bluuebunny/crossref_metadata_2025_split huggingface dataset:
Repetitive transcranial magnetic stimulation impacts the executive function of patients with vascular cognitive impairment: a systematic review and meta-analysis
Authors: Wang Xu , Ding Qixin , Li Yuefang , Li Tianshu , Li Yakun , Yin Jialin , Zhuang Weisheng 
Published: June 2024

ObjectiveExecutive dysfunction is a core symptom of vascular cognitive impairment (VCI), which seriously affects patients’ prognosis. This paper aims to investigate the effectiveness of rTMS on executive function in VCI.MethodsThe databases selected for this study included Pubmed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang, China Science and Technology Journal Database (VIP), and China Biology Medicine Disc (CBM). The screening times were conducted from the time of library construction until August 23, 2023. The inclusion criteria for this meta-analysis were randomized controlled trials (RCTs) on rTMS for VCI, which include executive function scores. The primary metrics were executive subscale scores of the Cognitive Comprehensive Scale and total scores of the Executive Specificity Scale. The secondary metrics were subscale scores of the Executive Specificity Scale. The quality of each eligible study was assessed using the Cochrane Risk of Bias tool. Meta-analysis and bias analysis were performed using Stata (version 16.0) and RevMan (version 5.3).ResultsA total of 20 high-quality clinical RCTs with 1,049 samples were included in this paper. The findings from the primary outcomes revealed that within the rTMS group, there were significantly higher scores observed for the executive sub-item on the cognitive composite scale (SMD = 0.93, 95% CI = 0.77–1.08, p &lt; 0.00001, I2 = 14%) and the total score on the executive specific scale (SMD = 0.69, 95% CI = 0.44–0.94, p &lt; 0.00001, I2 = 0%) compared to the control group. As for the secondary outcome measures, as shown by the Trail Making Test-A (time) (MD = −35.75, 95% CI = −68.37 to −3.12, p = 0.03, I2 = 55%), the Stroop-C card (time) (SMD = −0.46, 95% CI = −0.86 to −0.06, p = 0.02, I2 = 0%) and the Stroop-C card (correct number) (SMD = 0.49, 95% CI = 0.04–0.94, p = 0.03, I2 = 0%), the experimental group shorts time and enhances accuracy of executive task in comparison to the control group. Subgroup analysis of the main outcome demonstrated that intermittent theta burst stimulation (iTBS), higher frequency, lower intensity, longer duration, and combined comprehensive therapy exhibited superior efficacy.ConclusionrTMS is effective in the treatment of the executive function of VCI. The present study has some limitations, so multi-center, large-sample, objective indicators and parameters are needed to further explore in the future.Systematic review registration:https://www.crd.york.ac.uk/prospero/, CRD42023459669.
A simple and effective machine learning model for predicting the stability of intracranial aneurysms using CT angiography
Authors: Luo Sha , Wen Li , Jing Yang , Xu Jingxu , Huang Chencui , Dong Zhang , Wang Guangxian 
Published: June 2024

BackgroundIt is vital to accurately and promptly distinguish unstable from stable intracranial aneurysms (IAs) to facilitate treatment optimization and avoid unnecessary treatment. The aim of this study is to develop a simple and effective predictive model for the clinical evaluation of the stability of IAs.MethodsIn total, 1,053 patients with 1,239 IAs were randomly divided the dataset into training (70%) and internal validation (30%) datasets. One hundred and ninety seven patients with 229 IAs from another hospital were evaluated as an external validation dataset. The prediction models were developed using machine learning based on clinical information, manual parameters, and radiomic features. In addition, a simple model for predicting the stability of IAs was developed, and a nomogram was drawn for clinical use.ResultsFourteen machine learning models exhibited excellent classification performance. Logistic regression Model E (clinical information, manual parameters, and radiomic shape features) had the highest AUC of 0.963 (95% CI 0.943–0.980). Compared to manual parameters, radiomic features did not significantly improve the identification of unstable IAs. In the external validation dataset, the simplified model demonstrated excellent performance (AUC = 0.950) using only five manual parameters.ConclusionMachine learning models have excellent potential in the classification of unstable IAs. The manual parameters from CTA images are sufficient for developing a simple and effective model for identifying unstable IAs.
Cerebral air embolism: neurologic manifestations, prognosis, and outcome
Authors: Červeňák Vladimír , Všianský Vít , Cviková Martina , Brichta Jaroslav , Vinklárek Jan , Štefela Jakub , Haršány Michal , Hájek Michal , Herzig Roman , Kouřil Dávid , Bárková Veronika , Filip Pavel , Aulický Petr , Weiss Viktor 
Published: June 2024

