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Record W4416954271 · doi:10.3389/fneur.2025.1609558

Knowledge mapping and research trends on rehabilitation of patients with mechanical ventilation in the ICU from 2005 to 2024: a bibliometric analysis via CiteSpace and Bibliometrix

2025· review· en· W4416954271 on OpenAlexaboutno aff
Xizhen Kang, Jun Tian, Yanan Yang, Ye Zhu, Hui Teng, Haifan Xiao, Qing Shu

Bibliographic record

VenueFrontiers in Neurology · 2025
Typereview
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
FundersWuhan UniversityZhongnan Hospital of Wuhan UniversityNatural Science Foundation of Hubei Province
KeywordsRehabilitationMechanical ventilationIntensive care unitRandomized controlled trialClinical trialMEDLINEIntensive care

Abstract

fetched live from OpenAlex

Objective: Early rehabilitation, which refers to multidisciplinary, structured interventions initiated during the acute phase of illness, aimed at promoting physical recovery, reducing disability, and preventing complications, is essential for critically ill patients with mechanical ventilation. To review literature related to early rehabilitation in patients with mechanical ventilation in the intensive care unit, the paper aims to identify research topics and frontiers, report on current research trends, and offer valuable insights and perspectives for future development in the field. Methods: This study retrieved related publications from the Web of Science Core Collection database on March 12, 2025. After collecting the data, CiteSpace V.6.1. R6 was used to conduct a visual analysis of countries, institutions, authors, cited journals, cited references, and keywords. Bibliometrix 4.1.3 was used to generate the main information, country collaboration map, and three-field plot. The data was visualized through knowledge maps and collaborative networks. Results: We obtained a total of 375 articles on early rehabilitation in patients with mechanical ventilation. The number of annual publications has generally shown a steady growth trend in the past 20 years, with an annual growth rate of 21.59%. The United States, Brazil, Australia, and England are major contributing countries. North American and European countries have established the most intensive cooperation networks. Most of the active scholars, institutions, and journals in this field come from the United States, Canada, Australia, and England. Our research shows that ICU-acquired weakness, pulmonary dysfunction, and disorder of consciousness are important issues as well as challenges that need to be addressed urgently. Conclusion: This study analyzed the current status of early rehabilitation in patients with mechanical ventilation in the intensive care unit via CiteSpace and Bibliometrix, then identified the research hotspots and frontiers on it. While current evidence remains limited, methodologically rigorous multicenter randomized controlled trials with large cohorts are warranted to establish robust evidence regarding rehabilitation efficacy in mechanically ventilated patients. Emerging innovations in rehabilitation protocols are anticipated to progressively optimize clinical pathways as research methodologies advance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.818
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.047
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.1820.216
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.037
GPT teacher head0.376
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
Domainnot available
GenreReview

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in NeurologySame topicIntensive Care Unit Cognitive DisordersFrench-language works237,207