Statistical Tests Research Articles

The impact of alcohol consumption on economic growth in Thailand

The nighttime economy has always been an important part of tourism in Thailand. The alcohol industry contends that lifting alcohol restrictions will promote tourism and, consequently, generate additional income. Endogenous Growth Theory, however, emphasizes on investing in human capital, innovation, and knowledge as the most important factors that affect economic growth for a nation. Alcohol consumption incurs opportunity costs, as households lose financial resources and time that could be invested in children’s development. Relaxing control measures to promote alcohol consumption should impede economic development by diminishing the quality of human resources. The paper, therefore, aims to estimate the impact of alcohol consumption on economic growth by using 1990–2019 annual data from Thailand. By adopting Autoregressive Distributed Lag (ARDL) approach, the results reveal that alcohol consumption has significant and negative effects on economic growth in the long run. The statistic tests demonstrate no presence of serial correlation, heteroskedasticity, as well as, endogeneity problems. The finding has been corroborated in international studies, in which alcohol consumption contributes to substantial social and economic costs of the society.

Vocational Education Administration, Bilateral System under the Office of the Vocational Education Commission Kalasin Province

Background and Aims: Vocational education administration Dual system of educational institutions under the Office of the Vocational Education Commission. It is a professional education arrangement that arises from an agreement between an educational institution and a business establishment. The main objective is to develop and train professional skills for students. To prepare for future work the objectives of this research are to study the following: (1) Level of administration of vocational education, dual system, of vocational education in Kalasin Province. According to the standards for managing vocational education in the dual system of the Vocational Education Commission. To assess the quality and efficiency of operations at the operational level. 2) Compare the level of vocational education administration in the dual system of vocational education in Kalasin Province. To find differences in management in various areas and the use of various approaches to develop educational quality. (3) Study guidelines for promoting or developing the administration of vocational education, a dual system, of educational institutions under the Office of the Vocational Education Commission, Kalasin Province. To suggest ways to improve and develop educational administration to be more efficient. Methodology: In this research the sample group used was a total of 196 people. The research tool was a questionnaire with a 5-level rating scale, which had a confidence value of 0.81 and an internal consistency (IOC) in the range of 0.6-1.00. This questionnaire was designed to inquire about the administration of vocational education. Dual system of educational institutions under the Kalasin Provincial Vocational Education Institute. For data analysis use basic statistics, including frequency, percentage, mean, standard deviation and statistical tests used to compare differences, including t-test and F-test. Results: The results of the research found that: (1) Vocational education administration overall, it was at a high level. (2) Results of comparative analysis of opinions regarding vocational education administration classified by position, educational level, and size of educational institution found that there was no difference. (3) Guidelines for developing vocational education administration It is necessary to be supported and encouraged to be able to develop and adapt to the changes in today's industrial world. The various areas that should be developed include: 1) Quality of graduates: They must have knowledge and abilities that are accepted by the industry. 2) Curriculum development: Curriculum should be developed together with entrepreneurs and other stakeholders. 3) Measurement and evaluation: An effective measurement and evaluation system should be developed. 4) Cooperation between Educational institutions and business establishments: There should be strong relationships and cooperation in developing students. Conclusion: Vocational education administration Dual system of educational institutions under the Office of the Vocational Education Commission Kalasin Province. It is necessary to strengthen cooperation between educational institutions and enterprises. By giving the private sector an opportunity to participate in setting criteria and guidelines in various areas to be clear and consistent with the needs of the labor market. In this regard, there should be an effective evaluation process in order for management to be systematic and produce good results.

Impact of the mini-map on the interpretation of spatial situations in the virtual geographical space of a video game

ABSTRACT Mini-map as a world map in miniature format is often used as the most important cartographic element to facilitate the navigation and orientation of users in virtual geographical space. It provides detailed information about the position, orientation, nearby objects or terrain around the user in a compact and comprehensive way. The authors of this article wanted to find out whether the mini-map helps users with different levels of knowledge about the game to understand and interpret spatial situations that occur when playing in the virtual geographical space. The study was conducted in the form of an offline survey that required respondents to watch five short videos depicting different spatial situations during the League of Legends game. The 60 respondents were divided into 3 different groups whose responses were analyzed using statistical tests and mini-map heatmap eye-tracking analysis. The results of the study confirm that there is a correlation between the mini-map and the correctness of the interpretation of spatial situations in the game in all groups investigated. Previous gaming experiences were found to reduce the need to use a mini-map to interpret spatial situations, proving that video games provide players with comprehensive information about various events on the user interface.

