bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comparative cross-sectional study of the impact of COVID-19 pandemic on obstetrics and gynecology admissions in Croatia
Authors: Kalanj Karolina , Mikuš Mislav , Peček Mirta , Orbanić Ante , Marshall Rick , Orešković Stjepan , Orešković Slavko 
Published: February 2025

BackgroundThe COVID-19 pandemic placed unprecedented pressure on healthcare systems worldwide and altered patients' perceptions of the system's ability to protect them from virus transmission. One significant consequence was a marked decline in hospital activity, a trend observed globally. This study aims to evaluate the impact of COVID-19 on hospitalization rates among patients with gynecological disorders in Croatia. It compares the number of patients treated surgically vs. conservatively before the pandemic (2017–2019) and during the pandemic (2020–2022) using the Diagnostic-Related Group (DRG) patient classification system. The DRG system is designed to group patients based on similar clinical conditions, complexity, and resource utilization. Hospital activity categorized by DRGs was analyzed to assess the impact of the COVID-19 pandemic on case volumes within DRG groups associated with gynecological and obstetric disorders.Materials and methodsWe conducted a comparative descriptive cross sectional study of the pre-post type according to STROBE guidelines to determine the impact of COVID-19 pandemic on hospital admission rates for patients with conditions associated with illnesses and abnormalities of the female reproductive system, as well as pregnancy, delivery, and the puerperium. The publicly available data collected by Croatian Institute of Public Health (CIPH) and the Croatian Health Insurance Fund (CHIF) were the main data source for this study. All gynecological hospital admissions in Croatia were grouped based on the Australian Refined Diagnosis Related Groups (AR-DRGs) and analyzed over two time periods: before (2017–2019) and during the pandemic (2020–2022).ResultsThe average number of gynecological patients in all hospitals during the pandemic was 62,257 compared to pre-pandemic when the average number of patients was 71,519, a decrease of 15.5%. The results show a 10.56% decrease in the total number of non-surgical admissions and 12.8% decrease of surgical admissions across the hospital network during the pandemic (2020–2022).ConclusionThe COVID-19 pandemic led to a significant decline in inpatient treatments in gynecology and obstetrics departments in Croatia. Our findings highlight the need for obstetrics and gynecology practitioners to develop innovative strategies to maintain or enhance patient access to appropriate care while ensuring stringent infection prevention measures for both patients and healthcare personnel. Furthermore, investing in healthcare system resilience is crucial to maintaining core functions during future crises. The lessons learned from the COVID-19 pandemic provide a valuable opportunity to fortify healthcare systems and must not be ignored.
Burden of rheumatoid arthritis in India from 1990 to 2021: insights from the Global Burden of Disease Database
Authors: Shi Wei , Liang Xinyu , Zhang Huafeng , Li Hui 
Published: February 2025

ObjectiveRheumatoid arthritis (RA) significantly impacts individual health and society. This study aims to analyze the burden of RA in India from 1990 to 2021 and provide predictions to inform national prevention and control strategies.MethodsUtilizing data from the 2021 Global Burden of Disease (GBD) database, this study describes changes in incidence, prevalence, and disability-adjusted life years (DALY) related to RA in India from 1990 to 2021, while also observing variations across 31 geographical regions.ResultsFrom 1990 to 2021 in India, the incidence, prevalence, and DALY rates of RA showed an increasing trend, with all age-standardized rates being significantly higher in females than in males. The age group of 65–69 years showed the highest incidence rate, while the prevalence peaked at 75–79 years. The forecast results indicate that the age-standardized incidence and DALY rates of RA in India will show an upward trend from 2022 to 2036. There were considerable differences in prevalence across different regions. In 2021, the highest male prevalence was in Uttarakhand, while Goa had the lowest. For females, Tamil Nadu had the highest prevalence, and Madhya Pradesh had the lowest. Overall, areas with high Socio-Demographic Index (SDI) showed a higher disease burden, whereas Kerala, despite a higher SDI, had the lowest burden.ConclusionUsing the GBD database, our findings show that the disease burden of RA in India is on the rise from 1990 to 2021. The prevalence of RA in different regions of India is significantly different, which may be related to local economy and development. The high prevalence of RA in Indian women requires more attention to the early diagnosis and treatment of RA.
Predictive value of early neutrophil-to-lymphocyte ratio and C-reactive protein in pediatric steroid-sensitive nephrotic syndrome
Authors: Maimaititusvn Gulinuer , Jvnaiti Nilupaer , Kulaixi Maierhaba , Liu Fang 
Published: February 2025

