Spearman Correlation Research Articles

Prospective evaluation of an AI algorithm for real-time LVEF assessment in acute coronary syndrome using left coronary angiograms: the CathEF multicenter study

Abstract Background Acute assessment of Left Ventricular Ejection Fraction (LVEF) is critical at time of percutaneous coronary intervention to optimize clinical management. The CathEF artificial intelligence algorithm offers a novel approach for real-time, intra-procedural LVEF assessment using routinely obtained left coronary artery angiograms without additional dye use[1]. Our objective was to evaluate the real-time application of the CathEF algorithm for LVEF measurement during coronary angiogram procedures in patients with acute coronary syndrome (ACS) and to compare its performance with transthoracic echocardiography (TTE) and left ventriculography. Methods The CathEF study is a prospective multi-center study that recruited ACS patients undergoing coronary angiography at two institutions from July 2022 to July 2023. Using the CathEF algorithm and the PACS-AI software, we analyzed 2 to 4 left coronary angiogram videos per procedure for LVEF assessment to compare to ventriculography (if indicated) and echocardiography performed during the same hospitalization. Operators were blinded to the CathEF AI-generated results. The primary measure was the algorithm's area under the receiving-operating characteristic curve (AUC) in identifying LVEF <40% or ≥40% compared to TTE-LVEF. Results 240 patients (32% female, average age 66 ± 12 years) were enrolled, with 207 undergoing TTE during index hospitalization (coronary angiogram to TTE mean delay of 0.8±6.3 days). The CathEF algorithm analyzed 881 coronary angiogram videos, averaging 3.12±1.66 per patient. Indications for angiography included unstable angina (18%), NSTEMI (47%), and STEMI (35%). The algorithm took under one minute to apply. CathEF’s performance yielded an AUC of 0.90 (95% CI, 0.840-0.96) and an MAE of 6.81% ± 0.43, with a Spearman correlation of 0.52. Conclusions This study provides proof-of-concept for prospective deployment of an AI algorithm at point-of-care with reliable LVEF measurement in real-time during ACS. This innovation holds the potential to ensure all ACS patients can receive prompt and appropriate care based on their LVEF.CathEF algorithm applied to an angiogramPACS-AI : Platform used to apply CathEF

The relationship between perceived parental phubbing and smartphone addiction in adolescents

Abstract Background Parental phubbing refers to the degree to which parents reduce or ignore their interactions with their children while taking care of their smartphones. Today, it has become important to conduct studies to understand the effects of parental phubbing on adolescents, which is increasing globally. This study aims to evaluate the relationship between perceived parental phubbing and smartphone addiction as well as depression in adolescents. Methods In this cross-sectional study, 314 adolescents aged 10-18 years who applied to the general pediatrics outpatient clinics of a university hospital in Ankara, the capital of Türkiye, were included. The questionnaire form used for data collection consisted of questions about the sociodemographic information of the participants, ‘Perceived Parental Phubbing Scale’, ‘Kutcher Adolescent Depression Scale Short Form’, and ‘Smartphone Addiction Short Form for Adolescents’ items. Descriptive statistics, Mann Whitney U, Kruskal Wallis H test and Spearman correlation analysis were used to analyse the data. A value of p < 0.05 was considered statistically significant. Results Depression and smartphone addiction levels were found to be significantly lower in adolescents who did not smoke, engaged in regular physical activity and had a close group of friends (p < 0.05). It was also found that the level of perceived parental phubbing was significantly higher in adolescents whose parents’ education level was above high school and who felt lonely (p < 0.05). Low level positive correlations was found between perceived parental phubbing and both depression (r = 0.116, p = 0.041) and smartphone addiction (r = 0.128, p = 0.023). Conclusions As the level of parental phubbing perceived by adolescents increased, the levels of depression and smartphone addiction in adolescents increased. These negative effects of parental phubbing on adolescents should be taken into consideration by mental health professionals. Key messages • It is important to consider and question parental phubbing as one of the related factors in adolescents with high levels of smartphone addiction and depression. • There is a need for studies to increase the awareness of parents, who are important role models for adolescents, about the concept of phubbing and its effects on adolescents’ mental health.

