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
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
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
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
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
Purpose research on nursing sensitive indicators in tumor Patients application effect in immune-related skin toxicity management. Method select our hospital April to June, 202360 cases patients with immune therapy set...Purpose research on nursing sensitive indicators in tumor Patients application effect in immune-related skin toxicity management. Method select our hospital April to June, 202360 cases patients with immune therapy settings as the control group. August-October, 2023 60 cases the patients treated with immune therapy were the experimental group. The control group adopted regular nursing methods, while the experimental group sensitive Indicators, evidence-based give preventive care. The social situation, psychological state, physical function, quality of life score, incidence of skin toxicity caused by immune checkpoint inhibitors, moderate and above of the two groups of patients were compared. Incidence of skin toxicity. Result: experience group SAS score, SDS score higher than the control group, the difference was statistically significant (P < 0.05);The incidence of skin toxic reactions caused by immune checkpoint inhibitors and the incidence of moderate and above skin toxic reactions in the experimental group are lower than those in the control group, and the difference is statistically significant (P < 0.05). Conclusion: sensitive indicator guidance evidence-based preventive care can reduce the degree of immune-related skin toxicity, improve the psychological state and quality of life of tumor patients treated with immune therapy and reduce the incidence of adverse reactions, improve nursing quality and patient satisfaction.展开更多
To systematically incorporate multiple influencing factors,the coupled-state frequency memory(Co-SFM)network is proposed.This model integrates Copula estimation with neural networks,fusing multilevel data information,...To systematically incorporate multiple influencing factors,the coupled-state frequency memory(Co-SFM)network is proposed.This model integrates Copula estimation with neural networks,fusing multilevel data information,which is then fed into downstream learning modules.Co-SFM employs an upstream fusion module to incorporate multilevel data,thereby constructing a macro-plate-micro data structure.This configuration helps identify and integrate characteristics from different data levels,facilitating a deeper understanding of the internal links within the financial system.In the downstream model,Co-SFM uses a state-frequency memory network to mine hidden frequency information within stock prices,and the multifrequency patterns of sequential data are modeled.Empirical results show that Co-SFM s prediction accuracy for stock price trends is significantly better than that of other models.This is especially evident in multistep medium and long-term trend predictions,where integrating multilevel data results in notably improved accuracy.展开更多
Introduction: Malnutrition is an important reason for consultation in Mali’s health facilities and remains a major public health problem. The aim of this study was to describe the epidemioclinical profile and associa...Introduction: Malnutrition is an important reason for consultation in Mali’s health facilities and remains a major public health problem. The aim of this study was to describe the epidemioclinical profile and associated factors with performance indicators of integrated management of severe acute malnutrition in children aged 06 to 59 months. Methodology: this was a cross-sectional study with retrospective data collection (January 2021 to December 2022). All children hospitalized for severe acute malnutrition in the pediatric department and whose medical records were usable were included. Data collected using a standardized questionnaire was analyzed with SPSS Version 20 software. Results: A total of 534 children were included. The 12 to 23 months age group (49.1%) and the female sex (53.18%) were the most affected. Fully vaccinated children by age represented 49.4%. The predominant form of malnutrition was marasmus (77.7%). Diarrhea/vomiting (30.3%), fever (18.4%) and cough (15.5%) were the main reasons for consultations. Cure, discontinuation and death rates were 78.5%, 2.1% and 9.2%, respectively. On univariate analysis, the factors statistically associated with performance indicators (cure, drop-out, death) were gastroenteritis (P-value Conclusion: This study reveals that the frequency of severe acute malnutrition remains high at the Kalaban Coro reference health center. Better prevention of illnesses such as malaria, gastroenteritis, and respiratory infections, as well as timely referral, could help facilitate its management.展开更多
