bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting the risk of gastroparesis in critically ill patients after CME using an interpretable machine learning algorithm – a 10-year multicenter retrospective study
Authors: Liu Yuan , Zhao Songyun , Du Wenyi , Shen Wei , Zhou Ning 
Published: January 2025

BackgroundGastroparesis following complete mesocolic excision (CME) can precipitate a cascade of severe complications, which may significantly hinder postoperative recovery and diminish the patient’s quality of life. In the present study, four advanced machine learning algorithms—Extreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), and k-nearest neighbor (KNN)—were employed to develop predictive models. The clinical data of critically ill patients transferred to the intensive care unit (ICU) post-CME were meticulously analyzed to identify key risk factors associated with the development of gastroparesis.MethodsWe gathered 34 feature variables from a cohort of 1,097 colon cancer patients, including 87 individuals who developed gastroparesis post-surgery, across multiple hospitals, and applied a range of machine learning algorithms to construct the predictive model. To assess the model’s generalization performance, we employed 10-fold cross-validation, while the receiver operating characteristic (ROC) curve was utilized to evaluate its discriminative capacity. Additionally, calibration curves, decision curve analysis (DCA), and external validation were integrated to provide a comprehensive evaluation of the model’s clinical applicability and utility.ResultsAmong the four predictive models, the XGBoost algorithm demonstrated superior performance. As indicated by the ROC curve, XGBoost achieved an area under the curve (AUC) of 0.939 in the training set and 0.876 in the validation set, reflecting exceptional predictive accuracy. Notably, in the k-fold cross-validation, the XGBoost model exhibited robust consistency across all folds, underscoring its stability. The calibration curve further revealed a favorable concordance between the predicted probabilities and the actual outcomes of the XGBoost model. Additionally, the DCA highlighted that patients receiving intervention under the XGBoost model experienced significantly greater clinical benefit.ConclusionThe onset of postoperative gastroparesis in colon cancer patients remains an elusive challenge to entirely prevent. However, the prediction model developed in this study offers valuable assistance to clinicians in identifying key high-risk factors for gastroparesis, thereby enhancing the quality of life and survival outcomes for these patients.
Screening key genes for intracranial aneurysm rupture using LASSO regression and the SVM-RFE algorithm
Authors: Wu Qi , Yang Chunli , Huang Cuilan , Lin Zhiying 
Published: January 2025

BackgroundAlthough an intracranial aneurysm (IA) is widespread and fatal, few drugs can be used to prevent its rupture. This study explored the molecular mechanism and potential targets of IA rupture through bioinformatics methods.MethodsThe gene expression matrices of GSE13353, GSE122897, and GSE15629 were downloaded. Differentially expressed genes (DEGs) were screened using the limma package. Functional enrichment analysis was performed, and a PPI network was constructed. Furthermore, candidate key genes were identified using the least absolute shrinkage and selection operator (LASSO) regression model, support vector machine-recursive feature elimination (SVM-RFE) analysis, and PPI network analysis. ROC analysis was conducted to further verify the diagnostic value of the key genes.ResultsA total of 334 DEGs were screened, including 175 upregulated genes and 159 downregulated genes. Further functional analysis suggested that the DEGs were enriched in inflammation and immune response pathways. Fourteen hub genes were identified using the two algorithms. The PPI networks of the hub genes were analyzed using the Cytoscape plugin CytoNCA to obtain two key genes (IL10 and Integrin α5 (ITGA5)). The ROC curve analysis showed that the AUC values of IL10 and ITGA5 were 0.801, and 0.786, respectively. In addition, the two key genes were significantly positively correlated with macrophages and Treg (T) cells. The immune score and ESTIMATE score of the ruptured IA group were significantly higher than those of the unruptured IA group.ConclusionThe increase in IL-10 and ITGA5 may weaken the vascular wall by promoting inflammation in blood vessels and immune cells, which could have a harmful effect on the rupture of IAs.
Blood urea nitrogen-to-albumin ratio as a new prognostic indicator of 1-year all-cause mortality in patients with IPF
Authors: Ge Shaobo , Li Yuer , Li Rui , Liu Jin , Zhang Rui , Fu Hongyan , Tang Jingjing , Zhang Jie , Zhang Nali , Zhang Ming 
Published: January 2025