ObjectiveThis study aims to investigate the predictive value of early neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) levels for relapse and adverse prognosis within one year in children diagnosed with steroid-sensitive nephrotic syndrome (SSNS).MethodsThis study included a total of 145 pediatric patients diagnosed with steroid-sensitive nephrotic syndrome (SSNS) between January 2016 and December 2021. We collected early neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) levels, along with relevant clinical data, and conducted a one-year follow-up of the patients. Based on the follow-up outcomes, the patients were categorized into two groups: those who experienced a relapse and those who did not. We assessed the diagnostic and predictive value of NLR and CRP for relapse within one year using receiver operating characteristic (ROC) curve analysis and the Cox proportional hazards regression model.ResultsAfter an average follow-up period of one year, 95 patients (65.52%) experienced relapse, while 50 patients (34.48%) did not. Significant differences were noted between the relapse and non-relapse groups regarding neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), C-reactive protein (CRP), 24-hour urinary protein levels, age at onset, and parental education level (P &lt; 0.05). Cox proportional hazards regression analysis identified age at onset, NLR, CRP, and 24-hour urinary protein levels as significant risk factors for relapse in patients with steroid-sensitive nephrotic syndrome (SSNS). Receiver operating characteristic (ROC) curve analysis for the combined prediction of relapse using NLR, CRP, and 24-hour urinary protein levels demonstrated good predictive value, with an area under the curve (AUC) of 0.858 (95% CI: 0.80–0.916, P &lt; 0.001). Kaplan-Meier survival analysis indicated that patients with elevated NLR (≥ 2.90) and CRP (≥ 25.30) exhibited the highest relapse rates and shorter survival times. Further Cox proportional hazards analysis revealed that children in the high NLR and high CRP groups were at an increased risk of relapse, rehospitalization, infection, prolonged cumulative steroid use, renal insufficiency, secondary hypertension, and other adverse outcomes within one year.ConclusionEarly levels of Neutrophil-to-Lymphocyte Ratio (NLR) and C-Reactive Protein (CRP) demonstrate significant predictive value for relapse and adverse prognosis within one year in children with Steroid-Sensitive Nephrotic Syndrome (SSNS). These markers can serve as effective tools for auxiliary clinical assessment.
Pyrotinib-assisted whole brain radiotherapy alleviates HER2-positive advanced breast cancer and brain metastases: a prospective study in patients
Authors: Zhou Fulin , Zhang Cui , He Mingyuan , Ren Yu , Yue Hongshuang , Tan Zhihua , Zhang Shaolin , Li Yong , Liu Shu 
Published: February 2025