Understanding the relationship between modern pollen and vegetation is crucial for interpreting fossil pollen records and assessing human impact on the environment,both of which are essential for effective environment...Understanding the relationship between modern pollen and vegetation is crucial for interpreting fossil pollen records and assessing human impact on the environment,both of which are essential for effective environmental management strategies.Despite numerous studies on fossil pollen records in the Rif landscape,research specifically focusing on modern pollen and its implications for understanding human impact on the natural landscape is notably lacking.This paper presents novel anthropogenic pollen indicators for the Rif Mountains and seeks to evaluate the gradients of human impact on the southern Mediterranean landscape.We employed a combination of modern pollen analysis,vegetation survey,and ordination techniques,incorporating various environmental and land-use variables.Canonical correspondence analysis(CCA)allowed us to evaluate the relationships between pollen types and environmental variables,helping us identify key anthropogenic pollen indicators associated with land use and human activities:Poaceae,Cannabist,Olea-t,and Asteraceae for cultivation;Brassicaceae,Genista-t,Poaceae,Asteraceae and Plantago-t,for grazing;Apiaceae,Urtica-t and Genista-t for slashing and burning.Additionally,an anthropogenic index score(AIS)was calculated for each sampled location.Correspondence analysis(CA)was then used to correlate each specific pollen type with levels of human impact as follows(a)low(e.g.,Cedrus atlantica-t,Quercus canariensis-t),(b)moderate(e.g.,Erica-t,Arbutus unedo-t,Eucalyptus-t),and(c)high(e.g.,Cannabis-t,Brassicaceae,Olea-t,Nicotiana-t).This paper enhances our comprehension of land-use dynamics and impact levels,providing essential insights for evaluating anthropogenic impact trends and human-induced changes in the Rif Mountains landscape.展开更多
BACKGROUND Although the etiology of nonalcoholic fatty liver disease(NAFLD)has not been thoroughly understood,the emerging roles of anthropometric indicators in assessing and predicting the risk of NAFLD have been hig...BACKGROUND Although the etiology of nonalcoholic fatty liver disease(NAFLD)has not been thoroughly understood,the emerging roles of anthropometric indicators in assessing and predicting the risk of NAFLD have been highlighted by accumulating evidence.AIM To evaluate the causal relationships between five anthropometric indicators and NAFLD employing Mendelian randomization(MR)design.METHODS The Anthropometric Consortium provided genetic exposure data for five anthropometric indicators,including hip circumference(HC),waist circumference(WC),waist-to-hip ratio(WHR),body mass index(BMI),and body fat percentage(BF).Genetic outcome data for NAFLD were obtained from the United Kingdom Biobank and FinnGen Consortium.Genome-wide significant single nucleotide polymorphisms were chosen as instrumental variables.Univariable MR(UVMR)and multivariable MR(MVMR)designs with analytical approaches,including inverse variance weighted(IVW),MR-Egger,weighted median(WM),and weighted mode methods,were used to assess the causal relationships between anthropometric indicators and NAFLD.RESULTS Causal relationships were revealed by UVMR,indicating that a higher risk of NAFLD was associated with a perunit increase in WC[IVW:odds ratio(OR)=2.67,95%CI:1.42-5.02,P=2.25×10^(−3)],and BF was causally associated with an increased risk of NAFLD(WM:OR=2.23,95%CI:1.07-4.66,P=0.033).The presence of causal effects of WC on the decreased risk of NAFLD was supported by MVMR after adjusting for BMI and smoking.However,no causal association between BF and NAFLD was observed.In addition,other causal relationships of HC,WHR(BMI adjusted),and BMI with the risk of NAFLD were not retained after FDR correction.CONCLUSION This study establishes a causal relationship,indicating that an increase in WC is associated with a higher risk of NAFLD.This demonstrates that a suitable decrease in WC is advantageous for preventing NAFLD.展开更多
The determination of the compressibility of clay soils is a major concern during the design and construction of geotechnical engineering projects.Directly acquiring precise values of compression indicators from consol...The determination of the compressibility of clay soils is a major concern during the design and construction of geotechnical engineering projects.Directly acquiring precise values of compression indicators from consolidation tests is cumbersome and time-consuming.Based on experimental results from a series of index tests,this study presents a hybrid method that combines the extreme gradient boosting(XGBoost)model with the Bayesian optimization strategy to show the potential for achieving higher accuracy in predicting the compressibility indicators of clay soils.The results show that the proposed XGBoost model selected by Bayesian optimization can predict compression indicators more accurately and reliably than the artificial neural network(ANN)and support vector machine(SVM)models.In addition to the lowest prediction error,the proposed XGBoost-based method enhances the interpretability by feature importance analysis,which indicates that the void ratio is the most important factor when predicting the compressibility of clay soils.This paper highlights the promising prospect of the XGBoost model with Bayesian optimization for predicting unknown property parameters of clay soils and its capability to benefit the entire life cycle of engineering projects.展开更多
