Objectives:We systematically reviewed the rational use of medicines using the World Health Organization/International Network of Rational Use of Drugs(WHO/INRUD)core drug use indicators.We also assessed the impact of ...Objectives:We systematically reviewed the rational use of medicines using the World Health Organization/International Network of Rational Use of Drugs(WHO/INRUD)core drug use indicators.We also assessed the impact of the coronavirus disease 2019 pandemic and the National Drug Policy(NDP)2005 on the rational use of medicines.Methods:Searches were conducted in PubMed,Scopus,and Google Scholar databases to identify studies that met our eligibility criteria.Assessment of the quality of studies was conducted using the Joanna Briggs Institute criteria for analytical studies.We reported and compared the median values of WHO/INRUD core drug use indicators with standard thresholds.Data were presented with median,interquartile range(IQR),and percentages.MannWhitney and Kruskal-Wallis tests were conducted to assess for statistical significance(P<0.05)across variables.Results:Thirty-one studies were included in the review,comprising 50,931 patient encounters across 268 health facilities.Within prescribing indicators,average number of medicines per patient encountered[3.4(IQR:3.0to 4.0)],percentage of medicines prescribed by generic[50.4%(IQR:47.4%to 65.0%)],percentage of encounters with antibiotic prescribed[40.2%(IQR:30.5%to 52.7%)],percentage of encounters with injection prescribed[18%(IQR:3.2%to 30.0%)]and the percentage of medicines prescribed from essential medicines list[82.0%(IQR:66.4%to 89.3%)].The median percentage of encounters with antibiotics(P=0.04)and the median percentage of medicines prescribed by generics(P=0.03)increased during and after the COVID-19 pandemic.Prescribing indicators were worse in primary and secondary health facilities,with significant differences in the median percentage of encounters with antibiotics(P=0.007)and injections(P=0.0002)across primary,secondary,and tertiary health facilities.There were improvements across all prescribing indicators after the implementation of NDP 2005.Conclusions:Core drug use indicators in Nigerian health facilities deviated from the WHO/INRUD thresholds,with noticeable improvement after the implementation of NDP 2005.More efforts are needed to improve rational drug use in Nigerian hospitals.展开更多
Background: The irrational use of medicines remains a key health problem in many developing countries. The overuse of antibiotics is a key driver of antimicrobial resistance (AMR). This study surveyed antibiotic use a...Background: The irrational use of medicines remains a key health problem in many developing countries. The overuse of antibiotics is a key driver of antimicrobial resistance (AMR). This study surveyed antibiotic use and adherence to the World Health Organization (WHO) prescribing indicators at the Request Muntanga Hospital in the Kalomo District of Southern Province, Zambia. Materials and Methods: This cross-sectional study was conducted from July 2023 to September 2023 at Request Muntanga Hospital in Zambia and reviewed 600 medical record prescriptions which were issued from July 1, 2022 to June 30, 2023 using the WHO prescribing indicators. The collected data were analyzed using Statistical Package for Social Sciences version 23.0. Results: From the 600 prescriptions sampled, 1246 medicines were prescribed, with antibiotics making up 86.7% of the encounters. Additionally, the average number of drugs prescribed per encounter was 2.1 and the prevalence of polypharmacy was 61.3%. Further, 17.8% of medicines were prescribed as injectables. Furthermore, 76.7% of the drugs were prescribed from the Zambia Essential Medicines List and 38.9% by generic names. Conclusions: This study found a high use of antibiotics and deviations from the WHO/International Network of Rational Use of Drugs (INRUD) core prescribing indicators at the Request Muntanga Hospital indicating non-adherence to the prescribing indicators. There is a need to promote adherence to the WHO/INRUD core prescribing indicators to promote the rational use of antibiotics and prevent the emergence and spread of AMR.展开更多
BACKGROUND Nutritional and inflammatory indicators are crucial in assessing the nutritional health and immune function of patients with cancer,which are factors closely associated with the diagnosis and treatment of c...BACKGROUND Nutritional and inflammatory indicators are crucial in assessing the nutritional health and immune function of patients with cancer,which are factors closely associated with the diagnosis and treatment of colorectal cancer(CRC).AIM To explore the relationship between nutritional and inflammatory indicators and microsatellite stability(MSS)status in CRC.METHODS The clinical data of 56 patients who underwent surgical treatment for CRC were collected.Furthermore,the expressions of nutritional(levels of serum albumin,triglycerides,serum cholesterol,and body mass index)and inflammatory response indicators(absolute neutrophil count,absolute lymphocyte count,absolute monocyte count,neutrophil-to-lymphocyte ratio,and lymphocyte-to-monocyte ratio)as well as their correlation with microsatellite instability(MSI)status were investigated in patients with CRC.RESULTS Compared to the patients with MSS tumors,those with MSI tumors demonstrated significantly lower levels of two nutritional indicators,namely serum albumin and body mass index(P<0.05).Moreover,patients in the MSI group demonstrated significantly lower absolute lymphocyte counts and higher neutrophil-to-lymphocyte ratio than those in the MSS group(P<0.05),indicating pronounced differences in inflammatory responses and immune states between the two groups.CONCLUSION Certain nutritional and inflammatory indicators exhibit significant differences among patients with MSI and MSS CRC,highlighting their potential role in the clinical treatment and health management of this specific population.展开更多
Colonoscopy remains the cornerstone of colorectal cancer prevention and survei-llance,but the procedure’s effectiveness is entirely dependent upon various quali-ty indicators,such as detection rates,withdrawal time,a...Colonoscopy remains the cornerstone of colorectal cancer prevention and survei-llance,but the procedure’s effectiveness is entirely dependent upon various quali-ty indicators,such as detection rates,withdrawal time,adequate bowel prepara-tion,cecal intubation rate and patient outcomes.Despite progress in endoscopic techniques,challenges persist in maintaining endoscopists’consistent perfor-mance and improving quality metrics.Artificial intelligence(AI)has emerged as a“game changer”in the gastroenterology field,offering the opportunity to signifi-cantly increase colonoscopy quality.This review highlights the role of AI-driven technologies such as deep learning,computer vision,and real-time feedback me-chanisms in optimizing key quality indicators of colonoscopy.The implementa-tion of AI in colonoscopy may reduce human error,improve endoscopist’s consis-tency in real-time decision making,ensuring higher reliability and standardiza-tion during the procedure.Furthermore,AI has the potential to reshape how en-doscopists perform and evaluate procedures,while improved lesion characte-rization may enable more precise selection for resection,reducing morbidity and the incidence of interval cancers.The review also addresses challenges and limi-tations in AI integration,including cost-effectiveness and its impact on endosco-pist training.AI holds substantial promise for advancing colonoscopy quality and elevating overall patient care,paving the way for more effective and personalized medical approaches.展开更多
