Advancing healthcare through laboratory on a chip technology:Transforming microorganism identification and diagnostics

In a recent case report in the World Journal of Clinical Cases,emphasized the crucial role of rapidly and accurately identifying pathogens to optimize patient treatment outcomes.Laboratory-on-a-chip(LOC)technology has emerged as a transformative tool in health care,offering rapid,sensitive,and specific identification of microorganisms.This editorial provides a comprehensive overview of LOC technology,highlighting its principles,advantages,applications,challenges,and future directions.Success studies from the field have demonstrated the practical benefits of LOC devices in clinical diagnostics,epidemiology,and food safety.Comparative studies have underscored the superiority of LOC technology over traditional methods,showcasing improvements in speed,accuracy,and portability.The future integration of LOC with biosensors,artificial intelligence,and data analytics promises further innovation and expansion.This call to action emphasizes the importance of continued research,investment,and adoption to realize the full potential of LOC technology in improving healthcare outcomes worldwide.

Practice patterns among ophthalmic surgeons in treating concomitant oculoplastic conditions in preoperative period:A questionnaire-based study

BACKGROUND Addressing oculoplastic conditions in the preoperative period ensures both the safety and functional success of any ophthalmic procedure.Some oculoplastic conditions,like nasolacrimal duct obstruction,have been extensively studied,whereas others,like eyelid malposition and thyroid eye disease,have received minimal or no research.AIM To investigate the current practice patterns among ophthalmologists while treating concomitant oculoplastic conditions before any subspecialty ophthalmic intervention.METHODS A cross-sectional survey was disseminated among ophthalmologists all over India.The survey included questions related to pre-operative evaluation,anaesthetic and surgical techniques preferred,post-operative care,the use of adjunctive therapies,and patient follow-up patterns.RESULTS A total of 180 ophthalmologists responded to the survey.Most practitioners(89%)felt that the ROPLAS test was sufficient during pre-operative evaluation before any subspecialty surgery was advised.The most common surgical techniques employed were lacrimal drainage procedures(Dacryocystorhinostomy)(63.3%),eyelid malposition repair(36.9%),and ptosis repair(58.7%).Post-operatively,47.7%of respondents emphasized that at least a 4-week gap should be maintained after lacrimal drainage procedures and eyelid surgeries.Sixty-seven percent of ophthalmologists felt that topical anaesthetic procedures should be preferred while performing ocular surgeries in thyroid eye disease patients.CONCLUSION Approximately 50%of ophthalmologists handle prevalent oculoplastic issues themselves,seeking the expertise of an oculoplastic surgeon under particular conditions.Many ophthalmologists still favor using ROPLAS as a preliminary screening method before proceeding with cataract surgery.Eyelid conditions and thyroid eye disease are not as commonly addressed before subspecialty procedures compared to issues like nasolacrimal duct obstruction and periocular infections.

Importance of etiologies of secondary diabetes:How often do we think off in clinical practice?

The article"Secondary diabetes due to different etiologies:Four case reports"by Song et al,published in the World Journal of Clinical Cases,delves into the identi-fication of rare causes of secondary diabetes and emphasizes the necessity for healthcare professionals to recognize these conditions.Failure to do so can result in treatment delays and compromised patient outcomes.The article discusses spe-cific types of diabetes,including maturity onset of diabetes in young,pancreas-related diseases,endocrinopathies,drug-induced diabetes,infections,and con-genital genetic syndromes associated with diabetes mellitus.Case summaries highlight how patients with secondary diabetes,stemming from conditions such as Williams-Beuren syndrome and pituitary adenoma,often exhibit distinct characteristics overlooked in clinical practice.The authors stress the importance of a holistic diagnostic approach and advocate for proactive management through early intervention,including genetic tests and antibody detection.Increased awa-reness and education are crucial for timely identification and proper management,ultimately improving patient well-being.These findings prompt a call to action for healthcare professionals to consider rare causes of secondary diabetes,facili-tating better glycemic control and overall patient care.