Hubungan Kualitas Tidur Dengan Kejadian Hipertensi Pada Lansia di Desa Sukadaya Kecamatan Sukawangi Kabupaten Bekasi 2023

Hypertension is a non-communicable disease caused by various risk factors. One of the factors that causes hypertension is sleep quality. Sleep quality is a process when a person is sleeping, which is done to maintain a state of sleep and to obtain the appropriate Rapid Eye Movement (REM) and Non Rapid Eye Movement (NREM) stages. A person's habit of not sleeping enough or having poor quality sleep can increase the risk of increased blood pressure or hypertension. The aim of this research is to determine the relationship between sleep quality in the elderly and the incidence of hypertension in the elderly in Sukadaya Village, Sukawangi District, Bekasi Regency in 2023. The type of research used is quantitative research with observational methods (cross sectional), a sample of 170 people aged 60 years. tThe sampling technique uses simple random sampling. Sleep quality data was collected using the PSQI questionnaire directly and blood pressure measurements. This research stated that the sleep quality of the respondents was in the poor category, 86 respondents 50.6%, and the blood pressure of the respondents was categorized as high, 98 respondents 57.6%. The statistical test results showed that the p-value = 0.000 (α < 0.05). So this shows that H0 is rejected, which means that there is a relationship between sleep quality and the incidence of hypertension in the elderly in Sukadaya Sukawangi Bekasi 2023.

Total knee arthroplasty reimbursement is declining overall and at a marginally faster rate amongst female orthopaedic surgeons: A Medicare analysis

BackgroundWhile the prevalence of total knee arthroplasty (TKA) is increasing, reimbursement is declining. The purpose of this study was to determine how surgeon gender influences procedure volume, reimbursement, practice style, and patient demographics for TKAs nationally and regionally between 2013 and 2021. MethodsThe Medicare Physician and Other Practitioners database was queried from 2013 to 2021 for procedure volume, TKA reimbursement, surgeon characteristics, and patient demographics for any surgeon who performed at least ten primary TKAs per year. Statistical tests were conducted to analyze differences based on surgeon gender, geography, and year. ResultsOf the 2,415,802 TKAs performed between 2013 and 2021, 1.5 % were billed by female surgeons. The number of TKAs performed annually increased by 29.1 % for female surgeons and decreased by 2.6 % for male surgeons. Between 2013 and 2021, reimbursement for TKAs decreased by 23.9 % for male surgeons and 26.2 % for female surgeons. In 2021, male surgeons were reimbursed $1017 per TKA while female surgeons were reimbursed $964 (p = 0.049). Male surgeons performed more TKAs annually in 2021 (Male: 39.3, Female: 30.9, p < 0.001), more total billable services (Male: 4148.0, Female: 2719.3, p < 0.001), and more unique billable services (Male: 70.7, Female: 55.3, p < 0.001) than female surgeons. ConclusionsFemale representation among surgeons who perform TKAs is increasing nationally. However, male surgeons treat more patients, perform more total billable services, and perform more unique billable services than female surgeons. TKA reimbursement is decreasing at a faster rate for female surgeons than male surgeons, although this is likely due to geographical differences.

Association of biofilm and microbial metrics with healing rate in older adults with chronic venous leg ulcers.