In China, meteorological forecasting relies on meteorological data obtained from regional and national stations. However, there were discrepancies between the data collected from the meteorological station at the pass...In China, meteorological forecasting relies on meteorological data obtained from regional and national stations. However, there were discrepancies between the data collected from the meteorological station at the passion fruit growing base and the data from regional and national stations. Consequently, the high and low temperature disaster indicators determined by the meteorological station at the passion fruit growing base cannot be applied to meteorological forecasting. To address this issue and facilitate the monitoring and early warning of high and low temperature disasters in passion fruit cultivation in Fujian, China, we used multi-source hourly temperature data (including the data from meteorological observation stations in passion fruit growing bases, the nearest regional stations, and national surface conventional meteorological observation stations) in three cities in southwestern Fujian (Longyan, Sanming, and Zhangzhou) spanning the years 2020 to 2022. By employing comprehensive statistical analysis methods (0.5 interval division and Cumulative frequency), we identified that passion fruit in southwestern Fujian was susceptible to high temperature disasters during the blooming-fruiting period, as well as low temperature disasters during the sprouting period. Consequently, we developed high and low temperature disaster indicators based on data from regional and national stations for different phenological periods of passion fruit in this region.展开更多
BACKGROUND Conventional five-port laparoscopic surgery,the current standard treatment for colorectal carcinoma(CRC),has many disadvantages.AIM To assess the influence of reduced-port laparoscopic surgery(RPLS)on perio...BACKGROUND Conventional five-port laparoscopic surgery,the current standard treatment for colorectal carcinoma(CRC),has many disadvantages.AIM To assess the influence of reduced-port laparoscopic surgery(RPLS)on perioperative indicators,postoperative recovery,and serum inflammation indexes in patients with CRC.METHODS The study included 115 patients with CRC admitted between December 2019 and May 2023,52 of whom underwent conventional five-port laparoscopic surgery(control group)and 63 of whom underwent RPLS(research group).Comparative analyses were performed on the following dimensions:Perioperative indicators[operation time(OT),incision length,intraoperative blood loss(IBL),and rate of conversion to laparotomy],postoperative recovery(first postoperative exhaust,bowel movement and oral food intake,and bowel sound recovery time),serum inflammation indexes[high-sensitivity C-reactive protein(hs-CRP),tumor necrosis factor-α(TNF-α),and interleukin-6(IL-6)],postoperative complications(anastomotic leakage,incisional infection,bleeding,ileus),and therapeutic efficacy.RESULTS The two groups had comparable OTs and IBL volumes.However,the research group had a smaller incision length;lower rates of conversion to laparotomy and postoperative total complication;and shorter time of first postoperative exhaust,bowel movement,oral food intake,and bowel sound recovery;all of which were significant.Furthermore,hs-CRP,IL-6,and TNF-αlevels in the research group were significantly lower than the baseline and those of the control group,and the total effective rate was higher.CONCLUSION RPLS exhibited significant therapeutic efficacy in CRC,resulting in a shorter incision length and a lower conversion rate to laparotomy,while also promoting postoperative recovery,effectively inhibiting the inflammatory response,and reducing the risk of postoperative complications.展开更多
Quality indicators in healthcare refer to measurable and quantifiable parameters used to assess and monitor the performance,effectiveness,and safety of healthcare services.These indicators provide a systematic way to ...Quality indicators in healthcare refer to measurable and quantifiable parameters used to assess and monitor the performance,effectiveness,and safety of healthcare services.These indicators provide a systematic way to evaluate the quality of care offered,and thereby to identify areas for improvement and to ensure that patient care meets established standards and best practices.Respiratory therapists play a vital role in areas of clinical administration such as infection control practices and quality improvement initiatives.Quality indicators serve as essential metrics for respiratory therapy departments to assess and enhance the overall quality of care.By systematically tracking and analyzing indicators related to infection control,treatment effectiveness,and adherence to protocols,respiratory care practitioners can identify areas to improve and implement evidence-based changes.This article reviewed how to identify,implement,and monitor quality indicators specific to the respiratory therapy departments to set benchmarks and enhance patient outcomes.展开更多
This paper proposes an intelligent management system (IMS) to help managers in their delicate and tedious task of exploiting the plethora of data (indicators) contained in management dashboards. This system is based o...This paper proposes an intelligent management system (IMS) to help managers in their delicate and tedious task of exploiting the plethora of data (indicators) contained in management dashboards. This system is based on intelligent agents, ontologies and data mining. It is implemented by PASSI (Process for Agent Societies Specification and Implementation) methods for agent design and implementation, the Methodology for Knowledge Modeling and Hot-Winters for data prediction. Intelligent agents not only track indicators but also store the knowledge of managers within the company. Ontologies are used to manage the representation and presentation aspects of knowledge. Data mining makes it possible to: make the most of all available data;model the industrial process of data selection, exploration and modeling;and transform behaviors into predictive indicators. An instance of the IMS named SYGISS, currently in operation within a large brewery organization, allows us to observe very interesting results: the extraction of indicators is done in less than 5 minutes whereas manual extraction used to take 14 days;the generation of dashboards is instantaneous whereas it used to take 12 hours;the interpretation of indicators is instantaneous whereas it used to take a day;forecasts are possible and are done in less than 5 minutes whereas they did not exist with the old management. These important contributions help to optimize the management of this organization.展开更多
