Evidence map›Paper›PMID 42662816›Full record

ArticleInternational journal of endocrinology2026

Efficacy of Appropriate Techniques of Traditional Chinese Medicine and Physical Therapy in Patients With Insulin-Associated Lipohypertrophy: A Systematic Review and Meta-Analysis.

Liqing Jiang, Honglian Fang, Xumei Tao, Liping Wang

Abstract read
In one paragraph

Article in International journal of endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Liqing JiangDepartment of Gerontology, The Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing, China, njmu.edu.cn.ORCID https://orcid.org/0000-0001-8424-5248
Honglian FangDepartment of Gerontology, The Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing, China, njmu.edu.cn.
Xumei TaoDepartment of Gerontology, The Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing, China, njmu.edu.cn.
Liping WangDepartment of Gerontology, The Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing, China, njmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: The study aimed to investigate the effectiveness of Traditional Chinese Medicine (TCM) and physical therapy on the lipohypertrophy (LH) people by conducting meta-analyses of randomized controlled trials (RCTs). Methods: We performed a literature search on China Knowledge Network Infrastructure (CNKI), Wanfang Data, VIP.com, PubMed, Web of Science, Cochrane Library, and ClinicalTrials.gov in June 30, 2024, for RCTs. Standardized mean difference (SMD) or odds ratio (OR) with 95% confidence intervals (CIs) was calculated. Subgroup analyses, sensitivity analyses, and publication bias analyses were also conducted. Results: A total of 31 RCTs involving 3496 participants with LH were included in this analysis. Meta-analyses revealed that appropriate TCM interventions significantly improved the curative effect in individuals with LH (OR = 5.52; 95% CI: 3.98-7.65; Conclusion: The present meta-analysis suggests that appropriate technology of TCM intervention was effective in improving the curative effect, HbA1c level, FBG, and 2hPG. Physical therapy may be effective for the treatment of LH. However, the quality of the included RCTs for appropriate technology of TCM is low to moderate and the number of RCTs for physical therapy is limited.

Indexed as

HbA1clipohypertrophymeta-analysisphysical therapyTraditional Chinese Medicine

Identifiers

PMID42662816
PMCPMC13520793

What OpenQuestion holds

Textmetadata
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.