Multifactorial Analysis Research Articles

The Predictive Role of Cardiac Troponin Elevation Ratio Combined With Heart Function Index Model in the Prognosis of Non-ST-Segment Elevation Myocardial Infarction Patients.

Non-ST-segment elevation myocardial infarction (NSTEMI) is a common form of coronary artery disease, and its prognosis is influenced by multiple factors. This study aimed to analyze the predictive role of the combined application of cardiac troponin and cardiac function indices in NSTEMI patients' prognosis. NSTEMI patients were screened and included in the study. Cardiac troponin elevation ratio (cardiac troponin I (cTnI)/upper limit of normal (ULN)) was measured upon admission, and cardiac function was assessed. General clinical data, laboratory parameters, Grace score, New York Heart Association (NYHA) functional class, complications, and mortality data were collected. The correlation between mortality in NSTEMI patients and clinical parameters was analyzed, and a nomogram prediction model for NSTEMI patient mortality was established. A total of 252 NSTEMI patients were included. Female gender, elevated high-sensitivity C-reactive protein (H-CRP), left ventricular ejection fraction (LVEF) < 50%, NYHA class III and IV, and cTnI/ULN elevation by 36.25-fold were significantly independently associated with mortality outcomes. Multifactorial logistic analysis indicated that these indices remained associated with mortality. A nomogram model predicting NSTEMI patient mortality was constructed using these indices, with an area under the curve (AUC) of 0.911, sensitivity of 97.5%, and specificity of 72.8%. This predictive model outperformed the Grace score (AUC = 0.840). In NSTEMI patients, a 36.25-fold increase in cTnI/ULN, coupled with NYHA class III and IV, independently predicted prognosis. We developed a nomogram model integrating cTnI/ULN and cardiac function indices, aiding clinicians in assessing risk and implementing early interventions for improved outcomes.

Association between cardiovascular health and serum vitamin D and its interaction with prediabetes and diabetes

BackgroundPrediabetes and diabetes are common and serious public health problems, and high blood glucose can lead to serious cardiovascular complications. The purpose of this article was to explore the link between CVH levels and the incidence of prediabetes and diabetes in people over 20 years old, and whether serum vitamin D status could alter this relationship. Materials and MethodsData, from six consecutive cycles of the NHANES database from 2007 to 2018 were combined, eligible participants were aged ≥20 years. After excluding missing data, a total of 19,992 subjects were enrolled in the study. Significant risk factors for prediabetes and diabetes were analyzed using univariate and multivariate logistic regression. Exploring the interaction of VD and CVH on prediabetes and diabetes based on multifactorial regression analysis. ResultsThe prevalence of prediabetes among all participants was 36.15% and the prevalence of diabetes was 16.39%. CVH and vitamin D levels are influential factors in prediabetes and diabetes, and are negatively associated with the risk of developing prediabetes and diabetes. Compared with normoglycemia, poorer CVH and vitamin D deficiency only had a synergistic multiplicative interaction on the development of diabetes, and no significant interaction was observed for the development of prediabetes. Compared with prediabetes, poorer CVH and vitamin D deficiency still had a synergistic additive interaction on the development of diabetes. ConclusionsAlthough the cross-sectional study only determine the association and do not prove causality, the current results can be used to prompt people to improve their lifestyle and risk factors to prevent prediabetes or diabetes through higher CVH and adequate Vitamin D.

Cluster analysis of Model for End-stage Liver Disease and European System for Cardiac Operative Risk Evaluation for predicting operative mortality after concomitant tricuspid valve surgery

