bluuebunny/crossref_metadata_2025_split huggingface dataset:
Construction of a poor prognosis prediction and visualization system for intracranial aneurysm endovascular intervention treatment based on an improved machine learning model
Authors: Lei Chunyu , Fu Anhui , Li Bin , Zhou Shengfu , Liu Jun , Cao Yu , Zhou Bo 
Published: January 2025

ObjectiveTo evaluate the clinical utility of improved machine learning models in predicting poor prognosis following endovascular intervention for intracranial aneurysms and to develop a corresponding visualization system.MethodsA total of 303 patients with intracranial aneurysms treated with endovascular intervention at four hospitals (FuShun County Zigong City People's Hospital, Nanchong Central Hospital, The Third People's Hospital of Yibin, The Sixth People's Hospital of Yibin) from January 2022 to September 2023 were selected. These patients were divided into a good prognosis group (n = 207) and a poor prognosis group (n = 96). An improved machine learning model was employed to analyze patient clinical data, aiding in the construction of a prediction model for poor prognosis in intracranial aneurysm endovascular intervention. This model simultaneously performed feature selection and weight determination. Logistic multivariate analysis was used to validate the selected features. Additionally, a visualization system was developed to automatically calculate the risk level of poor prognosis.ResultsIn the training set, the improved machine learning model achieved a maximum F1 score of 0.8633 and an area under the curve (AUC) of 0.9118. In the test set, the maximum F1 score was 0.7500, and the AUC was 0.8684. The model identified 10 key variables: age, hypertension, preoperative aneurysm rupture, Hunt-Hess grading, Fisher score, ASA grading, number of aneurysms, intraoperative use of etomidate, intubation upon leaving the operating room, and surgical time. These variables were consistent with the results of logistic multivariate analysis.ConclusionsThe application of improved machine learning models for the analysis of patient clinical data can effectively predict the risk of poor prognosis following endovascular intervention for intracranial aneurysms at an early stage. This approach can assist in formulating intervention plans and ultimately improve patient outcomes.
Analysis of risk factors for acute cerebral infarction in patients with intracranial tuberculosis
Authors: Huang Xiao-Shan , Qiu Xiao-Wei , Wang An-Long , He Fei , Wang Yi-Jing 
Published: January 2025

ObjectiveAcute cerebral infarction is a common complication of intracranial tuberculosis (TB), causing irreversible damage to brain tissue and significantly affecting patient prognosis. This study aims to explore the risk factors associated with acute cerebral infarction in patients with intracranial tuberculosis.MethodsWe retrospectively analyzed data from eligible intracranial TB patients treated at our hospital between January 2020 and March 2023. Based on MRI findings, patients were categorized into a cerebral infarction group and a non-infarction group. Clinical data, cerebrospinal fluid (CSF) examinations, and imaging features (such as hydrocephalus, cerebral arteritis, and meningeal thickening) were compared between the two groups. Binary logistic regression analysis was used to identify risk factors for acute cerebral infarction in patients with intracranial TB.ResultsA total of 102 patients were included, with 24 in the cerebral infarction group and 78 in the non-infarction group. Male patients accounted for 87.5% in the infarction group and 58.3% in the non-infarction group. Patients with a Glasgow Coma Scale (GCS) score of 3–10 accounted for 45.8% in the infarction group compared to 15.4% in the non-infarction group. The incidence of hydrocephalus, cerebral arteritis, and meningeal thickening was significantly higher in the infarction group (37.5, 54.2, and 79.2%, respectively) compared to the non-infarction group (6.4, 6.4, and 43.6%, respectively) (p &lt; 0.05). The parenchymal type of intracranial TB was less frequent in the infarction group (20.8%) than in the non-infarction group (56.4%), while the mixed type was more frequent in the infarction group (62.5%) compared to the non-infarction group (26.9%) (p &lt; 0.05). Patients with meningeal thickening involving the cisterns and basal cisterns had a higher risk of cerebral infarction (p &lt; 0.05). Multivariate binary logistic regression analysis revealed that male sex (OR = 13.56; 95% CI 1.25–38.30) and cerebral arteritis (OR = 19.32; 95% CI 0.94–37.64) were independent risk factors for cerebral infarction in intracranial TB patients.ConclusionMale sex and the presence of cerebral arteritis are independent risk factors for acute cerebral infarction in patients with intracranial tuberculosis.
The research progress and prospects of circadian rhythm in obesity: a bibliometric analysis
Authors: Dou Ye , Guo Xiaojin , Wang Xuefei , He Aolong , Li Fanghe , Gao Kuo 
Published: January 2025

