Diagnostic accuracy of endoscopic ultrasonographic shear wave elastography for assessing early chronic pancreatitis using the Japanese diagnostic criteria 2019.

Background and Aim: Endoscopic ultrasound shear wave elastography (EUS-SWE) can facilitate an objective evaluation of pancreatic fibrosis. Although it is primarily applied in evaluating chronic pancreatitis, its efficacy in assessing early chronic pancreatitis (ECP) remains underinvestigated. This study evaluated the diagnostic accuracy of EUS-SWE for assessing ECP diagnosed using the Japanese diagnostic criteria 2019. Methods: In total, 657 patients underwent EUS-SWE. Propensity score matching was used, and the participants were classified into the ECP and normal groups. ECP was diagnosed using the Japanese diagnostic criteria 2019. Pancreatic stiffness was assessed based on velocity (Vs) on EUS-SWE, and the optimal Vs cutoff value for ECP diagnosis was determined. A practical shear wave Vs value of ≥50% was considered significant. Results: Each group included 22 patients. The ECP group had higher pancreatic stiffness than the normal group (2.31 ± 0.67 m/s vs. 1.59 ± 0.40 m/s, p < 0.001). The Vs cutoff value for the diagnostic accuracy of ECP, as determined using the receiver operating characteristic curve, was 2.24m/s, with an area under the curve of 0.82 (95% confidence interval: 0.69-0.94). A high Vs was strongly correlated with the number of EUS findings (rs = 0.626, p < 0.001). Multiple regression analysis revealed that a history of acute pancreatitis and ≥2 EUS findings were independent predictors of a high Vs. Conclusions: There is a strong correlation between EUS-SWE findings and the Japanese diagnostic criteria 2019 for ECP. Hence, EUS-SWE can be an objective and invaluable diagnostic tool for ECP diagnosis.

The relationship between general self-efficacy and nursing practice competence for second-year nurses: Empirical quantitative research.

AIM: To examine the relationship between general self-efficacy and nursing practice competence for nurses in the second year of employment. DESIGN: A cross-sectional design was used. DATA SOURCES: The study included 596 nurses in their second year of employment at 75 medical facilities across Japan and used an online questionnaire survey for data collection. RESULTS: The covariance structure analysis showed the path from general self-efficacy (latent variable) to nursing practice competence. Positive correlations were found between all factors on both scales. Multiple regression analysis results showed that the general self-efficacy factors of 'positivity in behavior' and 'confidence in social competence' affect nursing practice competence. CONCLUSION: This study emphasizes the importance of enhancing the general self-efficacy of second-year nurses to improve their nursing practice competence. To achieve this, it suggests developing strategies from the perspective of the factors that comprise general self-efficacy. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: The findings suggest that improving general self-efficacy can enhance nursing practice competence, which could inform the development of interventions to support nurses in improving their competence. The study provides basic data for improving nurses' practice competence. IMPACT: This study is the first to establish a relationship between general self-efficacy and nursing practice competence among second-year nurses. It demonstrates the significance of general self-efficacy in enhancing nursing practice competence, particularly for second-year nurses worldwide who may be struggling with their nursing practice competence and considering leaving the profession. The findings offer practical implications for stakeholders involved in nursing education and training programs, with potential applications in professional development. REPORTING METHOD: This manuscript adheres to the STROBE guidelines for the reporting of cross-sectional studies. PATIENT OR PUBLIC CONTRIBUTION: There was no patient or public contribution.

Consumer awareness and knowledge regarding use of non-steroidal anti-inflammatory drugs (NSAIDs) in a metropolitan area.

