Knowledge domain and emerging trends in chronic prostatitis/chronic pelvic pain syndrome from 1970 to 2020: a scientometric analysis based on VOSviewer and CiteSpace
Bibliographic record
Abstract
BACKGROUND: Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a common urological disease, and research on CP/CPPS has increased over the past 50 years. However, few studies have statistically analyzed these publications. In this work, we conducted the knowledge domain and highlighted current research hotspots and emerging trends in CP/CPPS from 1970 to 2020 based on VOSviewer and CiteSpace. METHODS: Relevant original articles were obtained from the Web of Science (WoS) database between 1970 and 2020. VOSviewer and CiteSpace software were used to perform the analysis and visualization of scientific productivity and emerging trends. RESULTS: Our results show that the articles related to CP/CPPS have dramatically increased every year from 1 publication in 1970 to 111 publications in 2020. The USA dominated the field in all countries, and Queen's University (Canada) has more extensive cooperating relationships with other institutions. J. Curtis Nickel may have a significant influence on CP/CPPS research with more publications and cocitations. The Journal of Urology is the foremost productive journal and has the most citations of all the journals. A total of 11 major clusters were explored based on the reference cocitation analysis (RCA). Definition, incidence rate or clinical characteristics, etiology or pathogenesis, epidemiological studies (cross-sectional study and cohort study), clinical studies (inflammation, pain, lower urinary tract symptoms (LUTS), α-blockers, antibiotic) and relationships with other diseases [benign prostatic hyperplasia (BPH), prostate cancer, sexual dysfunction] are the knowledge bases for CP/CPPS research. The treatment mode also changed gradually from anti-inflammatory therapy to symptom improvement, and NIH-CPSI was taken as the evaluation criterion. CONCLUSIONS: This scientometric study comprehensively reviewed publications related to CP/CPPS during the past 50 years using quantitative and qualitative methods, and the information provides some references for scholars to conduct further research on CP/CPPS.
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.015 |
| 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) | 0.003 | 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 teacher head, 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".