BackgroundCerebral air embolism (CAE) is an uncommon medical emergency with a potentially fatal course. We have retrospectively analyzed a set of patients treated with CAE at our comprehensive stroke center and a hyperbaric medicine center. An overview of the pathophysiology, causes, diagnosis, and treatment of CAE is provided.ResultsWe retrospectively identified 11 patients with cerebral venous and arterial air emboli that highlight the diversity in etiologies, manifestations, and disease courses encountered clinically. Acute-onset stroke syndrome and a progressive impairment of consciousness were the two most common presentations in four patients each (36%). Two patients (18%) suffered from an acute-onset coma, and one (9%) was asymptomatic. Four patients (36%) were treated with hyperbaric oxygen therapy (HBTO), high-flow oxygen therapy without HBOT was started in two patients (18%), two patients (18%) were in critical care at the time of diagnosis and three (27%) received no additional treatment. CAE was fatal in five cases (46%), caused severe disability in two (18%), mild disability in three (27%), and a single patient had no lasting deficit (9%).ConclusionCerebral air embolism is a dangerous condition that necessitates high clinical vigilance. Due to its diverse presentation, the diagnosis can be missed or delayed in critically ill patients and result in long-lasting or fatal neurological complications. Preventative measures and a proper diagnostic and treatment approach reduce CAE’s incidence and impact.
Decoding Wilson disease: a machine learning approach to predict neurological symptoms
Authors: Yang Yulong , Wang Gang-Ao , Fang Shuzhen , Li Xiang , Ding Yufeng , Song Yuqi , He Wei , Rao Zhihong , Diao Ke , Zhu Xiaolei , Yang Wenming 
Published: June 2024

ObjectivesWilson disease (WD) is a rare autosomal recessive disorder caused by a mutation in the ATP7B gene. Neurological symptoms are one of the most common symptoms of WD. This study aims to construct a model that can predict the occurrence of neurological symptoms by combining clinical multidimensional indicators with machine learning methods.MethodsThe study population consisted of WD patients who received treatment at the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine from July 2021 to September 2023 and had a Leipzig score ≥ 4 points. Indicators such as general clinical information, imaging, blood and urine tests, and clinical scale measurements were collected from patients, and machine learning methods were employed to construct a prediction model for neurological symptoms. Additionally, the SHAP method was utilized to analyze clinical information to determine which indicators are associated with neurological symptoms.ResultsIn this study, 185 patients with WD (of whom 163 had neurological symptoms) were analyzed. It was found that using the eXtreme Gradient Boosting (XGB) to predict achieved good performance, with an MCC value of 0.556, ACC value of 0.929, AUROC value of 0.835, and AUPRC value of 0.975. Brainstem damage, blood creatinine (Cr), age, indirect bilirubin (IBIL), and ceruloplasmin (CP) were the top five important predictors. Meanwhile, the presence of brainstem damage and the higher the values of Cr, Age, and IBIL, the more likely neurological symptoms were to occur, while the lower the CP value, the more likely neurological symptoms were to occur.ConclusionsTo sum up, the prediction model constructed using machine learning methods to predict WD cirrhosis has high accuracy. The most important indicators in the prediction model were brainstem damage, Cr, age, IBIL, and CP. It provides assistance for clinical decision-making.
Rapid axial roll test outperforms alternative positional tests in identifying the affected ear in HSC-BPPV: an observational cohort study
Authors: Xing Juanli , Yun Yanning , Zhang Shu , Yang Pan , Bai Xiongxiong , Zhang Leyi , Zhang Ming 
Published: June 2024

