bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of electronic records on mortality among patients in hospital and primary healthcare settings: a systematic review and meta-analyses
Authors: Bogale Tariku Nigatu , Derseh Lemma , Abraham Loko , Willems Herman , Metzger Jonathan , Abere Biruhtesfa , Tilaye Mesfin , Hailegeberel Tewodros , Bekele Tadesse Alemu 
Published: June 2024

BackgroundElectronic medical records or electronic health records, collectively called electronic records, have significantly transformed the healthcare system and service provision in our world. Despite a number of primary studies on the subject, reports are inconsistent and contradictory about the effects of electronic records on mortality. Therefore, this review examined the effect of electronic records on mortality.MethodsThe review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses 2020 guideline. Six databases: PubMed, EMBASE, Scopus, CINAHL, Cochrane Library, and Google Scholar, were searched from February 20 to October 25, 2023. Studies that assessed the effect of electronic records on mortality and were published between 1998 and 2022 were included. Joanna Briggs Institute quality appraisal tool was used to assess the methodological quality of the studies. Narrative synthesis was performed to identify patterns across studies. Meta-analysis was conducted using fixed effect and random-effects models to estimate the pooled effect of electronic records on mortality. Funnel plot and Egger's regression test were used to assess for publication bias.ResultsFifty-four papers were found eligible for the systematic review, of which 42 were included in the meta-analyses. Of the 32 studies that assessed the effect of electronic health record on mortality, eight (25.00%) reported a statistically significant reduction in mortality, 22 (68.75%) did not show a statistically significant difference, and two (6.25%) studies reported an increased risk of mortality. Similarly, among the 22 studies that determined the effect of electronic medical record on mortality, 12 (54.55%) reported a statistically significant reduction in mortality, and ten (45.45%) studies didn't show a statistically significant difference. The fixed effect and random effects on mortality were OR = 0.95 (95% CI: 0.93–0.97) and OR = 0.94 (95% CI: 0.89–0.99), respectively. The associated I-squared was 61.5%. Statistical tests indicated that there was no significant publication bias among the studies included in the meta-analysis.ConclusionDespite some heterogeneity among the studies, the review indicated that the implementation of electronic records in inpatient, specialized and intensive care units, and primary healthcare facilities seems to result in a statistically significant reduction in mortality. Maturity level and specific features may have played important roles.Systematic Review RegistrationPROSPERO (CRD42023437257).
Universal machine learning approach to volcanic eruption forecasting using seismic features
Authors: Rey-Devesa Pablo , Carthy Joe , Titos Manuel , Prudencio Janire , Ibáñez Jesús M. , Benítez Carmen 
Published: June 2024

Introduction: Volcano seismology has successfully predicted several eruptions and includes many reliable methods that have been adopted extensively by volcanic observatories; however, there are several problems that still lack solutions. Meanwhile, the overwhelming success of data-driven models to solve predictive complex real-world problems positions them as an effective addition to the monitoring systems deployed in volcanological observatories.Methods: By applying signal processing techniques on seismic records, we extracted four different seismic features, which usually change their trend when the system is approaching an eruptive episode. We built a temporal matrix with these parameters then defined a label for each temporal moment according to the real state of the volcanic activity (Unrest, Pre-Eruptive, Eruptive). To solve the remaining problem developing early warning systems that are transferable between volcanoes, we applied our methodology to databases associated with different volcanic systems, including data from both explosive and effusive episodes, recorded at several volcanic scenarios with open and closed conduits: Mt. Etna, Bezymianny, Volcán de Colima, Mount St. Helens and Augustine.Results and Discussion: This work proposes the use of Neural Networks to classify the volcanic state of alert based on the behaviour of these features, providing a probability of having an eruption. This approach offers a Machine Learning tool for probabilistic short-term volcanic eruption forecasting, transferable to different volcanic systems. This innovative method classifies the state of volcanic hazard in near real-time and estimates a probability of the occurrence of an eruption, resulting in a period from at least hours to several days to forecast an eruption.
Associations of oxidative balance score with hyperuricemia and gout among American adults: a population-based study
Authors: Wang Kai , Wu Jinyi , Deng Minggang , Nie Jiaqi , Tao Fengxi , Li Qingwen , Luo Xin , Xia Fang 
Published: June 2024