Healthcare waste management (HCWM) is an important aspect of healthcare delivery globally because of its hazardous and infectious components that have potential for adverse health and environmental impacts. The paper ...Healthcare waste management (HCWM) is an important aspect of healthcare delivery globally because of its hazardous and infectious components that have potential for adverse health and environmental impacts. The paper introduces a set of indicators for assessing HCWM systems in hospitals. These indicators are: HCWM policies and standard operating procedures, management and oversight, logistics and budget support, training and occupational health and safety, and treatment, disposal and waste treatment equipment housing. By plotting a mark on a continuum which is defined as good and poor on the extremes and is connected with all other marks in a spoke arrangement, it’s possible to describe a baseline for HCWM in any specific hospital. This baseline can be used to improve awareness of the actors and policy-makers, compare the same hospital at a different point in time, to compare observations by different evaluators and to track improvements. Results suggest that in Kenya, the application of such indicators is useful for evaluating which priorities should be addressed to improve outcomes in HCWM systems. Systematic sampling technique was used to identify and collect data by use of observational checklist, interviews, visual verification and review of documents and a HCWM assessment tool. The objective is to suggest an integrated management tool as a method to identify prevailing problems with a HCWM system. The method can be replicated in other contexts worldwide, with a focus on the developing world. The integrated indicators focus on management of HCW and not its potential impact on human health and environment, an area recognized to be critical for future research.展开更多
This study aimed to investigate treatment-related symptoms in lung cancer patients undergoing chemotherapy and radiotherapy,as well as effective self-care strategies to alleviate these symptoms.A total of 202 lung can...This study aimed to investigate treatment-related symptoms in lung cancer patients undergoing chemotherapy and radiotherapy,as well as effective self-care strategies to alleviate these symptoms.A total of 202 lung cancer patients were surveyed using a treatment-related symptom checklist,Karnofsky Performance Status scale,and a self-care symptom relief questionnaire.The results showed that the most common treatment-related symptoms included fatigue(93.07%),loss of appetite(88.12%),nausea(82.67),hair loss(74.75%),vomiting(66.83%),pain(64.85%),taste changes(62.87%)and constipation(60.89%).The study also gathered patients’self-care methods that they found effective in alleviating these symptoms.Findings suggest that lung cancer patients bear a significant burden of treatment-related symptoms,and various self-care strategies reported by the patients were effective in managing these symptoms.展开更多
This study examines how socio-economic characteristics predict flood risk in London,England,using machine learning algorithms.The socio-economic variables considered included race,employment,crime and poverty measures...This study examines how socio-economic characteristics predict flood risk in London,England,using machine learning algorithms.The socio-economic variables considered included race,employment,crime and poverty measures.A stacked generalization(SG)model combines randomforest(RF),support vector machine(SVM),and XGBoost.Binary classification issues employ RF as the basis model and SVM as the meta-model.In multiclass classification problems,RF and SVM are base models while XGBoost is meta-model.The study utilizes flood risk labels for London areas and census data to train these models.This study found that SVM performs well in binary classifications with an accuracy rate of 0.60 and an area under the curve of 0.62.XGBoost outperforms other multiclass classification methods with 0.62 accuracy.Multiclass algorithms may perform similarly to binary classification jobs due to reduced data complexity when combining classes.The statistical significance of the result underscores their robustness,respectively.The findings reveal a significant correlation between flood risk and socio-economic factors,emphasizing the importance of these variables in predicting flood susceptibility.These results have important implications for disaster relief management and future research should focus on refining these models to improve predictive accuracy and exploring socio-economic factors.展开更多
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.