PurposeThe whole-brain radiotherapy (WRBT)-based therapeutic efficacy is often limited against human epidermal growth factor receptor 2 (HER2+)-positive advanced breast cancer (BC) and brain metastases (BM), requiring more effective treatment options. This prospective study evaluates the effectiveness and safety of combining WBRT with pyrotinib in patients with HER2+ advanced BC and BM.MethodsThe enrolled patients (n = 26, from April 2019 to March 2022) were divided into two treatment groups. Group 1 (p-WBRT) received pyrotinib initially, followed by subsequent WBRT. Group 2 (WBRT-p) received WBRT concurrently with pyrotinib. The intracranial progression-free survival (iPFS) was determined.ResultsIn the WBRT-p group (n = 11), the median iPFS was recorded as 25.0 months (95% CI, 15.3–34.7), while the overall survival (OS) rates in 1–4 years were 100, 54.5, 9.1, and 0%, respectively. The intracranial objective response rate (iORR) and intracranial clinical benefit rate (iCBR) were 63.6 and 90.9%, respectively. In the p-WBRT group (n = 15), the median iPFS was around 22.0 months (95% CI, 4.3–39.7), and the OS rates in 1–4 years were 100, 53.3, 33.3, and 6.7%, respectively. The iORR and iCBR values were 66.7 and 80.0%, respectively. Notably, no significant differences in iPFS, OS, iORR, and iCBR were observed between treatment groups. Although some instances of adverse events, such as vomiting and reduced white blood cells and neutrophil counts, were evident, these adverse events were grades 1–3.ConclusionWBRT combined with pyrotinib exhibited exceptional tolerability, showing long iPFS in patients with HER2+ advanced BC and BM.
Association between advanced lung cancer inflammation index and acute gouty arthritis in Dalian, China: a cross-sectional study
Authors: Xiu Ziran , Gao Zhengnan , Luo Lan 
Published: February 2025

IntroductionAcute gouty arthritis (AGA) is an inflammatory joint disease. The advanced lung cancer inflammation index (ALI) evaluates inflammation. This study investigates the association between ALI and AGA.MethodsWe included 652 participants in this cohort study, dividing them into two groups: those with AGA and a control group without AGA. We employed logistic regression to examine the ALI-AGA relationship, using restricted cubic splines (RCS) to assess dose–response relationships, performing subgroup analyses, and conducting interaction tests. K-fold cross-validation was applied for model assessment. Receiver operating characteristic (ROC) curves were applied to visualize and compare the predictive value of ALI and other inflammatory indices for AGA.ResultsAmong the 652 participants, the AGA group exhibited significantly lower ALI values compared to the control group. Multivariate logistic regression identified an inverse relationship between ALI and AGA. RCS analysis indicated an L-shaped non-linear relationship between ALI levels and AGA, with inflection points at an ALI of 23.38. Subgroup analyses showed no significant interactions between ALI levels and AGA after stratifying by age, hypertension, coronary heart disease (CHD), and diabetes (DM). The results from the ROC curves indicate that ALI may serve as a better predictor of AGA.ConclusionThis cross-sectional study found a significant inverse correlation between ALI levels and AGA prevalence. Moreover, the ALI could serve as a more accurate diagnostic tool for AGA and offer a novel approach for further investigating the relationship between inflammation and AGA.
Global research prospects and trends in TFH cells and tumors: a bibliometric analysis
Authors: Lei Hao , Hu Jin , Zhu Junpeng , Li Runze , Zhao Yu , Zhao Yaqi , He Guisheng , Song Tao , Lu Chong , Zheng Wuping , Li Lei , Liu Chunping , Chen Hengyu 
Published: February 2025

