Evidence map›Paper›PMID 38167939›Full record

ArticleScientific reports2024

Classification and prognostic factors of patients with cervical spondylotic myelopathy after surgical treatment: a cluster analysis.

Xiao Fan, Rui Chen, Haoge Huang, Gangqiang Zhang, Shuai Zhou, Xin Chen, Yanbin Zhao, Yinze Diao, Shengfa Pan, Fengshan Zhang and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. A Study on Prognostic Risk Factors of Cervical Spondylotic Myelopathy.Journal of Korean Neurosurgical Society · 2025
    Article
  5. Review
  6. 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

12 authors.

Xiao Fan *Department of Orthopaedics, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Rui Chen *Department of Orthopaedics, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Haoge HuangDepartment of Orthopaedics, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Gangqiang ZhangDepartment of Orthopaedics, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Shuai ZhouDepartment of Orthopaedics, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Xin ChenDepartment of Orthopaedics, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Yanbin ZhaoDepartment of Orthopaedics, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Yinze DiaoDepartment of Orthopaedics, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Shengfa PanDepartment of Orthopaedics, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Fengshan ZhangDepartment of Orthopaedics, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Yu SunDepartment of Orthopaedics, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Feifei ZhouDepartment of Orthopaedics, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China. orthozhou@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying potential prognostic factors of CSM patients could improve doctors' clinical decision-making ability. The study retrospectively collected the baseline data of population characteristics, clinical symptoms, physical examination, neurological function and quality of life scores of patients with CSM based on the clinical big data research platform. The modified Japanese Orthopedic Association (mJOA) score and SF-36 score from the short-term follow-up data were entered into the cluster analysis to characterize postoperative residual symptoms and quality of life. Four clusters were yielded representing different patterns of residual symptoms and quality of patients' life. Patients in cluster 2 (mJOA RR 55.8%) and cluster 4 (mJOA RR 55.8%) were substantially improved and had better quality of life. The influencing factors for the better prognosis of patients in cluster 2 were young age (50.1 ± 11.8), low incidence of disabling claudication (5.0%) and pathological signs (63.0%), and good preoperative SF36-physiological function score (73.1 ± 24.0) and mJOA socre (13.7 ± 2.8); and in cluster 4 the main influencing factor was low incidence of neck and shoulder pain (11.7%). We preliminarily verified the reliability of the clustering results with the long-term follow-up data and identified the preoperative features that were helpful to predict the prognosis of the patients. This study provided reference and research basis for further study with a larger sample data, extracting more patient features, selecting more follow-up nodes, and improving clustering algorithm.

Indexed as

Spinal Cord DiseasesSpondylosisCervical VertebraeCluster AnalysisHumansPrognosisProspective StudiesQuality of LifeReproducibility of ResultsRetrospective StudiesTreatment Outcome

Identifiers

PMID38167939
PMCPMC10762243

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