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.
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.
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Purpose research on nursing sensitive indicators in tumor Patients application effect in immune-related skin toxicity management. Method select our hospital April to June, 202360 cases patients with immune therapy settings as the control group. August-October, 2023 60 cases the patients treated with immune therapy were the experimental group. The control group adopted regular nursing methods, while the experimental group sensitive Indicators, evidence-based give preventive care. The social situation, psychological state, physical function, quality of life score, incidence of skin toxicity caused by immune checkpoint inhibitors, moderate and above of the two groups of patients were compared. Incidence of skin toxicity. Result: experience group SAS score, SDS score higher than the control group, the difference was statistically significant (P < 0.05);The incidence of skin toxic reactions caused by immune checkpoint inhibitors and the incidence of moderate and above skin toxic reactions in the experimental group are lower than those in the control group, and the difference is statistically significant (P < 0.05). Conclusion: sensitive indicator guidance evidence-based preventive care can reduce the degree of immune-related skin toxicity, improve the psychological state and quality of life of tumor patients treated with immune therapy and reduce the incidence of adverse reactions, improve nursing quality and patient satisfaction.
基金The National Natural Science Foundation of China(No.72173018).
文摘To systematically incorporate multiple influencing factors,the coupled-state frequency memory(Co-SFM)network is proposed.This model integrates Copula estimation with neural networks,fusing multilevel data information,which is then fed into downstream learning modules.Co-SFM employs an upstream fusion module to incorporate multilevel data,thereby constructing a macro-plate-micro data structure.This configuration helps identify and integrate characteristics from different data levels,facilitating a deeper understanding of the internal links within the financial system.In the downstream model,Co-SFM uses a state-frequency memory network to mine hidden frequency information within stock prices,and the multifrequency patterns of sequential data are modeled.Empirical results show that Co-SFM s prediction accuracy for stock price trends is significantly better than that of other models.This is especially evident in multistep medium and long-term trend predictions,where integrating multilevel data results in notably improved accuracy.
文摘Introduction: Malnutrition is an important reason for consultation in Mali’s health facilities and remains a major public health problem. The aim of this study was to describe the epidemioclinical profile and associated factors with performance indicators of integrated management of severe acute malnutrition in children aged 06 to 59 months. Methodology: this was a cross-sectional study with retrospective data collection (January 2021 to December 2022). All children hospitalized for severe acute malnutrition in the pediatric department and whose medical records were usable were included. Data collected using a standardized questionnaire was analyzed with SPSS Version 20 software. Results: A total of 534 children were included. The 12 to 23 months age group (49.1%) and the female sex (53.18%) were the most affected. Fully vaccinated children by age represented 49.4%. The predominant form of malnutrition was marasmus (77.7%). Diarrhea/vomiting (30.3%), fever (18.4%) and cough (15.5%) were the main reasons for consultations. Cure, discontinuation and death rates were 78.5%, 2.1% and 9.2%, respectively. On univariate analysis, the factors statistically associated with performance indicators (cure, drop-out, death) were gastroenteritis (P-value Conclusion: This study reveals that the frequency of severe acute malnutrition remains high at the Kalaban Coro reference health center. Better prevention of illnesses such as malaria, gastroenteritis, and respiratory infections, as well as timely referral, could help facilitate its management.