BackgroundNumerous studies have shown a link between circadian rhythms disruptions and a higher risk of obesity. This article aims to conduct an extensive bibliometric analysis to deepen our understanding of the relationship between circadian rhythms and obesity.MethodsThe literature related to the circadian rhythm of obesity, published from the inception of the Web of Science Core Collection (WoSCC) until June 30, 2024, was extracted from the WoSCC databases (SCIE, SSCI, ESCI). Using CiteSpace, Vosviewer, WPS, and other software, this paper examines the publication trends, including the number of papers, countries/regions, institutions, authors, journals, references, and keywords.ResultsA total of 2,870 articles were included in this analysis, revealing a consistent year by year increase in research on the circadian rhythm of obesity. These publications originate from 460 institutions in 88 countries. Among the authors analysis, Garaulet, Marta was the most prolific, and Turek FW was the most co-cited. Proceedings of the National Academy of Sciences of the United States of America emerged as the journal with the highest number of publications, and American Journal of Physiology had the highest centrality. The most frequently used keywords were “obesity,” “circadian rhythm,” “circadian clock,” “metabolic syndrome,” “metabolism.” Additionally, research areas involving intermittent fasting, restricted feeding, and gut microbiota were rapidly developing and represented the forefront of research on circadian rhythms and obesity.ConclusionOur study demonstrates that research on circadian rhythms in obesity has been rapidly expanding, with increasingly in-depth exploration of the topic. It is recommended to strengthen cooperation between countries and institutions to jointly promote research in this field. The gene expression of obesity is an early hotspot in the study of circadian rhythm and obesity, and emerging research areas such as intermittent fasting, restricted feeding, endothelial nitric oxide synthase and gut microbiota will become significant hotspots and trends in the field of circadian rhythm and obesity. These findings provide researchers critical directions for future studies and may have significant implications for clinical practice and public health policy.
Preoperative CT-based radiomics nomogram to predict the micropapillary pattern in lung adenocarcinoma of size 2 cm or less
Authors: Pan Xiaoyu , Fu Liang , Lv Jiecai , Feng Lijuan , Li Kai , Chen Siqi , Deng Xi , Long Liling 
Published: January 2025

PurposeTo develop and validate a radiomics nomogram model for predicting the micropapillary pattern (MPP) in lung adenocarcinoma (LUAD) tumors of ≤2 cm in size.MethodsIn this study, 300 LUAD patients from our institution were randomly divided into the training cohort (n = 210) and an internal validation cohort (n = 90) at a ratio of 7:3, besides, we selected 65 patients from another hospital as the external validation cohort. The region of interest of the tumor was delineated on the computed tomography (CT) images, and radiomics features were extracted. A nomogram model was established using radiomics features, clinical features and conventional radiographic features. The nomogram model was compared with the radiomics model and the clinical model alone to test its diagnostic validity. Receiver operating characteristic (ROC) curves, areas under the ROC curves and decision curve analysis (DCA) results were plotted to evaluate the model performance and clinical application.ResultsThe nomogram model exhibited superior performance, with an AUC of 0.905 (95% confidence interval [CI]: 0.857-0.951) in the training cohort, which decreased to 0.817 (95% CI: 0.698-0.936) in the external validation cohort. The clinical model had AUCs of 0.820 (95% CI: 0.753-0.886) and 0.730 (95% CI: 0.572-0.888) in the training and external validation cohorts, respectively. The radiomics model had AUCs of 0.895 (95% CI: 0.840-0.949) and 0.800 (95% CI: 0.675-0.924) for training and external validation, respectively. DCA confirmed that the nomogram model had the better clinical benefit.ConclusionsThe nomogram model achieved promising prediction efficiency for identifying the presence of the MPP in LUAD tumors ≤2 cm, allowing clinicians to develop more rational and efficacious personalized treatment strategies.
Survival status of women with cervical cancer in Sub-Saharan Africa: a systematic review and meta-analysis, 2024
Authors: Emagneneh Tadele , Mulugeta Chalie , Ejigu Betelhem , Alamrew Abebaw , Hiwot Aynalem Yetwale , Feleke Sefineh Fenta 
Published: January 2025