Machine learning applications in healthcare clinical practice and research

Machine learning(ML)is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis,thus creating machines that can complete tasks otherwise requiring human intelligence.Among its various applications,it has proven groundbreaking in healthcare as well,both in clinical practice and research.In this editorial,we succinctly introduce ML applications and present a study,featured in the latest issue of the World Journal of Clinical Cases.The authors of this study conducted an analysis using both multiple linear regression(MLR)and ML methods to investigate the significant factors that may impact the estimated glomerular filtration rate in healthy women with and without non-alcoholic fatty liver disease(NAFLD).Their results implicated age as the most important determining factor in both groups,followed by lactic dehydrogenase,uric acid,forced expiratory volume in one second,and albumin.In addition,for the NAFLD-group,the 5th and 6th most important impact factors were thyroid-stimulating hormone and systolic blood pressure,as compared to plasma calcium and body fat for the NAFLD+group.However,the study's distinctive contribution lies in its adoption of ML methodologies,showcasing their superiority over traditional statistical approaches(herein MLR),thereby highlighting the potential of ML to represent an invaluable advanced adjunct tool in clinical practice and research.

Implementation strategies to improve evidence-based practice for post-stroke dysphagia identification and management:A before-andafter study

Objectives Even though guidelines are available to guide dysphagia identification and management practice,there is still a gap between evidence and practice,which requires improvement.The purpose of this study was to determine the effect of using tailored,multifaceted strategies to improve evidence-based post-stroke dysphagia identification and management practice in a community hospital.Methods Guided by the Knowledge to Action framework,the tailored,multifaceted strategies were developed and implemented for 5 months in a community hospital using a before-and-after study design.These strategies consisted of training intervention,policy intervention,and audit and feedback intervention.Nurses’level of knowledge and adherence,were collected in March 2019 and again in January 2020.Patients’quality of life and satisfaction were evaluated during the pre-intervention period(between February 2019 and April 2019)and the post-intervention period(between November 2019 and January 2020).Results A total of 55 patients with post-stroke dysphagia(28 in the pre-intervention period and 27 in the post-intervention period)and 17 registered nurses were recruited.Following implementation,there were statistically significant improvements in patients’outcomes(quality of life and satisfaction)and nurses’outcomes(level of knowledge and adherence).Conclusions This study assists in closing the research-practice gap by using tailored,multifaceted strategies to increase the use of evidence-based nursing care for dysphagia identification and management practices.

Two-Staged Method for Ice Channel Identification Based on Image Segmentation and Corner Point Regression

Identification of the ice channel is the basic technology for developing intelligent ships in ice-covered waters,which is important to ensure the safety and economy of navigation.In the Arctic,merchant ships with low ice class often navigate in channels opened up by icebreakers.Navigation in the ice channel often depends on good maneuverability skills and abundant experience from the captain to a large extent.The ship may get stuck if steered into ice fields off the channel.Under this circumstance,it is very important to study how to identify the boundary lines of ice channels with a reliable method.In this paper,a two-staged ice channel identification method is developed based on image segmentation and corner point regression.The first stage employs the image segmentation method to extract channel regions.In the second stage,an intelligent corner regression network is proposed to extract the channel boundary lines from the channel region.A non-intelligent angle-based filtering and clustering method is proposed and compared with corner point regression network.The training and evaluation of the segmentation method and corner regression network are carried out on the synthetic and real ice channel dataset.The evaluation results show that the accuracy of the method using the corner point regression network in the second stage is achieved as high as 73.33%on the synthetic ice channel dataset and 70.66%on the real ice channel dataset,and the processing speed can reach up to 14.58frames per second.

A real-time intelligent lithology identification method based on a dynamic felling strategy weighted random forest algorithm

Real-time intelligent lithology identification while drilling is vital to realizing downhole closed-loop drilling. The complex and changeable geological environment in the drilling makes lithology identification face many challenges. This paper studies the problems of difficult feature information extraction,low precision of thin-layer identification and limited applicability of the model in intelligent lithologic identification. The author tries to improve the comprehensive performance of the lithology identification model from three aspects: data feature extraction, class balance, and model design. A new real-time intelligent lithology identification model of dynamic felling strategy weighted random forest algorithm(DFW-RF) is proposed. According to the feature selection results, gamma ray and 2 MHz phase resistivity are the logging while drilling(LWD) parameters that significantly influence lithology identification. The comprehensive performance of the DFW-RF lithology identification model has been verified in the application of 3 wells in different areas. By comparing the prediction results of five typical lithology identification algorithms, the DFW-RF model has a higher lithology identification accuracy rate and F1 score. This model improves the identification accuracy of thin-layer lithology and is effective and feasible in different geological environments. The DFW-RF model plays a truly efficient role in the realtime intelligent identification of lithologic information in closed-loop drilling and has greater applicability, which is worthy of being widely used in logging interpretation.

