Longchun Hua
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Longchun Hua has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Jia Li
Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China
1 shared publication - Jianxun Cao
Nursing Department, Gansu Provincial Hospital, Lanzhou, China
1 shared publication - Wenyuan Li
School of Nursing, Evidence-Based Nursing Center, Lanzhou University, Lanzhou 730011, China
1 shared publication - Xiaoqin Wei
Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
1 shared publication - Ying Zhu
School of Nursing, Evidence-Based Nursing Center, Lanzhou University, Lanzhou 730011, China; North Sichuan College of Preschool Teacher Education, Sichuan, China
1 shared publication - Yu Zhu
Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China
1 shared publication
Latest Publications
- Top Cited Papers
- 18 May 2025
- Published by Springer Nature in Journal of Neurology
- Vol. 272 (6) , 1-9
MoCA and MMSE for the detection of post-stroke cognitive impairment: a comparative diagnostic test accuracy systematic review and meta‑analysis
Background and purpose Post-stroke cognitive impairment (PSCI) is one of the serious complications of stroke, which profoundly influences the quality of life of stroke survivors. The Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) are the two cognitive screening tools most widely used in stroke settings. Previous studies investigated the diagnostic accuracy of MoCA and MMSE but yielded controversial results. We conducted this study to compare the diagnostic accuracy of MoCA with MMSE for PSCI. Methods Embase, PubMed, CINAHL, Web of Science, and The Cochrane Library were searched until August 17, 2024 for diagnostic accuracy studies comparing MoCA and MMSE. Data extraction was performed by two independent researchers. Risk of bias and applicability assessment was evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Coupled forest plots and hierarchical summary receiver operating characteristic (hsROC) curves were created in R statistical software. Results 9 studies with 1,135 patients were included in this review. Most studies were at high risk of bias. MoCA displayed a pooled sensitivity of 0.80 (95% CI 0.72 to 0.86) and specificity of 0.79 (95% CI 0.71 to 0.85). MMSE displayed a sensitivity and specificity of 0.76 (95% CI 0.71 to 0.81) and 0.78 (95% CI 0.73 to 0.83), respectively. No difference was shown between these modalities (SEN p = 0.36, SPE p = 0.80). Conclusion No difference was observed between MoCA and MMSE in the detection of PSCI. We recommend both screeners be considered for the detection of PSCI based on the purpose of the test and by other metrics, such as acceptability and feasibility. Although it should be noted MoCA and MMSE were cognitive screening tools in stroke settings and not a substitute for detailed clinical assessment.
- 18 May 2025
- Published by Springer Nature in Journal of Neurology
- Vol. 272 (6) , 1-9
Top Cited PapersMoCA and MMSE for the detection of post-stroke cognitive impairment: a comparative diagnostic test accuracy systematic review and meta‑analysis
Background and purpose Post-stroke cognitive impairment (PSCI) is one of the serious complications of stroke, which profoundly influences the quality of life of stroke survivors. The Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) are the two cognitive screening tools most widely used in stroke settings. Previous studies investigated the diagnostic accuracy of MoCA and MMSE but yielded controversial results. We conducted this study to compare the diagnostic accuracy of MoCA with MMSE for PSCI. Methods Embase, PubMed, CINAHL, Web of Science, and The Cochrane Library were searched until August 17, 2024 for diagnostic accuracy studies comparing MoCA and MMSE. Data extraction was performed by two independent researchers. Risk of bias and applicability assessment was evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Coupled forest plots and hierarchical summary receiver operating characteristic (hsROC) curves were created in R statistical software. Results 9 studies with 1,135 patients were included in this review. Most studies were at high risk of bias. MoCA displayed a pooled sensitivity of 0.80 (95% CI 0.72 to 0.86) and specificity of 0.79 (95% CI 0.71 to 0.85). MMSE displayed a sensitivity and specificity of 0.76 (95% CI 0.71 to 0.81) and 0.78 (95% CI 0.73 to 0.83), respectively. No difference was shown between these modalities (SEN p = 0.36, SPE p = 0.80). Conclusion No difference was observed between MoCA and MMSE in the detection of PSCI. We recommend both screeners be considered for the detection of PSCI based on the purpose of the test and by other metrics, such as acceptability and feasibility. Although it should be noted MoCA and MMSE were cognitive screening tools in stroke settings and not a substitute for detailed clinical assessment.