Background: Non-steroidal anti-inflammatory drugs (NSAIDs) have well-known adverse effects, and numerous studies have shown inappropriate behaviors regarding their use. The primary aim of this study was to analyze the knowledge, attitudes, and behaviors regarding the use of NSAIDs simultaneously in one of the largest and most populated areas of Italy, Naples. Methods: From 2021 December 14th to 2022 January 4th, a cross-sectional survey study was conducted among community centers, working places, and universities using a snowball sampling method. For inclusion in the study, the participants were required to be at least 18 years old and residents in the metropolitan area of Naples. Three multiple linear regression analysis (MLRA) models were developed by including variables that could potentially be associated with the following outcomes of interest: knowledge (Model I), attitudes (Model II), and behavior (Model III) regarding the use of NSAIDs. Results: Data were acquired from 1,012 questionnaires administered to subjects evenly divided by gender with an average age of 36.8 years and revealed that only 7.9% of the participants self-admittedly did not take NSAIDs, while approximately half the participants (50%) admitted to occasionally using them. The results showed a statistically significant correlation between attitudes regarding the appropriate use of NSAIDs and less knowledge. The regression analyses indicated that behaviors regarding the appropriate use of NSAIDs were statistically significant in younger respondents, non-smokers, and those without children. These interesting results showed that behaviors regarding the appropriate use of NSAIDs were significantly higher among respondents with less knowledge and more positive attitudes. Conclusion: According to the collected data and statistical analysis results, it is possible to identify factors that can greatly affect inappropriate behaviors regarding the use of NSAIDs and establish targeted prevention programs.

Erratum: Effects of COVID-19-targeted non-pharmaceutical interventions on pediatric hospital admissions in North Italian hospitals, 2017 to 2022: a quasi-experimental study interrupted time-series analysis.

[This corrects the article DOI: 10.3389/fpubh.2024.1393677.].

Modeling of scour hole characteristics under turbulent wall jets using machine learning.

The novelty of the present study is to investigate the parameters that depict the scour hole characteristics caused by turbulent wall jets and develop new mathematical relationships for them. Four significant parameters i.e., depth of scouring, location of scour depth, height of the dune and location of dune crest are identified to represent a complete phenomenon of scour hole formation. From the gamma test, densimetric Froude number, apron length, tailwater level, and median sediment size are found to be the key parameters that affect these four dependent parameters. Utilizing the previous data sets, Multi Regression Analysis (linear and non-linear) has been performed to establish the relationships between the dependent parameters and influencing independent parameters. Further, artificial neural network-particle swarm optimisation (ANN-PSO) and gene expression programming (GEP) based models are developed using the available data. In addition, results obtained from these models are compared with proposed regression equations and the best models are identified employing statistical performance parameters. The performance of the ANN-PSO model (RMSE = 1.512, R2 = 0.605), (RMSE = 6.644, R2 = 0.681), (RMSE = 6.386, R2 = 0.727) and (RMSE = 1.754, R2 = 0.636) for predicting four significant parameters are more satisfactory than that of regression and other soft computing techniques. Overall, by analysing all the statistical parameters, uncertainty analysis and reliability index, ANN-PSO model shows good accuracy and predicts well as compared to other presented models.

Survival outcomes and prognostic factors of advanced gastrointestinal stromal tumors: in the era of multiple tyrosine kinase inhibitors.

Background: Tyrosine kinase inhibitors (TKIs) have shown great efficacy in the treatment of advanced gastrointestinal stromal tumors (GISTs), significantly prolonging the survival of patients. In the era of imatinib, a few studies reported some prognostic factors for patients with advanced GISTs, such as age, sex, performance status, diameter of the largest lesions, KIT exon mutations, and some hematological examination results. However, with the advent of more TKIs, the prognostic factors for patients with advanced GISTs have not been fully understood in the era of multiple TKIs. In this study, we aimed to identify independent prognostic factors associated with the survival of patients diagnosed with advanced GISTs. Methods: Data on clinicopathologic characteristics, treatment approaches, and survival were retrospectively collected for patients with primary unresectable or recurrent GISTs treated from January 2010 to July 2023 at the First Affiliated Hospital of Chongqing Medical University, China. Univariable and multivariable Cox proportional hazards regression models were used to identify independent prognostic factors of survival. Results: A total of 194 patients were included in the analysis. The median follow-up duration was 59.9 months (range, 2.7-141.7 months). The median overall survival (mOS) in this cohort was 76.5 months (95% confidence interval, 63.4 to 89.6 months). All patients received TKI therapy during the follow-up period, and 56.2% received two or more types of TKIs. In multivariable Cox analysis, younger age, a single lesion at enrollment, no previous use of TKIs, smaller tumor burden, good Eastern Cooperative Oncology Group performance status (ECOG PS ≤1), and lesions limited to the liver were independent prognostic factors for better survival. Conclusions: We found that a single lesion at enrollment, no previous use of TKIs, a smaller tumor burden, and lesions limited to the liver were associated with better survival. Drug resistance is a severe challenge for advanced GISTs, and several factors mentioned above may be correlated with the development of drug resistance, leading to the poor survival of patients.