Dynamic Hand Gesture-Based Person Identification Using Leap Motion and Machine Learning Approaches

Person identification is one of the most vital tasks for network security. People are more concerned about theirsecurity due to traditional passwords becoming weaker or leaking in various attacks. In recent decades, fingerprintsand faces have been widely used for person identification, which has the risk of information leakage as a resultof reproducing fingers or faces by taking a snapshot. Recently, people have focused on creating an identifiablepattern, which will not be reproducible falsely by capturing psychological and behavioral information of a personusing vision and sensor-based techniques. In existing studies, most of the researchers used very complex patternsin this direction, which need special training and attention to remember the patterns and failed to capturethe psychological and behavioral information of a person properly. To overcome these problems, this researchdevised a novel dynamic hand gesture-based person identification system using a Leap Motion sensor. Thisstudy developed two hand gesture-based pattern datasets for performing the experiments, which contained morethan 500 samples, collected from 25 subjects. Various static and dynamic features were extracted from the handgeometry. Randomforest was used to measure feature importance using the Gini Index. Finally, the support vectormachinewas implemented for person identification and evaluate its performance using identification accuracy. Theexperimental results showed that the proposed system produced an identification accuracy of 99.8% for arbitraryhand gesture-based patterns and 99.6% for the same dynamic hand gesture-based patterns. This result indicatedthat the proposed system can be used for person identification in the field of security.

The response of roots and the rhizosphere environment to integrative cultivation practices in paddy rice

Integrative cultivation practices(ICPs)are essential for enhancing cereal yield and resource use efficiency.However,the effects of ICP on the rhizosphere environment and roots of paddy rice are still poorly understood.In this study,four rice varieties were produced in the field.Each variety was treated with six different cultivation techniques,including zero nitrogen application(0 N),local farmers’practice(LFP),nitrogen reduction(NR),and three progressive ICP techniques comprised of enhanced fertilizer N practice and increased plant density(ICP1),a treatment similar to ICP1 but with alternate wetting and moderate drying instead of continuous flooding(ICP2),and the same practices as ICP2 with the application of organic fertilizer(ICP3).The ICPs had greater grain production and nitrogen use efficiency than the other three methods.Root length,dry weight,root diameter,activity of root oxidation,root bleeding rate,zeatin and zeatin riboside compositions,and total organic acids in root exudates were elevated with the introduction of the successive cultivation practices.ICPs enhanced nitrate nitrogen,the activities of urease and invertase,and the diversity of microbes(bacteria)in rhizosphere and non-rhizosphere soil,while reducing the ammonium nitrogen content.The nutrient contents(ammonium nitrogen,total nitrogen,total potassium,total phosphorus,nitrate,and available phosphorus)and urease activity in rhizosphere soil were reduced in all treatments in comparison with the non-rhizosphere soil,but the invertase activity and bacterial diversity were greater.The main root morphology and physiology,and the ammonium nitrogen contents in rhizosphere soil at the primary stages were closely correlated with grain yield and internal nitrogen use efficiency.These findings suggest that the coordinated enhancement of the root system and the environment of the rhizosphere under integrative cultivation approaches may lead to higher rice production.