Objective: To analyze the effectiveness of blood test indicators in the differential diagnosis of anemia. Methods: Sixty patients diagnosed with anemia (disease group) from June 2021 to June 2024 were selected. Based ...Objective: To analyze the effectiveness of blood test indicators in the differential diagnosis of anemia. Methods: Sixty patients diagnosed with anemia (disease group) from June 2021 to June 2024 were selected. Based on the type of disease, the group was subdivided into iron deficiency anemia (IDA) with 31 cases, hemolytic anemia (HA) with 11 cases, and aplastic anemia (AA) with 18 cases. Based on the severity of the disease, the group was divided into mild anemia (30 cases), moderate anemia (19 cases), and severe anemia (11 cases). Sixty healthy individuals (control group) were also included, and all underwent blood tests. Comparisons were made between the red blood cell (RBC) indicators of the disease group and the control group, the blood test indicators of different types of anemia, and the serum iron levels of varying severity of anemia. Results: Except for red cell distribution width (RDW), the RBC indicators in the disease group were lower than those in the control group (P < 0.05). Comparisons of RBC indicators among different types of anemia showed significant differences (P < 0.05). Serum iron levels varied significantly among different degrees of anemia severity (P < 0.05). Conclusion: Blood tests can detect anemia, distinguish types of anemia, and assess anemia severity, offering high diagnostic value.展开更多
This study provides a systematic investigation into the influence of feature selection methods on cryptocurrency price forecasting models employing technical indicators.In this work,over 130 technical indicators—cove...This study provides a systematic investigation into the influence of feature selection methods on cryptocurrency price forecasting models employing technical indicators.In this work,over 130 technical indicators—covering momentum,volatility,volume,and trend-related technical indicators—are subjected to three distinct feature selection approaches.Specifically,mutual information(MI),recursive feature elimination(RFE),and random forest importance(RFI).By extracting an optimal set of 20 predictors,the proposed framework aims to mitigate redundancy and overfitting while enhancing interpretability.These feature subsets are integrated into support vector regression(SVR),Huber regressors,and k-nearest neighbors(KNN)models to forecast the prices of three leading cryptocurrencies—Bitcoin(BTC/USDT),Ethereum(ETH/USDT),and Binance Coin(BNB/USDT)—across horizons ranging from 1 to 20 days.Model evaluation employs the coefficient of determination(R2)and the root mean squared logarithmic error(RMSLE),alongside a walk-forward validation scheme to approximate real-world trading contexts.Empirical results indicate that incorporating momentum and volatility measures substantially improves predictive accuracy,with particularly pronounced effects observed at longer forecast windows.Moreover,indicators related to volume and trend provide incremental benefits in select market conditions.Notably,an 80%–85% reduction in the original feature set frequently maintains or enhances model performance relative to the complete indicator set.These findings highlight the critical role of targeted feature selection in addressing high-dimensional financial data challenges while preserving model robustness.This research advances the field of cryptocurrency forecasting by offering a rigorous comparison of feature selection methods and their effects on multiple digital assets and prediction horizons.The outcomes highlight the importance of dimension-reduction strategies in developing more efficient and resilient forecasting algorithms.Future efforts should incorporate high-frequency data and explore alternative selection techniques to further refine predictive accuracy in this highly volatile domain.展开更多
Objective Blood culture remains the gold standard for diagnosing bloodstream infections.Clinical laboratories must ensure the quality of blood culture processes from receipt to obtaining definitive results.We examined...Objective Blood culture remains the gold standard for diagnosing bloodstream infections.Clinical laboratories must ensure the quality of blood culture processes from receipt to obtaining definitive results.We examined laboratory analytical indicators associated with positive blood culture results.Methods Blood cultures collected from Peking Union Medical College Hospital between January 1,2020,and December 31,2022,were retrospectively analyzed.The mode of transportation(piping logistics delivery vs.staff),source of blood cultures(outpatient/emergency department vs.inpatient department),rotation of personnel,and time of reception(8:00–19:59 vs.20:00–07:59)were compared between blood culture-positive and-negative results.Results Between 2020 and 2022,the total positive rate of blood culture was 8.07%.The positive rate of blood cultures in the outpatient/emergency department was significantly higher than that in the inpatient department(12.46%vs.5.83%;P<0.0001).The time-to-detection of blood cultures was significantly affected by the delivery mode and personnel rotation.The blood culture positive rate of the total pre-analytical time within 1 h was significantly higher than that within 1–2 h or>2 h(P<0.0170).Conclusion Laboratory analytical indicators such as patient source,transportation mode,and personnel rotation significantly impacted the positive detection rate or time of blood culture.展开更多
This paper focuses on the procurement of construction projects in universities,conducting research on the influencing factors of procurement risks in such projects.By combining questionnaire surveys with expert interv...This paper focuses on the procurement of construction projects in universities,conducting research on the influencing factors of procurement risks in such projects.By combining questionnaire surveys with expert interviews,numerous factors affecting procurement are analyzed.Subsequently,these factors are refined and summarized to construct a procurement risk evaluation index system for construction projects,which includes three first-level indicators,such as process management risk and ethical/legal risk,and is further subdivided into 13 second-level indicators.展开更多
There are multiple types of risks involved in the service of long-span railway bridges.Classical methods are difficult to provide targeted alarm information according to different situations of load anomalies and stru...There are multiple types of risks involved in the service of long-span railway bridges.Classical methods are difficult to provide targeted alarm information according to different situations of load anomalies and structural anomalies.To accurately alarm different risks of long-span railway bridges by structural health monitoring systems,this paper proposes a cross-cooperative alarm method using principal and secondary indicators during high-wind periods.It provides the prior criterion for monitoring systems under special conditions,defining the principal and secondary indicators,alarm levels,and thresholds based on the relationship between dynamic equilibrium equations and multiple linear regression analysis.Analysis of one-year monitoring data from a longspan railway cable-stayed bridge shows that the 10-min average cross-bridge wind speed(excitation indicator)can be selected as the principal indicator,while lateral displacement(response indicator)can serve as the secondary indicator.The threshold levels of the secondary indicator prioritize the safety of bridge operation(mainly aiming at the safety of trains traversing bridges),with values significantly lower than structural safety thresholds.This approach enhances alarm timeliness and effectively distinguishes between load anomalies,structural anomalies,and equipment failures.Consequently,it improves alarm accuracy and provides timely decision support for bridge maintenance,train traversing,and emergency treatment.展开更多
This editorial delves into the potential of systemic immune indicators(SIIs)as early predictors of renal damage in children with newly diagnosed type 1 diabetes mellitus.By exploring the recent study published by Cao ...This editorial delves into the potential of systemic immune indicators(SIIs)as early predictors of renal damage in children with newly diagnosed type 1 diabetes mellitus.By exploring the recent study published by Cao et al,this article aims to highlight the importance of early detection and intervention.This study compre-hensively analyzes various SIIs,examining their correlation with renal compli-cations in newly diagnosed type 1 diabetic children.The findings reveal a sig-nificant association between immune system dysregulation and the onset of renal damage,suggesting that certain immune indicators can be early markers for predicting renal complications.This editorial emphasizes the clinical implications and applications of utilizing SIIs for early detection in pediatric diabetes care.It underscores the importance of innovative diagnostic approaches and illustrates real-world applications and outcomes.Additionally,it addresses the challenges and considerations in adopting these indicators and outlines future research directions to enhance diabetes management in children.展开更多
Purpose-The indoor vibration compaction test(IVCT)was a key step in controlling the compaction quality for high-speed railway graded aggregate(HRGA),which currently had a research gap on the assessment indicators and ...Purpose-The indoor vibration compaction test(IVCT)was a key step in controlling the compaction quality for high-speed railway graded aggregate(HRGA),which currently had a research gap on the assessment indicators and compaction parameters.Design/methodology/approach-To address these issues,a novel multi-indicator IVCT method was proposed,including physical indicator dry density(ρd)and mechanical indicators dynamic stiffness(Krb)and bearing capacity coefficient(K20).Then,a series of IVCTs on HRGA under different compaction parameters were conducted with an improved vibration compactor,which could monitor the physical-mechanical indicators in real-time.Finally,the optimal vibration compaction parameters,including the moisture content(ω),the diameter-to-maximum particle size ratio(Rd),the thickness-to-maximum particle size ratio(Rh),the vibration frequency(f),the vibration mass(Mc)and the eccentric distance(re),were determined based on the evolution characteristics for the physical-mechanical indicators during compaction.Findings-All results indicated that theρd gradually increased and then stabilized,and the Krb initially increased and then decreased.Moreover,the inflection time of the Krb was present as the optimal compaction time(Tlp)during compaction.Additionally,optimal compaction was achieved whenωwas the water-holding content after mud pumping,Rd was 3.4,Rh was 3.5,f was the resonance frequency,and the ratio between the excitation force and the Mc was 1.8.Originality/value-The findings of this paper were significant for the quality control of HRGA compaction.展开更多
BACKGROUND Globally,it’s estimated that at least 1 billion people have a near and/or distance vision impairment that could have been prevented or is yet to be addressed.The burden of unaddressed vision impairment and...BACKGROUND Globally,it’s estimated that at least 1 billion people have a near and/or distance vision impairment that could have been prevented or is yet to be addressed.The burden of unaddressed vision impairment and blindness is estimated to be four times higher in low and intermediate-resource settings than in high-income settings.[1]展开更多
Detecting multiple analytes simultaneously,crucial in disease diagnosis and treatment prognosis,remains challenging.While planar sensing platforms demonstrate this capability,optical fiber sensors still lag behind.An ...Detecting multiple analytes simultaneously,crucial in disease diagnosis and treatment prognosis,remains challenging.While planar sensing platforms demonstrate this capability,optical fiber sensors still lag behind.An operando dual lossy mode resonance(LMR)biosensor fabricated on a D-shaped single-mode fiber(SMF)is proposed for quantification of clinical indicators of inflammatory process,like in COVID-19 infection.Dual LMRs,created via two-step deposition process,yield a nanostructure with distinct SnO_(2) thicknesses on the flat surface of the fiber.Theoretical and experimental analyses confirm its feasibility,showing a sensitivity around 4500 nm/RIU for both LMRs.A novel insight in spatially-separated biofunctionalization of the sensitive fiber regions is validated through fluorescence assays,showcasing selectivity for different immunoglobulins.Real-time and label-free detection of two inflammatory markers,C-reactive protein and Ddimer,empowers the platform capability with a minimum detectable concentration below 1μg/mL for both biomolecules,which is of clinical interest.This proof-of-concept work provides an important leap in fiber-based biosensing for effective and reliable multi-analyte detection,presenting a novel,compact and multi-functional analytical tool.展开更多
Objective:To explore the effectiveness of early enteral nutrition therapy in ICU patients with respiratory failure.Methods:A total of 76 ICU patients with respiratory failure,admitted from May 2024 to May 2025,were in...Objective:To explore the effectiveness of early enteral nutrition therapy in ICU patients with respiratory failure.Methods:A total of 76 ICU patients with respiratory failure,admitted from May 2024 to May 2025,were included in the study.They were divided into an observation group and a control group using a random number table method,and relevant treatment indicators were compared.Results:The total effective rate in the observation group was higher than that in the control group(p<0.05).After treatment,the observation group showed superior lung function,organ function,health status,nutritional status,body mass index,and blood gas analysis indicators compared to the control group(p<0.05).Conclusion:Early enteral nutrition therapy is effective in treating ICU patients with respiratory failure and is beneficial for improving their lung function,nutritional status,and blood gas parameters,making it worthy of promotion.展开更多
Additive Manufacturing(AM)can provide customized parts that conventional techniques fail to deliver.One important parameter in AM is the quality of the parts,as a result of the material extrusion 3D printing(3D-P)proc...Additive Manufacturing(AM)can provide customized parts that conventional techniques fail to deliver.One important parameter in AM is the quality of the parts,as a result of the material extrusion 3D printing(3D-P)procedure.This can be very important in defense-related applications,where optimum performance needs to be guaranteed.The quality of the Polyetherimide 3D-P specimens was examined by considering six control parameters,namely,infill percentage,layer height,deposition angle,travel speed,nozzle,and bed temperature.The quality indicators were the root mean square(Rq)and average(Ra)roughness,porosity,and the actual to nominal dimensional deviation.The examination was performed with optical profilometry,optical microscopy,and micro-computed tomography scanning.The Taguchi design of experiments was applied,with twenty-five runs,five levels for each control parameter,on five replicas.Two additional confirmation runs were conducted,to ensure reliability.Prediction equations were constructed to express the quality indicators in terms of the control parameters.Three modeling approaches were applied to the experimental data,to compare their efficiency,i.e.,Linear Regression Model(LRM),Reduced Quadratic Regression Model,and Quadratic Regression Model(QRM).QRM was the most accurate one,still the differences were not high even considering the simpler LRM model.展开更多
While sustainability is widely recognized as a necessary path for development and climate change mitigation,there is no consensus on this concept’s goals and future aspirations.Advocates of a green economy believe th...While sustainability is widely recognized as a necessary path for development and climate change mitigation,there is no consensus on this concept’s goals and future aspirations.Advocates of a green economy believe that economic growth is a prerequisite for long-term progress and the modernization of society.This entails gradually transitioning to a more sustainable economy and addressing carbon emissions.Therefore,there is a need for the scientific community to investigate how different forms of modernization affect carbon emissions.This study examines the impact of modernization on carbon emissions in China,the world’s largest developing economy,focusing on five indicators of sustainable modernization:ecological modernization,agricultural modernization,digitalization,industrialization,and urbanization.The study analyzes data from 31 Chinese provincial-level regions between 2005 and 2020,using the GeoDetector technique to explore the effects of these indicators on carbon emissions.The spatial analysis reveals a distinct“core-periphery”structure of carbon emissions.The findings demonstrate that ecological modernization and digitalization contribute to reducing emissions.On the other hand,industrialization and urbanization have a positive influence on carbon emissions.Interestingly,agricultural modernization initially increases carbon emissions in the short term but has a diminishing effect in the long term.展开更多
To investigate the effects of plateau environments on driving fatigue,heart rate and electroencephalogram(EEG)signals were chosen as indicators to characterize driving fatigue.The study analyzed the variation in these...To investigate the effects of plateau environments on driving fatigue,heart rate and electroencephalogram(EEG)signals were chosen as indicators to characterize driving fatigue.The study analyzed the variation in these indicators as drivers transitioned into fatigued stages.By examining the sample entropy of EEG signals and the heart rate variation coefficient,a complex indicator of driving fatigue(CIDF)was established using principal component analysis to overcome the limitations of single-indicator methods.According to the CIDF values,the driving fatigue states in plateau areas were subdivided into three categories,including alertness,mild fatigue,and severe fatigue,by cluster analysis.Optimal binning determined thresholds for different driving fatigue states,which were validated through variance analysis.The results indicate that the CIDF values effectively distinguish the driving fatigue states of drivers in plateau areas.The CIDF thresholds for the alertness and the mild fatigue states are 0.34 and 0.50,respectively.A CIDF value greater than 0.50 indicates that the driver is in a severe fatigue state.展开更多
Acute pancreatitis (AP) is one of the more common gastrointestinal diseases in clinics and is characterized by rapid progression, many complications, and high mortality. When it develops into severe pancreatitis, its ...Acute pancreatitis (AP) is one of the more common gastrointestinal diseases in clinics and is characterized by rapid progression, many complications, and high mortality. When it develops into severe pancreatitis, its prognosis is poor. Therefore, early assessment of the degree of inflammatory response plays a crucial role in the treatment plan and prognosis of patients. More and more studies have shown that the levels of D-dimer (D-D), angiotensin-2 (Ang-2), phosphate, heparin-binding protein (HBP), retinol-binding protein-4 (RBP4), and osteoblastic protein (OPN) are closely related to the severity of acute pan-creatitis and can be used as effective indicators for early assessment of AP. In this paper, the research progress of the above indicators in assessing the severity of AP is summarized.展开更多
Despite their strategic hydrological importance for neighbouring areas,the Polish Carpathians are experiencing spatial chaos,which may weaken their adaptability to the progressive climate change.The article attempts t...Despite their strategic hydrological importance for neighbouring areas,the Polish Carpathians are experiencing spatial chaos,which may weaken their adaptability to the progressive climate change.The article attempts to answer the question of whether spatial planning,which is supposed to guarantee spatial order,fulfils its role and whether the knowledge of the natural conditions of spatial development is respected in the spatial planning process.Using GIS techniques,up to 238 communes were analysed in terms of their spatial coverage,the degree of scattered settlement,and the violation of natural barriers by location of buildings in areas that are threatened with mass movements or floods;by settlement on excessively inclined slopes and in areas with adverse climatic conditions.Spearman non-parametric rank correlation analysis and the multidimensional Principal Component Analysis(PCA)technique were performed to investigate relations between spatial chaos indicators and the planning situation.The analysis of the data has revealed that spatial planning does not fulfil its role.Serious errors in location of buildings have been noted even though the communes are covered by local spatial development plans.Scientific knowledge is not sufficiently transferred into planning documents,and bottom-up initiatives cannot replace systemic solutions.There is a need for strengthening the role of environmental studies documents in the spatial planning system.This would facilitate the transfer of scientific knowledge into the planning process and help to protect mountain areas.The development of a special spatial strategy for the Polish Carpathians in compliance with the Carpathian Convention is also recommended.展开更多
Background: Hypertensive disorder of pregnancy (HDP) is a group of diseases in which pregnancy and elevated blood pressure coexist. There is still a lack of reliable clinical tools to predict the incidence of HDP. The...Background: Hypertensive disorder of pregnancy (HDP) is a group of diseases in which pregnancy and elevated blood pressure coexist. There is still a lack of reliable clinical tools to predict the incidence of HDP. The purpose of this study was to establish and validate a nomogram prediction model for assessing the risk of HDP in pregnant women based on laboratory indicators and HDP risk factors. Method: A total of 307 pregnant women who were hospitalized in the obstetrics and gynecology department of our hospital were included in this study, and were randomly divided into a training cohort and validation cohort at a ratio of 7:3. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for the development of HDP on laboratory indicators as well as risk factors for HDP in the training cohort of patients. The results of the multivariate regression model were visualized by forest plots. A nomogram was constructed based on the results of multivariate logistic regression to predict the risk of HDP in pregnant women. The validity of the risk prediction model was evaluated by the area under the receiver operating characteristic curve (AUC), the consistency index (C-index), the calibration curve and the decision curve analysis (DCA). Results: BMI ≥ 25 Kg/m2, total cholesterol in early pregnancy, uric acid and proteinuria in late pregnancy were independent risk factors for HDP. The AUC and C-index of the nomogram constructed by the above four factors were both 0.848. The calibration curve is closely fitted with the ideal diagonal, showing a good consistency between the nomogram prediction and the actual observation of HDP. The DCA has demonstrated the great clinical utility of nomogram. Internal verification proves the reliability of the predicted nomograms. Conclusion: The BTUP nomogram model based on laboratory indicators and risk factors proposed in this study showed good predictive value for the risk assessment of HDP. It is expected to provide evidence for clinical prediction of the risk of HDP in pregnant women.展开更多
文摘Objectives:We systematically reviewed the rational use of medicines using the World Health Organization/International Network of Rational Use of Drugs(WHO/INRUD)core drug use indicators.We also assessed the impact of the coronavirus disease 2019 pandemic and the National Drug Policy(NDP)2005 on the rational use of medicines.Methods:Searches were conducted in PubMed,Scopus,and Google Scholar databases to identify studies that met our eligibility criteria.Assessment of the quality of studies was conducted using the Joanna Briggs Institute criteria for analytical studies.We reported and compared the median values of WHO/INRUD core drug use indicators with standard thresholds.Data were presented with median,interquartile range(IQR),and percentages.MannWhitney and Kruskal-Wallis tests were conducted to assess for statistical significance(P<0.05)across variables.Results:Thirty-one studies were included in the review,comprising 50,931 patient encounters across 268 health facilities.Within prescribing indicators,average number of medicines per patient encountered[3.4(IQR:3.0to 4.0)],percentage of medicines prescribed by generic[50.4%(IQR:47.4%to 65.0%)],percentage of encounters with antibiotic prescribed[40.2%(IQR:30.5%to 52.7%)],percentage of encounters with injection prescribed[18%(IQR:3.2%to 30.0%)]and the percentage of medicines prescribed from essential medicines list[82.0%(IQR:66.4%to 89.3%)].The median percentage of encounters with antibiotics(P=0.04)and the median percentage of medicines prescribed by generics(P=0.03)increased during and after the COVID-19 pandemic.Prescribing indicators were worse in primary and secondary health facilities,with significant differences in the median percentage of encounters with antibiotics(P=0.007)and injections(P=0.0002)across primary,secondary,and tertiary health facilities.There were improvements across all prescribing indicators after the implementation of NDP 2005.Conclusions:Core drug use indicators in Nigerian health facilities deviated from the WHO/INRUD thresholds,with noticeable improvement after the implementation of NDP 2005.More efforts are needed to improve rational drug use in Nigerian hospitals.
文摘Background: The irrational use of medicines remains a key health problem in many developing countries. The overuse of antibiotics is a key driver of antimicrobial resistance (AMR). This study surveyed antibiotic use and adherence to the World Health Organization (WHO) prescribing indicators at the Request Muntanga Hospital in the Kalomo District of Southern Province, Zambia. Materials and Methods: This cross-sectional study was conducted from July 2023 to September 2023 at Request Muntanga Hospital in Zambia and reviewed 600 medical record prescriptions which were issued from July 1, 2022 to June 30, 2023 using the WHO prescribing indicators. The collected data were analyzed using Statistical Package for Social Sciences version 23.0. Results: From the 600 prescriptions sampled, 1246 medicines were prescribed, with antibiotics making up 86.7% of the encounters. Additionally, the average number of drugs prescribed per encounter was 2.1 and the prevalence of polypharmacy was 61.3%. Further, 17.8% of medicines were prescribed as injectables. Furthermore, 76.7% of the drugs were prescribed from the Zambia Essential Medicines List and 38.9% by generic names. Conclusions: This study found a high use of antibiotics and deviations from the WHO/International Network of Rational Use of Drugs (INRUD) core prescribing indicators at the Request Muntanga Hospital indicating non-adherence to the prescribing indicators. There is a need to promote adherence to the WHO/INRUD core prescribing indicators to promote the rational use of antibiotics and prevent the emergence and spread of AMR.
基金Supported by Grants of the Suzhou Medical Key Discipline,No.SZXK202109Suzhou Clinical Key Disease Project,No.LCZX202111Suzhou Promoting Health through Science and Education Research Project,No.KJXW2021028.
文摘BACKGROUND Nutritional and inflammatory indicators are crucial in assessing the nutritional health and immune function of patients with cancer,which are factors closely associated with the diagnosis and treatment of colorectal cancer(CRC).AIM To explore the relationship between nutritional and inflammatory indicators and microsatellite stability(MSS)status in CRC.METHODS The clinical data of 56 patients who underwent surgical treatment for CRC were collected.Furthermore,the expressions of nutritional(levels of serum albumin,triglycerides,serum cholesterol,and body mass index)and inflammatory response indicators(absolute neutrophil count,absolute lymphocyte count,absolute monocyte count,neutrophil-to-lymphocyte ratio,and lymphocyte-to-monocyte ratio)as well as their correlation with microsatellite instability(MSI)status were investigated in patients with CRC.RESULTS Compared to the patients with MSS tumors,those with MSI tumors demonstrated significantly lower levels of two nutritional indicators,namely serum albumin and body mass index(P<0.05).Moreover,patients in the MSI group demonstrated significantly lower absolute lymphocyte counts and higher neutrophil-to-lymphocyte ratio than those in the MSS group(P<0.05),indicating pronounced differences in inflammatory responses and immune states between the two groups.CONCLUSION Certain nutritional and inflammatory indicators exhibit significant differences among patients with MSI and MSS CRC,highlighting their potential role in the clinical treatment and health management of this specific population.
文摘Colonoscopy remains the cornerstone of colorectal cancer prevention and survei-llance,but the procedure’s effectiveness is entirely dependent upon various quali-ty indicators,such as detection rates,withdrawal time,adequate bowel prepara-tion,cecal intubation rate and patient outcomes.Despite progress in endoscopic techniques,challenges persist in maintaining endoscopists’consistent perfor-mance and improving quality metrics.Artificial intelligence(AI)has emerged as a“game changer”in the gastroenterology field,offering the opportunity to signifi-cantly increase colonoscopy quality.This review highlights the role of AI-driven technologies such as deep learning,computer vision,and real-time feedback me-chanisms in optimizing key quality indicators of colonoscopy.The implementa-tion of AI in colonoscopy may reduce human error,improve endoscopist’s consis-tency in real-time decision making,ensuring higher reliability and standardiza-tion during the procedure.Furthermore,AI has the potential to reshape how en-doscopists perform and evaluate procedures,while improved lesion characte-rization may enable more precise selection for resection,reducing morbidity and the incidence of interval cancers.The review also addresses challenges and limi-tations in AI integration,including cost-effectiveness and its impact on endosco-pist training.AI holds substantial promise for advancing colonoscopy quality and elevating overall patient care,paving the way for more effective and personalized medical approaches.
文摘Objective: To analyze the effectiveness of blood test indicators in the differential diagnosis of anemia. Methods: Sixty patients diagnosed with anemia (disease group) from June 2021 to June 2024 were selected. Based on the type of disease, the group was subdivided into iron deficiency anemia (IDA) with 31 cases, hemolytic anemia (HA) with 11 cases, and aplastic anemia (AA) with 18 cases. Based on the severity of the disease, the group was divided into mild anemia (30 cases), moderate anemia (19 cases), and severe anemia (11 cases). Sixty healthy individuals (control group) were also included, and all underwent blood tests. Comparisons were made between the red blood cell (RBC) indicators of the disease group and the control group, the blood test indicators of different types of anemia, and the serum iron levels of varying severity of anemia. Results: Except for red cell distribution width (RDW), the RBC indicators in the disease group were lower than those in the control group (P < 0.05). Comparisons of RBC indicators among different types of anemia showed significant differences (P < 0.05). Serum iron levels varied significantly among different degrees of anemia severity (P < 0.05). Conclusion: Blood tests can detect anemia, distinguish types of anemia, and assess anemia severity, offering high diagnostic value.
文摘This study provides a systematic investigation into the influence of feature selection methods on cryptocurrency price forecasting models employing technical indicators.In this work,over 130 technical indicators—covering momentum,volatility,volume,and trend-related technical indicators—are subjected to three distinct feature selection approaches.Specifically,mutual information(MI),recursive feature elimination(RFE),and random forest importance(RFI).By extracting an optimal set of 20 predictors,the proposed framework aims to mitigate redundancy and overfitting while enhancing interpretability.These feature subsets are integrated into support vector regression(SVR),Huber regressors,and k-nearest neighbors(KNN)models to forecast the prices of three leading cryptocurrencies—Bitcoin(BTC/USDT),Ethereum(ETH/USDT),and Binance Coin(BNB/USDT)—across horizons ranging from 1 to 20 days.Model evaluation employs the coefficient of determination(R2)and the root mean squared logarithmic error(RMSLE),alongside a walk-forward validation scheme to approximate real-world trading contexts.Empirical results indicate that incorporating momentum and volatility measures substantially improves predictive accuracy,with particularly pronounced effects observed at longer forecast windows.Moreover,indicators related to volume and trend provide incremental benefits in select market conditions.Notably,an 80%–85% reduction in the original feature set frequently maintains or enhances model performance relative to the complete indicator set.These findings highlight the critical role of targeted feature selection in addressing high-dimensional financial data challenges while preserving model robustness.This research advances the field of cryptocurrency forecasting by offering a rigorous comparison of feature selection methods and their effects on multiple digital assets and prediction horizons.The outcomes highlight the importance of dimension-reduction strategies in developing more efficient and resilient forecasting algorithms.Future efforts should incorporate high-frequency data and explore alternative selection techniques to further refine predictive accuracy in this highly volatile domain.
基金supported by grants from the National High Level Hospital Clinical Research Funding(2022-PUMCH-B-074)Peking Union Medical College Hospital Research Funding for Postdoc(kyfyjj202320).
文摘Objective Blood culture remains the gold standard for diagnosing bloodstream infections.Clinical laboratories must ensure the quality of blood culture processes from receipt to obtaining definitive results.We examined laboratory analytical indicators associated with positive blood culture results.Methods Blood cultures collected from Peking Union Medical College Hospital between January 1,2020,and December 31,2022,were retrospectively analyzed.The mode of transportation(piping logistics delivery vs.staff),source of blood cultures(outpatient/emergency department vs.inpatient department),rotation of personnel,and time of reception(8:00–19:59 vs.20:00–07:59)were compared between blood culture-positive and-negative results.Results Between 2020 and 2022,the total positive rate of blood culture was 8.07%.The positive rate of blood cultures in the outpatient/emergency department was significantly higher than that in the inpatient department(12.46%vs.5.83%;P<0.0001).The time-to-detection of blood cultures was significantly affected by the delivery mode and personnel rotation.The blood culture positive rate of the total pre-analytical time within 1 h was significantly higher than that within 1–2 h or>2 h(P<0.0170).Conclusion Laboratory analytical indicators such as patient source,transportation mode,and personnel rotation significantly impacted the positive detection rate or time of blood culture.
文摘This paper focuses on the procurement of construction projects in universities,conducting research on the influencing factors of procurement risks in such projects.By combining questionnaire surveys with expert interviews,numerous factors affecting procurement are analyzed.Subsequently,these factors are refined and summarized to construct a procurement risk evaluation index system for construction projects,which includes three first-level indicators,such as process management risk and ethical/legal risk,and is further subdivided into 13 second-level indicators.
基金supported by the National Natural Science Foundation of China(Grants U23A20660,52008099,and 52378288)the Major Science and Technology Project of Yunnan Province,China(Grant 202502AD080007)the China Railway Engineering Corporation Science and Technology Research and Development Project(Grant 2022-Key-44).
文摘There are multiple types of risks involved in the service of long-span railway bridges.Classical methods are difficult to provide targeted alarm information according to different situations of load anomalies and structural anomalies.To accurately alarm different risks of long-span railway bridges by structural health monitoring systems,this paper proposes a cross-cooperative alarm method using principal and secondary indicators during high-wind periods.It provides the prior criterion for monitoring systems under special conditions,defining the principal and secondary indicators,alarm levels,and thresholds based on the relationship between dynamic equilibrium equations and multiple linear regression analysis.Analysis of one-year monitoring data from a longspan railway cable-stayed bridge shows that the 10-min average cross-bridge wind speed(excitation indicator)can be selected as the principal indicator,while lateral displacement(response indicator)can serve as the secondary indicator.The threshold levels of the secondary indicator prioritize the safety of bridge operation(mainly aiming at the safety of trains traversing bridges),with values significantly lower than structural safety thresholds.This approach enhances alarm timeliness and effectively distinguishes between load anomalies,structural anomalies,and equipment failures.Consequently,it improves alarm accuracy and provides timely decision support for bridge maintenance,train traversing,and emergency treatment.
文摘This editorial delves into the potential of systemic immune indicators(SIIs)as early predictors of renal damage in children with newly diagnosed type 1 diabetes mellitus.By exploring the recent study published by Cao et al,this article aims to highlight the importance of early detection and intervention.This study compre-hensively analyzes various SIIs,examining their correlation with renal compli-cations in newly diagnosed type 1 diabetic children.The findings reveal a sig-nificant association between immune system dysregulation and the onset of renal damage,suggesting that certain immune indicators can be early markers for predicting renal complications.This editorial emphasizes the clinical implications and applications of utilizing SIIs for early detection in pediatric diabetes care.It underscores the importance of innovative diagnostic approaches and illustrates real-world applications and outcomes.Additionally,it addresses the challenges and considerations in adopting these indicators and outlines future research directions to enhance diabetes management in children.
基金funded by the National Key R&D Program“Transportation Infrastructure”project(No.2022YFB2603400)the Technology Research and Development Plan Program of China State Railway Group Co.,Ltd.(No.Q2024T001)the National project pre research project of Suzhou City University(No.2023SGY019).
文摘Purpose-The indoor vibration compaction test(IVCT)was a key step in controlling the compaction quality for high-speed railway graded aggregate(HRGA),which currently had a research gap on the assessment indicators and compaction parameters.Design/methodology/approach-To address these issues,a novel multi-indicator IVCT method was proposed,including physical indicator dry density(ρd)and mechanical indicators dynamic stiffness(Krb)and bearing capacity coefficient(K20).Then,a series of IVCTs on HRGA under different compaction parameters were conducted with an improved vibration compactor,which could monitor the physical-mechanical indicators in real-time.Finally,the optimal vibration compaction parameters,including the moisture content(ω),the diameter-to-maximum particle size ratio(Rd),the thickness-to-maximum particle size ratio(Rh),the vibration frequency(f),the vibration mass(Mc)and the eccentric distance(re),were determined based on the evolution characteristics for the physical-mechanical indicators during compaction.Findings-All results indicated that theρd gradually increased and then stabilized,and the Krb initially increased and then decreased.Moreover,the inflection time of the Krb was present as the optimal compaction time(Tlp)during compaction.Additionally,optimal compaction was achieved whenωwas the water-holding content after mud pumping,Rd was 3.4,Rh was 3.5,f was the resonance frequency,and the ratio between the excitation force and the Mc was 1.8.Originality/value-The findings of this paper were significant for the quality control of HRGA compaction.
文摘BACKGROUND Globally,it’s estimated that at least 1 billion people have a near and/or distance vision impairment that could have been prevented or is yet to be addressed.The burden of unaddressed vision impairment and blindness is estimated to be four times higher in low and intermediate-resource settings than in high-income settings.[1]
基金support from the Spanish Agencia Estatal de Investigación(AEI)through project PID2023-149895OB-I00.
文摘Detecting multiple analytes simultaneously,crucial in disease diagnosis and treatment prognosis,remains challenging.While planar sensing platforms demonstrate this capability,optical fiber sensors still lag behind.An operando dual lossy mode resonance(LMR)biosensor fabricated on a D-shaped single-mode fiber(SMF)is proposed for quantification of clinical indicators of inflammatory process,like in COVID-19 infection.Dual LMRs,created via two-step deposition process,yield a nanostructure with distinct SnO_(2) thicknesses on the flat surface of the fiber.Theoretical and experimental analyses confirm its feasibility,showing a sensitivity around 4500 nm/RIU for both LMRs.A novel insight in spatially-separated biofunctionalization of the sensitive fiber regions is validated through fluorescence assays,showcasing selectivity for different immunoglobulins.Real-time and label-free detection of two inflammatory markers,C-reactive protein and Ddimer,empowers the platform capability with a minimum detectable concentration below 1μg/mL for both biomolecules,which is of clinical interest.This proof-of-concept work provides an important leap in fiber-based biosensing for effective and reliable multi-analyte detection,presenting a novel,compact and multi-functional analytical tool.
文摘Objective:To explore the effectiveness of early enteral nutrition therapy in ICU patients with respiratory failure.Methods:A total of 76 ICU patients with respiratory failure,admitted from May 2024 to May 2025,were included in the study.They were divided into an observation group and a control group using a random number table method,and relevant treatment indicators were compared.Results:The total effective rate in the observation group was higher than that in the control group(p<0.05).After treatment,the observation group showed superior lung function,organ function,health status,nutritional status,body mass index,and blood gas analysis indicators compared to the control group(p<0.05).Conclusion:Early enteral nutrition therapy is effective in treating ICU patients with respiratory failure and is beneficial for improving their lung function,nutritional status,and blood gas parameters,making it worthy of promotion.
文摘Additive Manufacturing(AM)can provide customized parts that conventional techniques fail to deliver.One important parameter in AM is the quality of the parts,as a result of the material extrusion 3D printing(3D-P)procedure.This can be very important in defense-related applications,where optimum performance needs to be guaranteed.The quality of the Polyetherimide 3D-P specimens was examined by considering six control parameters,namely,infill percentage,layer height,deposition angle,travel speed,nozzle,and bed temperature.The quality indicators were the root mean square(Rq)and average(Ra)roughness,porosity,and the actual to nominal dimensional deviation.The examination was performed with optical profilometry,optical microscopy,and micro-computed tomography scanning.The Taguchi design of experiments was applied,with twenty-five runs,five levels for each control parameter,on five replicas.Two additional confirmation runs were conducted,to ensure reliability.Prediction equations were constructed to express the quality indicators in terms of the control parameters.Three modeling approaches were applied to the experimental data,to compare their efficiency,i.e.,Linear Regression Model(LRM),Reduced Quadratic Regression Model,and Quadratic Regression Model(QRM).QRM was the most accurate one,still the differences were not high even considering the simpler LRM model.
基金National Natural Science Foundation of China,No.42371223,No.42401255。
文摘While sustainability is widely recognized as a necessary path for development and climate change mitigation,there is no consensus on this concept’s goals and future aspirations.Advocates of a green economy believe that economic growth is a prerequisite for long-term progress and the modernization of society.This entails gradually transitioning to a more sustainable economy and addressing carbon emissions.Therefore,there is a need for the scientific community to investigate how different forms of modernization affect carbon emissions.This study examines the impact of modernization on carbon emissions in China,the world’s largest developing economy,focusing on five indicators of sustainable modernization:ecological modernization,agricultural modernization,digitalization,industrialization,and urbanization.The study analyzes data from 31 Chinese provincial-level regions between 2005 and 2020,using the GeoDetector technique to explore the effects of these indicators on carbon emissions.The spatial analysis reveals a distinct“core-periphery”structure of carbon emissions.The findings demonstrate that ecological modernization and digitalization contribute to reducing emissions.On the other hand,industrialization and urbanization have a positive influence on carbon emissions.Interestingly,agricultural modernization initially increases carbon emissions in the short term but has a diminishing effect in the long term.
基金The National Natural Science Foundation of China(No.51768063,51868068).
文摘To investigate the effects of plateau environments on driving fatigue,heart rate and electroencephalogram(EEG)signals were chosen as indicators to characterize driving fatigue.The study analyzed the variation in these indicators as drivers transitioned into fatigued stages.By examining the sample entropy of EEG signals and the heart rate variation coefficient,a complex indicator of driving fatigue(CIDF)was established using principal component analysis to overcome the limitations of single-indicator methods.According to the CIDF values,the driving fatigue states in plateau areas were subdivided into three categories,including alertness,mild fatigue,and severe fatigue,by cluster analysis.Optimal binning determined thresholds for different driving fatigue states,which were validated through variance analysis.The results indicate that the CIDF values effectively distinguish the driving fatigue states of drivers in plateau areas.The CIDF thresholds for the alertness and the mild fatigue states are 0.34 and 0.50,respectively.A CIDF value greater than 0.50 indicates that the driver is in a severe fatigue state.
文摘Acute pancreatitis (AP) is one of the more common gastrointestinal diseases in clinics and is characterized by rapid progression, many complications, and high mortality. When it develops into severe pancreatitis, its prognosis is poor. Therefore, early assessment of the degree of inflammatory response plays a crucial role in the treatment plan and prognosis of patients. More and more studies have shown that the levels of D-dimer (D-D), angiotensin-2 (Ang-2), phosphate, heparin-binding protein (HBP), retinol-binding protein-4 (RBP4), and osteoblastic protein (OPN) are closely related to the severity of acute pan-creatitis and can be used as effective indicators for early assessment of AP. In this paper, the research progress of the above indicators in assessing the severity of AP is summarized.
基金supported by the Minister of Science of the Republic of Poland under the Programme“Regional initiative of excellence”.Agreement No.RID/SP/0010/2024/1.
文摘Despite their strategic hydrological importance for neighbouring areas,the Polish Carpathians are experiencing spatial chaos,which may weaken their adaptability to the progressive climate change.The article attempts to answer the question of whether spatial planning,which is supposed to guarantee spatial order,fulfils its role and whether the knowledge of the natural conditions of spatial development is respected in the spatial planning process.Using GIS techniques,up to 238 communes were analysed in terms of their spatial coverage,the degree of scattered settlement,and the violation of natural barriers by location of buildings in areas that are threatened with mass movements or floods;by settlement on excessively inclined slopes and in areas with adverse climatic conditions.Spearman non-parametric rank correlation analysis and the multidimensional Principal Component Analysis(PCA)technique were performed to investigate relations between spatial chaos indicators and the planning situation.The analysis of the data has revealed that spatial planning does not fulfil its role.Serious errors in location of buildings have been noted even though the communes are covered by local spatial development plans.Scientific knowledge is not sufficiently transferred into planning documents,and bottom-up initiatives cannot replace systemic solutions.There is a need for strengthening the role of environmental studies documents in the spatial planning system.This would facilitate the transfer of scientific knowledge into the planning process and help to protect mountain areas.The development of a special spatial strategy for the Polish Carpathians in compliance with the Carpathian Convention is also recommended.
文摘Background: Hypertensive disorder of pregnancy (HDP) is a group of diseases in which pregnancy and elevated blood pressure coexist. There is still a lack of reliable clinical tools to predict the incidence of HDP. The purpose of this study was to establish and validate a nomogram prediction model for assessing the risk of HDP in pregnant women based on laboratory indicators and HDP risk factors. Method: A total of 307 pregnant women who were hospitalized in the obstetrics and gynecology department of our hospital were included in this study, and were randomly divided into a training cohort and validation cohort at a ratio of 7:3. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for the development of HDP on laboratory indicators as well as risk factors for HDP in the training cohort of patients. The results of the multivariate regression model were visualized by forest plots. A nomogram was constructed based on the results of multivariate logistic regression to predict the risk of HDP in pregnant women. The validity of the risk prediction model was evaluated by the area under the receiver operating characteristic curve (AUC), the consistency index (C-index), the calibration curve and the decision curve analysis (DCA). Results: BMI ≥ 25 Kg/m2, total cholesterol in early pregnancy, uric acid and proteinuria in late pregnancy were independent risk factors for HDP. The AUC and C-index of the nomogram constructed by the above four factors were both 0.848. The calibration curve is closely fitted with the ideal diagonal, showing a good consistency between the nomogram prediction and the actual observation of HDP. The DCA has demonstrated the great clinical utility of nomogram. Internal verification proves the reliability of the predicted nomograms. Conclusion: The BTUP nomogram model based on laboratory indicators and risk factors proposed in this study showed good predictive value for the risk assessment of HDP. It is expected to provide evidence for clinical prediction of the risk of HDP in pregnant women.