Quantitative analysis of solid dosage forms of Atenolol by Raman spectroscopy.

OBJECTIVE: To develop a Raman spectroscopy-based analytical model for quantification of solid dosage forms of active pharmaceutical ingredient (API) of Atenolol.Significance: For the quantitative analysis of pharmaceutical drugs, Raman Spectroscopy is a reliable and fast detection method. As part of this study, Raman Spectroscopy is explored for the quantitative analysis of different concentrations of Atenolol. METHODS: Various solid-dosage forms of Atenolol were prepared by mixing API with excipients to form different solid-dosage formulations of Atenolol. Multivariate data analysis techniques, such as Principal Component Analysis (PCA) and Partial least square regression (PLSR) were used for the qualitative and quantitative analysis, respectively. RESULTS: As the concentration of the drug increased in formulation, the peak intensities of the distinctive Raman spectral characteristics associated with the API (Atenolol) gradually increased. Raman spectral data sets were classified using PCA due to their distinctive spectral characteristics. Additionally, a prediction model was built using PLSR analysis to assess the quantitative relationship between various API (Atenolol) concentrations and spectral features. With a goodness of fit value of 0.99, the root mean square errors of calibration (RMSEC) and prediction (RMSEP) were determined to be 1.0036 and 2.83 mg, respectively. The API content in the blind/unknown Atenolol formulation was determined as well using the PLSR model. CONCLUSIONS: Based on these results, Raman spectroscopy may be used to quickly and accurately analyze pharmaceutical samples and for their quantitative determination.

[Construction and application of a risk index of Echinococcus infection based on the classification of echinococcosis lesions].

OBJECTIVE: To investigate the feasibility of constructing the risk index of Echinococcus infection based on the classification of echinococcosis lesions, so as to provide insights into the management of echinococcosis. METHODS: The imaging data of echinococcosis cases were collected from epidemiological surveys of echinococcosis in China from 2012 to 2016, and the detection of incident echinococcosis cases was captured from the annual echinococcosis prevention and control reports across provinces (autonomous regions) and Xinjiang Production and Construction Corps in China from 2017 to 2022. After echinococcosis lesions were classified, a risk index of Echinococcus infection was constructed based on the principle of discrete distribution marginal probability and multi-group classification data tests. The correlation between the risk index of Echinococcus infection and the detection of incident echinococcosis cases was evaluated in the provinces (autonomous regions and corps) from 2017 to 2022, and the correlations between the short and medium-term risk indices and between the medium and long-term risk indices of Echinococcus infection were examined using a univariate linear regression model. RESULTS: A total of 4 014 echinococcosis cases in China from 2012 to 2016 were included in this study. The short-, medium- and long-term risk indices of E. granulosus infection varied in echinococcosis-endemic provinces (autonomous regions and corps) of China (χ2 = 4.12 to 708.65, all P values < 0.05), with high short- (0.058), medium- (0.137) and long-term risk indices (0.104) in Tibet Autonomous Region, and the short-, medium- and long-term risk indices of E. multilocularis infection varied in echinococcosis-endemic provinces (autonomous regions and corps) of China (χ2 = 6.74 to 122.60, all P values < 0.05), with a high short-term risk index in Sichuan Province (0.016) and high medium- (0.009) and long-term risk indices in Qinghai Province (0.018). There were no significant correlations between the risk index of E. granulosus infection and the detection of incident cystic echinococcosis cases during the study period (t = -0.518 to 2.265, all P values > 0.05), and strong correlations were found between the risk indices of E. multilocularis infection and the detection of incident alveolar echinococcosis cases (including mixed type) in 2018, 2020, 2021, 2022, during the period from 2017 through 2020, from 2017 through 2021, from 2017 through 2022 (all r values > 0.7, t = 2.521 to 3.692, all P values < 0.05). Linear regression models were established between the risk index of E. multilocular infection and the detection of alveolar echinococcosis cases (including mixed type), and the models were all statistically significant (b = 0.214 to 2.168, t = 2.458 to 3.692, F = 6.044 to 13.629, all P values < 0.05). The regression coefficients for the correlations between the medium- and short-term, and between the long- and medium-term risk indices of E. granulosus infection were 2.339 and 0.765, and the regression coefficients for the correlations between the medium- and short-term, and between the long- and medium-term risk indices of E. multilocular infection were 0.280 and 1.842, with statistical significance seen in both the regression coefficients and regression models (t = 16.479 to 197.304, F = 271.570 to 38 928.860, all P values < 0.05). CONCLUSIONS: The risk index of Echinococcus infection has been successfully established based on the classification of echinococcosis lesions, which may provide insights into the prevention and control, prediction, diagnosis and treatment, and classified management of echinococcosis.