Applying an Improved Dung Beetle Optimizer Algorithm to Network Traffic Identification

Network traffic identification is critical for maintaining network security and further meeting various demands of network applications.However,network traffic data typically possesses high dimensionality and complexity,leading to practical problems in traffic identification data analytics.Since the original Dung Beetle Optimizer(DBO)algorithm,Grey Wolf Optimization(GWO)algorithm,Whale Optimization Algorithm(WOA),and Particle Swarm Optimization(PSO)algorithm have the shortcomings of slow convergence and easily fall into the local optimal solution,an Improved Dung Beetle Optimizer(IDBO)algorithm is proposed for network traffic identification.Firstly,the Sobol sequence is utilized to initialize the dung beetle population,laying the foundation for finding the global optimal solution.Next,an integration of levy flight and golden sine strategy is suggested to give dung beetles a greater probability of exploring unvisited areas,escaping from the local optimal solution,and converging more effectively towards a global optimal solution.Finally,an adaptive weight factor is utilized to enhance the search capabilities of the original DBO algorithm and accelerate convergence.With the improvements above,the proposed IDBO algorithm is then applied to traffic identification data analytics and feature selection,as so to find the optimal subset for K-Nearest Neighbor(KNN)classification.The simulation experiments use the CICIDS2017 dataset to verify the effectiveness of the proposed IDBO algorithm and compare it with the original DBO,GWO,WOA,and PSO algorithms.The experimental results show that,compared with other algorithms,the accuracy and recall are improved by 1.53%and 0.88%in binary classification,and the Distributed Denial of Service(DDoS)class identification is the most effective in multi-classification,with an improvement of 5.80%and 0.33%for accuracy and recall,respectively.Therefore,the proposed IDBO algorithm is effective in increasing the efficiency of traffic identification and solving the problem of the original DBO algorithm that converges slowly and falls into the local optimal solution when dealing with high-dimensional data analytics and feature selection for network traffic identification.

Identification and evaluation of shale oil micromigration and its petroleum geological significance

Taking the Lower Permian Fengcheng Formation shale in Mahu Sag of Junggar Basin,NW China,as an example,core observation,test analysis,geological analysis and numerical simulation were applied to identify the shale oil micro-migration phenomenon.The hydrocarbon micro-migration in shale oil was quantitatively evaluated and verified by a self-created hydrocarbon expulsion potential method,and the petroleum geological significance of shale oil micro-migration evaluation was determined.Results show that significant micro-migration can be recognized between the organic-rich lamina and organic-poor lamina.The organic-rich lamina has strong hydrocarbon generation ability.The heavy components of hydrocarbon preferentially retained by kerogen swelling or adsorption,while the light components of hydrocarbon were migrated and accumulated to the interbedded felsic or carbonate organic-poor laminae as free oil.About 69% of the Fengcheng Formation shale samples in Well MY1 exhibit hydrocarbon charging phenomenon,while 31% of those exhibit hydrocarbon expulsion phenomenon.The reliability of the micro-migration evaluation results was verified by combining the group components based on the geochromatography effect,two-dimension nuclear magnetic resonance analysis,and the geochemical behavior of inorganic manganese elements in the process of hydrocarbon migration.Micro-migration is a bridge connecting the hydrocarbon accumulation elements in shale formations,which reflects the whole process of shale oil generation,expulsion and accumulation,and controls the content and composition of shale oil.The identification and evaluation of shale oil micro-migration will provide new perspectives for dynamically differential enrichment mechanism of shale oil and establishing a“multi-peak model in oil generation”of shale.

Tree: Reducing the use of restrictive practices on psychiatric wards through virtual reality immersive technology training

BACKGROUND Restrictive practices(RPs)are defined by measures linked to physical and chemical restraints to reduce the movement or control behaviours during any emergency.Seclusion is an equal part of RPs intended to isolate and reduce the sensory stimulation to safeguard the patient and those within the vicinity.Using interventions by way of virtual reality(VR)could assist with reducing the need for RPs as it could help reduce anxiety or agitation by way of placing users into realistic and immersive environments.This could also aid staff to and change current RPs.AIM To assess the feasibility and effectiveness of using a VR platform to provide reduction in RP training.METHODS A randomised controlled feasibility study,accompanied by evaluations at 1 month and 6 months,was conducted within inpatient psychiatric wards at Southern Health National Health Service Foundation Trust,United Kingdom.Virti VR scenarios were used on VR headsets to provide training on reducing RPs in 3 inpatient psychiatric wards.Outcome measures included general self-efficacy scale,generalised anxiety disorder assessment 7(GAD-7),Burnout Assessment Tool 12,the Everyday Discrimination Scale,and the Compassionate Engagement and Action Scale.RESULTS Findings revealed statistically significant differences between the VR and treatment as usual groups,in the Everyday Discrimination Scale items Q8 and Q9:P=0.023 and P=0.040 respectively,indicating higher levels of perceived discrimination in the VR group.There were no significant differences between groups in terms of general self-efficacy,generalised anxiety disorder assessment 9,and Burnout Assessment Tool 12 scores.A significant difference was observed within the VR group for compassionate engagement from others(P=0.005)over time.Most respondents recorded System Usability Scale scores above 70,with an average score of 71.79.There was a significant reduction in rates of RPs in the VR group vs treatment as usual group with a fluctuating variability observed in the VR group likely due to external factors not captured in the study.CONCLUSION Ongoing advancement of VR technology enables the possibility of creating scenarios and simulations tailored to healthcare environments that empower staff by providing more comprehensive and effective training for handling situations.

