Evolutionary trend analysis and knowledge structure mapping of endothelial dysfunction in sepsis: a bibliometrics study
Bibliographic record
Abstract
BACKGROUND: A pathophysiological feature of septic organ failure is endothelial dysfunction in sepsis (EDS). The physiological and pathological mechanism of sepsis is considered to be vascular leakage caused by endothelial dysfunction. These pathological changes lead to systemic organ injury. However, an analysis using bibliometric methods has not yet been conducted in the field of EDS. This study was conducted to provide an overview of knowledge structure and research trends in the field of EDS. METHODS: Based on previous research, a literature search was performed in the Web of Science Core Collection (WoSCC) for publications associated with EDS published between the year 2003 and 2023. Various types of data from the publications, such as citation frequency, authorship, keywords and highly cited articles, were extracted. The "Create Citation Report" feature in the WoSCC was employed to calculate the Hirsch index (h-index) and average citations per item (ACI) of authors, institutions, and countries. To conduct bibliometric and visualization analyses, three bibliometric tools were used, including R-bibliometrix, CiteSpace (co-citation analysis of references), and VOSviewer (co-authorship analysis of institutions, co-authorship analysis of authors, co-occurrence analysis of keywords). RESULTS: After excluding invalid records, the study finaly included 4,536 publications with 135,386 citations. Most of these publications originated in the USA, China, Germany, Canada, and Japan. Harvard University emerged as the most prolific institution, while professor Jong-Sup Bae and his research team at Kyungpook National University emerged as authors with the greatest influence. The "protein C", "tissue factor", "thrombin", "glycocalyx", "acute kidney injury", "syndecan-1" and "biomarker" were identified as prominent areas of research. Future research may focus on molecular mechanisms (such as as vascular endothelial [VE]-cadherin regulation) and therapeutic interventions to enhance endothelial repair and function. CONCLUSION: Our findings show a growing interest in EDS research. Key areas for future research include signaling pathways, molecular mechanisms, endothelial repair, and interactions between endothelial cells and other cell types in sepsis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.023 | 0.026 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".