ObjectiveThe current study aimed to assess the relationships between oxidative balance score (OBS) and OBS subclasses (dietary and lifestyle OBS) with risks of hyperuricemia (HUA) and gout among American adults.MethodsParticipants in the National Health and Nutrition Examination Survey from 2007 to 2018 were initially recruited and then the final sample was restricted to adults without missing values about serum uric acid, gout, OBS, and covariates. Rao-Scott adjusted chi-square test and analysis of variance were utilized to compare the baseline characteristics in adults of different quartiles of OBS, while the weighted stepped logistic regression models were used to explore the associations of overall, dietary, and lifestyle OBS with the risks of HUA and gout. Weighted restricted cubic spline analyses were conducted to explore the nonlinear dose-response associations.ResultsThe final sample consisted of 22,705 participants aged 20 years and older, which was representative of approximately 197.3 million non-institutionalized American adults. HUA and gout prevalence decreased with OBS quartiles. Compared with adults in the first quartile of OBS, those in the second (OR: 0.85, 95% CI: 0.72–0.99), third (OR: 0.71, 95% CI: 0.58–0.85), and fourth (OR: 0.48, 95% CI: 0.38–0.61) quartiles of OBS had reduced risks of hyperuricemia. Similarly, adults in the second (OR: 0.70, 95% CI: 0.51–0.97) quartile of OBS was associated with lower gout risk in comparison to adults in the lowest quartile. Regarding OBS subclasses, dietary and lifestyle OBS were both negatively correlated with the risk of HUA, and only higher lifestyle OBS was significantly associated with lower gout risk. Furthermore, the subgroup analyses and interaction effects also substantiated similar effects. Significant nonlinear dose-response relationships were observed between overall, dietary, and lifestyle OBS with HUA risk as well as that of lifestyle OBS with gout risk.ConclusionThis study strongly suggests the significant negative associations of OBS with HUA and gout in American adults and provides a dietary and lifestyle guideline to reduce the risks.
The circadian syndrome is a better predictor for psoriasis than the metabolic syndrome via an explainable machine learning method — the NHANES survey during 2005–2006 and 2009–2014
Authors: Gu Yunfan , Ye Xinglan , Zhao Wenting , He Shiwei , Zhang Weiming , Zeng Xianyu 
Published: June 2024

ObjectiveTo explore the association between circadian syndrome (CircS) and Metabolic Syndrome (MetS) with psoriasis. Compare the performance of MetS and CircS in predicting psoriasis.MethodsAn observational study used data from the NHANES surveys conducted in 2005–2006 and 2009–2014. We constructed three multiple logistic regression models to investigate the relationship between MetS, CircS, and their components with psoriasis. The performance of MetS and CircS in predicting psoriasis was compared using five machine-learning algorithms, and the best-performing model was explained via SHAP. Then, bidirectional Mendelian randomization analyses with the inverse variance weighted (IVW) as the primary method were employed to determine the causal effects of each component.ResultA total of 9,531 participants were eligible for the study. Both the MetS (OR = 1.53, 95%CI: 1.07–2.17, P = 0.02) and CircS (OR = 1.40, 95%CI: 1.02–1.91, P = 0.039) positively correlated with psoriasis. Each CircS algorithmic model performs better than MetS, with Categorical Features+Gradient Boosting for CircS (the area under the precision-recall curve = 0.969) having the best prediction effect on psoriasis. Among the components of CircS, elevated blood pressure, depression symptoms, elevated waist circumference (WC), and short sleep contributed more to predicting psoriasis. Under the IVW methods, there were significant causal relationships between WC (OR = 1.52, 95%CI: 1.34−1.73, P = 1.35e-10), hypertension (OR = 1.68, 95%CI: 1.19−2.37, P = 0.003), depression symptoms (OR = 1.39, 95%CI: 1.17−1.65, P = 1.51e-4), and short sleep (OR = 2.03, 95%CI: 1.21–3.39, p = 0.007) with psoriasis risk.ConclusionCircS demonstrated superior predictive ability for prevalent psoriasis compared to MetS, with elevated blood pressure, depression symptoms, and elevated WC contributing more to the prediction.
A dynamic reconfiguration model and method for load balancing in the snow-shaped distribution network
Authors: Luo Fengzhang , Wu Xuan , Wang Zhe , Duan Jiali 
Published: June 2024

