- ICH GCP
- 미국 임상 시험 레지스트리
- 임상시험 NCT05465980
Development and Validation of the Prediction Model for Cognitive Impairment
Development and Validation of the Prediction Model for Cognitive Impairment in Elderly Patients After Acute Ischemic Stroke
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.
연구 개요
상태
정황
상세 설명
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.
연구 유형
등록 (예상)
연락처 및 위치
연구 연락처
- 이름: Xiaohua Xie, master
- 전화번호: +86 13560779836
- 이메일: 13560779836@163.com
연구 연락처 백업
- 이름: Simin Cao, master
- 전화번호: 15625063093
- 이메일: Symina_2021@163.com
참여기준
자격 기준
공부할 수 있는 나이
건강한 자원 봉사자를 받아들입니다
연구 대상 성별
샘플링 방법
연구 인구
설명
Inclusion Criteria:
- Patients age 60 years or older.
- Stroke occurring within 7 days.
- Meet the diagnostic criteria of Chinese Guidelines for the Diagnosis and Treatment of Acute ischemic Stroke 2018.
- Informed consent.
Exclusion Criteria:
- Incomplete main clinical data;
- Patients with transient ischemic attack;
- Patients had cognitive dysfunction before enrollment.
공부 계획
연구는 어떻게 설계됩니까?
디자인 세부사항
연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
|
MMSE score
기간: From July 1, 2022 to May 31, 2025
|
The primary outcome will be assessed by the Mini-mental State Examination(MMSE) scale
|
From July 1, 2022 to May 31, 2025
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공동 작업자 및 조사자
수사관
- 수석 연구원: Xiaohua Xie, master, Shenzhen Second People's Hospital
연구 기록 날짜
연구 주요 날짜
연구 시작 (예상)
기본 완료 (예상)
연구 완료 (예상)
연구 등록 날짜
최초 제출
QC 기준을 충족하는 최초 제출
처음 게시됨 (실제)
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
QC 기준을 충족하는 마지막 업데이트 제출
마지막으로 확인됨
추가 정보
이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .