Indispensable for Anesthesia and Intensive Care Units: End-Tidal Carbon Dioxide and Capnography: A Bibliometric Analysis during 1980-2022
Bibliographic record
Abstract
Objective: In this study, we aimed to determine the most cited first 50 publications on end-tidal carbon dioxide (ETCO 2 ) and capnography from past to present using various bibliometric citation analysis methods, and to reveal the intellectual structure of the subject through co-citation analysis.Additionally, we aimed to identify the most active authors, institutions, journals, and countries in this field, and to demonstrate global productivity quantitatively.Methods: A total of 2508 publications on ETCO 2 published between 1980 and 2022 were downloaded from the Web of Science database and analyzed using citation and co-citation analyses.VOSviewer (Version 1.6.19)software was utilized to perform citation and co-citation analyses, and bibliometric network visualization maps were created. Results:The top 3 countries with the highest publication productivity in ETCO 2 research were the USA (1008), England (220), and Canada (118).The top 3 journals were Anesthesia and Analgesia(148), Anaesthesia (127), and Anesthesiology (89).The most active institutions were Research Libraries UK (98), Harvard University (80), and The University of California System (71).The top 3 authors were Petak F. ( 22), Tusman G. ( 22), and Weil MH. ( 19).The citation density of the top 50 articles in terms of total citations ranged from 83 to 448, while the average citation density per year ranged from 5.39 to 16.23.Among the top 50 most cited articles, the first two journals with the most publications were Annals of Emergency Medicine (8 articles) and Anesthesia and Analgesia (4 articles).Conclusion: Globally, an increasing trend in publications on ETCO 2 can be observed from the past to the present.Research leadership in the development of ETCO 2 literature is predominantly held by economically strong developed or developing countries.Evaluation of citation and co-citation analyses reveals that the most influential studies on ETCO 2 /capnography focus on sedation, endotracheal intubation, cardiopulmonary resuscitation (CPR)/cardiac arrest, and dead space topics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.036 | 0.070 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".