The snow-shaped distribution network (SDN) is a cable distribution network composed of eight (or six) 10 kV feeders from four (or three) substations in a regular connection. Compared with the traditional 10 kV distribution network, SDN can support a wide range of load transfer among six or eight feeders. Aiming at the problem of load spatial-temporal unbalanced condition caused by the integration of distributed generators (DGs) and different load types in different feeders, this paper proposes a dynamic reconfiguration strategy for load balancing in SDN considering DGs and energy storage system (ESS). Firstly, the basic structure of SDN is analyzed and the power flow model for its dynamic reconfiguration is developed. Secondly, the dynamic reconfiguration optimization model for load balancing in SDN considering DGs and ESS is proposed to utilize the load transfer capability to mitigate the load unbalanced condition and reduce active power loss. Thirdly, the original non-convex model is converted into a mixed-integer second-order cone programming (MISOCP) model by applying the second-order cone relaxation and the big-M method, which is solved by CPLEX solver. Finally, the effectiveness of the proposed model and method are verified by an actual case in Tianjin and IEEE 33-node system. The analysis results show that the proposed method can significantly alleviate the load unbalanced spatial-temporal distribution and improve the economic efficiency by regulating the operation of SDN including ESS optimization and dynamic reconfiguration.
Non-viral-mediated gene transfer of OX40 ligand for tumor immunotherapy
Authors: Rakitina Olga A. , Kuzmich Alexey I. , Bezborodova Olga A. , Kondratieva Sofia A. , Pleshkan Victor V. , Zinovyeva Marina V. , Didych Dmitry A. , Sass Aleksandr V. , Snezhkov Eugene V. , Kostina Maria B. , Koksharov Maksim O. , Alekseenko Irina V. 
Published: June 2024

BackgroundImmune checkpoint blockade (ICB) is rapidly becoming a standard of care in the treatment of many cancer types. However, the subset of patients who respond to this type of therapy is limited. Another way to promote antitumoral immunity is the use of immunostimulatory molecules, such as cytokines or T cell co-stimulators. The systemic administration of immunotherapeutics leads to significant immune-related adverse events (irAEs), therefore, the localized antitumoral action is needed. One way to achieve this is intratumoral non-viral gene-immune therapy, which allows for prolonged and localized gene expression, and multiple drug administration. In this study, we combined the previously described non-viral gene delivery system, PEG-PEI-TAT copolymer, PPT, with murine OX40L-encoding plasmid DNA.MethodsThe resulting OX40L/PPT nanoparticles were characterized via gel mobility assay, dynamic light scattering analysis and in vitro transfection efficiency evaluation. The antitumoral efficacy of intratumorally (i.t.) administered nanoparticles was estimated using subcutaneously (s.c.) implanted CT26 (colon cancer), B16F0 (melanoma) and 4T1 (breast cancer) tumor models. The dynamics of stromal immune cell populations was analyzed using flow cytometry. Weight loss and cachexia were used as irAE indicators. The effect of combination of i.t. OX40L/PPT with intraperitoneal PD-1 ICB was estimated in s.c. CT26 tumor model.ResultsThe obtained OX40L/PPT nanoparticles had properties applicable for cell transfection and provided OX40L protein expression in vitro in all three investigated cancer models. We observed that OX40L/PPT treatment successfully inhibited tumor growth in B16F0 and CT26 tumor models and showed a tendency to inhibit 4T1 tumor growth. In B16F0 tumor model, OX40L/PPT treatment led to the increase in antitumoral effector NK and T killer cells and to the decrease in pro-tumoral myeloid cells populations within tumor stroma. No irAE signs were observed in all 3 tumor models, which indicates good treatment tolerability in mice. Combining OX40L/PPT with PD-1 ICB significantly improved treatment efficacy in the CT26 subcutaneous colon cancer model, providing protective immunity against CT26 colon cancer cells.ConclusionOverall, the anti-tumor efficacy observed with OX40L non-viral gene therapy, whether administered alone or in combination with ICB, highlights its potential to revolutionize cancer gene therapy, thus paving the way for unprecedented advancements in the cancer therapy field.
Relationship between frailty and depressive symptoms in older adults: role of activities of daily living and sleep duration
Authors: Song Wei , Liu Manyu , Ye Ting , Wang Dong , Yuan Quan , Li Fen , Wang Qiushi , Ma Yana 
Published: June 2024

