Evidence map›Paper›PMID 39239257›Full record

ArticleFrontiers in bioengineering and biotechnology2024

Lumbar osteopathic manipulative treatment can improve KOA symptoms: short-term efficacy observation and mechanism analysis.

Peiyu Du, Xi Li, Shilin Yin, Wenyi Li, Xilong Sun, Zekun Zhang, Jianyong Zhao, Gao Shijun, Shuangqing Du, Di Zhang

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

10 authors.

Peiyu Du *Spine Surgery Department, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Xi Li *Orthopedics Department, The First Hospital of Hebei Chinese Medicine University, Shijiazhuang, China.
Shilin YinOrthopedics Department, The First Hospital of Hebei Chinese Medicine University, Shijiazhuang, China.
Wenyi LiSpine Surgery Department, Hebei Provincial People's Hospital, Shijiazhuang, China.
Xilong SunSpine Surgery Department, Hebei Provincial People's Hospital, Shijiazhuang, China.
Zekun ZhangImaging Department, The First Hospital of Hebei Chinese Medicine University, Shijiazhuang, China.
Jianyong ZhaoSpine Surgery Department, Cangzhou Integrated Chinese and Western Medicine Hospital, Cangzhou, China.
Gao ShijunJoint Surgery Department, The Third Hospital of Hebei Medical University, Shijiazhuang, China.
Shuangqing DuOrthopedics Department, The First Hospital of Hebei Chinese Medicine University, Shijiazhuang, China.
Di ZhangSpine Surgery Department, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Manipulative treatment can effectively improve knee pain and function, but no previous studies have shown that lumbar osteopathic manipulative treatment can improve knee symptoms. To explore the influence of lumbar manipulation on KOA and analyze its principlerelationship between coronal position of lumbar spine and KOA. Methods: Patients were divided into OMT group and DT group according to treatment. WOMAC scores were compared between the two groups, and X-ray examinations before and after treatment were performed in OMT group to analyze the imaging changes. Results: Both OMT group and DT group showed significant improvement in WOMAC score after treatment, and the improvement in OMT group was better than that in DT group. After OMT treatment, cTMI( Conclusion: Compared with drug therapy, lumbar manipulation can better improve WOMAC scores in KOA patients. It relives symptoms by loosening muscles and correcting small joint disorders to improve local knee alignment.

Indexed as

knee osteoarthritismanual therapymechanism analysisosteopathic manipulative treatmentspine-pelvis-lower limbs

Identifiers

PMID39239257
PMCPMC11374657

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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.