CILP1 and NTproBNP in pulmonary hypertension and right ventricular pressure overload: a translational experimental study

Abstract Introduction Cartilage intermediate layer protein 1 (CILP1) has emerged as a novel marker of right ventricular (RV) dysfunction in pulmonary hypertension (PH), although there is still little evidence on its role in different scenarios of RV pressure overload. The aim of our study was to analyze CILP1 as a biomarker of RV remodeling and PH severity, and compare it with N-terminal pro-brain natriuretic peptide (NTproBNP), in different experimental models of RV pressure overload. Methods Three different experimental models of RV pressure overload compared to a sham procedure were evaluated in 24 Yucatan pigs: chronic postcapillary PH by pulmonary vein banding (M1, n=6); chronic PH by aorto-pulmonary shunting (M2, n=6); RV pressure overload by PA banding (thus without PH) (M3, n=6); and sham procedure (M0, n=6). Animals were evaluated at 8 months after surgery by right heart catheterization, cardiac magnetic resonance (CMR), and blood/histological sampling. Levels of CILP1 and NTproBNP at the RV myocardium and blood were determined with dedicated ELISA and compared among groups by Wilcoxon test with Bonferroni correction. Associations between biomarkers and RV performance indices and pulmonary arterial pressure (PAP) were assessed with Spearman correlation test. Results M1 animals developed chronic postcapillary PH with normal left ventricular (LV) performance and RV maladaptive hypertrophy (RV fibrosis and systolic dysfunction). M2 animals developed chronic precapillary PH associated with LV dilatation and RV maladaptive hypertrophy. On contrast, M3-animals developed severe RV pressure overload (without PH) and hypertrophy but maintained normal RV systolic function. CILP1 and NTproBNP levels were moderately correlated (R=0.56, p=0.002). CILP1 levels in RV myocardium and plasma were significantly higher in M1, whereas NTproBNP plasma levels were significantly higher in M2 (Figure 1). CILP1 in plasma and RV myocardium significantly correlated with PAP, while myocardial CILP1 levels also correlated with RV extracellular volume (RV-ECV) by CMR (Figure 2). NTproBNP myocardial levels correlated with RV ejection fraction and RV-ECV and plasmatic levels correlated with PAP (Figure 2). Conclusions CILP1 levels were increased in the presence of PH and isolated RV dysfunction, whereas NTproBNP levels were increased in the model of PH, RV dysfunction and LV remodeling. Myocardial levels of both peptides correlated with diffuse fibrosis, estimated by CMR, whereas plasmatic levels of both biomarkers correlated with PAP. This suggests that CILP1 may be a more specific marker of RV dysfunction in PH, being less dependent of LV parameters.CILP1 and NTproBNP levels among modelsCorrelation with PAP & RV remodeling

Investigation of the Knowledge Level of Hospital Managers About Strategic Management Tools and Their Use

Objectives: Effective and efficient implementation of all elements of strategic management is important for health organizations to achieve their future goals. This study aims to examine the knowledge levels of hospital managers about strategic management tools, their usage of these tools, and the priorities and needs in tool selection. Materials and Methods: The population of the study is the managers working in private hospitals in Antalya Province. 90 managers constitute the sample of the study. The data were collected by face-to-face questionnaire method. The questionnaire includes sociodemographic characteristics form and statements to measure the level of knowledge and use of strategic management tools. Mann Whitney U and Kruskal-Wallis tests were applied to examine the differences between groups, and Spearman Correlation Analysis was applied to examine the relationships between variables. SPSS.25 Package Program was used to analyze the data obtained. Statistical significance was accepted at 0.05 level. Results: 59% of the participants were female, 63% had a bachelor's degree, and the majority (41%) were middle managers. Those who did not receive managerial training and strategic management training were the majority (54% and 71%, respectively). When the knowledge level of the managers about strategic management tools was analyzed, mission and vision (98.9%) received the highest score, and value chain analysis (73.3%) received the lowest score. It was observed that the priorities of the administrators in the selection of strategic management tools were different between the groups according to gender, level of education, and type of school graduated from. In addition, statistically significant relationships were found between the priorities in the selection of strategic management tools and age, professional experience and years of working in the organization. Conclusion: Managers have limited knowledge and use of strategic management tools and there are differences in the selection of strategic management tools according to their sociodemographic status.