The presence of microbial biofilms in many human chronic wounds led to the hypothesis that biofilms delay healing of these wounds. We tested this hypothesis in a population of 117 older individuals with venous leg ulcers who were receiving standardised therapy, including frequent debridement. Debridement specimens were analysed for the amount of bacterial biomass by two independent methods: a microscopic approach that scored the relative size and number of bacterial aggregates, interpreted as a biofilm metric, and conventional enumeration by agar plating for viable bacteria. The plating protocol yielded three distinct values: the total viable bacterial count, bleach-tolerant bacteria, and the log reduction in viable bacteria upon bleach treatment. Wound healing rates over an 8-week observation period were calculated as the rate of decrease of the equivalent diameter of the wound. There was no statistically significant association between wound healing and the biofilm metric in any of the three analyses performed (p ≥0.15). In all three statistical tests, wound healing was associated with the log reduction caused by bleach treatment (p ≤0.004); wounds that harboured bacteria that were more bleach-susceptible healed more slowly. A refinement of the model of chronic wound infection pathogenesis is proposed in which dormant bacteria constitute a persistent nidus and outgrowth of metabolically active cells impairs healing. This model constitutes a new hypothesis as metabolic activity was not directly measured in this investigation.

Sequence-to-Sequence Models and Their Evaluation for Spoken Language Normalization of Slovenian

Sequence-to-sequence models have been applied to many challenging problems, including those in text and speech technologies. Normalization is one of them. It refers to transforming non-standard language forms into their standard counterparts. Non-standard language forms come from different written and spoken sources. This paper deals with one such source, namely speech from the less-resourced highly inflected Slovenian language. The paper explores speech corpora recently collected in public and private environments. We analyze the efficiencies of three sequence-to-sequence models for automatic normalization from literal transcriptions to standard forms. Experiments were performed using words, subwords, and characters as basic units for normalization. In the article, we demonstrate that the superiority of the approach is linked to the choice of the basic modeling unit. Statistical models prefer words, while neural network-based models prefer characters. The experimental results show that the best results are obtained with neural architectures based on characters. Long short-term memory and transformer architectures gave comparable results. We also present a novel analysis tool, which we use for in-depth error analysis of results obtained by character-based models. This analysis showed that systems with similar overall results can differ in the performance for different types of errors. Errors obtained with the transformer architecture are easier to correct in the post-editing process. This is an important insight, as creating speech corpora is a time-consuming and costly process. The analysis tool also incorporates two statistical significance tests: approximate randomization and bootstrap resampling. Both statistical tests confirm the improved results of neural network-based models compared to statistical ones.

Management implications of latent TB among under-five children at risk: Insights from a community study in Mumbai, India.

Latent tuberculosis infection (LTBI) management is crucial to WHO's End TB Strategy. Indian guidelines recommend treating under-five children with household TB contacts after ruling out active TB, regardless of TBI testing. However, the precise LTBI burden among children in high TB burden settings like India is unknown. A community-based study in Mumbai's urban slums screened and managed under-five children at LTBI risk to understand its epidemiology and inform TB control interventions. Total 369 eligible under-five children were enrolled for the study. LTBI screening was done using Tuberculin skin test and Interferon gamma release assay. Active TB was ruled out before initiation of TB preventive therapy among LTBI positives. Statistical tests like chi-square, logistic regression analysis and Hosmer-Lemeshow test were used. Overall, LTBI prevalence among under-five children was 12.4% by IGRA and 21.4% by TST. Undernourished children had significantly lower LTBI positivity by IGRA (p = 0.027), while those with household contacts, longer contact duration and drug-resistant tuberculosis (DR-TB) exhibited proportionally greater IGRA positivity (p = <0.001). The study found a lower LTBI prevalence among under-five children compared to adults, with key risk factors being HHC, DR-TB contact, and prolonged exposure. These findings suggest the need to revise or revisit the TPT framework for this age group in India, particularly by implementing a test-and-treat approach.

Prevalence, Mortality, and Associated Anomalies in Esophageal Atresia: A Retrospective Study of Finnish Population Data (2004-2017).