ObjectivePatients requiring concomitant tricuspid surgery represent a heterogeneous cohort with significant comorbidities and varying degrees of organ and right ventricular dysfunction. However, surgeons can rely on little beyond intuition and experience when discussing operative risks. The objective of the study is to assess how the Model for End-stage Liver Disease score complements the European System for Cardiac Operative Risk Evaluation II in risk assessment. MethodsWe performed a single-center retrospective cohort study of 369 consecutive patients who underwent concomitant tricuspid valve surgery from 2011 to 2020. Multivariate analysis of factors affecting operative mortality was performed, producing 2 multivariate risk prediction models, one consisting of European System for Cardiac Operative Risk Evaluation II components and the other consisting of both European System for Cardiac Operative Risk Evaluation II components and Model for End-stage Liver Disease. The models were compared by measuring c-statistic using the Hanley-McNeil method. This was further evaluated with category-free net reclassification improvement index. K-means clustering was performed using Model for End-stage Liver Disease and European System for Cardiac Operative Risk Evaluation II values after scalar transformation as independent variables and operative mortality as the dependent variable. ResultsThe Model for End-stage Liver Disease is an independent predictor of operative mortality, with an adjusted odds ratio of 1.286 per point. Inclusion of the Model for End-stage Liver Disease improves the discriminatory power of the European System for Cardiac Operative Risk Evaluation II for operative mortality, with a difference in area under the curve of 0.128 [0.0341-0.222] (P = .0076). The net reclassification improvement index of incorporating Model for End-stage Liver Disease with European System for Cardiac Operative Risk Evaluation II was 0.959 [0.515-1.392], indicating significant improvement in risk reclassification. Cluster analysis identified a unique cohort of patients with intermediate-to-high Model for End-stage Liver Disease, not previously identified with European System for Cardiac Operative Risk Evaluation II alone, who experienced high operative mortality. ConclusionsModel for End-stage Liver Disease score as a quantifier of hepatorenal dysfunction complements European System for Cardiac Operative Risk Evaluation II in predicting operative mortality after tricuspid valve surgery.

AB003. Clinical analysis of central nervous system (CNS) World Health Organization (WHO) grade 4 gliomas with IDH-mutant versus IDH-wildtype focused on CDKN2A homozygous deletion.

We are primarily investigating the prognostic role of cell-cycle-dependent kinase inhibitor (CDKN)-2A homozygous deletion in central nervous system (CNS) World Health Organization (WHO) grade 4 gliomas. Additionally, traditional prognostic factors for grade 4 gliomas will be examined, and our results will be validated. We conducted a retrospective analysis of glioma cohorts in our institute. Medical records were reviewed for 142 glioblastoma patients for 15 years, and pathological slides were examined again for the updated diagnosis according to the 2021 WHO classification of CNS tumors. The isocitrate dehydrase (IDH) mutation and CDKN2A deletion were examined by next generation sequencing (NGS) analysis using ONCO accuPanel®. Traditional prognostic factors including age, WHO performance status, extent of resection, and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation were examined. After the exclusion of 6 patients with poor status of pathologic samples, 136 glioblastoma that were diagnosed by previous WHO criteria were changed into 29 (21.3%) astrocytoma, IDH-mutant, CNS WHO grade 4 and 107 (78.7%) glioblastoma, IDH-wildtype, CNS WHO grade 4. Among them, 61 patients (56.0%) had CDKN2A deletion. Group A with IDH-wildtype and CDKN2A deletion had a mean overall survival (OS) of 15.70 months [95% confident interval (CI): 13.86-17.54], group B with IDH-mutant and CDKN2A deletion had a mean OS of 19.37 months (95% CI: 13.43-25.30), group C with IDH-wildtype and intact CDKN2A had a mean OS of 22.63 months (95% CI: 20.10-25.17), and group D with IDH-mutant and intact CDKN2A had a mean OS of 33.38 months (95% CI: 29.35-37.40). Multifactor analysis showed following factors were independently associated with OS: age [≥50 vs. <50 years; hazard ratio (HR) 4.642], extent of resection (gross total resection vs. others; HR 5.523), WHO performance (0, 1 vs. 2; HR 5.007), MGMT promoter methylation, (methylated vs. unmethylated; HR 5.075), IDH mutation (mutant vs. wildtype; HR 6.358), and CDKN2A deletion (absence vs. presence; HR 13.452). The presenting study suggests that CDKN2A deletion should play a powerful prognostic role in CNS WHO grade 4 gliomas as well as low-grade glioma. Even if CNS WHO grade 4 gliomas had mutant IDH, they can have poor clinical outcomes due to CDKN2A deletion.