Factors influencing self-management behaviors in persons with lupus nephritis: A cross-sectional study.

Background: Patients with lupus nephritis experience disease symptoms and side effects from treatment. Although self-management behaviors are important in patients with this disease, there is limited research on the factors influencing these behaviors. Objective: This study aimed to examine the factors influencing self-management behaviors in patients with lupus nephritis. Methods: This cross-sectional study was conducted in 240 patients with lupus nephritis at a university hospital in Thailand between August 2019 and December 2020 using a random sampling method. Data were collected using a demographic and clinical characteristic questionnaire, Self-Management Behavior Questionnaire, Self-efficacy for Managing Chronic Disease: A 6-item Scale, Knowledge about Lupus Nephritis Questionnaire, Family Support Scale, Social Networks in Adult Life Questionnaire, and Memorial Symptom Assessment Scale for Lupus Nephritis. Descriptive statistics and multiple linear regression analyses were employed. Results: The participants reported a moderate level of self-management behaviors. Multiple regression analyses revealed that disease duration, income, symptoms, self-efficacy, knowledge, family support, social networks, and classes of lupus nephritis significantly explained 21% of the variance in self-management behaviors (R2 = 0.21; F(8,231) = 7.73; p <0.001). Family support (ß = 0.32, p <0.001) and symptoms (ß = -0.23, p <0.001) were significant determinants of self-management behaviors in patients with lupus nephritis. Conclusion: The findings provide valuable insight for nurses to better understand the factors influencing self-management behaviors in patients with lupus nephritis. Patients with low family support and high symptom severity may face difficulty in performing self-management behaviors. Nurses should pay more attention to these patients and provide family-based interventions to optimize self-management behaviors in this population.

Addressing the Gap: Racial Disparities and Public Health Strategies in the Epidemiology of Gastrointestinal Stromal Tumors.