文摘Understanding the relationship between modern pollen and vegetation is crucial for interpreting fossil pollen records and assessing human impact on the environment,both of which are essential for effective environmental management strategies.Despite numerous studies on fossil pollen records in the Rif landscape,research specifically focusing on modern pollen and its implications for understanding human impact on the natural landscape is notably lacking.This paper presents novel anthropogenic pollen indicators for the Rif Mountains and seeks to evaluate the gradients of human impact on the southern Mediterranean landscape.We employed a combination of modern pollen analysis,vegetation survey,and ordination techniques,incorporating various environmental and land-use variables.Canonical correspondence analysis(CCA)allowed us to evaluate the relationships between pollen types and environmental variables,helping us identify key anthropogenic pollen indicators associated with land use and human activities:Poaceae,Cannabist,Olea-t,and Asteraceae for cultivation;Brassicaceae,Genista-t,Poaceae,Asteraceae and Plantago-t,for grazing;Apiaceae,Urtica-t and Genista-t for slashing and burning.Additionally,an anthropogenic index score(AIS)was calculated for each sampled location.Correspondence analysis(CA)was then used to correlate each specific pollen type with levels of human impact as follows(a)low(e.g.,Cedrus atlantica-t,Quercus canariensis-t),(b)moderate(e.g.,Erica-t,Arbutus unedo-t,Eucalyptus-t),and(c)high(e.g.,Cannabis-t,Brassicaceae,Olea-t,Nicotiana-t).This paper enhances our comprehension of land-use dynamics and impact levels,providing essential insights for evaluating anthropogenic impact trends and human-induced changes in the Rif Mountains landscape.
基金Supported by Science and Technology Research Project of Sichuan Administration of Traditional Chinese Medicine,No.2023MS419.
文摘BACKGROUND Although the etiology of nonalcoholic fatty liver disease(NAFLD)has not been thoroughly understood,the emerging roles of anthropometric indicators in assessing and predicting the risk of NAFLD have been highlighted by accumulating evidence.AIM To evaluate the causal relationships between five anthropometric indicators and NAFLD employing Mendelian randomization(MR)design.METHODS The Anthropometric Consortium provided genetic exposure data for five anthropometric indicators,including hip circumference(HC),waist circumference(WC),waist-to-hip ratio(WHR),body mass index(BMI),and body fat percentage(BF).Genetic outcome data for NAFLD were obtained from the United Kingdom Biobank and FinnGen Consortium.Genome-wide significant single nucleotide polymorphisms were chosen as instrumental variables.Univariable MR(UVMR)and multivariable MR(MVMR)designs with analytical approaches,including inverse variance weighted(IVW),MR-Egger,weighted median(WM),and weighted mode methods,were used to assess the causal relationships between anthropometric indicators and NAFLD.RESULTS Causal relationships were revealed by UVMR,indicating that a higher risk of NAFLD was associated with a perunit increase in WC[IVW:odds ratio(OR)=2.67,95%CI:1.42-5.02,P=2.25×10^(−3)],and BF was causally associated with an increased risk of NAFLD(WM:OR=2.23,95%CI:1.07-4.66,P=0.033).The presence of causal effects of WC on the decreased risk of NAFLD was supported by MVMR after adjusting for BMI and smoking.However,no causal association between BF and NAFLD was observed.In addition,other causal relationships of HC,WHR(BMI adjusted),and BMI with the risk of NAFLD were not retained after FDR correction.CONCLUSION This study establishes a causal relationship,indicating that an increase in WC is associated with a higher risk of NAFLD.This demonstrates that a suitable decrease in WC is advantageous for preventing NAFLD.
