Evidence map›Paper›PMID 40904577›Full record

SynthesisFrontiers in psychiatry2025

Effect of nonpharmacologic therapies on depressive symptoms in patients with chronic fatigue syndrome: a network meta-analysis.

Baiyi Jiang, Mengru Cao, Xue Xia, Long Wang

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Baiyi JiangDepartment of Graduate School, Heilongjiang University of Chinese Medicine, Harbin, China.
Mengru CaoDepartment of Medicine IV, The Tumour Hospital of Harbin Medical University, Harbin, China.
Xue XiaDepartment of Graduate School, Heilongjiang University of Chinese Medicine, Harbin, China.
Long WangDepartment of Acupuncture and Moxibustion, The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Depression or depressive symptoms exacerbate the burden in patients with chronic fatigue syndrome (CFS). The therapeutic effects of various non-pharmacological interventions remain unclear. Objective: This paper aims to evaluate the effectiveness of different non-pharmacological measures in alleviating depression or depressive symptoms in patients with CFS through network meta-analysis. Methods: PubMed, Cochrane Library, Web of Science, Embase, CNKI, Wanfang, CBM, VIP, and Sinomed databases were searched for randomized controlled trials (RCTs) until March 26, 2025. The Cochrane Risk of Bias Assessment Tool 2.0 was utilized to appraise the risk of bias. A network meta-analysis was conducted using the GeMTC package in R (4.4.2). This protocol has been registered in PROSPERO (CRD420251020737). Results: 47 RCTs involving 4,028 participants were included. Compared with control measures, diet therapy was most effective in improving depression or depressive symptoms in patients with CFS (SMD = -5.64, 95% CI: -8.98 to -2.29), followed by moxibustion (Mox) (SMD = -2.91, 95% CI: -4.61 to -1.22), acupuncture (Ap) + Mox + acupoint embedding (SMD = -3.16, 95% CI: -0.39 to -5.98), and Ap + Mox (SMD = -2.53, 95% CI: -1.17 to -3.91). Conclusion: Diet therapy is the most effective in improving depression or depressive symptoms in patients with CFS, followed by Mox. Further carefully designed RCTs are warranted to substantiate these findings. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD420251020737.

Indexed as

chronic fatigue syndromedepressionnetwork meta-analysisnon-pharmacological therapysystematic review

Identifiers

PMID40904577
PMCPMC12401970

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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.