IntroductionPrevious studies have demonstrated that frailty is associated with depressive symptoms among older people and significantly increase the risk of difficulty in activities of daily living (ADL). However, uncertainties remain regarding the mechanisms behind such relationship. The aim of this study was to investigate the mediating effect of ADL in the relationship between frailty and depressive symptoms among older adults in China, and to explore to what extend sleep duration moderated the association between ADL and depressive symptoms.MethodsIn this study, we carried out cross-sectional descriptive analysis and 1,429 participants were included in the analysis. A survey was conducted using questionnaires and instruments measuring frailty, depressive symptoms, ADL and sleep duration. Bootstrap analyses served to explore the impact of ADL in mediating frailty and depressed symptoms, as well as the effect of sleep duration in moderating ADL and depressive symptoms.ResultsCompared to the robust group, the mediating effects of ADL between frailty and depressive symptoms were significant in the prefrail group and the frail group. The interaction term between sleep duration and ADL was significantly presented in the regression on depressive symptoms. Specifically, the Johnson–Neyman technique determined a range from 8.31 to 10.19 h for sleep duration, within which the detrimental effect of frailty on depressive symptoms was offset.ConclusionSleep duration moderated the indirect effect of ADL on the association between frailty and depressive symptoms. This provides support for unraveling the underlying mechanism of the association between frailty and depressive symptoms. Encouraging older adults to enhance ADL and obtain appropriate sleep duration might improve depressive symptoms for older adults with frailty and prefrailty.
The association between ferritin levels and all-cause mortality in stroke patients
Authors: Xia Xuefen , Liu Jiongjiong , Fang Wenqiang , Chen Zhibo , Wang Jie , Xu Huiqin 
Published: June 2024

PurposeThe purpose of study was to describe the association between ferritin and all-cause mortality of cases with stroke.MethodsClinical data derived from Multiparameter Intelligent Monitoring in Intensive Care were analyzed. The primary endpoint was 30-day mortality. The potential prognostic roles of Ferritin L were analyzed by Cox proportional hazard models. The independent prognostic roles of Ferritin L in the cases were analyzed by smooth curve fitting.ResultsConcerning 30-day mortality, the HR (95% CI) for a high Ferritin (≥373) was 1.925 (1.298, 2.854; p = 0.00113), compared to a low ferritin (&lt; 373). After adjusting for multiple confounders, the HR (95% CI) for a high Ferritin (≥373) was 1.782 (1.126, 2.820; p = 0.01367), compared to a low Ferritin (&lt; 373). A non-linear association between Ferritin and 30-day mortality was found. Using recursive algorithm and two-piecewise linear regression model, inflection point (IP) was calculated, which was 2,204. On the left side of the IP, there was a positive relationship between Ferritin and 30-day mortality, and the effect size, 95% CI and p value were 1.0006 (1.0004, 1.0009) p &lt; 0.0001, respectively. On the right of the IP, the effect size, 95% CI and p value were 1.0000 (1.0000, 1.0000) and 0.3107, respectively.ConclusionFerritin was associated with increased risk of stroke; it is important to further examine the association if the increased uric acid would increase the outcome of stroke in a longitudinal study. The non-linear relationship between Ferritin and all-cause mortality of stroke was observed. Ferritin was a risk factor for the outcome of stroke when ferritin was &lt;2204.
Leveraging machine learning to develop a postoperative predictive model for postoperative urinary retention following lumbar spine surgery
Authors: Malnik Samuel L. , Porche Ken , Mehkri Yusuf , Yue Sijia , Maciel Carolina B. , Lucke-Wold Brandon P. , Robicsek Steven A. , Decker Matthew , Busl Katharina M. 
Published: June 2024