Relationship between NT-proBNP, echocardiographic abnormalities and functional status in patients with subclinical diabetic cardiomyopathy

Abstract Background Persons with diabetes are at risk for developing a cardiomyopathy through several pathophysiological mechanisms independent of traditional risk factors for heart failure. Among those with so-called diabetic cardiomyopathy (DbCM), the relationship between natriuretic peptides, cardiac structural abnormalities and functional capacity is largely unknown. Purpose This study aimed to evaluate associations between NT-proBNP concentrations, clinical characteristics, echocardiographic findings, health status and activity, and outcomes from cardiopulmonary exercise testing Methods The Aldose Reductase Inhibition for Stabilization of Exercise Capacity in Heart Failure Trial (ARISE-HF) trial is evaluating the effects of AT-001, a novel aldose-reductase inhibitor in participants with DbCM without a prior history of heart failure (1). Participants were included if they had a known diagnosis of type 2 diabetes and age ≥60 (or ≥45 with a duration of diabetes of ≥10 years or estimated glomerular filtration rate ≤60 mL/min/1.73m2). Participants were required to have evidence of one of: structural cardiac abnormality, elevated cardiac biomarkers, or impaired exercise tolerance, defined as a peak oxygen uptake (VO2) ≤75% of predicted. In this prespecified subgroup analysis of the ARISE-HF trial, 685 participants with baseline echocardiography data, laboratory investigations, and functional assessment were included. Participants were stratified by N-terminal pro-B type natriuretic peptide (NT-proBNP) quartiles, and correlation with echocardiographic and functional parameters were assessed using Spearman correlation test. Results The mean age of participants was 67.4 years and 50% were female. The mean duration of type 2 diabetes was 14.5 years with a mean hemoglobin A1c of 6.98. The median NT-proBNP was 71 (Q1, Q3: 33, 135) ng/L. No association was observed between NT-proBNP concentrations and echocardiographic parameters of either diastolic or systolic dysfunction including global longitudinal strain, left ventricular ejection fraction, left ventricular mass index, left atrial volume index, E/e’, or right ventricular systolic pressure (Figure 1). In contrast, NT-proBNP was significantly correlated with components of the Kansas City Cardiomyopathy Questionnaire (P<0.001), the Physical Activity Scale in the Elderly (P=0.004), duration of cardiopulmonary exercise testing (P<0.001), peak VO 2 (P<0.001), and ratio of minute ventilation/carbon dioxide production (P=0.002; Figure 2). Conclusion Among highly selected patients with subclinical DbCM, elevated NT-proBNP concentrations are associated with worse health status, lower activity levels, and reduced functional capacity, but not with cardiac structural abnormalities. These findings suggest that regardless of cardiac structural abnormalities, biomarker concentrations reflect important deterioration in functional capacity in affected individuals.

Texture Analysis and Prediction of Response to Neoadjuvant Treatment in Patients with Locally Advanced Rectal Cancer

Background: The purpose of this study is to determine the relationship between the texture analysis extracted from preoperative rectal magnetic resonance (MR) studies and the response to neoadjuvant treatment. Materials and Methods: In total, 88 patients with rectal adenocarcinoma who underwent staging MR between 2017 and 2022 were retrospectively enrolled. After the completion of neoadjuvant treatment, they underwent surgical resection. The tumour regression grade (TRG) was collected. Patients with TRG 1–2 were classified as responders, while patients with TRG 3 to 5 were classified as non-responders. A texture analysis was conducted using LIFEx software (v 7.6.0), where T2-weighted MR sequences on oriented axial planes were uploaded, and a region of interest (ROI) was manually drawn on a single slice. Features with a Spearman correlation index > 0.5 have been discarded, and a LASSO feature selection has been applied. Selected features were trained using bootstrapping. Results: According to the TRG classes, 49 patients (55.8%) were considered responders, while 39 (44.2) were non-responders. Two features were associated with the responder class: GLCM_Homogeneity and Discretized Histo Entropy log 2. Regarding GLCM_Homogeneity, the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were 0.779 (95% CIs = 0.771–0.816), 86% (80–90), and 67% (60–71). Regarding Discretized Histo Entropy log 2, we found 0.775 AUC (0.700–0.801), 80% sensitivity (74–83), and 63% specificity (58–69). Combining both radiomics features the radiomics signature diagnostic accuracy increased (AUC = 0.844). Finally, the AUC of 1000 bootstraps were 0.810. Conclusions: Texture analysis can be considered an advanced tool for determining a possible correlation between pre-surgical MR data and the response to neoadjuvant therapy.

Examining self-efficacy among recent graduates of postgraduate dental education programs.