Background Gastrointestinal stromal tumors (GISTs) represent the most common mesenchymal neoplasms of the gastrointestinal tract, arising from the interstitial cells of Cajal. These tumors bridge the nervous system and muscular layers of the gastrointestinal tract, playing a crucial role in the digestive process. The incidence of GISTs demonstrates notable variations across different racial and ethnic groups, underscoring the need for in-depth analysis to understand the interplay of genetic, environmental, and socioeconomic factors behind these disparities. Linear regression analysis is a pivotal statistical tool in such epidemiological studies, offering insights into the temporal dynamics of disease incidence and the impact of public health interventions. Methodology This investigation employed a detailed dataset from 2009 to 2020, documenting GIST incidences across Asian, African American, Hispanic, and White populations. A meticulous preprocessing routine prepared the dataset for analysis, which involved data cleaning, normalization of racial terminologies, and aggregation by year and race. Linear regression models and Pearson correlation coefficients were applied to analyze trends and correlations in GIST incidences across the different racial groups, emphasizing an understanding of temporal patterns and racial disparities in disease incidence. Results The study analyzed GIST cases among four racial groups, revealing a male predominance (53.19%) and an even distribution of cases across racial categories: Whites (27.66%), Hispanics (25.53%), African Americans (24.47%), and Asians (22.34%). Hypertension was the most common comorbidity (32.98%), followed by heart failure (28.72%). The linear regression analysis for Asians showed a decreasing trend in GIST incidences with a slope of -0.576, an R-squared value of 0.717, and a non-significant p-value of 0.153. A significant increasing trend was observed for Whites, with a slope of 0.581, an R-squared value of 0.971, and a p-value of 0.002. African Americans exhibited a moderate positive slope of 0.277 with an R-squared value of 0.470 and a p-value of 0.201, indicating a non-significant increase. Hispanics showed negligible change over time with a slope of -0.095, an R-squared value of 0.009, and a p-value of 0.879, suggesting no significant trend. Conclusions This study examines GIST incidences across racial groups, revealing significant disparities. Whites show an increasing trend (p = 0.002), while Asians display a decreasing trend (p = 0.153), with stable rates in African Americans and Hispanics. Such disparities suggest a complex interplay of genetics, environment, and socioeconomic factors, highlighting the need for targeted research and interventions that address these differences and the systemic inequalities influencing GIST outcomes.

Use of Statistics in Plant Cell Tissue Culture.

Statistics and experimental design are important tools for plant cell and tissue culture researchers and should be used when planning and conducting experiments as well as during the analysis and interpretation of experimental results. The chapter provides basic concepts important to the statistical analysis of data obtained from plant tissue culture experiments and illustrates the application of common statistical procedures to analyze binomial, count, and continuous data for experiments with different treatment factors as well as identifying trends of dosage treatment factors.

Exploring Selenoprotein P in Liver Cancer: Advanced Statistical Analysis and Machine Learning Approaches.

Selenoprotein P (SELENOP) acts as a crucial mediator, distributing selenium from the liver to other tissues within the body. Despite its established role in selenium metabolism, the specific functions of SELENOP in the development of liver cancer remain enigmatic. This study aims to unravel SELENOP's associations in hepatocellular carcinoma (HCC) by scrutinizing its expression in correlation with disease characteristics and investigating links to hormonal and lipid/triglyceride metabolism biomarkers as well as its potential as a prognosticator for overall survival and predictor of hypoxia. SELENOP mRNA expression was analyzed in 372 HCC patients sourced from The Cancer Genome Atlas (TCGA), utilizing statistical methodologies in R programming and machine learning techniques in Python. SELENOP expression significantly varied across HCC grades (p < 0.000001) and among racial groups (p = 0.0246), with lower levels in higher grades and Asian individuals, respectively. Gender significantly influenced SELENOP expression (p < 0.000001), with females showing lower altered expression compared to males. Notably, the Spearman correlation revealed strong positive connections of SELENOP with hormonal markers (AR, ESR1, THRB) and key lipid/triglyceride metabolism markers (PPARA, APOC3, APOA5). Regarding prognosis, SELENOP showed a significant association with overall survival (p = 0.0142) but explained only a limited proportion of variability (~10%). Machine learning suggested its potential as a predictive biomarker for hypoxia, explaining approximately 18.89% of the variance in hypoxia scores. Future directions include validating SELENOP's prognostic and diagnostic value in serum for personalized HCC treatment. Large-scale prospective studies correlating serum SELENOP levels with patient outcomes are essential, along with integrating them with clinical parameters for enhanced prognostic accuracy and tailored therapeutic strategies.

A Nationwide Nepalese Study to Establish Reference Intervals for Major Biochemical Analytes with Elucidation of Nepalese Features of Reference Values.

