Evidence map›Paper›PMID 40046928›Full record

ArticleFrontiers in medicine2025

Clinical characteristics and surgical treatment comparison of multisegmental spinal tuberculosis: a retrospective analysis.

Zongqiang Yang, Zhangui Gu, Qiang Liu, Long Ma, Le Fei, Ningkui Niu, Jiandang Shi

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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.

Zongqiang Yang *Department of Orthopedic, General Hospital of Ningxia Medical University, Yinchuan, China.
Zhangui Gu *Department of Orthopedic, General Hospital of Ningxia Medical University, Yinchuan, China.
Qiang Liu *Department of Orthopedic, General Hospital of Ningxia Medical University, Yinchuan, China.
Long MaFirst Clinical Medical College, Ningxia Medical University, Yinchuan, China.
Le FeiDepartment of Orthopedic, General Hospital of Ningxia Medical University, Yinchuan, China.
Ningkui NiuDepartment of Orthopedic, General Hospital of Ningxia Medical University, Yinchuan, China.
Jiandang ShiDepartment of Orthopedic, General Hospital of Ningxia Medical University, Yinchuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: To analyze the therapeutic efficacy of intervertebral surgery in the treatment of multisegmental spinal tuberculosis (MSTB) by evaluating its clinical outcomes and perioperative indicators, thereby providing evidence-based insights to optimize surgical strategies and improve clinical decision-making. Methods: This retrospective cohort study analyzed 134 MSTB patients treated at our hospital between January 2000 and June 2022. Based on the surgical approach, patients were divided into two groups: Group A ( Results: The mean follow-up duration was 63.24 ± 9.16 months for Group A and 64.05 ± 9.74 months for Group B. Group A demonstrated significantly shorter operative time and reduced intraoperative blood loss compared to Group B ( Conclusion: Both intervertebral and non-intervertebral surgical strategies for MSTB can effectively restore spinal alignment and achieve satisfactory neurological recovery, provided that strict surgical indications are adhered to. Intervertebral surgery, with its shorter operative time and lower intraoperative blood loss, may offer additional perioperative advantages and serve as a viable option for MSTB management.

Indexed as

clinical characteristicsefficacy evaluationmanagementmultisegmental spinal tuberculosissurgical treatment

Identifiers

PMID40046928
PMCPMC11880997

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Registered trials

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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.