BackgroundT follicular helper (TFH) cells, a subset of CD4+Th cells, play a critical role in B cell activation, proliferation, and differentiation primarily within B follicles in secondary lymphoid organs, essential processes for effective antibody responses. TFH cells are also implicated in various conditions, including autoimmune diseases, cancer, infectious diseases, allergies, and vaccine reactions. Despite their broad impact, a review of the literature on TFH cells and tumors has not been conducted. We aimed to fill this gap by providing a detailed analysis of the research landscape concerning TFH cells and tumors.MethodWe conducted a bibliometric analysis of literature on TFH cells and tumors from 2012 to 2024 using the Web of Science Core Collection (WoSCC). For an analysis of the global research landscape, we employed VOSviewer (version 1.6.20), CiteSpace 6.2.R6 software, and the “bibliometric” package in R language (version 4.3.2) to evaluate data on countries/regions, authors and cited authors, institutions, journals, references, and keywords. We also conducted a systematic review to summarize the global research trends, prospects, and hotspots in this field.ResultsOur analysis included contributions from 60 countries/regions, 7,864 authors, 35,853 cited authors, 1,756 institutions, 385 academic journals, 50883 references, 222 keywords, and 1,181published papers. Over the past decade, the volume of research on TFH cells and tumors had consistently increased. China published the most papers, more than double that of the United States. The top 2 authors ranked by publication volume were Gaulard, Philippe (14 articles, 379 citations), and De leval, Laurence (12 articles, 236 citations) Notably, 9 of the top 10 most published institutions were from China. Frontiers in Immunology and Immunity were the leading journals in publications and citations. A cluster analysis revealed a shift in research focus from “expression”,”B cells” and “survival” to “tumor microenvironment”, “tumor infiltrating immune cells” and “immune infiltration” in recent years.ConclusionThis bibliometric analysis suggests that TFH cells hold significant research value and potential clinical applications in tumor immunotherapy. Moreover, the bibliometric analysis offers valuable references and guidance for related research endeavors. It also points out the prevailing issues and challenges in TFH cell research, and underscores the need for further basic and clinical research to advance the related fields.
Survival prognostic nomogram for young metastatic non-small cell lung cancer: a study of the US SEER database and a Chinese cohort
Authors: Li Yu , Cao Lei , Ding Yawen , Liu Lei , Zhu Yonggang , Cao Feng 
Published: February 2025

ObjectiveYoung patients diagnosed with non-small cell lung cancer (NSCLC) present unique clinical, pathological, and genetic features, resulting in a highly heterogeneous patient population. The current TNM staging system is insufficient for accurately predicting their prognosis. This study aims to develop a nomogram model for survival prediction in young patients with metastatic NSCLC at initial diagnosis and further verify the effectiveness of the model.MethodsThis study enrolled 961 young patients diagnosed with metastatic NSCLC in the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017. The patients were allocated into a training cohort (n = 673) and an internal validation cohort (n = 288). An additional 215 patients from the Fourth Hospital of Hebei Medical University were included as a Chinese external validation cohort. Univariate and multivariate Cox regression analyses were conducted in the training cohort to identify independent risk factors influencing survival, which were used to develop a nomogram model. The model’s effectiveness was evaluated using C-index, calibration curve, receiver operating characteristic (ROC) curve, decision curve analysis (DCA) curve, and Kaplan–Meier survival curve.ResultsThe multifactorial Cox regression model identified eight independent risk factors influencing overall survival (OS): race, marital status, histological type, T stage, N stage, liver metastasis, chemotherapy, and radiotherapy (all P &lt; 0.05). These factors were incorporated into the nomogram, which achieved a C-index of 0.673 [95% confidence interval (CI) = 0.661–0.685]. The nomogram exhibited excellent prognostic value in both internal (C-index = 0.662, 95% CI = 0.643–0.681) and external (C-index = 0.724, 95% CI = 0.702–0.746) validation cohorts. In addition, calibration curves for 0.5-,1-, 2-, 3-, and 5-year OS probabilities showed close agreement between predicted and observed survival outcomes across various time points. Additionally, ROC curve analysis and Kaplan–Meier curves highlighted the robust discriminatory power of the model based on survival outcomes. Moreover, the DCA analysis revealed that the incremental net benefit of this model was significantly superior to that of the TNM staging system alone.ConclusionsA nomogram model has been developed and validated to accurately predict the OS of young patients with metastatic NSCLC at initial diagnosis, demonstrating superior performance compared to the traditional TNM staging system. This model offers valuable guidance for precise predictions and making rational treatment decisions in clinical practice.
Identification of potential diagnostic targets and therapeutic strategies for anoikis-related biomarkers in lung squamous cell carcinoma using machine learning and computational virtual screening
Authors: Zhang Xin , Zou Jing , Ning Jinghua , Zhao Yanhong , Qu Run , Zhang Yuzhe 
Published: February 2025