Despite immense importance of reference intervals (RIs) for clinical diagnosis, there have been no reliable RIs available for Nepalese. Hence, this nationwide study was organized to establish RIs for 30 common biochemical parameters. This study was conducted following the harmonized protocol provided by IFCC Committee on Reference Interval and Decision Limits (C-RIDL) with recruitment of 617 apparently healthy volunteers (18 - 65 years) by near-equal gender balance from 5 major cities. Fasting blood were collected, serum was separated and measured collectively using Beckman-Coulter/Olympus AU480 chemistry analyzer. The sources of variations of reference values (RVs) were evaluated by multiple regression analysis and nested ANOVA. Latent abnormal values exclusion (LAVE) method was applied to reduce influence of latent diseases. RIs were standardized based on a value-assigned serum panel provided by C-RIDL. By ANOVA, no between-city differences were observed, while sex-related changes were typically noted for urate, creatinine, iron, γ-glutamyl transferase (GGT), immunoglobulin M, and transferrin, but not for high-density lipoprotein cholesterol. Age-related changes were observed for total cholesterol (TC), triglyceride, low-density lipoprotein cholesterol, and C-reactive protein (CRP). RIs were successfully derived all parametrically. The LAVE procedure was effective in lowering upper limits for aspartate aminotransferase, alanine aminotransferase (ALT), and CRP. Compared to other collaborating countries, Nepalese RIs were low for urea, cholesterols, ALT, and high for triglyceride, GGT, CRP, immunoglobulin G, and complements. The RIs for major chemistry analytes were derived and standardized for nationwide use in Nepal. This study distinctly elucidated sources of variation and international features of Nepalese RIs. Supplementary Information: The online version supplementary material available at 10.1007/s12291-023-01123-6.

Empirical analysis of dust and noise pollutants produced in the wood-CNC machining process.

In the manufacturing processes, consideration of sustainability is of particular importance. The current study is concerned with the influences of changing the process variables on the reduction of pollutions in the wood-CNC machining operation. Noise and dust are the studied pollutants in the present research work. Process variables include feed rate, spindle speed, step-over, and depth of cut, and the aim is to predict the behavior of aforementioned pollutants variations in the current process. The amounts of these harmful factors are measured based on existing standards. In order to analyze the findings, adaptive neuro-fuzzy inference system (ANFIS) and regression analysis methods have been employed, separately. The effects of process parameters on response variables have been comprehensively studied. The research findings demonstrated that for the present problem, ANFIS outcomes are more accurate. According to the mean absolute error (MAE) criterion, the prediction errors of ANFIS for noise and dust factors were computed to, in turn, 0.50 and 14.89. Meanwhile, the error values for prediction of noise and dust responses using regression analysis were calculated as 1.54 and 34.62, respectively.

Divergent thinking as a predictor of life skills in patients with schizophrenia: Evidence from the modified Tinkertoy Test.

Aim: Patients with schizophrenia often exhibit poor life skills, posing significant clinical challenges. Life skills comprise cognitive functions crucial for planning daily activities, including divergent thinking. However, the cognitive deficits contributing to these diminished skills among patients with schizophrenia are underexplored. This study introduces a modified Tinkertoy Test (m-TTT) to investigate the correlation between life skills, divergent thinking, and psychological assessment tools in patients with schizophrenia. Methods: Fifty-two patients with schizophrenia, alongside a control group, matched for sex, age, and education, were evaluated using psychological assessment tools. For the patient group, the Life Skills Profile (LSP) and Positive and Negative Syndrome Scale were administered to measure functional abilities and psychiatric symptoms, respectively. Additionally, duration of disease and antipsychotic daily dosage levels were assessed exclusively in the patient group. Both groups were evaluated with the m-TTT, Idea Fluency Test (IFT), Design Fluency Test (DFT), and Brief Assessment of Cognition in Schizophrenia (BACS) to comprehensively assess cognitive functions. A stepwise multiple regression model was conducted to identify significant correlates of LSP total score among the patient group. Results: The schizophrenia group scored notably lower than the neurotypical controls on the m-TTT, IFT, DFT, and BACS. Our stepwise multiple regression analysis highlighted that the LSP total score was significantly correlated with the total m-TTT score and presence of negative symptoms. Conclusion: Divergent thinking could be a crucial factor in the life skills of individuals with schizophrenia. Rehabilitation programs based on this cognitive function might enhance their daily living capabilities.