BackgroundIdiopathic pulmonary fibrosis (IPF) is an interstitial lung disease characterized by chronic inflammation and progressive fibrosis. The blood urea nitrogen-to-albumin ratio (BAR) is a comprehensive parameter associated with inflammation status; however, it is unknown whether the BAR can predict the prognosis of IPF.MethodsThis retrospective study included 176 patients with IPF, and 1-year all-cause mortality of these patients was recorded. A receiver operating characteristic (ROC) curve was used to explore the diagnostic value of BAR for 1-year all-cause mortality in IPF patients, and the survival rate was further estimated using the Kaplan–Meier survival curve. Cox proportional hazards regression model and forest plot were used to assess the association between the BAR and 1-year all-cause mortality in IPF patients.ResultsThe BAR of IPF patients was significantly higher in the non-survivor group than in the survivor group [0.16 (0.13–0.23) vs. 0.12 (0.09–0.17) mmol/g, p = 0.002]. The area under the ROC curve for predicting 1-year all-cause mortality in IPF patients was 0.671, and the optimal cut-off value was 0.12 mmol/g. The Kaplan–Meier survival curve showed that the 1-year cumulative survival rate of IPF patients with a BAR ≥0.12 was significantly decreased compared with the patients with a BAR &lt;0.12. The Cox regression model and forest plot showed that the BAR was an independent prognostic biomarker for 1-year all-cause mortality in IPF patients (HR = 2.778, 95% CI 1.020–7.563, p = 0.046).ConclusionThe BAR is a significant predictor of 1-year all-cause mortality of IPF patients, and high BAR values may indicate poor clinical outcomes.
Improving ADR reporting in Jordan: a qualitative exploration of pharmacists’ perspectives
Authors: Suleiman Amal K. 
Published: January 2025

BackgroundCommunity pharmacists are most accessible to patients. Hence, they have a crucial role in ensuring drug safety by detecting and reporting adverse drug reactions (ADRs). However, there may be gaps in their knowledge of ADR reporting systems and barriers they face in reporting.ObjectiveThis study aims to assess community pharmacists’ knowledge of ADR reporting systems in the Kingdom of Jordan, identify the barriers they face in reporting ADRs, and explore the broader factors that influence their involvement in pharmacovigilance activities.MethodsIn-depth, semi-structured, face-to-face interviews were held with 20 community pharmacists from different regions of Jordan to evaluate their understanding of ADR reporting, the obstacles they encountered, and the elements that could motivate them to report ADRs. The interviews were transcribed and subjected to thematic analysis to find recurrent themes and insights. The thematic analysis highlighted opportunities for continuing education and an absence of formal training as the main barriers to ADR reporting.ResultsPharmacists reported dissatisfaction with time limits in their hectic work situations and the complexity of reporting procedures, especially the length and information demanded by ADR reporting forms. Another factor influencing low reporting rates was a perceived lack of acknowledgment and feedback. Participants proposed that encouraging ADR reporting with professional recognition or compensation and improving and digitizing the reporting process would promote increased participation.ConclusionADR reporting presents considerable difficulties for community pharmacists in Jordan, mostly because of administrative obstacles and an absence of official support and training. Enhancing pharmacovigilance efforts in Jordan could be achieved by providing incentives, simplifying the reporting procedure, and incorporating reporting into the current pharmacy management software.
Sarcopenia is a risk factor for postoperative delirium in geriatric hip fracture patients: a retrospective study
Authors: Qi Yi-Ming , Li Hao-Tao , Chang Shi-Min , Hu Sun-Jun , Du Shou-Chao , Liu Chen-Dong , Chu Yong-Qian , Rui Yun-Feng 
Published: January 2025