A review of clinical practice guidelines on the management of preeclampsia and nursing inspiration

Objectives:To review,evaluate,and synthesize the recommendations of guidelines on preeclampsia(PE)from a nursing perspective.Methods:This is a systematic review of international and national guidelines on PE.Electronic databases and related guideline websites were searched from 2013 to 2023.After systematic retrieval and screening,we used the AGREE II tool to appraise the methodological quality of guidelines that met the eligibility criteria.Then,we analyzed and summarized the recommendations using descriptive analysis and the framework method.Furthermore,we rated the quality of evidence and the strength of the recommendations using the GRADE approach.Results:Ten guidelines were included,among which eight were deemed“clinically useful”and records were extracted.In total,31 recommendations,including 46 items on the nursing management of PE,were summarized from three aspects:1)antenatal care(18 recommendations),including the assessment and regular monitoring of PE,standardized blood pressure(BP)measurement,prevention education for PE,antihypertensive agent monitoring,and magnesium sulfate(MgSO_(4))use;2)intrapartum care(4 recommendations),including childbirth care;3)postpartum care(9 recommendations),including regular nursing monitoring,breastfeeding care and longer-term health counseling.Most of the evidence was rated as“very low”(19/46)or“moderate”(15/46)quality.For the strength of the recommendations,30 items were graded as“strong”and 16 items were rated as“weak”.Conclusions:This study provides professional,evidence-based nursing care resources both for preservice education for nursing staff and health care education for women with PE to help them detect and treat PE in a timely manner.

Pollution source identification methods and remediation technologies of groundwater: A review

Groundwater is an important source of drinking water.Groundwater pollution severely endangers drinking water safety and sustainable social development.In the case of groundwater pollution,the top priority is to identify pollution sources,and accurate information on pollution sources is the premise of efficient remediation.Then,an appropriate pollution remediation scheme should be developed according to information on pollution sources,site conditions,and economic costs.The methods for identifying pollution sources mainly include geophysical exploration,geochemistry,isotopic tracing,and numerical modeling.Among these identification methods,only the numerical modeling can recognize various information on pollution sources,while other methods can only identify a certain aspect of pollution sources.The remediation technologies of groundwater can be divided into in-situ and ex-situ remediation technologies according to the remediation location.The in-situ remediation technologies enjoy low costs and a wide remediation range,but their remediation performance is prone to be affected by environmental conditions and cause secondary pollution.The ex-situ remediation technologies boast high remediation efficiency,high processing capacity,and high treatment concentration but suffer high costs.Different methods for pollution source identification and remediation technologies are applicable to different conditions.To achieve the expected identification and remediation results,it is feasible to combine several methods and technologies according to the actual hydrogeological conditions of contaminated sites and the nature of pollutants.Additionally,detailed knowledge about the hydrogeological conditions and stratigraphic structure of the contaminated site is the basis of all work regardless of the adopted identification methods or remediation technologies.