基金Project(202206370130)supported by the China Scholarship CouncilProject(2023ZZTS0034)supported by the Fundamental Research Funds for the Central Universities of Central South University,China。
文摘The determination of the compressibility of clay soils is a major concern during the design and construction of geotechnical engineering projects.Directly acquiring precise values of compression indicators from consolidation tests is cumbersome and time-consuming.Based on experimental results from a series of index tests,this study presents a hybrid method that combines the extreme gradient boosting(XGBoost)model with the Bayesian optimization strategy to show the potential for achieving higher accuracy in predicting the compressibility indicators of clay soils.The results show that the proposed XGBoost model selected by Bayesian optimization can predict compression indicators more accurately and reliably than the artificial neural network(ANN)and support vector machine(SVM)models.In addition to the lowest prediction error,the proposed XGBoost-based method enhances the interpretability by feature importance analysis,which indicates that the void ratio is the most important factor when predicting the compressibility of clay soils.This paper highlights the promising prospect of the XGBoost model with Bayesian optimization for predicting unknown property parameters of clay soils and its capability to benefit the entire life cycle of engineering projects.
文摘In China, meteorological forecasting relies on meteorological data obtained from regional and national stations. However, there were discrepancies between the data collected from the meteorological station at the passion fruit growing base and the data from regional and national stations. Consequently, the high and low temperature disaster indicators determined by the meteorological station at the passion fruit growing base cannot be applied to meteorological forecasting. To address this issue and facilitate the monitoring and early warning of high and low temperature disasters in passion fruit cultivation in Fujian, China, we used multi-source hourly temperature data (including the data from meteorological observation stations in passion fruit growing bases, the nearest regional stations, and national surface conventional meteorological observation stations) in three cities in southwestern Fujian (Longyan, Sanming, and Zhangzhou) spanning the years 2020 to 2022. By employing comprehensive statistical analysis methods (0.5 interval division and Cumulative frequency), we identified that passion fruit in southwestern Fujian was susceptible to high temperature disasters during the blooming-fruiting period, as well as low temperature disasters during the sprouting period. Consequently, we developed high and low temperature disaster indicators based on data from regional and national stations for different phenological periods of passion fruit in this region.
文摘BACKGROUND Conventional five-port laparoscopic surgery,the current standard treatment for colorectal carcinoma(CRC),has many disadvantages.AIM To assess the influence of reduced-port laparoscopic surgery(RPLS)on perioperative indicators,postoperative recovery,and serum inflammation indexes in patients with CRC.METHODS The study included 115 patients with CRC admitted between December 2019 and May 2023,52 of whom underwent conventional five-port laparoscopic surgery(control group)and 63 of whom underwent RPLS(research group).Comparative analyses were performed on the following dimensions:Perioperative indicators[operation time(OT),incision length,intraoperative blood loss(IBL),and rate of conversion to laparotomy],postoperative recovery(first postoperative exhaust,bowel movement and oral food intake,and bowel sound recovery time),serum inflammation indexes[high-sensitivity C-reactive protein(hs-CRP),tumor necrosis factor-α(TNF-α),and interleukin-6(IL-6)],postoperative complications(anastomotic leakage,incisional infection,bleeding,ileus),and therapeutic efficacy.RESULTS The two groups had comparable OTs and IBL volumes.However,the research group had a smaller incision length;lower rates of conversion to laparotomy and postoperative total complication;and shorter time of first postoperative exhaust,bowel movement,oral food intake,and bowel sound recovery;all of which were significant.Furthermore,hs-CRP,IL-6,and TNF-αlevels in the research group were significantly lower than the baseline and those of the control group,and the total effective rate was higher.CONCLUSION RPLS exhibited significant therapeutic efficacy in CRC,resulting in a shorter incision length and a lower conversion rate to laparotomy,while also promoting postoperative recovery,effectively inhibiting the inflammatory response,and reducing the risk of postoperative complications.
文摘Quality indicators in healthcare refer to measurable and quantifiable parameters used to assess and monitor the performance,effectiveness,and safety of healthcare services.These indicators provide a systematic way to evaluate the quality of care offered,and thereby to identify areas for improvement and to ensure that patient care meets established standards and best practices.Respiratory therapists play a vital role in areas of clinical administration such as infection control practices and quality improvement initiatives.Quality indicators serve as essential metrics for respiratory therapy departments to assess and enhance the overall quality of care.By systematically tracking and analyzing indicators related to infection control,treatment effectiveness,and adherence to protocols,respiratory care practitioners can identify areas to improve and implement evidence-based changes.This article reviewed how to identify,implement,and monitor quality indicators specific to the respiratory therapy departments to set benchmarks and enhance patient outcomes.
