Global Research Trends in Lithium Toxicity from 1913 to 2015: A Bibliometric Analysis
Bibliographic record
Abstract
Lithium salts have been used to treat psychiatric disorders since the 1940s and are currently used in prophylaxis and treatment of depression and bipolar disorder. Therefore, we conducted this study to assess lithium toxicity-related publications using bibliometric approaches from a health point of view to assess global research trends in the lithium toxicity field to offer guidance to future research in this field. The data were retrieved from the online version of Scopus database on 6 August 2016. All records with the term 'lithium' in the title were retrieved, and those related to lithium toxicity were evaluated. There were a total of 1241 publications related to lithium toxicity published from 1913 to 2016. Articles (971 or 78.2%) were the most common type, followed by letters (179 or 14.4%) and reviews (61 or 4.9%). The annual publication of articles increased slightly after 1950 and the total number of publications related to lithium toxicity fluctuated with three peaks occurred in 1978, 1985 and 2014. The USA was the predominant country (25.38%), followed by the UK (7.82%), France (6.85%) and Canada (3.55%). Denmark had the highest productivity of publication after standardization by gross domestic product and population size. The average number of citations per article was 9.24, and the h-index for all publications in the field of lithium toxicity was 46. The highest h-index value was achieved by the USA (31) followed by the UK (21) and Canada (13). The Lancet was the highest ranked journal with 27 articles, followed by American Journal of Psychiatry with 23 articles. This study provides a bibliometric analysis on the global research trends in lithium toxicity studies during 1913-2015. There has been a progressive increase in the number of publications related to lithium toxicity published in the last decade, and most of the studies related to lithium toxicity arose from the USA and the UK.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.101 | 0.173 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".