Evidence map›Paper›PMID 30708349›Full record

Trial reportNeuroImage. Clinical2019

Computerized cognitive training for Chinese mild cognitive impairment patients: A neuropsychological and fMRI study.

Bin-Yin Li, Na-Ying He, Yuan Qiao, Hong-Min Xu, Yi-Zhou Lu, Pei-Jing Cui, Hua-Wei Ling, Fu-Hua Yan, Hui-Dong Tang, Sheng-Di Chen

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in NeuroImage. Clinical, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 12 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 12 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

40 citing papers in PubMed, 12 syntheses or guidelines pooled it.

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  4. Digital Therapeutics in China: Comprehensive Review.Journal of medical Internet research · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Bin-Yin LiDepartment of Neurology & Institute of Neurology, Rui Jin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Na-Ying HeDepartment of Radiology, Rui Jin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Yuan QiaoDepartment of Neurology & Institute of Neurology, Rui Jin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Hong-Min XuDepartment of Radiology, Rui Jin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Yi-Zhou LuDepartment of Neurology & Institute of Neurology, Rui Jin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Pei-Jing CuiDepartment of Geriatrics, Rui Jin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Hua-Wei LingDepartment of Radiology, Rui Jin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Fu-Hua YanDepartment of Radiology, Rui Jin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China. Electronic address: yfh11655@rjh.com.cn.
Hui-Dong TangDepartment of Neurology & Institute of Neurology, Rui Jin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China. Electronic address: funground@163.com.
Sheng-Di ChenDepartment of Neurology & Institute of Neurology, Rui Jin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China. Electronic address: chensd@rjh.com.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComputerized multi-model training has been widely studied for its effect on delaying cognitive decline. In this study, we designed the first Chinese-version computer-based multi-model cognitive training for mild cognitive impairment (MCI) patients. Neuropsychological effects and neural activity changes assessed by functional MRI were both evaluated.

methodMCI patients in the training group were asked to take training 3-4 times per week for 6 months. Neuropsychological and resting-state fMRI assessment were performed at baseline and at 6 months. Patients in both groups were continuously followed up for another 12 months and assessed by neuropsychological tests again.

results78 patients in the training group and 63 patients in the control group accomplished 6-month follow-up. Training group improved 0.23 standard deviation (SD) of mini-mental state examination, while control group had 0.5 SD decline. Addenbrooke's cognitive examination-revised scores in attention (p = 0.002) and memory (p = 0.006), as well as stroop color-word test interference index (p = 0.038) and complex figure test-copy score (p = 0.035) were also in favor of the training effect. Difference between the changes of two groups after training was not statistically significant. The fMRI showed increased regional activity at bilateral temporal poles, insular cortices and hippocampus. However, difference between the changes of two groups after another 12 months was not statistically significant.

conclusionsMulti-model cognitive training help MCI patients to gained cognition benefit, especially in memory, attention and executive function. Functional neuroimaging provided consistent neural activation evidence. Nevertheless, after one-year follow up after last training, training effects were not significant. The study provided new evidence of beneficial effect of multi-model cognitive training.

Indexed as

AgedCerebral CortexChinaCognitive DysfunctionCognitive RemediationFemaleFollow-Up StudiesHumansMagnetic Resonance ImagingMaleMiddle AgedPilot ProjectsTherapy, Computer-AssistedTreatment OutcomeCognitive therapyMild cognitive impairmentNeuroimagingNeuropsychology

Identifiers

PMID30708349
PMCPMC6354286

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.