Evidence map›Paper›PMID 39777048›Full record

ArticleFrontiers in aging neuroscience2024

Research on the application of functional near-infrared spectroscopy in differentiating subjective cognitive decline and mild cognitive impairment.

Zheng Wang, Chaojie Niu, Yong Duan, Hao Yang, Jinpeng Mi, Chao Liu, Guodong Chen, Qihao Guo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in aging neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
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

8 authors.

Zheng Wang *Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Chaojie Niu *Jiangsu Provincial Key Laboratory of Advanced Robotics, and Robotics and Microsystems Center, School of Mechanical and Electrical Engineering, Soochow University, Suzhou, China.
Yong Duan *Jiangsu Provincial Key Laboratory of Advanced Robotics, and Robotics and Microsystems Center, School of Mechanical and Electrical Engineering, Soochow University, Suzhou, China.
Hao YangSchool of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, China.
Jinpeng MiInstitute of Machine Intelligence (IMI), University of Shanghai for Science and Technology, Shanghai, China.
Chao LiuJiangsu Provincial Key Laboratory of Advanced Robotics, and Robotics and Microsystems Center, School of Mechanical and Electrical Engineering, Soochow University, Suzhou, China.
Guodong ChenJiangsu Provincial Key Laboratory of Advanced Robotics, and Robotics and Microsystems Center, School of Mechanical and Electrical Engineering, Soochow University, Suzhou, China.
Qihao GuoDepartment of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Alzheimer's disease (AD) is a common neurological disorder. Based on clinical characteristics, it can be categorized into normal cognition (NC), subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia (AD). Once the condition begins to progress, the process is usually irreversible. Therefore, early identification and intervention are crucial for patients. This study aims to explore the sensitivity of fNIRS in distinguishing between SCD and MCI. Methods: An in-depth analysis of the Functional Connectivity (FC) and oxygenated hemoglobin (HbO) characteristics during resting state and different memory cognitive tasks is conducted on two patient groups to search for potential biomarkers. The 33 participants were divided into two groups: SCD and MCI. Results: Functional connectivity strength during the resting state and hemodynamic changes during the execution of Verbal Fluency Tasks (VFT) and MemTrax tasks were measured using fNIRS. The results showed that compared to individuals with MCI, patients with SCD exhibited higher average FC levels between different channels in the frontal lobe during resting state, with two channels' FC demonstrating significant ability to distinguish between SCD and MCI. During the VFT task, the overall average HbO concentration in the frontal lobe of SCD patients was higher than that of MCI patients from 5 experimental paradigm. Receiver operating characteristic analysis indicated that the accuracy of the above features in distinguishing SCD from MCI was 78.8%, 72.7%, 75.8%, and 66.7%, respectively. Discussion: fNIRS could potentially serve as a non-invasive biomarker for the early detection of dementia.

Indexed as

Alzheimer’s diseaseearly diagnosisfunctional near-infrared spectroscopyMCISCD

Identifiers

PMID39777048
PMCPMC11703808

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.