ObjectiveLung squamous cell carcinoma (LUSC) is a common subtype of non-small cell lung cancer (NSCLC) characterized by high invasiveness, high metastatic potential, and drug resistance, resulting in poor patient prognosis. Anoikis, a specific form of apoptosis triggered by cell detachment from the extracellular matrix (ECM), plays a crucial role in tumor metastasis. Resistance to anoikis is a key mechanism by which cancer cells acquire metastatic potential. Although several studies have identified biomarkers related to LUSC, the role of anoikis-related genes (ARGs) remains largely unexplored.MethodsAnoikis-related genes were obtained from the Harmonizome and GeneCards databases, and 222 differentially expressed genes (DEGs) in LUSC were identified via differential expression analysis. Univariate Cox regression analysis identified 74 ARGs significantly associated with survival, and a prognostic model comprising 8 ARGs was developed using LASSO and multivariate Cox regression analyses. The model was internally validated using receiver operating characteristic (ROC) curves and Kaplan-Meier (K-M) survival curves. Differences in immune cell infiltration and gene expression between high- and low-risk groups were analyzed. Virtual drug screening and molecular dynamics simulations were performed to evaluate the therapeutic potential of CSNK2A1, a key gene in the model. Finally, in vitro experiments were conducted to validate the therapeutic effects of the identified drug on LUSC.ResultsThe 8-gene prognostic model demonstrated excellent predictive performance and stability. Significant differences in immune cell infiltration and immune microenvironment characteristics were observed between the high- and low-risk groups, suggesting the critical role of ARGs in shaping the immune landscape of LUSC. Virtual drug screening identified Dihydroergotamine as having the highest binding affinity for CSNK2A1. Molecular dynamics simulations confirmed that the CSNK2A1-Dihydroergotamine complex exhibited strong binding stability. Further in vitro experiments demonstrated that Dihydroergotamine significantly inhibited LUSC cell viability, migration, and invasion, and downregulated CSNK2A1 expression.ConclusionThis study is the first to construct an anoikis-related prognostic model for LUSC, highlighting its role in the tumor immune microenvironment and providing insights into personalized therapy. Dihydroergotamine exhibited significant anti-LUSC activity and holds promise as a potential therapeutic agent. CSNK2A1 emerged as a robust candidate for early diagnosis and a therapeutic target in LUSC.
Navigating exercise attitudes and emotional positivity in adulthood during the COVID-19 pandemic: evidence from Shandong Province
Authors: Meng Ran , Dong Chen 
Published: February 2025

IntroductionDuring the onset of the COVID-19 pandemic, understanding public attitudes and emotional responses towards physical exercise became crucial. This study aimed to explore the relationship between positive emotions and attitudes towards physical exercise among adults in Shandong Province, China, and to identify the influence of demographic factors such as gender, age, and education levels on these attitudes and emotions.MethodsA cross-sectional study was conducted among 404 adults in Shandong Province, China. Data were collected through surveys that assessed participants’ attitudes towards physical exercise and their emotional positivity. Quantitative analysis was performed to examine the correlations and differences based on demographic variables, including gender, age, and education levels.ResultsA robust positive correlation was found between positive emotions and attitudes towards physical exercise, with an emotional positivity ratio of 2.01±1.38% among respondents. Significant differences in attitudes and emotional positivity were observed based on demographic factors. Specifically, male participants had a higher mean score in behavioral intention and control compared to females. Older adults (&gt;41 years) demonstrated more positive exercise attitudes, with a higher total score of 4.05 ± 0.54 compared to younger age groups. Additionally, respondents with a graduate degree and above reported the highest emotional positivity rate, outpacing those with lower educational levels.DiscussionThe findings indicate that demographic factors, including gender, age, and education levels, play a crucial role in shaping attitudes and emotional responses towards exercise, especially during a global health crisis. These insights highlight the importance of considering demographic differences when promoting physical exercise and designing public health interventions. Future research should further explore the underlying mechanisms and potential interventions to enhance positive attitudes and emotional responses towards physical exercise across diverse populations.