DC-FIPD: Fraudulent IP Identification Method Based on Homology Detection

Currently,telecom fraud is expanding from the traditional telephone network to the Internet,and identifying fraudulent IPs is of great significance for reducing Internet telecom fraud and protecting consumer rights.However,existing telecom fraud identification methods based on blacklists,reputation,content and behavioral characteristics have good identification performance in the telephone network,but it is difficult to apply to the Internet where IP(Internet Protocol)addresses change dynamically.To address this issue,we propose a fraudulent IP identification method based on homology detection and DBSCAN(Density-Based Spatial Clustering of Applications with Noise)clustering(DC-FIPD).First,we analyze the aggregation of fraudulent IP geographies and the homology of IP addresses.Next,the collected fraudulent IPs are clustered geographically to obtain the regional distribution of fraudulent IPs.Then,we constructed the fraudulent IP feature set,used the genetic optimization algorithm to determine the weights of the fraudulent IP features,and designed the calculation method of the IP risk value to give the risk value threshold of the fraudulent IP.Finally,the risk value of the target IP is calculated and the IP is identified based on the risk value threshold.Experimental results on a real-world telecom fraud detection dataset show that the DC-FIPD method achieves an average identification accuracy of 86.64%for fraudulent IPs.Additionally,the method records a precision of 86.08%,a recall of 45.24%,and an F1-score of 59.31%,offering a comprehensive evaluation of its performance in fraud detection.These results highlight the DC-FIPD method’s effectiveness in addressing the challenges of fraudulent IP identification.

Preceptors'experiences in guiding nursing students to use research findings and to implement evidence-based practice

Objective:Evidence-based practices(EBPs)have been taught to students by identifying the best evidence/evidence from research results.However,the experiences of Indonesian nurse preceptors in helping students implement research findings have not been explored thoroughly.This study aimed to explore Indonesian nurse preceptors in guiding nursing students to use research findings.Methods:This study used interpretive phenomenology analysis that involves 9 nurse preceptors from hospitals in West Kalimantan,Indonesia.Semi-structured in-depth interviews were recorded and then transcribed verbatim.Results:Three themes were generated during the analysis:“types of student supervision,”“issues during supervision,”and“the need for research literacy and supervision.”Conclusions:Nurse preceptors need support to supervise the nursing students to use research findings.In addition to upgrading nursing skills,nurse preceptors must receive training in research and its utilization.Developing an appropriate strategy to assist students in using research findings will enhance the promotion of evidence-based nursing practices on a daily basis.

Assessment of Knowledge, Attitudes, and Practices Regarding Hepatitis B among Students at Gaston Berger University of Saint-Louis in 2024

Introduction: Hepatitis B is a public health problem. This study aimed to investigate the knowledge, attitudes, and practices of students at Gaston Berger University of Saint-Louis regarding hepatitis B. Methods: A descriptive cross-sectional study was conducted in March 2024 within the university’s social campus among a sample of 800 students. Results: The sex ratio favored men at 1.5, and the average age was 23.3 years with a standard deviation of 2.7 years. Among students, 26.6% had never heard of the term “hepatitis B”, and 60% knew it was a liver disease. Young people and adolescents were identified as the most exposed population group by 52.3% of respondents. According to 53.7% of the sample, hepatitis B would be a curable disease. Furthermore, 95.0% of the surveyed individuals were not vaccinated against hepatitis B, and 36.3% were afraid of living with an infected person. While 63.0% had poor knowledge, 78.8% had negative attitudes, and poor practices were observed in 6.9% of participants. Conclusion: This study highlighted a lack of knowledge and concerning attitudes among students regarding hepatitis B. The results underscore the need to intensify information and awareness campaigns about this disease, as well as the importance of promoting vaccination and encouraging appropriate preventive practices among the student population.

Study of Harmful Vaginal Practices of Women in the Municipality of Ouagadougou, Burkina Faso

Introduction: Vaginal practices include washing, altering, cutting, cleaning, enhancing, drying, tightening, lubricating, or loosening of the vagina, labia, clitoris, or hymen. This study aimed to investigate the different vaginal practices of women using non-pharmaceutical products. Methodology: This was a cross-sectional study with descriptive and analytical purposes that took place from January 15 to April 23, 2023, in the four largest markets in the municipality of Ouagadougou. This was performed using the data collection sheet in the KoboCollect application. Epi info 7.2.5.0. software was used for data analysis. For the analysis of associated factors, a p-value Results: In total, 977 women were surveyed. Among them, 43.19% underwent vaginal procedures using non-pharmaceutical products. The female practitioners were 34.34 ± 7.44 years old. The products used included plants, mineral substances, ointments, tablets, and solutions. Among the practicing women, 40.99% were looking for vaginal tightening. The main purpose was to maintain their partners (45.97%). Three-point thirty-two percent (3.32%) of the women who underwent vaginal procedures had reported adverse events. Conclusion: Raising awareness of the consequences of vaginal practices and encouraging women to go to a health center for any gynecological problem could significantly reduce the prevalence of vaginal practices.