BackgroundVarious factors contribute to postoperative delirium (POD) in elderly patients undergoing hip fracture surgeries. Sarcopenia was defined as the progressive loss of skeletal muscle mass and strength associated with aging. The aim of this study was to explore the prevalence of POD and sarcopenia in geriatric patients undergoing hip fracture surgeries and to investigate the correlation between preoperative sarcopenia and POD.MethodsAfter applying specific inclusion and exclusion criteria, the information of 234 patients were retrospectively collected. POD was screened for with 4A’s Test and diagnosed with DSM-5 criteria. The incidences of POD and sarcopenia were calculated. The demographic and perioperative features as well as comorbidities of delirious and non-delirious patients were analyzed and the risk factors analysis for POD in elderly hip fracture patients were conducted through univariate analysis and multivariate regression analysis.Results48.7% patients were diagnosed of POD, 78.95% of which were females. The average age of delirious and non-delirious patients were 84.75 years and 80.63 years, respectively. The incidence of sarcopenia was 41.02% for all the included patients with 60.53% for delirious patients and 20.55% for non-delirious patients. Results of univariate analysis showed that sarcopenia (OR:5.281, 95%CI 2.988–9.337, p = 0.000), age increase per year (OR:1.128, 95CI 1.070–1.190, p = 0.000), operation duration increase (OR:1.017, 95%CI 1.004–1.030, p = 0.011), intertrochanteric fracture (OR:2.571, 95%CI 1.517–4.358, p = 0.000), dementia (OR: 6.029, 95%CI 2.532–14.359, p = 0.000), ASA &gt; 2 (OR: 6.955, 95%CI 3.461–13.976, p = 0.000), coronary heart disease (OR: 2.201, 95%CI 1.257–3.854, p = 0.006), renal insufficiency (OR: 2.215, 95%CI 1.187–4.133, p = 0.012) and COPD (OR: 2.554, 95%CI 1.414–4.615, p = 0.002) were risk factors for POD. Results of multivariate analysis identified sarcopenia (OR: 2.457, 95% CI 1.226–4.923, p = 0.011), ASA &gt; 2 (OR: 3.968, 95% CI 1.805–8.722, p = 0.001), dementia (OR: 3.912, 95% CI 1.390–11.014, p = 0.010) and coronary heart disease (OR: 2.176, 95% CI 1.044–4.538, p = 0.038) as independent risk factors for POD in geriatric hip fracture patients.ConclusionThe incidences of POD and sarcopenia in geriatric hip fracture patients are high. Sarcopenia is an independent risk factor for POD in geriatric hip fracture patients.
The role of neutrophilia in hyperlactatemia, blood acidosis, impaired oxygen transport, and mortality outcome in critically ill COVID-19 patients
Authors: Yasseen Basma A. , Elkhodiry Aya A. , El-sayed Hajar , Zidan Mona , Kamel Azza G. , Badawy Mohamed A. , Hamza Marwa S. , El-Messiery Riem M. , El Ansary Mohamed , Abdel-Rahman Engy A. , Ali Sameh S. 
Published: January 2025

IntroductionCOVID-19 severity and high in-hospital mortality are often associated with severe hypoxemia, hyperlactatemia, and acidosis, yet the key players driving this association remain unclear. It is generally assumed that organ damage causes toxic acidosis, but since neutrophil numbers in severe COVID-19 can exceed 80% of the total circulating leukocytes, we asked if metabolic acidosis mediated by the glycolytic neutrophils is associated with lung damage and impaired oxygen delivery in critically ill patients.MethodsBased on prospective mortality outcome, critically ill COVID-19 patients were divided into ICU- survivors and ICU-non-survivors. Samples were analyzed to explore if correlations exist between neutrophil counts, lung damage, glycolysis, blood lactate, blood pH, hemoglobin oxygen saturation, and mortality outcome. We also interrogated isolated neutrophils, platelets, and PBMCs for glycolytic activities.ResultsArterial blood gas analyses showed remarkable hypoxemia in non-survivors with no consistent differences in PCO2 or [HCO3−]. The hemoglobin oxygen dissociation curve revealed a right-shift, consistent with lower blood-pH and elevated blood lactate in non-survivors. Metabolic analysis of different blood cells revealed increased glycolytic activity only when considering the total number of neutrophils.ConclusionThis indicates the role of neutrophilia in hyperlactatemia and lung damage, subsequently contributing to mortality outcomes in severe SARS-CoV-2 infection.
Self-reported health, persistent symptoms, and daily activities 2 years after hospitalization for COVID-19
Authors: Alhasan Roda , Rafsten Lena , Larsson Alexandra C. , Sunnerhagen Katharina S. , Persson Hanna C. 
Published: January 2025

