Clinical Trial Details
— Status: Not yet recruiting
Administrative data
| NCT number |
NCT05465980 |
| Other study ID # |
20223357018 |
| Secondary ID |
|
| Status |
Not yet recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
September 1, 2022 |
| Est. completion date |
September 30, 2024 |
Study information
| Verified date |
June 2022 |
| Source |
Shenzhen Second People's Hospital |
| Contact |
Xiaohua Xie, master |
| Phone |
+86 13560779836 |
| Email |
13560779836[@]163.com |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
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.
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.