To examine the perceived self-efficacy of dentists who recently completed Graduate Dental Education (GDE) programs and identify how closely it aligns with their supervisors' assessments of them. Self-efficacy has been associated with academic pursuits, motivation, and engagement, which may affect how dental providers practice, seek continuing education, and pursue future opportunities. METHODS: Recent graduates of military GDE programs rated their self-efficacy on specific tasks within each of the seven domains of dental competencies. Their supervisors completed a similar survey, rating the graduate's performance in the same tasks. Graduates' mean ratings were calculated for each domain, spearman correlations were calculated for all graduate-supervisor task ratings, and the magnitude of differences between graduate and supervisor domain means were examined. Graduates' perceived self-efficacy ranged from 3.57 to 4.41 out of 5.0. Correlations for each task were universally weak (ρ = -0.04-0.27). Correlations for domain means were also weak (ρ = 0.06-0.14). Overall, graduates rated themselves lower than their supervisors, with mean differences ranging from -0.17 (p=0.003, Cohen's d=0.20) for Professionalism to -0.95 (p<0.001, Cohen's d=0.90) for Health Promotion. Overall, graduates' perceived self-efficacy was moderate to high for 26 tasks across seven domains. However, in aggregate, graduates underestimated their abilities compared to performance measures from their current supervisors, although effect sizes were small. The accuracy of graduates' self-efficacy varied by program length and the clinical specialty of their supervisors. High-performing graduates always underestimated themselves while low-performing graduates often overestimated themselves.

Effects of eHealth literacy on maternal and neonatal outcomes

ABSTRACT eHealth literacy plays a crucial role during pregnancy, as maternal health behavior can influence health outcomes for both mother and child. This study assessed the impact of eHealth literacy on maternal-fetal health outcomes through a cross-sectional analysis of 1,265 pregnant women admitted to a tertiary maternity hospital in Turkey between April and July 2022. Data on sociodemographic information, obstetric variables, birth outcomes, Internet usage, and eHealth Literacy Scale (eHEALS) were collected. Kolmogorov-Smirnov, Mann – Whitney U, Kruskal-Wallis, and Spearman correlation were used for data analysis. The median age of women was 28 years, and the mean gestational age was 38.6 weeks. Median eHealth literacy score was 21 (range:8-40). Pregnant women who had planned pregnancies, received spousal support, attended 9–12 antenatal care visits, received vaccinations, adhered to iron and folic acid supplementation, engaged in regular physical activity, and maintained regular sleep patterns exhibited higher eHealth scores (all p < .001). eHEALS scores were higher in women who experienced normal vaginal deliveries (p < .001), while lower eHEALS scores were noted in those with comorbidities (p = .001). The study suggested that higher eHealth literacy among pregnant women was associated with improved health-promoting behaviors, more favorable health perceptions, increased utilization of health services, and better maternal and fetal outcomes.

Application of mass cytometry in multiparametric characterization of precancerous cervical lesions.

Cervical cancer (CC) is the fourth most common malignant tumor in women worldwide. Detecting different biomarkers together on single cells by novel method mass cytometry could contribute to more precise screening. Liquid-based cytology (LBC) cervical samples were collected (N = 53) from women categorized as normal and precancerous lesions. Human papillomavirus was genotyped by polymerase chain reaction, while simultaneous examination of the expression of 29 proteins was done by mass cytometry (CyTOF). Differences in cluster abundances were assessed with Spearman's rank correlation as well as high dimensional data analysis (t-SNE, FlowSOM). Cytokeratin (ITGA6, Ck5, Ck10/13, Ck14, Ck7) expression patterns allowed determining the presence of different cells in the cervical epithelium. FlowSOM analysis enabled to phenotype cervical cells in five different metaclusters and find new markers that could be important in CC screening. The markers Ck18, Ck18, and CD63 (Metacluster 3) showed significantly increasing associated with severity of the precancerous lesions (Spearman rank correlation rho 0.304, p = 0.0271), while CD71, KLF4, LRIG1, E-cadherin, Nanog and p53 (Metacluster 1) decreased with severity of the precancerous lesions (Spearman rank correlation rho -0.401, p = 0.0029). Other metaclusters did not show significant correlation, but metacluster 2 (Ck17, MCM, MMP7, CD29, E-cadherin, Nanog, p53) showed higher abundance in low- and high-grade intraepithelial lesion cases. CyTOF appears feasible and should be considered when examining novel biomarkers on cervical LBC samples. This study enabled us to characterize different cells in the cervical epithelium and find markers and populations that could distinguish precancerous lesions.

