Evidence map›Paper›PMID 33635741›Full record

ArticleThe British journal of radiology2021

Imaging features and atypical signs of symptomatic vertebral haemangioma: a retrospective single-centre analysis of 118 patients.

Lihua Zhang, Ben Wang, Songbo Han, Shaomin Yang, Liang Jiang, Huishu Yuan, Zhongjun Liu

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The British journal of radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

7 authors at 2 institutions in 1 country.

Lihua ZhangDepartments of Radiology, Peking University Third Hospital, Beijing, China.
Ben WangDepartments of Orthopaedics, Peking University Third Hospital, Beijing, China.
Songbo HanDepartments of Radiology, Peking University Third Hospital, Beijing, China.
Shaomin YangDepartments of Pathology, Peking University Third Hospital, Beijing, China.
Liang JiangDepartments of Orthopaedics, Peking University Third Hospital, Beijing, China.
Huishu YuanDepartments of Radiology, Peking University Third Hospital, Beijing, China.
Zhongjun LiuDepartments of Orthopaedics, Peking University Third Hospital, Beijing, China.
Peking University · CNPeking University Third Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesSymptomatic vertebral haemangioma (SVH) can present with atypical imaging features. Thus, this study analysed the imaging features of SVH using CT and MRI to improve SVH awareness.

methodsWe retrospectively analysed CT and MRI characteristics of 118 patients with clinically and pathologically confirmed SVH.

resultsOverall, 118 patients were diagnosed with SVH, including 79 females and 39 males (mean age, 45.76 ± 16.36 years). The thoracic spine (

conclusionSVH was predominantly located in the thoracic spine. Involvement of multiple segments, posterior attachment localisation, absence of honeycomb or polka-dot signs, compression fracture, and atypical ADVANCES IN KNOWLEDGE: The imaging features of SVHs are not fully understood. We examined the largest series of SVH cases reported to date.

Indexed as

AdolescentAdultAgedCervical VertebraeChildDiagnosis, DifferentialDiagnostic ErrorsFemaleFractures, CompressionHemangiomaHumansLumbar VertebraeMagnetic Resonance ImagingMaleMiddle AgedMultidetector Computed Tomography

Identifiers

PMID33635741
PMCPMC8506172
OpenAlexW3130281629

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.