Current status and influencing factors of fear of surgery in patients with oral and maxillofacial tumors.

This study aimed to investigate the incidence and severity of surgical fear in patients with oral and maxillofacial tumors. The survey participants were composed of patients with oral and maxillofacial tumors, who were scheduled to undergo surgery. A general information questionnaire, the Surgical Fear Questionnaire (SFQ), the Patient Health Questionnaire (PHQ)-9, and the Generalized Anxiety Disorder (GAD)-7 score were used for the investigation. A total of 203 patients were investigated. Among them, 85.22% had fear of surgery. The median score of SFQ was 20, and the quartile was (6, 36). The patients were categorized into none, mild, moderate, and severe groups according fear level. Gender, diabetes, obvious discomfort before surgery, PHQ-9, and GAD-7 scores were the variables with statistical difference in each fear level. Multifactor analysis showed that women were more likely to have moderate and severe fear than men (OR=2.19, P=0.03; OR=2.72, P=0.01), patients with obvious preoperative discomfort symptoms were more inclined to have no fear (OR=4.73, P=0.02), and patients with diabetes were more likely to have severe fear (OR=3.33, P=0.02). The incidence rates of depression and anxiety were 31.03% and 24.63%, respectively. The incidence of anxiety and depression in patients with severe fear was 40.00%. Surgical fear was moderately positively correlated with anxiety (r=0.491, P<0.001) and depression (r=0.514, P<0.001). The fear of surgery in patients with oral and maxillofacial tumors is common and distributed in all levels. Medical staff can screen and assess patients with moderate and severe fear of surgery in accordance with the influencing factors and implement targeted interventions to reduce fear of surgery, anxiety, and depression on the basis of the source of fear.

Evaluation of gingival thickness obtained from intraoral scanning registration with cone beam computed tomography at different acquisition modes

To investigate the reliability of gingival thickness measurements obtained from the registration of intraoral scans with cone beam computed tomography (CBCT) examinations at different acquisition modes. CBCT examinations of 9 porcine hemimandibles were acquired using the OP300 Maxio unit operating at the highest-dose protocol with the smallest voxel size as the reference standard for visualizing the gingival surface. Subsequently, the hemimandibles were surrounded by water to simulate soft tissue attenuation of radiation, and additional CBCT examinations were acquired in 4 modes: Endo, High-resolution, Standard-resolution, and Low-dose. These CBCT datasets were registered with corresponding intraoral scans obtained with the Carestream Dental 3600 intraoral scanning system using the Blue Sky Plan 4 software. Four oral radiologists measured the buccal gingival thickness on cross-sectional reconstructions at 4 measurement sites and 2 distances from the gingival margin in the CBCT reference standard examinations and examinations obtained with water and intraoral scan registration. Multifactorial analysis of variance was used to assess the influence of acquisition mode, measurement site, and distance from the gingival margin on measurements (α = 5%; statistical power = 90%). Buccal gingival thickness measurements obtained via CBCT after registration with intraoral scanning were not significantly influenced by acquisition mode (P = .153) or measurement site (P = .089). Gingival thickness measurements derived from the registration of intraoral scans with CBCT examinations at different acquisition modes appear to be reliable.