Ultra-Processed Food Consumption and Its Relationship with Diet Quality Among Malaysian Young Adults

The global rise in ultra-processed food (UPF) consumption presents potential public health challenges. UPFs, laden with additives and extensively marketed, are increasingly prevalent in modern diets. However, there is limited research on UPF consumption among Malaysian young adults, particularly its relationship with diet quality. This cross-sectional study aimed to investigate the relationship between UPF consumption and diet quality among 177 young adults aged 18 to 29 years from Terengganu, Johor, and Perak. A two-day 24-hour dietary recall was used to assess UPF intake, classified by the NOVA system, while diet quality was evaluated using the Standardised-Malaysian Healthy Eating Index (S-MHEI). The S-MHEI was adopted with the scores for each food group (adequacy component) calculated according to the recommended servings per food group expressed per 1,000 kcaL. Statistical analyses, including Spearman correlation, were conducted using SPSS version 25 to determine the relationship between UPF consumption and diet quality with statistical significance set at p&lt;0.05. The median total energy intake was 1,417 kcaL (IQR=735.38), with UPFs contributing 38.6% of this intake. The median S-MHEI score was 44.65 (IQR=12.77), indicating that 74.6% of participants had poor diet quality. Statistical analysis found no significant relationship between UPF consumption and diet quality (p=0.395). Although no significant association was found, this study lays the groundwork for further research on nutrition and health among Malaysian young adults.

Assessment of psychosocial parameters in adolescents seeking orthodontic treatment

AimThe aim of this study was to investigate the psychosocial impact of malocclusion and the motivation for seeking orthodontic treatment among adolescents.MethodsA cross-sectional study included 102 adolescents (ages 11–18) whose malocclusion was rated using 3 occlusal indices: IOTN, DAI, and PAR. The participants answered three structured questionnaires selected to measure Oral Health Related Quality of Life (OHRQoL) through the short form of the Child Oral Health Impact Profile (COHIP), the patient's perceived impact related to orthodontics through the Psychosocial Impact of Dental Aesthetics Questionnaire (PIDAQ), and self-esteem through the Rosenberg Self-Esteem Scale (RSES). Independent two-tailed t-tests, one-way mixed analysis of variance (ANOVA), and Spearman's correlations were used to test various associations.ResultsPatients with higher malocclusion scores displayed increased psychosocial impact with weak to moderate correlations (0.2 < r < 0.3; p < 0.05), but 98% wished their teeth looked better, and 70% were unhappy about their smile esthetics. The IOTN esthetic component AC was better associated with psychosocial implications of malocclusion (p < 0.01). Self-motivated patients (over 80%) had higher impactful psychosocial scores than patients whose parents were motivated for treatment. Sex did not influence the findings. Older adolescents and bullied individuals were more affected by the psychological burden of malocclusion.ConclusionThe results indicate the prevalence of psychosocial and esthetic impacts of malocclusion over oral and functional problems. PIDAQ discriminated better than COHIP between varying degrees of dental aesthetics. The results suggest that the orthodontist should explore patients' expectations of treatment outcomes, not only the chief complaint.

The relation between dietary polysaccharide intake and urinary excretion of tetraglucoside.

The urinary metabolite tetraglucoside (Glc4) is a potential biomarker for hepatic glycogen storage diseases (GSDs). Glc4 is believed to reflect body glycogen content and/or turnover. However, dietary polysaccharide intake may influence Glc4 excretion, potentially limiting the utility of Glc4 as a monitoring biomarker in hepatic GSDs. We aimed to investigate the association of dietary polysaccharide intake with Glc4 excretion. Urinary Glc4 excretion (mmol/mmol creatinine and mmol/24 h) was analyzed using a validated LC-MS/MS method. Data was analyzed from 65 kidney transplant recipients and 58 healthy kidney donors in the TransplantLines cohort study. Spearman's correlation and multivariable linear regression analyses were performed. In the multivariable analysis, dry lean body mass (DLBM), dietary polysaccharide intake, transplantation status, age, sex, and glycated hemoglobin (HbA1c) served as independent variables. Daily variation was examined in 21 healthy individuals of urinary Glc4 excretion in 2-h collections over a 24-h period. Mixed generalized additive models were built to study the association of prior polysaccharide intake with Glc4 excretion. No (univariate) associations were found between polysaccharide intake and Glc4 excretion. However, a significant interaction between DLBM and polysaccharide on 24 h Glc4 excretion was observed in the multivariate analysis. Glc4 excretion throughout the day exhibited no relationship to prior polysaccharide intake. Our findings suggest an indirect effect of polysaccharide intake on Glc4 excretion, potentially due to changes in muscle glycogen content and/or turnover. We have found no evidence that dietary polysaccharides under normal intakes increase urinary Glc4 directly.

