Knowledge Mapping and Research Hotspots of Comorbidities in Psoriasis: A Bibliometric Analysis from 2004 to 2022

Adjunctive Chinese medicine therapy reduces relapse of psoriasis vulgaris after discontinuation of biologics: a prospective registry-based cohort study

BACKGROUND

Biologics have revolutionized psoriasis treatment; however, relapse of psoriasis after discontinuation of biologics remains unresolved.

OBJECTIVE

To assess the impact of adjunctive Chinese medicine (CM) therapy on relapse of psoriasis vulgaris (PV) after discontinuation of biologics.

METHODS

We constructed a prospective cohort study through a psoriasis case registry platform that enrolled patients treated with biologics (in combination with or without CM). The endpoint event was relapse, defined as loss of psoriasis area and severity index (PASI) 75.

RESULTS

A total of 391 patients completed the study and were included in the analysis, of whom 169 (43.2%) experienced relapse during follow-up. To minimize the bias, a 1:1 propensity score matching (PSM) was performed, generating matched cohorts of 156 individuals per group. Adjuvant CM therapy significantly associated with reduced incidence of relapse (HR =0.418, 95% CI = 0.289 ∼ 0.604, p < 0.001), and the protective effect of CM in the subgroup analysis was significant. In addition, PASI 90 response and disease duration were associated with relapse (p < 0.05).

CONCLUSION

Adjunctive CM therapy is associated with reduced relapse incidence in PV after discontinuation of biologics.

The Impact of Shared Assistance between Dermatology and Internal Medicine on Patients with Psoriasis

Background: The care of psoriatic patients requires a multidisciplinary approach that addresses not only skin involvement but also cardiovascular risk factors. Coordination between dermatology and internal medicine departments, with a specific focus on treatment and long-term follow-up, can substantially improve the course of a disease and its associated complications. Objective: to evaluate the effects of the holistic management of patients with psoriasis by a multidisciplinary team consisting of dermatology and internal medicine specialists. Methods: We conducted an observational, prospective, single-center case-control study between October 2016 and December 2019 in San Jorge University Hospital (Huesca, Spain). Cases included patients undergoing follow-up in the combined dermatology and internal medicine clinic. The control group consisted of an equivalent number of randomly selected, age- and sex-matched patients with moderate-to-severe psoriasis who were seen in the general dermatology department of the same hospital during the same time period. Main outcomes and measures: The primary outcome was the control of psoriatic disease and cardiovascular risk factors such as weight, blood pressure, waist circumference, body mass index (BMI), SCORE index (Systematic Coronary Risk Evaluation), and blood test parameters, as well as diet, physical exercise, and habits such as tobacco and alcohol consumption. To compare data collected over time, data were grouped into three time periods: baseline (t1), intermediate (t2), and final (t3). Results: The case group consisted of 27 patients, and the control group consisted of 25 patients. Multivariate analysis was used to evaluate the relationship between the 10-year risk of experiencing a cardiovascular event (SCORE) and the clinical characteristics and analytical variables of patients with psoriasis and controls (n = 52). The variables that were significantly associated with a higher 10-year risk of experiencing a cardiovascular event were age (OR, 1.33; CI95% 1.21-1.50; p < 0.001); smoking (OR, 5.05, CI95% 1.07-27.37; p = 0.047); PASI (OR, 7.98, CI95% 2.32-35.86; p = 0.003); BSA (OR, 1.22, CI95% 1.01-1.49; p = 0.044); and being a control patient (OR, 3.26; CI95% 0.84-13.56; p = 0.029). Conclusions: Pharmacological and behavioral interventions carried out as part of the procedure of the multidisciplinary clinic resulted in improvements in the following variables relative to the control group: PASI, BSA, DLQI, PSOLIFE, lipid profile, insulin and HOMA-IR GGT levels, vitamin D levels, and SCORE. These findings indicate the beneficial effect of the multidisciplinary clinic, which reduced the risk of cardiovascular events in psoriatic patients with metabolic comorbidities.

Bibliometric analysis and description of research trends on T cells in psoriasis over the past two decades (2003-2022)

Background

It is now understood that T cells play a key role in the occurrence and development of psoriasis. Herein, a bibliometric analysis was conducted to summarize the content and trends of T cell-related research in psoriasis.

Methods

A bibliometric analysis was conducted on publications pertaining to T cells in psoriasis between 2003 and 2022 retrieved from the Web of Science Core Collection (WoSCC) database using tools such as CiteSpace, the Bibliometrix R package, and VOSviewer.

