Construction and Clinical Validation Study of a Prediction Model for Depression After Ischemic Stroke

Recruiting now

Conditions studied: Post-stroke Depression

In brief

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.

Key facts

Study ID

NCT07294274

Run by

Min Su

People needed

488

Starts

2025-11-01

Expected to finish

2026-07-20

Last updated by the study team

2026-02-05

Who can join

Age: any. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Patients with acute ischemic stroke;
• Admission within 7 days of symptom onset;
• The patient and/or the family members sign a written informed consent form.

You may not qualify if…

• Confusion of consciousness,severe cognitive impairment, etc
• Individuals with a history of depression, schizophrenia, bipolar disorder, etc;
• Individuals unable to participate in neuropsychological examinations due to hearing im pairments, lack of coordination, or neurological deficits, including se vere aphasia.

Where it is running

• The First Affiliated Hospital of Chongqing Medical University — Chongqing, China (enrolling)

Full record on ClinicalTrials.gov

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