Evidence map›Paper›PMID 36658505›Full record

Observational studyBMC psychiatry2023

Prognostic prediction of subjective cognitive decline in major depressive disorder based on immune biomarkers: a prospective observational study.

Meiti Wang, Zheyi Wei, Qinte Huang, Weijie Yang, Chenglin Wu, Tongdan Cao, Jie Zhao, Dongbin Lyu, Fan Wang, Ni Zhou and 7 more

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 27% of its field
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, 11 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  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

17 authors at 3 institutions in 1 country.

Meiti Wang *Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Zheyi Wei *Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Qinte HuangShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Weijie YangShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Chenglin WuShanghai Pudong New Area Mental Health Center, School of Medicine, Tongji University, Shanghai, 200120, China.
Tongdan CaoShanghai Huangpu District Mental Health Center, Shanghai, 200040, China.
Jie ZhaoShanghai Huangpu District Mental Health Center, Shanghai, 200040, China.
Dongbin LyuShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Fan WangShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Ni ZhouShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Haijing HuangShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Mengke ZhangShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Yiming ChenShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Yi XuShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Weiliang MaShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Zheng ChenShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Wu HongShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China. drhongwu@126.com.
Shanghai Mental Health Center · CNShanghai Jiao Tong University · CNTongji University · CN

Funding

National Key Research and Development Program of China 2016YFC0906300National Natural Science Foundation of China 81701344Shanghai Mental Health Center General Projects 2021-YJ-02Shanghai Municipal Health Bureau 201740115Shanghai "Science and Technology Innovation Action Plan" medical innovation research 21Y11905600Shanghai "Science and Technology Innovation Action Plan" Natural Science Foundation of Shanghai 21ZR1455100
6 · The paper itself

Abstract

objectiveSubjective cognitive decline (SCD) is highlighted in patients with major depressive disorder (MDD), which impairs objective cognitive performance and worsens the clinical outcomes. Immune dysregulation is supposed to be the potential mechanism of cognitive impairment. However, the peripheral immune biomarkers in patients troubled with MDD and SCD are not conventionally described.

methodsA prospective-observational study was conducted for 8 weeks. Subjective cognitive function was measured using the Chinese version of the 20-item perceived deficits questionnaire-depression (PDQ-D) and depression symptoms were evaluated with Hamilton Depression Rating Scale-17 (HDRS-17). Luminex assays were used to measure 48 immune cytokines in plasma at baseline. Integrating these results and clinicopathological features, a logistic regression model was used to develop a prognostic prediction.

resultsTotally, 114 patients were enrolled in this study. Among the patients who completed follow-up, 56% (N = 50) had residual subjective cognitive decline, and 44% (N = 50) did not. The plasma levels of FGF basic, INF-γ, IL-1β, MCP-1, M-CSF and SCF were increased and the levels of IL-9, RANTES and PDGF-BB were decreased in the SCD group. Additionally, Basic FGF, IFN-γ, IL-1β, and SCF were positively correlated and IL-9, RANTES, and PDGF-BB were negatively correlated with the PDQ-D scores after treatment. Notably, combinations of cytokines (SCF and PDGF-BB) and PDQ-D scores at baseline showed good performance (The area under the receiver operating characteristic curve = 0.818) in the prediction of subjective cognitive decline.

conclusionA prognostic model based on protein concentrations of SCF, PDGF-BB, and scores of PDQ-D showed considerable accuracy in predicting residual subjective cognitive decline in depression.

Indexed as

Cognitive DysfunctionMajor Depressive DisorderBecaplerminBiomarkersCytokinesHumansInterleukin-9PrognosisProspective StudiesBecaplerminBiomarkersCytokinesInterleukin-9Immune biomarkersMajor depressive disorderPredictive modelSubjective cognitive decline

Identifiers

PMID36658505
PMCPMC9850523
OpenAlexW4317435785

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.