The aim of the study was to investigate the prevalence of esophageal atresia (EA), frequency of associated anomalies, and mortality from 2004 to 2017 in the Finnish population. We hypothesized the Spitz classification and the presence of other congenital malformations would predict mortality in patients with EA as well as assumed the survival to be high among patients with EA. This retrospective, population-based study was based on the registries maintained by THL Finnish Institute for Health and Welfare and Statistics Finland. The cases were identified and classified according to the World Health Organization's International Classification of Diseases and Health Related Problems (ICD) revisions 9 and 10 (ICD-9 and ICD-10) codes and accompanying written diagnoses. Associated anomalies were classified based on the EUROCAT criteria, and minor anomalies were excluded. All statistical tests were performed as a two-sided significance level set at p < 0.05. The chi-square or Fisher's exact test was utilized for categorical variables. The change in prevalence rates during the study period was evaluated with linear regression. In total, 337 cases with EA were identified including 295 (87.5%) live births, 17 (5.0%) stillbirths, and 25 (7.4%) terminations of pregnancy. The total prevalence for EA in Finland was 4.17/10,000 births with no significant change during the study period, p = 0.35. Neonatal mortality was 5% (n = 15) and 1-year survival was 91.5%. Mortality was associated with syndromic cases (p = 0.002). The Spitz classification predicted neonatal mortality better than cardiac anomalies alone (p < 0.001 and p = 0.6, respectively). Type C was the most common atresia type (65.9%) followed by type A (14.8%) and B (6.8%). The most common group of associated malformations were heart defects (35.0%) followed by other gastrointestinal tract malformations (15.3%) and limb anomalies (12.2%). Syndromic cases (12.2%) were associated with type A and B atresias (p = 0.001). VACTERL association was observed in 16.6% of the cases. The overall prevalence of EA remains stable and relatively high in Finland. Despite the high prevalence of co-occurring malformations, the overall survival rate is high. Spitz classification predicted neonatal survival well.

Revolution or risk?-Assessing the potential and challenges of GPT-4V in radiologic image interpretation.

ChatGPT-4 Vision (GPT-4V) is a state-of-the-art multimodal large language model (LLM) that may be queried using images. We aimed to evaluate the tool's diagnostic performance when autonomously assessing clinical imaging studies. A total of 206 imaging studies (i.e., radiography (n = 60), CT (n = 60), MRI (n = 60), and angiography (n = 26)) with unequivocal findings and established reference diagnoses from the radiologic practice of a large university hospital were accessed. Readings were performed uncontextualized, with only the image provided, and contextualized, with additional clinical and demographic information. Responses were assessed along multiple diagnostic dimensions and analyzed using appropriate statistical tests. With its pronounced propensity to favor context over image information, the tool's diagnostic accuracy improved from 8.3% (uncontextualized) to 29.1% (contextualized, first diagnosis correct) and 63.6% (contextualized, correct diagnosis among differential diagnoses) (p ≤ 0.001, Cochran's Q test). Diagnostic accuracy declined by up to 30% when 20 images were re-read after 30 and 90 days and seemed unrelated to the tool's self-reported confidence (Spearman's ρ = 0.117 (p = 0.776)). While the described imaging findings matched the suggested diagnoses in 92.7%, indicating valid diagnostic reasoning, the tool fabricated 258 imaging findings in 412 responses and misidentified imaging modalities or anatomic regions in 65 images. GPT-4V, in its current form, cannot reliably interpret radiologic images. Its tendency to disregard the image, fabricate findings, and misidentify details, especially without clinical context, may misguide healthcare providers and put patients at risk. Question Can Generative Pre-trained Transformer 4 Vision (GPT-4V) interpret radiologic images-with and without clinical context? Findings GPT-4V performed poorly, demonstrating diagnostic accuracy rates of 8% (uncontextualized), 29% (contextualized, most likely diagnosis correct), and 64% (contextualized, correct diagnosis among differential diagnoses). Clinical relevance The utility of commercial multimodal large language models, such as GPT-4V, in radiologic practice is limited. Without clinical context, diagnostic errors and fabricated findings may compromise patient safety and misguide clinical decision-making. These models must be further refined to be beneficial.

Implementation of SAMPL Guidelines in 100 clinical medicine articles: enhancing statistical reporting and recommendations for biomedical journals