BackgroundDespite the availability of vaccination and early treatment, cervical cancer remains a significant public health concern globally, particularly in Sub-Saharan Africa, where access to screening and treatment is often limited.MethodsIn this study, researchers conducted a survey of four international databases—Medline/PubMed, Scopus, Web of Science, and Henare—along with Google Scholar to search for gray literature. The keywords used for searching the international databases included “Uterine Cervical Neoplasms [Mesh],” “Survival OR Survival Analysis OR Survival Rate,” and “Sub-Saharan countries” (including the names of specific countries). Six researchers independently screened and extracted data from the articles. All studies published in English were included without restriction and assessed for quality using the adapted Newcastle–Ottawa Scale for cohort and cross-sectional studies. The results of this systematic review were reported in accordance with the PRISMA checklist.ResultsOut of the 2,180 articles initially identified, 23 were deemed eligible and reported on the survival status of patients with cervical cancer in Sub-Saharan Africa. This study assessed the multi-year survival rates (1, 2, 3, 4, and 5 years) of patients with cervical cancer. Based on the random-effects model, the overall pooled 1-year survival was 65.0% [95% confidence interval (CI), 52–78] with I² = 99.31 and p-value &lt; 0.001. The 2-year survival rate was 60% (95% CI, 46–74) with I² = 99.12 and p-value &lt; 0.001, the 3-year survival was 48% (95% CI, 35–62) with I² = 98.45 and p-value &lt; 0.001, the 4-year survival was 42.9% (95% CI, 32.7–53.1) with I² = 96.80 and p-value &lt; 0.001, and the 5-year survival was 35% (95% CI, 27–44) with I² = 98.74 and p-value &lt; 0.001.ConclusionsThis systematic review and meta-analysis found that the survival rates for patients with cervical cancer in Sub-Saharan Africa are much lower than the global averages. The results show that the 5-year survival rate can be as low as 35%, highlighting serious challenges in managing cervical cancer in this region. To address this issue, collaboration among governments, healthcare providers, and international organizations is essential to enhance the availability and quality of care. Future research should focus on developing effective early detection and treatment strategies and monitoring long-term survival outcomes.
Real-world experiences with brentuximab vedotion-based regimens in systemic anaplastic large cell lymphoma: a multi-center retrospective study
Authors: Zhao Zhiqiang , Yu Qinchuan , Su Liping , He Jianxia , Tao Jie , Xi Yanfeng , Guo Yujiao , Luo Yanhong , Wang Lieyang 
Published: January 2025

BackgroundBrentuximab vedotin (BV) has demonstrated high remission rates in clinical trials for systemic anaplastic large cell lymphoma (sALCL), yet its real-world effectiveness in China remains unconfirmed. This retrospective observational study evaluates BV-based regimens in patients with sALCL, treated from 2020 to 2023.MethodsA multi-center observational retrospective study was conducted on patients with sALCL received BV plus cyclophosphamide, doxorubicin, and prednisone (CHP) upfront or BV plus gemcitabine, oxaliplatin(GemOx), gemcitabine, cisplatin, dexamethasone(GDP), or isocyclophosphamide, carboplatin, etoposide (ICE)for later lines. Primary endpoints were complete response rate (CRR) and overall response rate (ORR); secondary endpoints included progression-free survival (PFS), overall survival (OS), duration of response (DOR), and the incidence of adverse events (AEs).ResultsAmong the 38 patients (28 newly diagnosed and 10 with refractory/relapsed disease), the ORR were 100% (with 89.3% CR) for newly diagnosed patients and 70% (with 50% CR) for refractory/relapsed patients. The median duration of response was 14 months for newly diagnosed patients and 23.8 months for those with refractory/relapsed disease. 2-year Survival rates were 100% for newly diagnosed patients and 80% for refractory/relapsed patients, with 2-year PFS rates of 92.8% and 70%, respectively. Neurological toxicities were commonly observed but resolved following the completion of treatment.ConclusionBV has proven to be effective and well-tolerated in real-world settings for the treatment of sALCL, reinforcing its potential as a promising option for first-line or subsequent therapy. The sustained efficacy observed post-CR suggests that these patients may have a prolonged disease control.
Epidemiological characterization of COVID-19 in children under 18 years old in Mexico: an analysis of the pandemic
Authors: Takane-Cabrera Isamu Daniel , Ortega-Vargas Fanny Yasmin , Díaz-Torres Ilen Adriana , Herrera-González Aldo Agustin , Villa Antonio R. , García-León Miguel Leonardo , Bautista-Carbajal Patricia , Pérez-Sastre Miguel A. , Cortazar-Maldonado Luis Alberto , Díaz-Ramírez Jorge Baruch , Wong-Chew Rosa Maria 
Published: January 2025

