ArticleClinical spine surgery2020
Bibliometric Analysis of the 100 Most Cited Articles on Intervertebral Disk Research: From 1900 to 2017 Year.
Article in Clinical spine surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Global trends and hotspots of macrophage-related research in intervertebral disc degeneration from 2005 to 2025: a bibliometric and visualized analysis.Frontiers in immunology · 2026Pooled it
- Assessment of influential authors and articles in spine surgery research: a narrative review.Journal of spine surgery (Hong Kong) · 2026Review
- Bibliometric analysis of the top 100 most cited studies in apolipoprotein E (ApoE) research.Narra J · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
STUDY
designA bibliometric review of the literature. OBJECT: To analyze and quantify the most frequently cited papers in intervertebral disk research. SUMMARY OF BACKGROUND DATA: The number of citations that a paper has received reflects its impact in related research area. In the field of disk research, however, it remains unknown which papers are most cited. By searching related literature databases, we identified the most cited 100 articles that advanced the understanding of the intervertebral disk to provide a historic view of scientific research of the disk. MATERIALS AND
methodsIntervertebral disk original research-related publications from January 1, 1900 to December 31, 2017 were retrieved from the Web of Science database. Each retrieved article was analyzed using the Cited Reference Search tool to identify the most cited articles. The number of citations, year of publication, publishing journal, authorship, country of publication, and the knowledge maps of keywords were gathered and generated.
resultsThe number of citations of the 100 selected articles ranges from 209 to 1269, and they were published from 1953 to 2009. Basic research is the most common type of study (n=60), followed by epidemiological study (n=40). Spine published 57 of the most cited 100 papers. The greatest contribution came from the United States of America (n=41), followed by the United Kingdom (n=18) and Japan (n=9). Frequently appearing keywords classified into 3 clusters: "biological study," "clinical study," and "imageological study." The keyword "degeneration" was mentioned the most, 51 items, and the word "development" was the latest hot spot in the most cited articles.
conclusionsIn the field of disk research, some papers were heavily cited more than 100 times, suggesting these studies have substantially contributed to the body of knowledge of the intervertebral disk and findings were widely accepted by related clinicians and scientists.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.