 25 years.

Population-based retrospective observational study.

Record linkage from the population-based healthcare utilisation database of Lombardy, Italy, between 2004 and 2023.

All beneficiaries of the Italian National Health Service (NHS) aged 50–85 years residing in Lombardy. Data were separately analysed for each year from 2004 to 2023, with thus the availability of 20 study populations.

Comorbidities were traced via the medical services provided by the NHS, and the overall quantification was obtained by the Multisource Comorbidity Score, which was developed and validated for the Italian population. The temporal analysis of the 20 yearly temporal comorbidity rates was obtained by the Age-Cohort-Period models. The comorbidities prevalence trends were forecasted from 2025 to 2050.

From 2004 to 2023, the prevalence of comorbidities declined from 46% to 40% in men and from 47% to 42% in women. An increase in prevalence between the ages of 50 and 85 years was observed for both women (from 33% to 63%) and men (from 29% to 67%). A declining prevalence was observed among cohorts born from 1922 to 1970 for both women (by 33%) and men (by 50%). A continued decline in the absolute number and prevalence rate of comorbidities is expected for both women and men until 2050.

The decline in ageing-related comorbidity prevalence over time may persist up to 2050. Improved medical care and public health initiatives benefiting individuals born in more recent years may counterbalance the expected trend of increasing comorbidity prevalence due to population ageing.