BackgroundContemporary observations indicate insufficient quality in the reporting of statistical data. Despite the publication of the SAMPL guidelines in 2015, they have not been widely adopted. The aim of this article is to highlight the incorporation of SAMPL Guidelines in the statistical reviews of articles related to clinical medicine, as well as the changes implemented by authors in revised manuscripts as a result of such guidance. An additional objective is to provide recommendations for biomedical journals regarding the necessity of integrating SAMPL Guidelines into their daily practices. MethodsThe study incorporated 100 selected statistical reviews of original clinical medicine articles from 8 biomedical journals, conducted between 2016 and 2023. Each of these reviews suggested specific SAMPL Guidelines to be implemented in the revised manuscript. It was evaluated which specific SAMPL Guidelines were most frequently enforced and what changes resulted from their implementation. ResultsSeventy-five percent of the manuscripts in question garnered acceptance following a solitary round of statistical evaluation. Among the most frequently recommended and subsequently implemented SAMPL Guidelines by the authors are a more thorough description of the purpose of the applied statistical tests (65%), indication of the practical significance of the obtained results, including calculation of relevant effect size measures (64%), analysis of assumptions necessary for the application of specific statistical tests (58%), and consideration of the impact of outlier values on the obtained results (34%). ConclusionTo improve the quality of statistical reporting in biomedical journals, greater emphasis should be placed on implementing SAMPL Guidelines.

Leveraging Machine Learning for Sophisticated Rental Value Predictions: A Case Study from Munich, Germany

There has been very limited research conducted to predict rental prices in the German real estate market using an AI-based approach. From a general perspective, conventional approaches struggle to handle large amounts of data and fail to consider the numerous elements that affect rental prices. The absence of sophisticated, data-driven analytical tools further complicates this situation, impeding stakeholders, such as tenants, landlords, real estate agents, and the government, from obtaining the accurate insights necessary for making well-informed decisions in this area. This paper applies novel machine learning (ML) approaches, including ensemble techniques, neural networks, linear regression (LR), and tree-based algorithms, specifically designed for forecasting rental prices in Munich. To ensure accuracy and reliability, the performance of these models is evaluated using the R2 score and root mean squared error (RMSE). The study provides two feature sets for model comparison, selected by particle swarm optimisation (PSO) and CatBoost. These two feature selection methods identify significant variables based on different mechanisms, such as seeking the optimal solution with an objective function and converting categorical features into target statistics (TSs) to address high-dimensional issues. These methods are ideal for this German dataset, which contains 49 features. Testing the performance of 10 ML algorithms on two sets helps validate the robustness and efficacy of the AI-based approach utilising the PyTorch framework. The findings illustrate that ML models combined with PyTorch-based neural networks (PNNs) demonstrate high accuracy compared to standalone ML models, regardless of feature changes. The improved performance indicates that utilising the PyTorch framework for predictive tasks is advantageous, as evidenced by a statistical significance test in terms of both R2 and RMSE (p-values &lt; 0.001). The integration results display outstanding accuracy, averaging 90% across both feature sets. Particularly, the XGB model, which exhibited the lowest performance among all models in both sets, significantly improved from 0.8903 to 0.9097 in set 1 and from 0.8717 to 0.9022 in set 2 after being combined with the PNN. These results showcase the efficacy of using the PyTorch framework, enhancing the precision and reliability of the ML models in predicting the dynamic real estate market. Given that this study applies two feature sets and demonstrates consistent performance across sets with varying characteristics, the methodology may be applied to other locations. By offering accurate projections, it aids investors, renters, property managers, and regulators in facilitating better decision-making in the real estate sector.

Rice Leaf Diseases Classification Using Deep Learning Algorithms for Smartphone Application Development: An Empirical Study

Rice is the most widely consumed grain across the world. The rice plants often suffer from diseases. Early detection of such diseases and adopting remedial measures can help the farmers to avoid major losses and can produce best-quality crops in large quantities. However, the conventional rice leaf disease detection techniques are often not accurate, time-consuming and sometimes require laboratory testing. In this context, automatic rice leaf disease detection techniques are presented based on the various deep learning classifiers (namely MobileNetV2, ResNet50, VGG16 and Le-Net5) and an Android application is also developed in order to instantly determine the possible rice diseases from the uploaded rice leaf images captured by the smartphone. The developed models are tested using the publicly available benchmark rice leaf dataset containing three types of rice leaf diseases, namely bacterial leaf blight, leaf smut and brown spot. Experimental results show that MobileNetV2 model performed better compared to other models in terms of classification accuracy, recall and [Formula: see text]-score. The results of statistical significance test also confirmed the superiority of the MobileNetV2 model over other compared deep learning models.

Combined detection of serum adiponectin and pregnancy-associated plasma protein A for early prediction of gestational diabetes mellitus.