Impact of Documented Fall-Risk, Self-Reported Health and Confidence to Prevent Falls on Concern About Falling Among Community-Dwelling Older Adults: Secondary Analysis of a Randomized Clinical Trial.

Purpose: Individuals identified as high fall risk are expected to have high concern about falling. However, perception and individual factors that influence concern about falling have yet to be thoroughly studied. We aimed to understand factors that influence concern about falling among older adults with increased risk for falling. Patients and Methods: This was a secondary analysis of a clinical trial among community-dwelling older adults (age ≥65 years old) at high risk for falls (n = 178). Descriptive and regression analyses were used. We analyzed the relationship between participants' baseline concern about falling - categorized into three groups: low (7-8), moderate (9-13), and high (≥14) - and factors that may impact their concern. Exploratory factors included age, sex, self-reported health status and confidence to address fall risks, fall risk scores, and physical performance measures. Results: Among these individuals, 15.2% reported low concern about falling. On average, individuals in higher concern about falling groups had higher fall risk scores (low [5.7], moderate [6.4], and high [8.0]; p < 0.001). Our regression model showed that the odds of being in a higher concern group increased by 21% for every one unit increase in fall risk score and increased by 67% for every one unit increase toward poorer health rating. Conversely, for every one unit increase in self-reported confidence, the odds of being in a higher concern group decreased by 27.5%. Conclusion: Knowledge of older adults' fall risk, health status, and concerns about falling can be used to assist in the personalization of fall prevention interventions for a more holistic approach.

Development of a Nomogram That Predicts the Risk of Atrial Fibrillation in Patients with Coronary Heart Disease.

Objective: To explore the risk factors of atrial fibrillation (AF) in patients with coronary heart disease (CHD), and to construct a risk prediction model. Methods: The participants in this case-control study were from the cardiovascular Department of Changzhou Affiliated Hospital of Nanjing University of Chinese Medicine from June 2016 to June 2023, and they were divided into AF group and non-AF group according to whether AF occurred during hospitalization. The clinical data of the two groups were compared by retrospective analysis. Multivariate Logistic regression analysis was used to investigate the risk factors of AF occurrence in CHD patients. The nomogram model was constructed with R 4.2.6 language "rms" package, and the model's differentiation, calibration and effectiveness were evaluated by drawing ROC curve, calibration curve and decision curve. Results: A total of 1258 patients with CHD were included, and they were divided into AF group (n=92) and non-AF group (n=1166) according to whether AF was complicated. Logistic regression analysis showed that age, coronary multiple branch lesion, history of heart failure, history of drinking, pulmonary hypertension, left atrial diameter, left ventricular end-diastolic diameter and diabetes mellitus were independent risk factors for the occurrence of AF in CHD patients (P < 0.05). The ROC curve showed that the AUC of this model was 0.956 (95% CI (0.916, 0.995)) and the consistency index was 0.966. The calibration curve of the model is close to the ideal curve. The analysis of decision curve shows that the prediction value of the model is better when the probability threshold of the model is 0.042~0.963. Conclusion: The nomogram model established in this study for predicting the risk of AF in patients with CHD has better predictive performance and has certain reference value for clinical identification of high-risk groups prone to AF in patients with CHD.

Prediction model for severe maternal morbidity in pregnant women with hypertensive disorders of pregnancy.