ObjectiveThe study aimed to describe the characteristics and risk factors associated with disease severity across six waves of COVID-19 in the pediatric population in Mexico.MethodsA cohort study was conducted using data from the Mexican Ministry of Health, covering the period from March 2020 to March 2023. The dataset included patients under 18 years of age with confirmed SARS-CoV-2 infection. Univariate, bivariate, and logistic regression analyses were performed to determine demographic and clinical characteristics, mortality across waves, and age group distributions.ResultsOf the total cohort, 9.5% were children, with 497,428 confirmed cases. Among these, 50% were male, 4.4% required hospitalization, and there were 1,447 (0.03%) deaths. The highest prevalence was observed in the 12–17-year age group (52%), followed by the 5–11-year age group (32%), with incidence rates peaking towards the end of 2021 and the early 2022. Although the 0–2-year age group represented 9.6% of cases, it had higher hospitalization (40%), ICU admission (58%), and case fatality rate (CFR) (44%). Cardiovascular disease, hypertension, diabetes and immunosuppression were identified as risk factors for severe outcomes. The initial wave displayed the highest CFR (OR 5.28) especially in children aged 0–2 years.ConclusionsChildren were less affected during the pandemic compared to adults; however, children under two years-old experienced more severe outcomes. Currently, with 95% of the population estimated to be immune due to vaccination and/or prior infection, children under 2 years of age are now at higher risk of severe disease and should be evaluated for vaccination as a public health policy.
Ultrasound-guided thoracic paravertebral injection of dexamethasone palmitate combined with ropivacaine for the treatment of thoracic herpes zoster-related pain: protocol for a prospective, randomized controlled, single-center study
Authors: Wang Liu , Xu Shengrong , Jiang Zongbin , He Ruilin 
Published: January 2025

BackgroundHerpes zoster (HZ) patients often experience herpes zoster-associated pain (ZAP). Thoracic paravertebral nerve block has been proven effective in relieving ZAP and reducing the incidence of postherpetic neuralgia (PHN). Compared to dexamethasone, dexamethasone palmitate (DXP) has stronger anti-inflammatory effects, a longer duration of action, and fewer adverse reactions. This study evaluates the efficacy and safety of ultrasound-guided thoracic paravertebral injection of DXP combined with ropivacaine for treating thoracic ZAP, compared to traditional famciclovir therapy.MethodsThis prospective, randomized, controlled, open-label, endpoint-blinded, single-center trial will recruit 254 patients with ZAP. Patients will be randomly assigned in a 1:1 ratio to the intervention group (thoracic paravertebral injections of DXP combined with ropivacaine and antiviral therapy) or the control group (antiviral therapy). Assessments will include pain intensity, quality of life, sleep quality, inflammatory markers, and adverse events.Ethics and registrationThis study strictly adheres to the 2013 SPIRIT Statement and the Declaration of Helsinki and has been approved by the Ethics Committee of the Second Affiliated Hospital of Guangxi Medical University (Approval Number: 2024-KY(0505)). This clinical trial is registered on the Chinese Clinical Trial Registry platform (ChiCTR) at https://www.chictr.org.cn/index.html (ChiCTR2400087273), registered on 2024-07-24. The results will be disseminated through scientific journals and conferences, aiming to provide evidence supporting the global management of ZAP. The study is expected to start on 1 August 2024, and continue until 31 July 2027.
An autonomous navigation method for orchard mobile robots based on octree 3D point cloud optimization
Authors: Li Hailong , Huang Kai , Sun Yuanhao , Lei Xiaohui , Yuan Quanchun , Zhang Jinqi , Lv Xiaolan 
Published: January 2025