IntroductionPostoperative urinary retention (POUR) is the inability to urinate after a surgical procedure despite having a full bladder. It is a common complication following lumbar spine surgery which has been extensively linked to increased patient morbidity and hospital costs. This study hopes to development and validate a predictive model for POUR following lumbar spine surgery using patient demographics, surgical and anesthesia variables.MethodsThis is a retrospective observational cohort study of 903 patients who underwent lumbar spine surgery over the period of June 2017 to June 2019 in a tertiary academic medical center. Four hundred and nineteen variables were collected including patient demographics, ICD-10 codes, and intraoperative factors. Least absolute shrinkage and selection operation (LASSO) regression and logistic regression models were compared. A decision tree model was fitted to the optimal model to classify each patient’s risk of developing POUR as high, intermediate, or low risk. Predictive performance of POUR was assessed by area under the receiver operating characteristic curve (AUC-ROC).Results903 patients were included with average age 60 ± 15 years, body mass index of 30.5 ± 6.4 kg/m2, 476 (53%) male, 785 (87%) white, 446 (49%) involving fusions, with average 2.1 ± 2.0 levels. The incidence of POUR was 235 (26%) with 63 (7%) requiring indwelling catheter placement. A decision tree was constructed with an accuracy of 87.8%.ConclusionWe present a highly accurate and easy to implement decision tree model which predicts POUR following lumbar spine surgery using preoperative and intraoperative variables.
Cashew nut (Anacardium occidentale L.) and cashew nut oil reduce cardiovascular risk factors in adults on weight-loss treatment: a randomized controlled three-arm trial (Brazilian Nuts Study)
Authors: Meneguelli Talitha Silva , Kravchychyn Ana Claudia Pelissari , Wendling Aline Lage , Dionísio Ana Paula , Bressan Josefina , Martino Hercia Stampini Duarte , Tako Elad , Hermsdorff Helen Hermana Miranda 
Published: June 2024

IntroductionCashew nut contains bioactive compounds that modulate satiety and food intake, but its effects on body fat during energy restriction remains unknown. This study aimed to assess the effects of cashew nut and cashew nut oil on body fat (primary outcome) as well as adiposity, cardiometabolic and liver function markers (secondary outcomes).Materials and methodsAn eight-week (8-wk) randomized controlled-feeding study involved 68 adults with overweight/obesity (40 women, BMI: 33 ± 4 kg/m2). Participants were randomly assigned to one of the energy-restricted (−500 kcal/d) groups: control (CT, free-nuts), cashew nut (CN, 30 g/d), or cashew nut oil (OL, 30 mL/d). Body weight, body composition, and blood collection were assessed at the baseline and endpoint of the study.ResultsAfter 8-wk, all groups reduced significantly body fat (CT: −3.1 ± 2.8 kg; CN: −3.3 ± 2.7 kg; OL: −1.8 ± 2.6 kg), body weight (CT: −4.2 ± 3.8 kg; CN: −3.9 ± 3.1 kg; OL: −3.4 ± 2.4 kg), waist (CT: −5.1 ± 4.6 cm; CN: −3.9 ± 3.9 cm; OL: −3.7 ± 5.3 cm) and hip circumferences (CT: −2.9 ± 3.0 cm; CN: −2.7 ± 3.1 cm; OL: −2.9 ± 2.3 cm). CN-group reduced liver enzymes (AST: −3.1 ± 5.3 U/L; ALT: −6.0 ± 9.9 U/L), while the OL-group reduced LDL-c (−11.5 ± 21.8 mg/dL) and atherogenic index (−0.2 ± 0.5). Both intervention groups decreased neck circumference (CN: −1.0 ± 1.2 cm; OL: −0.5 ± 1.2 cm) and apo B (CN: −6.6 ± 10.7 mg/dL; OL: −7.0 ± 15.3 mg/dL).ConclusionAfter an 8-wk energy-restricted intervention, all groups reduced body fat (kg), weight, and some others adiposity indicators, with no different effect of cashew nut or cashew nut oil. However, participants in the intervention groups experienced additional reductions in atherogenic marker, liver function biomarkers, and cardiovascular risk factors (neck circumference and apo B levels), with these effects observed across the OL group, CN group, and both intervention groups, respectively.Clinical trial registration:https://ensaiosclinicos.gov.br/rg/RBR-8xzkyp2, identifier 8xzkyp2.