Early diagnosis of gestational diabetes mellitus (GDM) reduces the risk of adverse perinatal and maternal outcomes. At present, the value of serum adiponectin (ADP) and pregnancy-associated plasma protein A (PAPP-A) in clinical practice for the diagnosis of GDM in early pregnancy is unclear. To investigate the predictive value of serum ADP and PAPP-A in GDM. The electronic medical record data of all pregnant women from Zhongshan People's Hospital from 2018 to 2021 were retrospectively collected and divided into GDM group and control group according to whether GDM occurred. ADP and PAPP-A levels of the 2 groups were detected in early pregnancy, and the related factors of GDM were analyzed by binary logistic regression analysis. Receiver operating characteristic (ROC) curves of ADP and PAPP-A in predicting GDM in the early pregnancy were plotted and their clinical predictive value was analyzed. The significance level for all statistical tests is 0.05. Compared with the non-GDM group, the ADP of the GDM group was significantly lower than that of the non-GDM group [(8.19 ± 2.24) vs. (10.04 ± 2.73)]mg/L, the difference between groups was statistically significant (P < .05), and the multiple of median (MoM) of PAPP-A was significantly lower than that of the non-GDM group (1.13 ± 0.52) versus (1.45 ± 0.61) (P < .05). Binary logistic regression analysis showed that elevated serum ADP and PAPP-A levels were negatively correlated with the subsequent development of GDM [odds ratio (OR) 95% confidence interval (95% CI)] was 0.626 (0.536, 0.816), 0.934 (0.908, 0.961), respectively, P < .05.ROC curve analysis showed that the sensitivity and specificity of ADP and PAPP-A in predicting gestational diabetes were79.1% and 58.6%, respectively, 92.7% and 73.1%, and respectively. The area under curve (AUC) is 0.755 for ADP and 0.770 for PAPP-A. The AUC of the combined detection was 0.867, both of which were higher than that of single index diagnosis, and the sensitivity and specificity of the combined detection were 0.958 and 0.853, respectively. In summary, PAPP-A and ADP levels are independent related factors affecting the occurrence of GDM. The combined detection of PAPP-A and ADP should be utilized in diagnosing GDM to improve pregnancy outcomes for pregnant women.

DIGITAL TEACHING MATERIAL OF SUSTAINABLE LIFESTYLE THEME WITH ETHNO-PJBL TO PROMOTE STUDENTS’ KNOWLEDGE AND CREATIVE THINKING ABILITIES

Purpose: This study aims to analyze the effects of digital teaching materials on the theme of sustainable lifestyle integrated with Ethno-PjBL on knowledge and creative thinking skills in learning in the Merdeka Curriculum. Theoretical Framework: The idea behind the development of digital learning materials on the theme of sustainable lifestyle is to promote awareness and practice of sustainability among students through the integration of technology in learning. By combining a project-based learning model enriched by local cultural values (Ethno-PjBL), students are not only invited to understand the concept of sustainable lifestyle, but also how to apply it in their cultural context. Method: This study used a quasi-experimental method with a posttest only control group design. The sample of this study was grade X students at SMAN Kota Jambi, with the experimental class using integrated digital teaching materials ethno-PjBL and the control class using conventional learning methods. Data were analyzed using descriptive statistical tests, Kolmogorov-Smirnov normality tests, and Mann-Whitney tests. Results and Discussion: Digital teaching materials on sustainable lifestyle themes integrated with ethno-PjBL have a positive impact on students' knowledge and creative thinking skills. The experimental class using the digital teaching materials showed better results compared to the control class using conventional learning methods. Research Implications: The results of this study support the integration of sustainable lifestyle-themed digital teaching materials with the Ethno-PjBL approach, which not only strengthens students' academic knowledge, but also fosters creative thinking skills and awareness of local cultural values. The findings of this study can encourage educators and policy makers to further adopt and develop contextual and relevant digital teaching materials, especially those that focus on global issues such as sustainability, but are still integrated with local wisdom. The implications of this study also open up opportunities for further research to explore the potential of digital teaching materials in other subjects or at different levels of education.