Objectives: To investigate risk factors for severe maternal morbidity (SMM) in pregnant women with hypertensive disorders of pregnancy (HDP) and to develop a risk prediction model. Methods: A prospective observational cohort study was conducted among pregnant women who were hospitalized for hypertensive disorders of pregnancy (HDP) between January 2016 and December 2020 in Fujian College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Province, China (a training set), and a risk predictive model was constructed. Pregnant women with HDP who were hospitalized between January 2021 and December 2021 were selected as a validation set. Concordance index (C-index) and calibration curves were used to test predictive model discrimination and calibration. Results: We included 970 pregnant women (790 in the training set and 180 in the validation set). Least absolute shrinkage and selection operator regression was used to screen for nine related variables such as intra-uterine growth retardation (IUGR), diastolic blood pressure (DBP) and systolic blood pressure (SBP) at suspected diagnosis, total bilirubin, albumin (ALB), uric acid, total cholesterol, serum magnesium, and suspected gestational age. SBP at suspected diagnosis (OR =1.22, 95%CI:1.08-1.42) and total cholesterol (OR = 1.78, 95%CI:1.17-2.80) were independent risk factors of severe maternal morbidity in pregnant women with HDP. A nomogram was constructed, and internal validation of the nomogram model was done using the bootstrap self-sampling method. C-index in the training and the validation set was 0.798 and 0.909, respectively. Conclusion: Our prediction model can be used to determine gestational hypertension severity in pregnant women.

Clinical characteristics and logistic regression analysis of macrolide-resistant Mycoplasma pneumoniae pneumonia in children.

PURPOSE: To investigate macrolide-resistant Mycobacterium pneumoniae (MRMP) pneumonia in children and construct a logistic regression model for mutations in the Mycoplasma pneumoniae drug-resistant gene. METHODS: Clinical data of 281 children were analyzed. Sequencing confirmed a mutation at the A2063G locus of the 23 S rRNA gene in 227 children (A2063G group); 54 children showed no mutations (non-MRMP [NMRMP] group). We compared clinical features, laboratory tests, imaging, and bronchoscopy results and constructed a multifactorial logistic regression model to analyze risk and protective factors. RESULTS: The A2063G group had longer durations of fever and hospitalization before admission, a higher proportion of treatment with sodium methylprednisolone succinate (MPS)/dexamethasone, longer time to discontinue hormones, and higher probability of combined infections. Monocyte percentage was significantly higher in the A2063G group. Imaging suggested a higher incidence of infections in the right lung compared to both lungs. Univariate analysis revealed fever duration before admission, hormone dose and duration, monocyte percentage, and mixed infections as risk factors for Mycoplasma pneumoniae infection with the A2063G mutation. The logistic regression model showed that mixed infections were an independent risk factor for the A2063G locus mutation, whereas hormone dose was a protective factor. CONCLUSION: A prevalence of macrolide resistance of 80.8% among children was observed in the region. Logistic regression analysis revealed that co-infection with other respiratory pathogens is an independent risk factor for the development of resistance genes, while the use of hormone dosage acts as a protective factor.

Brazilian undergraduates' and dentists' knowledge on preventing, diagnosing and managing dentin hypersensitivity: A cross-sectional questionnaire study.

OBJECTIVES: To analyse the knowledge of dental undergraduates and dentists on the prevention, diagnosis and management of dentin hypersensitivity (DH); to compare their knowledge scores; and to understand the related variables using a regression model. METHODS: An original online questionnaire investigated the attitudes, self-reported knowledge ('how much they thought they knew') and real knowledge ('how much they really knew') of 132 students and 338 dentists. Data were analysed descriptively, both knowledge scores were compared using Mann-Whitney and Wilcoxon signed-rank tests and data were subjected to two multiple linear regression analyses considering real knowledge scores as the dependent variable (α < 0.05). RESULTS: The self-reported knowledge on DH was higher than the real knowledge for both students and dentists, but dentists presented the highest scores. Gingival recession and acidic diet were reported as the main predisposing factors for DH by undergraduates and dentists. Students normally managed DH with dietary and hygiene instructions followed by a desensitizing agent application, while dentists managed with occlusal adjustments. The mechanism of glutaraldehyde/HEMA and bioactive fillers on DH is widely unknown by students and dentists. The majority of the questioned individuals cannot differentiate DH from sensitivity of caries or molar-incisor hypomineralization. CONCLUSION: Both students and dentists overestimate their knowledge of DH, revealing deficiencies in prevention, diagnosis and management. Students' knowledge improves towards the end of the Dentistry course, while younger dentists and PhD holders are more knowledgeable. Institutions should implement ongoing DH education for undergraduates and conduct interventions for experienced professionals, especially older ones.