Development and Validation of the Prediction Model for Cognitive Impairment

Shenzhen University

Status: Not yet enrolling

Conditions: Stroke, Acute

Study type: Observational

Funder types: Other

Identifiers

NCT05465980

20223357018

Details and patient eligibility

About

According to the "Chinese Stroke Report" released in 2020, the incidence of stroke in China is 1114.8/100,000, acute ischemic stroke (AIS) accounts for 70% to 80% of the total number of stroke population, and elderly stroke patients are up to 2/3. About 1/3 of stroke patients would experience post-stroke cognitive impairment (PSCI), which seriously affected patients' quality of life and survival time, and increases disease and economic burden. Therefore, early identification, assessment, prevention and intervention of PSCI, and improvement of patients' quality of life and prognosis have become the focus of clinical research.

This is a prospective cohort study. We intend to: (1) continuously collect elderly AIS patients who will be admitted to the Department of Neurology, The Department of Rehabilitation and the Department of Gerontology of Shenzhen Second People's Hospital from 2022 year to 2024 year; (2) collect baseline and follow-up data, and build a prediction model for cognitive impairment in elderly AIS patients; (3) internal validation using Bootstrap model; (4) collect the data of the elderly AIS patients who will be admitted to Shenzhen Longhua District People's Hospital andShenzhen Longgang Central Hospital, and conduct external validation; (5) evaluate the predictive efficacy of the model.

Full description

This study consists of two parts. The first part is to develop a predictive model for cognitive impairment in elderly patients with acute ischemic stroke. Continuously collect the baseline data and follow-up data of elderly AIS patients admitted to the Shenzhen Second People's Hospital from September 2022 to December 2023, including general demographic data, laboratory examination indicators, imaging indicators and assessment scales. Take the occurrence of PSCI as the dependent variable and the risk factors of PSCI in elderly AIS patients will be analyzed. Multivariate Cox regression will be used to develop a prediction model for cognitive impairment in elderly AIS patients.

The second part is to do clinical evaluation of prediction model of cognitive impairment in elderly patients with acute ischemic stroke. Bootstrap method will be used for internal validation of the model. Continuously collect the data of elderly AIS patients from January 2024 to December 2024 from the other two hospitals in Guangdong Province, China. Externally validate the model and evaluate the clinical application effect of PSCI prediction model in elderly AIS patients using C-index, reclassification index, calibration curve, time-dependent ROC curve and other indicators. Finally, the model is presented by nomogram.

Enrollment: 496 estimated patients

Sex: All

Ages: 60+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. Patients age 60 years or older.
2. Stroke occurring within 7 days.
3. Meet the diagnostic criteria of Chinese Guidelines for the Diagnosis and Treatment of Acute ischemic Stroke 2018.
4. Informed consent.

Exclusion criteria

1. Incomplete main clinical data;
2. Patients with transient ischemic attack;
3. Patients had cognitive dysfunction before enrollment.