Three-dimensional (3D) LiDAR is crucial for the autonomous navigation of orchard mobile robots, offering comprehensive and accurate environmental perception. However, the increased richness of information provided by 3D LiDAR also leads to a higher computational burden for point cloud data processing, posing challenges to real-time navigation. To address these issues, this paper proposes a 3D point cloud optimization method based on the octree data structure for autonomous navigation of orchard mobile robots. This approach includes two key components: 1) In terms of orchard mapping, the spatial indexing and segmentation features of the octree data structure are introduced. According to the sparsity and density of the point cloud, the 3D orchard map is adaptively divided and the key information of the orchard is retained. 2) In terms of path planning, by using octree nodes as the unit nodes for RRT* random tree expansion, an improved RRT* algorithm based on octree is proposed. Field experiments were conducted in a pear orchard based on this method. The experimental results show that: 1) The overall number of point cloud data points in the map was reduced by approximately 76.32%, while important features, including tree morphology, trellis structure, and road surface information, were fully preserved. 2) When different octree node resolutions were applied, the improved RRT* algorithm demonstrated significant improvements in path generation time, sampling point utilization, path length, and curvature. The lateral tracking error increased as the resolution of octree nodes decreased. At a resolution of 0.20 m, the maximum average lateral tracking error was 0.079 m, indicating strong path trackability. This method exhibits tremendous potential for processing large-scale 3D point cloud data and enhancing path planning efficiency, providing a valuable technical reference for the real-time autonomous navigation of mobile robots in complex orchard environments.
The effect of a mindfulness-based cognitive therapy program on the spiritual health of mothers of infants admitted to the neonatal intensive care unit
Authors: Arasteh Naeime , Moghimian Shahrbabaki Reihane , Nematollahi Monirsadat , Ahmadi Atefe , Bagherian Behnaz 
Published: January 2025

IntroductionThe birth and admission of a premature infant to the NICU is often an unexpected experience and a mental and spiritual challenge for families. Spiritual health is an influential factor affecting how a mother faces and endures a stressful situation. Improving the mother's spiritual health requires cognitive therapy approaches, including mindfulness techniques. Nurses can help mothers of infants admitted to the NICU to go through the hospitalization period more peacefully by using mindfulness techniques. To this end, the present study sought to investigate the effect of a mindfulness-based cognitive therapy (MBCT) program on spiritual health in mothers of infants admitted to the NICU.MethodsThis quasi-experimental study was conducted using a pre-test-post-test design in two intervention and control groups. The participants were 50 mothers of infants admitted to the NICU of Afzalipur Hospital, Kerman, who were selected via convenience sampling and randomly divided into two control and intervention groups (25 mothers in each group). The intervention involved providing counseling using a short-term mindfulness-based cognitive therapy program carried out in four 2-h sessions for the participants in the intervention group. The participants in the control group received routine NICU care. The participants in both groups completed a demographic information questionnaire and the Spiritual WellBeing Scale (SWBS) before and after the intervention. The collected data were analyzed with SPSS-25 software.ResultsThe data showed no statistically significant difference between the two groups in terms of demographic characteristics (P &gt; 0.05). Moreover, the mean score of spiritual health in the intervention group was 92.80 ± 12.14 and that of the control group was 92.16 ± 16.35 before the intervention. The mean score of spiritual health in the intervention group was 104.04 ± 6.60 and that of the control group was 92.56 ± 16.35 after the intervention. The results of the paired samples t-test revealed a statistically significant difference in the mean scores of spiritual health and its dimensions before and after the intervention in the intervention group (P &lt; 0.001).DiscussionThe findings from the present study indicated that mindfulness-based cognitive therapy intervention was effective in improving the spiritual health of mothers with infants admitted to the NICU. NICU nurses can use mindfulness-based cognitive therapy as a practical intervention to improve the spiritual health of mothers of premature infants and promote the sense of meaningfulness and meaning of life in these mothers.