PurposeTo evaluate the utility of supine roll test (SRT) and alternative positional tests, such as head-shaking test (HST), seated supine positioning test (SSPT), bow and lean test (BLT), and rapid axial roll test (RART) in determining the affected semicircular canal of horizontal semicircular canal benign paroxysmal positional vertigo (HSC-BPPV).MethodsIn an observational cohort study, 553 patients diagnosed with HSC-BPPV were divided into five groups in terms of different positional tests received: SRT group (n = 110), HST+ SRT (n = 112), BLT + SRT (n = 114), SSPT+SRT (n = 108) and RART+SRT (n = 109). The same method was used for the last four groups: The patients were first subjected to different alternative positional tests and then to SRT, and the nystagmus was observed separately to determine the affected side. The primary outcomes compared included the accuracy and sensitivity of these tests in the determination of the affected semicircular canal in HSC-BPPV.ResultsPatients with nystagmus elicited by positional tests accounted for 84.99% (470/553). The elicitation rate of nystagmus of SRT was lowest, being 77.27% (85/110). The elicitation rate of nystagmus were higher in the test groups than in the control group, and RART+SRT group yielded the highest elicitation rate of nystagmus (95.41%, 104/109). Among the alternative positional tests, RART attained the highest elicitation rate of nystagmus (101/109, 92.66%). Comparison between alternative positional tests and SRT, RART and SRT showed obviously better agreement in determining the affected semicircular canal (85.45%, 96/109) and eliciting nystagmus (95.41%, Kappa = 0.642), but no difference was found in curative effect when the affected side was accurately determined (χ2 = 1.618, p = 0.655).ConclusionAll alternative positional tests are helpful for eliciting nystagmus in patients with HSC-BPPV, and the significant advantages of RART include high-sensitivity in eliciting nystagmus and high accuracy in determining the affected semicircular canal, which provided objective support for the correct diagnosis of HSC-BPPV and the successful reduction of otolith.
An investigation of association between human milk mineral patterns and infant growth
Authors: Sun Han , Xie Qinggang , Zhou Yalin , Liu Yang , Pan Jiancun , Xu Yajun , Jiang Shilong , Li Kaifeng 
Published: June 2024

IntroductionHuman milk is widely acknowledged as the optimal food for infant aged 0 ~ 6 months. While there has been extensive documentation on the mineral and trace element composition of human milk, results on the relationship between mineral content and infant growth remain mixed. This cross-sectional study aims to explore human milk mineral patterns and to investigate associations between human milk mineral patterns, human milk metabolomic profile and infant growth.MethodsA total of 200 breast milk samples from seven cities in China was included. Human milk mineral and trace elements was detected by inductively coupled plasma mass spectrometer (ICP-MS). K-means cluster analysis was utilized to derived human milk mineral patterns. Untargeted human milk metabolomic profiles was determined using high performance liquid chromatography–tandem mass spectrometry (HPLC–MS/MS). Differences of infant growth rate and metabolomic profiles were then compared across patterns identified.ResultsThree human milk mineral patterns were identified. Cluster I was characterized as the highest levels of potassium, magnesium and calcium, while the lowest levels of copper, zinc, manganese and selenium. Cluster II showed the most abundant sodium, iron, zinc, manganese and selenium. Cluster III had the lowest levels of sodium, potassium, magnesium, iron and calcium. Infants of cluster I showed significantly higher length-for-age z score (0.60 ± 2.03, p = 0.03). Compared with other clusters, samples of cluster I showed lower expression of metabolites of arachidonic acid (ARA) and nicotinate and nicotinamide metabolism pathway.DiscussionA human milk mineral pattern was identified which is related to increased infant growth rate and altered metabolic signature. Future work is needed to understand these human milk patterns in terms of biologic mechanisms and generalization to other populations.
Natural products for Gut-X axis: pharmacology, toxicology and microbiology in mycotoxin-caused diseases
Authors: Li Kaiqi , Wang Shiqi , Qu Wuyi , Ahmed Abdelkareem A. , Enneb Wael , Obeidat Mohammad Diya’ , Liu Hao-Yu , Dessie Tadelle , Kim In Ho , Adam Saber Y. , Cai Demin 
Published: June 2024