IntroductionSince the onset of the COVID-19 pandemic, 775 million cases have been reported globally. While many individuals recover fully, a significant proportion develop persistent symptoms. Numerous studies have investigated the long-term symptoms of COVID-19; however, the full extent and impact of these symptoms remain inadequately understood. The aim of this study was to investigate the prevalence of self-reported persistent symptoms, focusing on respiratory symptoms and fatigue and the impact on functional status 2 years after hospitalization for COVID-19.MethodsThis study is prospective and includes participants from a longitudinal multi-center cohort that follows patients previously hospitalized due to COVID-19 (n = 211). The current study encompasses the 2-year follow-up, using post-hospitalization questionnaire surveys. Analyzed data were collected before discharge and at the 2-year follow-up. Participants were grouped by age, sex and COVID-19 severity and group comparisons where conducted. Logistic regression analysis was used to study functional impairment.ResultsTwo years after hospital discharge due to COVID-19, 125 participants completed the 2-year follow-up. The mean age of participants was 66 years (SD 12.2), and 68% were male. The majority of participants reported present respiratory symptoms (n = 83, 69%) and fatigue (n = 98, 78%) at the 2-year follow-up. Persistent respiratory symptoms and fatigue impacted functional status substantially (p = &lt;0.001, p = 0.028, respectively). No significant differences were observed among groups depending on age, sex, or severity of COVID-19.ConclusionFor some individuals regardless of age, sex or COVID-19 severity, respiratory symptoms and fatigue may persist for up to 2 years following COVID-19. Hence, having available support from professionals knowledgeable about COVID-19 is imperative. Further research is important to unravel the mechanisms of long-term symptoms following COVID-19 and to develop effective therapeutic and rehabilitative interventions.
Utilizing machine-learning techniques on MRI radiomics to identify primary tumors in brain metastases
Authors: Yang W. L. , Su X. R. , Li S. , Zhao K. Y. , Yue Q. 
Published: January 2025

ObjectiveTo develop a machine learning-based clinical and/or radiomics model for predicting the primary site of brain metastases using multiparametric magnetic resonance imaging (MRI).Materials and methodsA total of 202 patients (87 males, 115 females) with 439 brain metastases were retrospectively included, divided into training sets (brain metastases of lung cancer [BMLC] n = 194, brain metastases of breast cancer [BMBC] n = 108, brain metastases of gastrointestinal tumor [BMGiT] n = 48) and test sets (BMLC n = 50, BMBC n = 27, BMGiT n = 12). A total of 3,404 quantitative image features were obtained through semi-automatic segmentation from MRI images (T1WI, T2WI, FLAIR, and T1-CE). Intra-class correlation coefficient (ICC) was used to examine segmentation stability between two radiologists. Radiomics features were selected using analysis of variance (ANOVA), recursive feature elimination (RFE), and Kruskal–Wallis test. Three machine learning classifiers were used to build the radiomics model, which was validated using five-fold cross-validation on the training set. A comprehensive model combining radiomics and clinical features was established, and the diagnostic performance was compared by area under the curve (AUC) and evaluated in an independent test set.ResultsThe radiomics model differentiated BMGiT from BMLC (13 features, AUC = 0.915 ± 0.071) or BMBC (20 features, AUC = 0.954 ± 0.064) with high accuracy, while the classification between BMLC and BMBC was unsatisfactory (11 features, AUC = 0.729 ± 0.114). However, the combined model incorporating radiomics and clinical features improved the predictive performance, with AUC values of 0.965 for BMLC vs. BMBC, 0.991 for BMLC vs. BMGiT, and 0.935 for BMBC vs. BMGiT.ConclusionThe machine learning-based radiomics model demonstrates significant potential in distinguishing the primary sites of brain metastases, and may assist screening of primary tumor when brain metastasis is suspected whereas history of primary tumor is absent.
Advances in fear memory erasure and its neural mechanisms
Authors: Guo Wenbo , Wang Xibo , Zhou Zihan , Li Yuhui , Hou Yani , Wang Keyan , Wei Ruyuan , Ma Xiaoyu , Zhang Hao 
Published: January 2025