The Effect of Complementary Acupressure Therapy on the Incidence of Nausea and Vomiting After Regional Block Anesthesia (Spinal Anesthesia) in the Recovery Room of the Imelda Buruh Indonesia General Hospital, Medan

Postoperative nausea and vomiting is one of the common side effects of spinal anesthesia. Nausea and vomiting affect patient morbidity such as stress, discomfort, dehydration, prolonging treatment time and increasing treatment costs. This study aims to determine the effect of acupressure therapy on the incidence of nausea and vomiting after spinal anesthesia in the recovery room of the Imelda Labor Indonesia General Hospital, Medan. This type of research is a quantitative study with a quasi-experimental research method. Data reports in the province of North Sumatra, there are 25,602 patients undergoing surgery. While at the Umim Labor Indonesia Hospital, Medan, the data on surgical patients as of January-March 2024 amounted to 666 patients, 250 patients were found to have spinal anesthesia. This study was conducted in February - June 2024 at the Imelda Labor Indonesia General Hospital, Medan. A sample of 20 respondents was taken.: The results of the statistical test obtained an α value of 0.000 (α &lt;0.05), thus it was concluded that there was an effect of acupressure therapy on the incidence of nausea and vomiting after spinal anesthesia at the Imelda Labor Indonesia General Hospital, Medan. Based on the characteristics of respondents based on age, they were in the age range of 36-40 years, which was 55%, based on gender, the majority of respondents were women, which was 60%, respondents based on a history of smoking were 65%, the distribution of respondents with a history of nausea and vomiting was 55% and the majority of respondents with an incidence of nausea and vomiting was 60%. The recommendation for this study is that acupressure therapy can be applied in nursing practice so that patients are able to do it independently. For the Imelda Labor Indonesia General Hospital, Medan, it is necessary to carry out a risk scoring of nausea and vomiting in patients before surgery to minimize the incidence of nausea and vomiting after surgery.

Comparison of treatment results of femoral shaft fracture with two methods of intramedullary nail (IMN) and plate

BackgroundFracture of the femur is one of the most common fractures that, if not stabilized and treated properly, may lead to severe disability, impairment of the individual’s efficiency, and numerous complications. This study aimed to evaluate the treatment results of femoral shaft fracture with two methods intramedullary nail (IMN) and Plate.Materials and methodsIn this cross-sectional study, 60 patients with femoral bone fractures were admitted to Imam Khomeini Hospital in Jiroft in 2020 and were treated for at least one year after discharge. They were divided into two treatment groups - Plate fracture fixation (n = 30) and IMN fracture fixation (n = 30). Data were collected using a researcher-made checklist including patient demographics and treatment outcomes. The collected data were analyzed using SPSS-v 26 statistical software and descriptive and inferential statistical tests at a significance level of p < 0.05.ResultsPatients in the Plate treatment group were generally older (50–60 years) compared to the IMN treatment group (30–40 years), and there were more men than women in both groups. Only 10% of patients in each group developed superficial infections after surgery. There were more cases of deep infections in the Plate group, but it was not statistically significant. The IMN group had fewer cases of malignancy and claudication compared to the Plate group. Patients in the IMN group also returned to functional activities faster than those in the Plate group, which was a statistically significant difference.ConclusionConsidering that deep infection, non-union, malunion, claudication, and ability to return to functional activities in the group using nails treated was less than the group treated with plates, the treatment method of femoral fracture using IMN is the preferred treatment method.

Genetic Insights into Sepsis: Mendelian Randomization Analysis of Cerebrospinal Fluid Metabolites.