Predicting angiographic coronary artery disease using machine learning and high-frequency QRS

AimExercise stress ECG is a common diagnostic test for stable coronary artery disease, but its sensitivity and specificity need to be further improved. In this paper, we construct a machine learning model for the prediction of angiographic coronary artery disease by HFQRS analysis of cycling exercise ECG.Methods and resultsThis study prospectively included 140 inpatients and 59 healthy volunteers undergoing cycling exercise ECG. The CHD group (N=104) and non-CHD group (N=95) were determined by coronary angiography gold standard. Automated HF QRS analysis was performed by the blinded method. The coronary group was predominantly male, with a higher prevalence of age, BMI, hypertension, and diabetes than the non-coronary group (P<0.001\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P<0.001$$\\end{document}), higher lipid levels in the coronary group (P<0.005\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P<0.005$$\\end{document}), significantly longer QRS duration during exercise testing (P<0.005\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P<0.005$$\\end{document}), more positive leads (P<0.001\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P<0.001$$\\end{document}), and a greater proportion of significant changes in HFQRS (P<0.001\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P<0.001$$\\end{document}). Age, Gender, Hypertension, Diabetes, and HF QRS Conclusions were screened by correlation analysis and multifactorial retrospective analysis to construct the machine learning models of the XGBoost Classifier, Logistic Regression, LightGBM Classifier, RandomForest Classifier, Artificial Neural Network and Support Vector Machine, respectively.ConclusionMale, elderly, with hypertension, diabetes mellitus, and positive exercise stress test HFQRS conclusions suggested a high risk of CHD. The best performance of the Logistic Regression model was compared, and a column line graph for assessing the risk of CHD was further developed and validated.

HGSHS-5:G-First results with the short version of the test for the Harvard Group Scale of Hypnotic Susceptibility and a comparison with the full version.

The HGSHS:A is one of the most commonly used measures of hypnotic suggestibility. However, this test suffers from low feasibility due to a time requirement exceeding 1 h, and from a questionable representation of the normal population. Recently, a short version of HGSHS-5:G was developed and published, and now the first results are available. The scope of this investigation was to verify the assumption of equally positioned and normally distributed scores, resulting in equally sized suggestibility groups in a number of different studies with full or short versions of HGSHS, and to compare the results of the 11-item score with the 5-item score, the latter being calculated from either the full version or the short version test. Data from 21 studies with testing for HGSHS were analyzed, 15 using the HGSHS:A full version and six using the HGSHS-5:G short version, for a total of 2,529 data sets. Position and distribution of both the 11-item score and the 5-item score were tested. Linear regression analysis was used to compare the two scores, as well as cross-table and weighted Cohen's kappa to determine the match of grouping into low and high suggestibility. To evaluate contributing factors to the observed differences in the study results, a multifactorial analysis of variance was performed. In the different studies, position and distribution of scores, as well as group sizes for low and high suggestibles, varied. All score distributions were found to be non-normal and shifted to the right from the middle score; the shift was more extensive with the 11-item score. The correlation between both scores calculated from full version tests was moderate (R 2 = 0.69), as was the match of suggestibility grouping (κ = 0.58). Studies using the short version involving less student-dominated populations showed sufficient agreement with the full version, but lower scores were caused by an increase in the zero score. A normal population is not represented in most applications of HGSHS, and grouping into low and high suggestibles varies, mainly due to different positions of score distributions. A direct comparison of full and short versions of HGSHS tested in the same subjects is still missing.

Strategic Siting of Direct Air Capture Facilities in the United States

Direct air capture (DAC) systems that capture carbon dioxide (CO2) directly from the atmosphere are garnering considerable attention for their potential role as negative emission technologies in achieving net-zero CO2 emission goals. Common DAC technologies are based either on liquid–solvent (L-DAC) or solid–sorbent (S-DAC) to capture CO2. A comprehensive multi-factor comparative economic analysis of the deployment of L-DAC and S-DAC facilities across various United States (U.S.) cities is presented in this paper. The analysis considers the influence of various factors on the favorability of DAC deployment, including local climatic conditions such as temperature, humidity, and CO2 concentrations; the availability of energy sources to power the DAC system; and costs for the transport and storage of the captured CO2 along with the consideration of the regional market and policy drivers. The deployment analysis in over 70 continental U.S. cities shows that L-DAC and S-DAC complement each other spatially, as their performance and operational costs vary in different climates. L-DAC is more suited to the hot, humid Southeast, while S-DAC is preferrable in the colder, drier Rocky Mountain region. Strategic deployment based on regional conditions and economics is essential for promoting the commercial adoptability of DAC, which is a critical technology to meet the CO2 reduction targets.