Assessment of Knowledge, Attitude and Practices among Healthcare Workers in a Tertiary Care Hospital on Needle Stick Injury

Purpose: Needle-stick injury (NSI) is one of the most potential occupational hazards for healthcare workers because of the transmission of blood-borne pathogens. As per recent data, around 30 lakh healthcare workers sustain Needle stick injuries each year. This study was conducted to assess healthcare workers’ knowledge, attitude and practices regarding needle stick injury. Materials & Methods: A cross-sectional study was conducted in a Tertiary Care Hospital over the period of 3 months. The study population consisted of Intern Doctors, Post Graduate resident Doctors, Staff Nurses, laboratory technicians of Government Medical College and New Civil Hospital, Surat (n = 300). The data were collected using a self-administered questionnaire via the means of Google Forms. Questionnaire was made with prior review literature. The data obtained were entered and analysed in Microsoft Excel. Results: The prevalence of NSI in our study was 46%, with a higher prevalence among the PG residents (72%). Overall scores regarding knowledge and attitude were better in PG residents (knowledge score > 7 in 71% and Attitude Score > 7 in 68% of PG Residents). Even though the PG residents scored highest in the knowledge category, the majority of them suffered needle stick injuries as a result of poor practice scores. Among those who had NSI (n = 139/300), 70% of study participants had superficial injuries, only 9% reported the incident, 18% got medical attention within 2 hours of the incident, and 7% followed up to recheck their viral markers status. Most incidents of NSI were due to hypodermic needles while recapping needles. Conclusion: Exposure to needle stick injuries and their underreporting remains a common problem. It is imperative that healthcare workers receive regular training on the proper handling of sharp objects. We can also draw the conclusion that preventing NSIs requires putting knowledge into practice.

Global systematic review and meta-analysis of knowledge, attitudes, and practices towards dengue fever among the general population

Objective:To determine the global level of knowledge,attitudes,and practices towards dengue fever among the general population.Methods:To complete this systematic review and meta-analysis,a thorough search for pertinent English-language literature was undertaken during the study's extension until October 2023.The search used Google Scholar,Scopus,PubMed/MEDLINE,Science Direct,Web of Science,EMBASE,Springer,and ProQuest.A quality assessment checklist developed using a modified Newcastle-Ottawa Scale for the cross-sectional study was used to evaluate the risk of bias in the included papers.Inverse variance and Cochran Q statistics were employed in the STATA software version 14 to assess study heterogeneity.When there was heterogeneity,the Dersimonian and Liard random-effects models were used.Results:59 Studies totaling 87353 participants were included in this meta-analysis.These investigations included 86278 participants in 55 studies on knowledge,20196 in 33 studies on attitudes,and 74881 in 29 studies on practices.The pooled estimates for sufficient knowledge,positive attitudes,and dengue fever preventive behaviors among the general population were determined as 40.1%(95%CI 33.8%-46.5%),46.8%(95%CI 35.8%-58.9%),and 38.3%(95%CI 28.4%-48.2%),respectively.Europe exhibits the highest knowledge level at 63.5%,and Africa shows the lowest at 20.3%.Positive attitudes are most prevalent in the Eastern Mediterranean(54.1%)and Southeast Asia(53.6%),contrasting sharply with the Americas,where attitudes are notably lower at 9.05%.Regarding preventive behaviors,the Americas demonstrate a prevalence of 12.1%,Southeast Asia at 28.1%,Western Pacific at 49.6%,Eastern Mediterranean at 44.8%,and Africa at 47.4%.Conclusions:Regional disparities about the knowledge,attitude and preventive bahaviors are evident with Europe exhibiting the highest knowledge level while Africa has the lowest.These findings emphasize the importance of targeted public health interventions tailored to regional contexts,highlighting the need for region-specific strategies to enhance dengue-related knowledge and encourage positive attitudes and preventive behaviors.