文摘This paper proposes an intelligent management system (IMS) to help managers in their delicate and tedious task of exploiting the plethora of data (indicators) contained in management dashboards. This system is based on intelligent agents, ontologies and data mining. It is implemented by PASSI (Process for Agent Societies Specification and Implementation) methods for agent design and implementation, the Methodology for Knowledge Modeling and Hot-Winters for data prediction. Intelligent agents not only track indicators but also store the knowledge of managers within the company. Ontologies are used to manage the representation and presentation aspects of knowledge. Data mining makes it possible to: make the most of all available data;model the industrial process of data selection, exploration and modeling;and transform behaviors into predictive indicators. An instance of the IMS named SYGISS, currently in operation within a large brewery organization, allows us to observe very interesting results: the extraction of indicators is done in less than 5 minutes whereas manual extraction used to take 14 days;the generation of dashboards is instantaneous whereas it used to take 12 hours;the interpretation of indicators is instantaneous whereas it used to take a day;forecasts are possible and are done in less than 5 minutes whereas they did not exist with the old management. These important contributions help to optimize the management of this organization.
文摘Healthcare waste management (HCWM) is an important aspect of healthcare delivery globally because of its hazardous and infectious components that have potential for adverse health and environmental impacts. The paper introduces a set of indicators for assessing HCWM systems in hospitals. These indicators are: HCWM policies and standard operating procedures, management and oversight, logistics and budget support, training and occupational health and safety, and treatment, disposal and waste treatment equipment housing. By plotting a mark on a continuum which is defined as good and poor on the extremes and is connected with all other marks in a spoke arrangement, it’s possible to describe a baseline for HCWM in any specific hospital. This baseline can be used to improve awareness of the actors and policy-makers, compare the same hospital at a different point in time, to compare observations by different evaluators and to track improvements. Results suggest that in Kenya, the application of such indicators is useful for evaluating which priorities should be addressed to improve outcomes in HCWM systems. Systematic sampling technique was used to identify and collect data by use of observational checklist, interviews, visual verification and review of documents and a HCWM assessment tool. The objective is to suggest an integrated management tool as a method to identify prevailing problems with a HCWM system. The method can be replicated in other contexts worldwide, with a focus on the developing world. The integrated indicators focus on management of HCW and not its potential impact on human health and environment, an area recognized to be critical for future research.
文摘This study aimed to investigate treatment-related symptoms in lung cancer patients undergoing chemotherapy and radiotherapy,as well as effective self-care strategies to alleviate these symptoms.A total of 202 lung cancer patients were surveyed using a treatment-related symptom checklist,Karnofsky Performance Status scale,and a self-care symptom relief questionnaire.The results showed that the most common treatment-related symptoms included fatigue(93.07%),loss of appetite(88.12%),nausea(82.67),hair loss(74.75%),vomiting(66.83%),pain(64.85%),taste changes(62.87%)and constipation(60.89%).The study also gathered patients’self-care methods that they found effective in alleviating these symptoms.Findings suggest that lung cancer patients bear a significant burden of treatment-related symptoms,and various self-care strategies reported by the patients were effective in managing these symptoms.
文摘This study examines how socio-economic characteristics predict flood risk in London,England,using machine learning algorithms.The socio-economic variables considered included race,employment,crime and poverty measures.A stacked generalization(SG)model combines randomforest(RF),support vector machine(SVM),and XGBoost.Binary classification issues employ RF as the basis model and SVM as the meta-model.In multiclass classification problems,RF and SVM are base models while XGBoost is meta-model.The study utilizes flood risk labels for London areas and census data to train these models.This study found that SVM performs well in binary classifications with an accuracy rate of 0.60 and an area under the curve of 0.62.XGBoost outperforms other multiclass classification methods with 0.62 accuracy.Multiclass algorithms may perform similarly to binary classification jobs due to reduced data complexity when combining classes.The statistical significance of the result underscores their robustness,respectively.The findings reveal a significant correlation between flood risk and socio-economic factors,emphasizing the importance of these variables in predicting flood susceptibility.These results have important implications for disaster relief management and future research should focus on refining these models to improve predictive accuracy and exploring socio-economic factors.