Introduction: The gastrointestinal tract is integral to defending against external contaminants, featuring a complex array of immunological, physical, chemical, and microbial barriers. Mycotoxins, which are toxic metabolites from fungi, are pervasive in both animal feed and human food, presenting substantial health risks.Methods: This review examines the pharmacological, toxicological, and microbiological impacts of natural products on mycotoxicosis, with a particular focus on the gut-x axis. The analysis synthesizes current understanding and explores the role of natural products rich in polysaccharides, polyphenols, flavonoids, and saponins. Results: The review highlights that mycotoxins can disrupt intestinal integrity, alter inflammatory responses, damage the mucus layer, and disturb the bacterial balance. The toxins' effects are extensive, potentially harming the immune system, liver, kidneys, and skin, and are associated with serious conditions such as cancer, hormonal changes, genetic mutations, bleeding, birth defects, and neurological issues. Natural products have shown potential anticancer, anti-tumor, antioxidant, immunomodulatory, and antitoxic properties.Discussion: The review underscores the emerging therapeutic strategy of targeting gut microbial modulation. It identifies knowledge gaps and suggests future research directions to deepen our understanding of natural products' role in gut-x axis health and to mitigate the global health impact of mycotoxin-induced diseases.
A systematic review and meta-analysis assessing the efficacy of Tuina for nocturnal enuresis in children
Authors: Chen Xin , Sun Wei-jie , Wang Jing-rong , Cai Ying-ying , Yu Xiao-dan 
Published: June 2024

Background: Desmopressin acetate (DDAVP) and behavioral interventions (BI) are cornerstone treatments for nocturnal enuresis (NE), a common pediatric urinary disorder. Despite the growing body of clinical studies on massage therapy for NE, comprehensive evaluations comparing the effectiveness of Tuina with DDAVP or BI are scarce. This study aims to explore the efficacy of Tuina in the management of NE.Methods: A systematic search of international databases was conducted using keywords pertinent to Tuina and NE. The inclusion criteria were limited to randomized controlled trials (RCTs) that evaluated NE treatments utilizing Tuina against DDAVP or BI. This meta-analysis included nine RCTs, comprising a total of 685 children, to assess both complete and partial response rates.Results: Tuina, used as a combination therapy, showed enhanced clinical efficacy and improved long-term outcomes relative to the control group. The therapeutic efficacy of Tuina was not directly associated with the number of acupoints used. Instead, employing between 11 and 20 acupoints appeared to have the most significant effect.Conclusion: The findings of this meta-analysis support the potential of Tuina as an adjunct therapy to enhance the sustained clinical efficacy of traditional treatments for NE. However, Tuina cannot completely replace DDAVP or BI in the management of NE. While this study illuminates some aspects of the effective acupoint combinations, further research is crucial to fully understand how Tuina acupoints contribute to the treatment of NE in children.Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=442644, identifier CRD42023442644.
Comparative effectiveness of clozapine and non-clozapine atypical antipsychotics provided by the Brazilian National Health System in adults with schizophrenia
Authors: Vieira Júlio César Menezes , Reis Edna Afonso , Guerra Augusto Afonso , Oliveira Helian Nunes de , Ruas Cristina Mariano 
Published: June 2024

