Construction and Clinical Validation Study of a Prediction Model for Depression After Ischemic Stroke
Condition(s) studied
Investigational drug(s) / intervention(s)
Group patients based on whether they have been diagnosed with PSD.: Group patients based on whether they have been diagnosed with PSD.
Study summary
Post-stroke depression (PSD) is the most common neuropsychiatric disorder after a stroke, with an incidence rate of 20% to 60%. PSD is not only associated with higher mortality rates, poorer recovery, more obvious cognitive impairments, greater economic burdens, and lower quality of life, but also brings additional medical expenses and care pressure to families. Society also needs to bear higher medical costs. Currently, the early diagnosis of PSD is difficult, which may lead to poor prognosis after stroke. This study aims to utilize machine learning technology to integrate multi-dimensional indicators of patients with ischemic stroke, establish a risk prediction model for PSD, and assist in early, accurate, and individualized assessment of PSD risk in clinical practice.
Eligibility
Primary outcome measure(s)
- The number of post-stroke depression (PSD) that occurs 3 months after stroke — 3 months after stroke
Trial sites (1)
| Facility | City | Region | Status |
|---|---|---|---|
| The First Affiliated Hospital of Chongqing Medical University | Chongqing | China | Recruiting |
More Min Su trials in China
Other trials for the same condition
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
View NCT07294274 on ClinicalTrials.gov ↗ ← All trials in China