Automated Extraction of Stroke Severity From Unstructured Electronic Health Records Using Natural Language Processing.

Multicenter electronic health records can support quality improvement and comparative effectiveness research in stroke. However, limitations of electronic health record-based research include challenges in abstracting key clinical variables, including stroke severity, along with missing data. We developed a natural language processing model that reads electronic health record notes to directly extract the National Institutes of Health Stroke Scale score when documented and predict the score from clinical documentation when missing. The study included notes from patients with acute stroke (aged ≥18 years) admitted to Massachusetts General Hospital (2015-2022). The Massachusetts General Hospital data were divided into training/holdout test (70%/30%) sets. We developed a 2-stage model to predict the admission National Institutes of Health Stroke Scale, obtained from the GWTG (Get With The Guidelines) stroke registry. We trained a model with the least absolute shrinkage and selection operator. For test notes with documented National Institutes of Health Stroke Scale, scores were extracted using regular expressions (stage 1); when not documented, least absolute shrinkage and selection operator was used for prediction (stage 2). The 2-stage model was tested on the holdout test set and validated in the Medical Information Mart for Intensive Care (2001-2012) version 1.4, using root mean squared error and Spearman correlation. We included 4163 patients (Massachusetts General Hospital, 3876; Medical Information Mart for Intensive Care, 287); average age, 69 (SD, 15) years; 53% men, and 72% White individuals. The model achieved a root mean squared error of 2.89 (95% CI, 2.62-3.19) and Spearman correlation of 0.92 (95% CI, 0.91-0.93) in the Massachusetts General Hospital test set, and 2.20 (95% CI, 1.69-2.66) and 0.96 (95% CI, 0.94-0.97) in the MIMIC validation set, respectively. The automatic natural language processing-based model can enable large-scale stroke severity phenotyping from the electronic health record and support real-world quality improvement and comparative effectiveness studies in stroke.

Artificial intelligence in rheumatology: perspectives and insights from a nationwide survey of U.S. rheumatology fellows.

Artificial Intelligence (AI) is poised to revolutionize healthcare by enhancing clinical practice, diagnostics, and patient care. Although AI offers potential benefits through data-driven insights and personalized treatments, challenges related to implementation, barriers, and ethical considerations necessitate further investigation. We conducted a cross-sectional survey using Qualtrics from October to December 2023 to evaluate U.S. rheumatology fellows' perspectives on AI in healthcare. The survey was disseminated via email to program directors, who forwarded it to their fellows. It included multiple-choice, Likert scale, and open-ended questions covering demographics, AI awareness, usage, and perceptions. Statistical analyses were performed using Spearman correlation and Chi-Square tests. The study received IRB approval and adhered to STROBE guidelines. The survey aimed to reach 528 U.S. rheumatology fellows. 95 fellows accessed the survey with response rate to each question varying between 85 and 95 participants. 57.6% were females, 66.3% aged 30-35, and 60.2% in their first fellowship year. There was a positive correlation between AI familiarity and confidence (Spearman's rho = 0.216, p = 0.044). Furthermore, 67.9% supported incorporating AI education into fellowship programs, with a significant relationship (p < 0.005) between AI confidence and support for AI education. Fellows recognized AI's benefits in reducing chart time (86.05%) and automating tasks (73.26%), but expressed concerns about charting errors (67.86%) and over-reliance (61.90%). Most (84.52%) disagreed with the notion of AI replacing them. Rheumatology fellows exhibit enthusiasm for AI integration yet have reservations about its implementation and ethical implications. Addressing these challenges through collaborative efforts can ensure responsible AI integration, prioritizing patient safety and ethical standards in rheumatology and beyond.

Improving the prediction of protein stability changes upon mutations by geometric learning and a pre-training strategy.

Accurate prediction of protein mutation effects is of great importance in protein engineering and design. Here we propose GeoStab-suite, a suite of three geometric learning-based models-GeoFitness, GeoDDG and GeoDTm-for the prediction of fitness score, ΔΔG and ΔTm of a protein upon mutations, respectively. GeoFitness engages a specialized loss function to allow supervised training of a unified model using the large amount of multi-labeled fitness data in the deep mutational scanning database. To further improve the downstream tasks of ΔΔG and ΔTm prediction, the encoder of GeoFitness is reutilized as a pre-trained module in GeoDDG and GeoDTm to overcome the challenge of lacking sufficient labeled data. This pre-training strategy, in combination with data expansion, markedly improves model performance and generalizability. In the benchmark test, GeoDDG and GeoDTm outperform the other state-of-the-art methods by at least 30% and 70%, respectively, in terms of the Spearman correlation coefficient.

