A bibliometric analysis of PCSK9 inhibitors from 2007 to 2022
Bibliographic record
Abstract
Background Since the approval of the proprotein convertase subtilisin/kexin type 9 (PCSK9) monoclonal antibodies for marketing in 2015, PCSK9 inhibitors have attracted significant interest in the field of cardiovascular endocrinology. A large number of clinical trials have confirmed the efficacy and safety of PCSK9 inhibitors in reducing cholesterol and the risk of cardiovascular events. No bibliometric analysis of PCSK9 inhibitors has been performed as of yet. This study aims to analyze the research trends and hotspots of PCSK9 inhibitors through bibliometric analysis. Methods We searched the Web of Science Core Collection (WoSCC) database for PCSK9 inhibitor-related publications from 2007 to 2022. Data visualization analysis was performed using CiteSpace software. Microsoft Excel and Graphpad software were used for the drawing of some tables and figures. Results A total of 1072 pieces of literature were retrieved between 2007 and 2022. The number of publications concerning PCSK9 inhibitors is growing annually. The top five countries with the most articles published were the United States, England, Canada, Italy, and France. Harvard University, Amgen, Brigham & Women’s Hospital, Harvard Medical School, and Imperial College London are the five institutions with the highest output. The Journal of Clinical Lipidology is the most popular journal in this field. The most frequently cited journal is the New England Journal of Medicine . As for authors, Sabatine MS and Giugliano RP from Brigham & Women’s Hospital have the highest number of published articles. Amgen is the funding agency for most of the research. According to keyword analysis, “low density lipoprotein”, “familial hypercholesterolemia”, “PCSK9 inhibitor”, “PCSK9”, and “efficacy” are the five keywords with the highest frequency of co-occurrence. Conclusion The past 15 years have witnessed a rapid and fruitful development of PCSK9 inhibitors. The research trend and focus for PCSK9 inhibitors are from the mechanism of reducing low-density lipoprotein cholesterol to related clinical trials. Developed countries such as the United States have contributed prominently in this area. Coronary artery and inflammation are currently at the forefront of research in the field and are in an explosion period.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.136 | 0.220 |
| 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) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".