Sepsis, a life-threatening response to infection leading to systemic inflammation and organ dysfunction, has been hypothesized to be influenced by metabolic alterations in cerebrospinal fluid (CSF). Despite extensive research, the specific metabolic pathways contributing to sepsis remain unclear. This study aims to elucidate the causal relationships between CSF metabolites and sepsis risk using Mendelian Randomization (MR), offering insights that could lead to novel therapeutic strategies. We conducted a two-sample MR analysis using genetic variants as instrumental variables (IVs) to investigate 338 CSF metabolites identified through a genome-wide association study. Data on sepsis-related outcomes were extracted from the genome-wide association study (GWAS) catalog encompassing 486,484 individuals of European descent. IVs were rigorously selected based on stringent genetic association and linkage disequilibrium criteria. Statistical analyses, including inverse variance weighting (IVW) and weighted median methods, were performed using the 'TwoSampleMR' package in R software, supplemented by comprehensive sensitivity analyses to ensure the robustness of our findings. Our analysis identified 19 CSF metabolites causally associated with sepsis risk. Notably, metabolites such as 1-palmitoyl-2-stearoyl-gpc (16:0/18:0) and 2-hydroxyglutarate showed significant negative correlations with sepsis risk. The reverse MR analysis further revealed that sepsis could negatively impact certain CSF metabolite levels, particularly Ribonate, suggesting a bidirectional relationship. These relationships were substantiated by rigorous statistical testing and sensitivity analyses confirming the absence of horizontal pleiotropy and the stability of our results across various MR methods. This study demonstrates significant causal associations between specific CSF metabolites and the risk of developing sepsis, highlighting the potential for these metabolites to serve as biomarkers or therapeutic targets. The bidirectional nature of these findings also suggests that sepsis itself may alter metabolic profiles, offering further avenues for intervention.

Oversight of Government Spending on Combating Covid-19

The research aims to analyze the federal government's expenditures in 2020 and 2021 related to combating the COVID-19 pandemic in search of fraud indicators. This period was characterized by a sudden increase in public spending, accompanied by less stringent procurement processes. The Newcomb-Benford Law describes the frequency of leading digits in datasets and is presented as an effective tool for identifying anomalies and fraud in financial records, being widely explored in various fields, particularly in audits and accounting. A comparison was made between the observed and expected frequencies for the first, second, and first two digits of the committed values, segregated by year or procurement method. The analysis was conducted through graphs and statistical tests to verify the adherence of distributions to the Newcomb-Benford Law. Commitments made in 2020 showed better adherence than those in 2021, suggesting a higher probability of manipulations or fraud in the second year of the pandemic. Additionally, expenditures resulting from bidding processes were more compliant when compared to non-bid expenditures, confirming the perception that there is a higher likelihood of manipulation or fraud in non-bid spending. The research reveals indications that can be interpreted as warnings for oversight and control bodies, with the proposed approach serving as a mechanism for auditing government expenditures, assisting in the selection of samples that require detailed analysis by auditors and investigator.

Chromatic Adaption of Two Universal Composites: Spectrophotometric Analysis

Objective: The purpose of this study was to evaluate the chromatic adaptability and color stability of two different composite resins, Omnichroma and Estelite Bulk-Fill Flow, in Class V restorations at different times. Materials and methods: Standardized Class V cavities were prepared on the labial surface of 34 extracted intact and noncarious human permanent molars. The dental elements were randomly divided into two groups according to the resin composite material. Group 1 was restored with Omnichroma (Tokuyama Dental Corporation Inc., Tokyo, Japan) and Group 2 was restored with Estelite BulkFill Flow Universal (Tokuyama Dental Corporation Inc., Tokyo, Japan). Color properties were assessed using a spectrophotometer, SpectroShadeTM Micro (MHT Optic Research, Niederhasli, Switzerland), at baseline (T0), immediately after Class V restoration (T1), 24 h after restoration (T2) and after thermocycling (T3) (ISO/TS 11405, 2015 protocol). Color difference (ΔE) was analyzed with a Student’s t-test and a Wilcoxon–Mann–Whitney test to evaluate the differences, in terms of chromatic adaptability, between the two materials (inter-group analysis) while Kruskal–Wallis test e Two-way ANOVA statistical tests were used to evaluate the color stability of each material over time (intra-group analysis). Results: Regarding the inter-group analysis, there were no statistically significant differences between the two materials in all the comparisons: T0–T1 (p = 0.9025), T0–T2 (p = 0.2779), T0–T3 (p = 0.4694). Moreover, both groups showed an average ΔE &gt; 2. In the intra-group analysis, no statistically significant differences were observed in either Group 1 (p = 0.954) or Group 2 (p = 0.8654). Conclusions: The in vitro color matching, assessed by spectrophotometry, of the two tested resin composites does not vary at different time intervals. Furthermore, even though both composites use different mechanisms to produce the color the human eye perceives, they show very similar chromatic adaptability.