Research on comprehensive assessment of coastal erosion intensity based on multi index method

The intensity of coastal erosion is a measure of the strength of erosion processes affecting coastal areas. Traditionally, assessments of coastal erosion intensity have relied on singular indices, such as the rate of shoreline retreat or erosion, often prioritizing higher rates over lower ones. This approach, however, lacks comprehensive consideration and scientific rigor. In this study, we adopt a more holistic approach by examining the Qionghai-Wanning coast on the eastern side of Hainan Island. We selected four indices that reflect local conditions and influence coastal erosion strength: Annual rate of shoreline change (T1), Beach annual down-cutting rate (T2), Beach slope (T3), Average particle size of the beach (T4). These indices were used to comprehensively evaluate the erosion intensity of the Qionghai-Wanning coast. The evaluation results categorized the study area into six grades: serious erosion (3.45%), strong erosion (6.90%), erosion (20.69%), micro erosion (44.38%), stabilization (20.69%), and accretion (3.45%). The findings indicate that, under the broader environmental trends of global warming and rising sea levels, most sandy coasts exhibit micro-erosion intensity. Areas experiencing strong and serious erosion are predominantly influenced by human activities, such as those occurring in promenade bays, artificial islands, and harbors. To further understand the relationship between these factors and erosion intensity, we employed the Spearman correlation coefficient method. The analysis revealed that the T1 and the T2 are the primary factors influencing coastal erosion intensity, with the T4 serving as a secondary factor. These factors collectively impact the force and energy absorption of the coast through wave and tidal actions, ultimately determining the intensity of coastal erosion. The multi-index assessment method for coastal erosion intensity demonstrated an accuracy of 82.75%, providing a scientific basis for the management, protection, and restoration of coastal areas.

Correlation The Level of Nutritional Knowledge, Breakfast Consumption Patterns With Nutritional Status of Age Students 10-12 MI Dakwatul Khoiriyah Kediri

Children aged 10–12 years need significant energy due to their rapid growth and active lifestyles. Their nutritional status is influenced by nutritional knowledge and breakfast habits. To examine the relationship between nutritional knowledge, breakfast habits, and nutritional status of students aged 10–12 years at MI Dakwatul Khoiriyah Kediri. A cross-sectional study with 40 students using questionnaires for nutritional knowledge, SQ-FFQ interviews to evaluate breakfast habits, and BMI for age index to determine nutritional status. Spearman correlation tests were used for analysis. The study found that 62.5% had low nutritional knowledge, 60% had infrequent breakfast habits, and 65% were malnourished. There is a significant relationship between the level of nutritional knowledge and nutritional status (p=0.000, r=0.688) and between the habit of rarely eating breakfast and poor nutritional status (p=0.000, r=0.812). There is a significant relationship between nutritional knowledge, breakfast habits, and nutritional status of students aged 10–12 years at MI Dakwatul Khoiriyah Kediri. Students should have daily breakfast to meet nutritional needs and improve nutritional status.

The Influence of Personal Protective Equipment (PPE) Usage, Age, Work Tenure on Workplace Accidents

Workplace accidents can reduce productivity, which occurs as a result of unsafe actions and unsafe conditions in the Small and Medium Enterprises (SMEs) of leather tanning in Magetan. Workplace accidents could be caused by workes low awareness of wearing Personal Protective Equipment (PPE), as well as factors like age and work tenure on workplace accidents in the leather tanning SMEs in Magetan 2024. The research design employed an observational analytic method with a Cross-Sectional approach. The sample size consisted 66 people out of a population of 190, selected through proportional random sampling. The variables of PPE use, age, and work tenure, which were collected through observation and interviews, were then processed and analyzed using the Spearman Correlation statistical test (r2). The results indicated that the use of PPE, including masks,gloves, and boots, was at 36,4%, the proportion of workers aged over 30 years was 54,5%, and those with a work tenure over 5 years was 59,1%. The analysis showed that PPE use (p=0.000) and age (p=0.035) had an impact on workplace accidents, with a correlation value of p=0.232 more than 0.05. The study concluded that the use of PPE and the age of workers in the leather tanning SMEs in Magetan influenced workplace accidents. It is recommended that management provide complete PPE such as masks, boots, gloves and conduct regular monitoring of PPE use conditions. Additionally, workers should use PPE according to standars while performing their duties.

