Evidence map›Paper›PMID 36311953›Full record

ArticleFrontiers in surgery2022

Characteristics and hotspots of the 50 most cited articles in the field of pre-psoas oblique lumbar interbody fusion.

Guang-Xun Lin, Chien-Min Chen, Shang-Wun Jhang, Ming-Tao Zhu, Pengfei Lyu, Bao-Shan Hu

Abstract read
In one paragraph

Article in Frontiers in surgery, 2022. 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
–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

2 citing papers in PubMed.

  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

6 authors.

Guang-Xun LinThe School of Clinical Medicine, The Third Clinical Medical College, Fujian Medical University, China.
Chien-Min ChenDivision of Neurosurgery, Department of Surgery, Changhua Christian Hospital, Changhua, Taiwan.
Shang-Wun JhangDivision of Neurosurgery, Department of Surgery, Changhua Christian Hospital, Changhua, Taiwan.
Ming-Tao ZhuDepartment of Neurosurgery, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Pengfei LyuDepartment of Breast Surgery, The First Affiliated Hospital of Hainan Medical University, Haikou, China.
Bao-Shan HuDepartment of Orthopedics, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: In the past decade, the field of pre-psoas oblique lumbar interbody fusion (OLIF) has developed rapidly, and with it, the literature on OLIF has grown considerably. This study was designed to analyze the top 50 articles in terms of the number of citations through bibliometric research to demonstrate the research characteristics and hotspots of OLIF. Method: Searching the Web of Science database yielded the 50 most cited publications in the OLIF field as of July 10, 2022. The publications were ranked according to the number of citations. The following sources were evaluated: the year of publications, the number of citations, authors, countries, institutions, journals, research topics, and keyword hotspots. Results: The most productive period was from 2017 to 2020, with 41 articles. The number of citations varied from 10 to 140, with an average of 35.52, and 1,776 citations were found. Conclusions: Certain articles can be distinguished from others using citation analysis as an accurate representation of their impact due to their long-term effectiveness and peer recognition. With these publications, researchers are provided with research priorities and hotspots through influential literature in the field of OLIF.

Indexed as

anterior to psoascitation analysismost citedoblique lumbar interbody fusionOLIFprepsoas

Identifiers

PMID36311953
PMCPMC9597085

What OpenQuestion holds

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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.