BackgroundIn nature, animals must learn to recognize danger signals and respond immediately to threats to improve their environmental adaptation. However, excessive fear responses can lead to diseases such as post-traumatic stress disorder, wherein traumatic events result in persistent traumatic memories. Therefore, erasing pathological fear memories in vivo is a crucial topic in neuroscience for understanding the nature of memories and treating clinically relevant diseases.Main textThis article reviews recent studies on fear memory erasure, erasure of short- and long-term memory, fear memory erasure and neuroplasticity, the neural circuitry and molecular mechanisms of fear memory erasure, and the roles of engram cells and perineuronal nets in memory erasure.ConclusionResearch on the mechanism of memory erasure is limited, and a plausible explanation for the essential difference between memory erasure and memory extinction still needs to be provided. Notably, this review may guide future studies on fear memory and its underlying molecular mechanisms, which may help to develop novel treatment strategies for post-traumatic stress disorder, anxiety, and other mental disorders.
Exploring the role of epileptic focus lateralization on facial emotion recognition in the spectrum of mesial temporal lobe epilepsy
Authors: Iannaccone Fabio , Pizzanelli Chiara , Lorenzini Francesca , Turco Francesco , Milano Chiara , Scarpitta Claudia , Tommasini Luca , Tognoni Gloria , Morganti Riccardo , Bonanni Enrica , Siciliano Gabriele 
Published: January 2025

IntroductionEvidence increasingly shows that facial emotion recognition (FER) is impaired in refractory mesial temporal lobe epilepsy (rMTLE), especially in patients with a right focus. This study explores FER in both mild (mMTLE) and refractory forms, examining the influence of epileptic focus lateralization on FER.Methods50 MTLE patients, categorized by epilepsy severity and focus lateralization, were compared with healthy controls. FER was assessed using the Ekman Faces Test (EFT), which evaluates recognition of six basic emotions, alongside a battery of cognitive and mood tests.ResultsmMTLE patients showed selective deficits in recognizing fear and anger, while rMTLE patients displayed broader deficits, affecting all emotions except surprise. Patients with a right focus underperformed across all negative emotions, whereas those with a left focus showed deficits mainly in fear and anger. Analysis indicated that early epilepsy onset was associated with poorer FER in right-focused patients; febrile seizures and mesial temporal sclerosis significantly impacted FER in left-focused patients.ConclusionMTLE affects circuits of FER even in mild subjects, although to a lesser extent than in refractory ones. Earlier onset of MTLE could disrupt the development of FER, possibly interfering during a critical phase of maturation of its circuits, when the focus is right. Conversely, left MTLE may cause less damage to FER circuits, requiring additional factors such as a history of febrile seizures and/or mesial temporal sclerosis for significant impact. Clinically, refractory and right-sided MTLE might be viewed as risk factors of FER deficits.
Evidence summary of lifestyle interventions in adults with metabolic dysfunction-associated steatotic liver disease
Authors: Chen Mei-jing , Chen Ying , Lin Jin-qing , Hu Rong , Liu Dun , Chen Jing-yi , Li Ka , Jiang Xiao-ying 
Published: January 2025

ObjectiveIn this study, our objective was to provide practice recommendations by thoroughly examining lifestyle interventions for adults diagnosed with metabolic dysfunction-associated steatotic liver disease (MASLD). This was achieved through a systematic review of the literature, specifically focusing on lifestyle modification interventions in adults with MASLD.MethodsThe PIPOST (Population, Intervention, Professional, Outcome, Setting, and Type of evidence) framework was used to identify the questions for summarizing evidence. Utilizing the 6S model for the hierarchy of evidence, a computerized search was conducted to retrieve articles pertaining to lifestyle interventions for adults with MASLD from websites such as the UpToDate Clinical Advisor, BMJ Best Practice, JBI Library, Cochrane Library, International Guidelines Library, and PubMed, among others. The available research included clinical decisions, clinical practice guidelines, evidence summaries, systematic evaluation, expert consensus, and expert opinions. Two researchers independently evaluated the methodology of the studies, and evidence was subsequently extracted and grouped thematically. Our review encompassed publications from January 2018 to March 2023.ResultsA total of 26 publications were identified for the final review, consisting of seven guidelines, nine systematic evaluations, and 10 expert consensuses/opinions. From these sources, we derived six themes, 28 pieces of evidence: intervention modalities, diet management, exercise management, weight loss management, personalized management, and multidisciplinary collaboration.ConclusionIn the management of adults with MASLD, healthcare professionals should embrace a multidisciplinary team approach, adhere to the best available evidence, and develop structured and personalized interventions based on the best evidence for lifestyle modifications.