Results

The study included a total of 3595 articles authored by 14,188 individuals, including all coauthors in article bylines. The Laboratory for Investigative Dermatology at Rockefeller University, led by James G Krueger, has made significant contributions to this field through focusing on the pathogenesis of psoriasis and exploring the potential of using biological agents to treat psoriasis. Furthermore, targeted inhibitors have significantly impacted the treatment of psoriasis, with researchers focusing on small-molecule targeted drugs as a new area of research that could potentially replace biological agents.

Conclusions

Research has established the efficacy and long-term safety of targeted inhibition of T cell-related targets. Deucravacitinib, a psoriasis treatment drug targeting TYK2 as an allosteric inhibitor, has attracted significant attention and raised high expectations.

A comprehensive overview of psoriatic research over the past 20 years: machine learning-based bibliometric analysis

Background

The surge in the number of publications on psoriasis has posed significant challenges for researchers in effectively managing the vast amount of information. However, due to the lack of tools to process metadata, no comprehensive bibliometric analysis has been conducted.

Objectives

This study is to evaluate the trends and current hotspots of psoriatic research from a macroscopic perspective through a bibliometric analysis assisted by machine learning based semantic analysis.

Methods

Publications indexed under the Medical Subject Headings (MeSH) term "Psoriasis" from 2003 to 2022 were extracted from PubMed. The generative statistical algorithm latent Dirichlet allocation (LDA) was applied to identify specific topics and trends based on abstracts. The unsupervised Louvain algorithm was used to establish a network identifying relationships between topics.

Results

A total of 28,178 publications were identified. The publications were derived from 176 countries, with United States, China, and Italy being the top three countries. For the term "psoriasis", 9,183 MeSH terms appeared 337,545 times. Among them, MeSH term "Severity of illness index", "Treatment outcome", "Dermatologic agents" occur most frequently. A total of 21,928 publications were included in LDA algorithm, which identified three main areas and 50 branched topics, with "Molecular pathogenesis", "Clinical trials", and "Skin inflammation" being the most increased topics. LDA networks identified "Skin inflammation" was tightly associated with "Molecular pathogenesis" and "Biological agents". "Nail psoriasis" and "Epidemiological study" have presented as new research hotspots, and attention on topics of comorbidities, including "Cardiovascular comorbidities", "Psoriatic arthritis", "Obesity" and "Psychological disorders" have increased gradually.

Conclusions

Research on psoriasis is flourishing, with molecular pathogenesis, skin inflammation, and clinical trials being the current hotspots. The strong association between skin inflammation and biologic agents indicated the effective translation between basic research and clinical application in psoriasis. Besides, nail psoriasis, epidemiological study and comorbidities of psoriasis also draw increased attention.

Global research trends in artificial intelligence for critical care with a focus on chord network charts: Bibliometric analysis

BACKGROUND

The field of critical care-related artificial intelligence (AI) research is rapidly gaining interest. However, there is still a lack of comprehensive bibliometric studies that measure and analyze scientific publications on a global scale. Network charts have traditionally been used to highlight author collaborations and coword phenomena (ACCP). It is necessary to determine whether chord network charts (CNCs) can provide a better understanding of ACCP, thus requiring clarification. This study aimed to achieve 2 objectives: evaluate global research trends in AI in intensive care medicine on publication outputs, coauthorships between nations, citations, and co-occurrences of keywords; and demonstrate the use of CNCs for ACCP in bibliometric analysis.

METHODS

The web of science database was searched for a total of 1992 documents published between 2013 and 2022. The document type was limited to articles and article reviews, and titles and abstracts were screened for eligibility. The characteristics of the publications, including preferred journals, leading research countries, international collaborations, top institutions, and major keywords, were analyzed using the category-journal rank-authorship-L-index score and trend analysis. The 100 most highly cited articles are also listed in detail.

RESULTS

Between 2018 and 2022, there was a sharp increase in publications, which accounted for 92.8% (1849/1992) of all papers included in the study. The United States and China were responsible for nearly 50% (936/1992) of the total publications. The leading countries, institutes, departments, authors, and journals in terms of publications were the US, Massachusetts Gen Hosp (US), Medical School, Zhongheng Zhang (China), and Science Reports. The top 3 primary keywords denoting research hotspots for AI in critically ill patients were mortality, model, and intensive care unit, with mortality having the highest burst strength (4.49). The keywords risk and system showed the highest growth trend (0.98) in counts over the past 4 years.

CONCLUSIONS

This study provides valuable insights into the potential for ACCP and future research opportunities. For AI-based clinical research to become widely accepted in critical care practice, collaborative research efforts are necessary to strengthen the maturity and robustness of AI-driven models using CNCs for display.