IntroductionCurrently, 21 million people live with the disease, mostly in low to middle-income countries. We aimed to assess the survival of patients with schizophrenia using clozapine compared with non-clozapine atypical antipsychotics provided by the Brazilian National Health System using real-world data.Materials and methodsThis is an open retrospective cohort study of patients diagnosed with schizophrenia to whom atypical antipsychotics were dispensed by the Brazilian National Health System between 2000 and 2015, based on deterministic-probabilistic pairing of administrative data records. The Kaplan-Meier method was used to estimate the cumulative probability of survival and the Cox proportional hazards model was adjusted to assess the risk factors for survival via the hazard ratio (HR).ResultParticipants were 375,352 adults with schizophrenia, with an overall survival rate of 76.0% (95%CI 75.0–76.0) at the end of the cohort. Multivariate analysis indicated a greater risk of death for men (HR=1.30; 95%CI 1.27–1.32), older adults (HR=17.05; 95%CI 16.52–17.60), and in the Southeast region of Brazil (HR=1.20; 95%CI 1.17–1.23). Patients who used non-clozapine atypical antipsychotics had a 21% greater risk of death when compared to those taking clozapine (HR=1.21; 95%CI 1.14–1.29). Additionally, a history of hospitalization for pneumonia (HR=2.17; 95%CI 2.11–2.23) was the main clinical variable associated with increased risk of death, followed by hospitalization for lung cancer (HR=1.82; 95%CI 1.58–2.08), cardiovascular diseases (HR=1.44; 95%CI 1.40–1.49) and any type of neoplasia (HR=1.29; 95%CI 1.19–1.40).DiscussionThis is the first published Brazilian cohort study that evaluated survival in people with schizophrenia, highlighting the impact of atypical antipsychotics. In this real-world analysis, the use of clozapine had a protective effect on survival when compared to olanzapine, risperidone, quetiapine, and ziprasidone.
Study on the relationship between body mass index and blood pressure indices in children aged 7–17 during COVID-19
Authors: Mao SuJie , Qian GuoPing , Xiao KaiWen , Xu Hong , Zhou Hao , Guo XiuJin 
Published: June 2024

BackgroundTo explore the relationship between body mass index (BMI), age, sex, and blood pressure (systolic blood pressure, SBP; diastolic blood pressure, DBP) in children during COVID-19, providing reference for the prevention and screening of hypertension in children.MethodsThis study adopted a large-scale cross-sectional design to investigate the association between BMI and blood pressure in 7-17-year-old students in City N, China, during COVID-19. Thirty-six primary and secondary schools in City N were sampled using a stratified cluster sampling method. A total of 11,433 students aged 7–17 years in City N, China, were selected for blood pressure (Diastolic blood pressure, DBP, Systolic blood pressure, SBP), height, and weight, Resting heart rate (RHR), chest circumference, measurements, and the study was written using the STROBE checklist. Data analysis was conducted using SPSS 26.0, calculating the mean and standard deviation of BMI and blood pressure for male and female students in different age groups. Regression analysis was employed to explore the impact of BMI, age, and sex on SBP and DBP, and predictive models were established. The model fit was evaluated using the model R2.ResultsThe study included 11,287 primary and secondary school students, comprising 5,649 boys and 5,638 girls. It was found that with increasing age, BMI and blood pressure of boys and girls generally increased. There were significant differences in blood pressure levels between boys and girls in different age groups. In regression models, LC, Age, BMI, and chest circumference show significant positive linear relationships with SBP and DBP in adolescents, while RHR exhibits a negative linear relationship with SBP. These factors were individually incorporated into a stratified regression model, significantly enhancing the model’s explanatory power. After including factors such as Age, Gender, and BMI, the adjusted R2 value showed a significant improvement, with Age and BMI identified as key predictive factors for SBP and DBP. The robustness and predictive accuracy of the model were further examined through K-fold cross-validation and independent sample validation methods. The validation results indicate that the model has a high accuracy and explanatory power in predicting blood pressure in children of different weight levels, especially among obese children, where the prediction accuracy is highest.ConclusionDuring COVID-19, age, sex, and BMI significantly influence blood pressure in children aged 7–17 years, and predictive models for SBP and DBP were established. This model helps predict blood pressure in children and reduce the risk of cardiovascular diseases. Confirmation of factors such as sex, age, and BMI provide a basis for personalized health plans for children, especially during large-scale infectious diseases, providing guidance for addressing health challenges and promoting the health and well-being of children.