Associations Between Inter-Limb Asymmetry in Lower Limb Strength and Jump Performance in 14–15-Year-Old Basketball Players

This study aims to (1) assess the inter-limb asymmetry in hip, knee, and ankle strength and countermovement jump (CMJ) performance among adolescent basketball players and (2) examine the relationship between inter-limb asymmetry and CMJ performance. Moreover, 30 adolescent basketball players (15 boys and 15 girls) aged 14 to 15 years participated in this study. The strength of the lower limb joints was measured using an isokinetic dynamometer at a speed of 60 degrees per second. Three maximal CMJs were performed, and the highest jump was used for the final analysis. The subjects were median-split into high-asymmetry (n = 15) and low-asymmetry (n = 15) groups based on the calculated strength asymmetry scores. The asymmetry scores were calculated using the formula: (dominant–non-dominant)/dominant* 100%. The inter-limb asymmetry data ranged from 12.2% to 21.6%. A Spearman correlation analysis showed that only the inter-limb asymmetry of the ankle plantar flexor was significantly correlated with the CMJ heights (ρ = −0.56, p = 0.001). An independent t-test revealed no significant differences in strength asymmetry between boys and girls (all p &gt; 0.05). The low-asymmetry group demonstrated significantly greater CMJ performance compared to the high-asymmetry group (ES = 1.11, 95% CI = 0.34–1.87, p = 0.007), indicating that inter-limb asymmetry of the ankle plantar flexor has a significant negative impact on CMJ performance. Coaches should focus on enhancing both the strength and symmetry of the ankle joints to improve athletic performance and prevent injuries in sports, where jumping is a common movement.

Red cell distribution width/albumin ratio as a marker for metabolic syndrome: findings from a cross-sectional study

BackgroundMetabolic syndrome (MetS) imposes a significant health burden on patients globally. Chronic low-grade inflammation is pivotal in the onset and progression of this condition. However, the role of the novel inflammatory marker, red cell distribution width to albumin ratio (RAR), in the development of MetS remains unclear.MethodsThis population-based cross-sectional study utilized data from the 2011–2020 National Health and Nutrition Examination Survey (NHANES). Participants included individuals over 18 years old with complete data on serum albumin concentration, red cell distribution, and MetS and its components. MetS was defined using the criteria established by the National Cholesterol Education Program Adult Treatment Panel III. The calculation formula for RAR is: RAR = Red cell distribution width (%)/serum albumin (g/dL). Study participants were stratified into four quartiles based on RAR levels. Logistic regression analysis and subgroup analysis were employed to explore the independent interaction between RAR and MetS, as well as investigate the relationship between RAR levels and the specific components of MetS. Finally, the receiver operating characteristic (ROC) curve was used to assess the predictive efficacy of RAR for MetS.ResultsA total of 4899 participants were included in this study, comprising 2450 males and 2449 females; 1715 individuals (35.01%) were diagnosed with MetS. As the quartile of RAR increased, the proportion of individuals with MetS also increased. Spearman correlation analysis indicated a positive correlation between RAR and the insulin resistance index HOMA-IR. Logistic regression analysis, adjusting for multiple confounding factors, showed that each standard deviation increase in RAR was associated with a significant 1.665-fold increase (95% CI, 1.404–1.975; P < 0.001) in the odds of MetS prevalence. In logistic regression analysis stratified by quartiles of RAR, the risks of MetS in Q1-Q4 were 1.372 (95% CI, 1.105–1.704; P = 0.004), 1.783 (95% CI, 1.434–2.216; P < 0.001), and 2.173 (95% CI, 1.729–2.732; P < 0.001), respectively. Subgroup analyses and interaction tests demonstrated that gender, age, race, education, smoking status, and physical activity modified the positive association between RAR and MetS (p for interaction < 0.05). Additionally, analysis of the area under the receiver operating characteristic (ROC) curve showed that the optimal cutoff value for predicting MetS using RAR was 3.1348 (sensitivity: 59.9%; specificity: 60.6%; and AUC: 0.628).ConclusionsIncreasing RAR levels are associated with a higher risk of MetS. Therefore, greater attention should be given to patients with high RAR levels for improved prevention and treatment of MetS.