Neuromonitoring in Severe Traumatic Brain Injury: A Bibliometric Analysis

Karagianni, Maria D.; Brotis, Alexandros; Gatos, Charalambos; Κalamatianos, Theodosis; Vrettou, Charikleia; Stranjalis, George; Fountas, Konstantinos

doi:10.1007/s12028-021-01428-5

Cited by 7 publications

(4 citation statements)

References 45 publications

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“…Only a few countries/regions not yet constructed cooperation tiles, namely Romania, Ethiopia, and Saudi Arabia. The active international collaboration could favor the collision of ideas and boost the breakthrough in this field [ 31 ].…”

Section: Resultsmentioning

confidence: 99%

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Explicating the publication paradigm by bibliometric approaches: A case of interplay between nanoscience and ferroptosis

Huang

Wang

Shu

et al. 2022

Health Care Science

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Background: Ferroptosis has been widely investigated as an emerging drug target, while its combination with nanoscience provides bourgeoning application prospects. The development of ferroptosis regulating nanomedicines have attracted worldwide attentions in recent years. It would be meaningful to describe the relevant publication paradigm.Methods: Herein, a bibliometric analysis was performed using the database of Web of Science Core Collection to clarify the publication paradigm. The development of related publications in the last 6 years was described, and the revolutionary trends were figured out. Ultimately, the possible future exploration directions were proposed. Results:The bibliometric analysis of 327 documents of interest indicated that the main research focus was in multiple fields including Materials science, Science & technology, Chemistry, and Pharmacology & pharmacy. With

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Section: Resultsmentioning

confidence: 99%

“…Other top-10 contributors like United States, Australia, and Japan also built a couple of cooperation Arabia. The active international collaboration could favor the collision of ideas and boost the breakthrough in this field [31].…”

Section: Coauthorship Visualizationmentioning

confidence: 99%

Explicating the publication paradigm by bibliometric approaches: A case of interplay between nanoscience and ferroptosis

Huang

Wang

Shu

et al. 2022

Health Care Science

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“…The methods above permits a more scientific interpretation of the research in the TBI field, including several studies in neuromonitoring 10 , rehabilitation 11 , pediatric TBI 12 , mild TBI 13 , and severe TBI 14 . Recently, The Lancet Neurology had an online article that reviewed the articles published in this journal 15 , but there is a lack of comprehensive bibliometric analysis of the TBI field to clearly state the gap in the study that pave the way for it to be carried out.…”

Section: Introductionmentioning

confidence: 99%

The recent two decades of traumatic brain injury: a bibliometric analysis and systematic review

Ye,

Li,

Zhong

et al. 2024

International Journal of Surgery

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Background: Traumatic brain injury (TBI) is a serious public health burden worldwide, with a mortality rate of 20%-30%; however, reducing the incidence and mortality rates of TBI remains a major challenge. This study provides a multidimensional analysis to explore the potential breakthroughs in TBI over the past two decades. Materials and Methods: We used bibliometric and Latent Dirichlet Allocation (LDA) analyses to analyze publications focusing on TBI published between 2003 and 2022 from the Web of Science Core Collection (WOSCC) database to identify core journals and collaborations among countries/regions, institutions, authors, and research trends. Results: Over the past 20 years, 41,545 articles on TBI from 3,043 journals were included, with 12,916 authors from 20,449 institutions across 145 countries/regions. The annual number of publications has increased ten-fold compared to previous publications. This study revealed that high-income countries, especially the United States, have a significant influence. Collaboration was limited to several countries/regions. The LDA results indicated that the hotspots included four main areas: “Clinical finding”, “Molecular mechanism”, “Epidemiology”, and “Prognosis”. Epidemiological research has consistently increased in recent years. Through epidemiological topic analysis, the main etiology of TBI has shifted from traffic accidents to falls in a demographically aging society. Conclusion: Over the past two decades, TBI research has developed rapidly, and its epidemiology has received increasing attention. Reducing the incidence of TBI from a preventive perspective is emerging as a trend to alleviate the future social burden; therefore, epidemiological research might bring breakthroughs in TBI.

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“…In particular, the rapid growth of multimodality neuromonitoring techniques has afforded clinicians and researchers alike with the opportunity for enhanced surveillance and recognition of previously imperceptible alterations in cerebral physiology with the ability to intervene before irreversible damage results. 1,2 These advancements have laid the foundation for personalized clinical management strategies aimed at optimizing physiological conditions, with evidence suggesting that this tailored approach may lead to improved patient outcomes. 3,4 Similarly, the advent of next-generation neuroimaging techniques has yielded crucial revelations about the functional connectivity networks within subcortical structures in patients with disorders of consciousness and hold promise for predicting the likelihood of recovery from coma.…”

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confidence: 99%

Artificial Intelligence and Machine Learning Applications in Critically Ill Brain Injured Patients

Vitt,

Mainali

2024

Semin Neurol

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The utilization of Artificial Intelligence (AI) and Machine Learning (ML) is paving the way for significant strides in patient diagnosis, treatment, and prognostication in neurocritical care. These technologies offer the potential to unravel complex patterns within vast datasets ranging from vast clinical data and EEG (electroencephalogram) readings to advanced cerebral imaging facilitating a more nuanced understanding of patient conditions. Despite their promise, the implementation of AI and ML faces substantial hurdles. Historical biases within training data, the challenge of interpreting multifaceted data streams, and the “black box” nature of ML algorithms present barriers to widespread clinical adoption. Moreover, ethical considerations around data privacy and the need for transparent, explainable models remain paramount to ensure trust and efficacy in clinical decision-making.This article reflects on the emergence of AI and ML as integral tools in neurocritical care, discussing their roles from the perspective of both their scientific promise and the associated challenges. We underscore the importance of extensive validation in diverse clinical settings to ensure the generalizability of ML models, particularly considering their potential to inform critical medical decisions such as withdrawal of life-sustaining therapies. Advancement in computational capabilities is essential for implementing ML in clinical settings, allowing for real-time analysis and decision support at the point of care. As AI and ML are poised to become commonplace in clinical practice, it is incumbent upon health care professionals to understand and oversee these technologies, ensuring they adhere to the highest safety standards and contribute to the realization of personalized medicine. This engagement will be pivotal in integrating AI and ML into patient care, optimizing outcomes in neurocritical care through informed and data-driven decision-making.

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Neuromonitoring in Severe Traumatic Brain Injury: A Bibliometric Analysis

Cited by 7 publications

References 45 publications

Explicating the publication paradigm by bibliometric approaches: A case of interplay between nanoscience and ferroptosis

Explicating the publication paradigm by bibliometric approaches: A case of interplay between nanoscience and ferroptosis

The recent two decades of traumatic brain injury: a bibliometric analysis and systematic review

Artificial Intelligence and Machine Learning Applications in Critically Ill Brain Injured Patients

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