Multifactor analysis of the infiltration characteristics of film hole irrigation under muddy water conditions

Film hole irrigation under muddy water conditions is a new and effective water-saving irrigation technology. In order to determine the influence of multiple factors on the infiltration process of film hole irrigation under muddy water conditions, 12 sets of indoor infiltration tests were conducted to investigate the effects of four key influencing factors (muddy water sand content, hole diameter, soil bulk density, and infiltration time) on the infiltration characteristics of irrigation with film holes under muddy water conditions, in this study. Based on the experimental data, accurate and effective soil water infiltration and vertical and horizontal wetting front transport models were constructed. Based on the modeling results, the standard regression coefficients of each influencing factor against the fitted parameters were calculated and the effects of the factors on the fitted parameters were analyzed. Error analysis showed that both models could effectively simulate the soil water infiltration process under experimental conditions. Infiltration time was the dominant factor influencing the cumulative infiltration per unit of film hole area, followed by hole diameter, muddy water sand content and lastly, soil bulk density. Infiltration time was also the main influencing factor of the vertical wetting front transport distance, followed by soil bulk density, muddy water sand content, and lastly, hole diameter. Similarly, infiltration time exerted the greatest effect on the horizontal transport distance, followed by hole diameter, soil bulk density and muddy water sand content. The model validation revealed that both the calculated and measured values were distributed around the 1:1 line, reflecting the accuracy of the models. The results of this study can provide theoretical support for the design of film hole irrigation systems under muddy water conditions.

The possibilities of predicting the individual risk of cervical cancer in women of reproductive age using mathematical modeling

Background. Cervical cancer (CC) refers to cancer of visual localization and in women of reproductive age remains one of the most common oncological diseases. The carcinogenesis of CC is caused by the persistence of highly oncogenic types of human papillomavirus (HPV), the level of carcinogenicity of which is the highest based on the criteria of the International Agency for Research on Cancer. However, cervical carcinogenesis does not occur in all cases of persistence of highly oncogenic types of HPV. This, in turn, determines the need for a thorough search, study and analysis of possible cofactors that can lead to neoplastic changes in the cervix.Aim. To develop a model for predicting the individual risk of CC in women of reproductive age, taking into account clinical, anamnestic, laboratory and histological data.Materials and methods. The material for the study was retrospective examination data from 251 patients of reproductive age who were treated at the Center for Gynecology and Reproductive Technologies of the National Medical Research Center “Medical and Rehabilitation Center”, Ministry of Health of Russia in the period 2015–2022. Results. Highly oncogenic HPV types were significantly more common in the group of patients with verified СС who took combined oral contraceptives (COC), compared with patients who did not take COC (p = 0.035). Multifactorial analysis allowed us to determine that long-term use of СОС for a total of more than 7 years is associated with a tendency to increase the risk of developing СС (hazard ratio 1.68; 95 % confidence interval 1.1–2.5; p = 0.010). According to the results of statistical calculation, the values of regression coefficients were obtained and the tendency to increase the risk of developing CC was predicted in the presence of such factors as: HPV type 16 persistence, body mass index, and the duration of COC intake in years.Conclusion. Thus, taking into account all possible risk factors for CC, the negative effect of cofactors, namely increased body mass index and prolonged intake of COC, on the course of HPV as the leading etiological factor of breast cancer, will allow us to identify groups at increased risk of developing CC, form an individual algorithm for monitoring and examination throughout the entire period of taking COC, as well as conduct individual cancer prevention by limiting the duration of taking COC.

Многофакторный анализ эффективности автономных транспортных средств на основе метода анализа среды функционирования

The design of robotic and unmanned vehicles includes a virtual commissioning stage that provides an analysis of the operation of objects using digital twins. Conducting a large number of experiments on models leads to the use of methods for evaluating the results obtained to choose the best design solution. A method of multifactorial anal-ysis of the efficiency of the complex of autonomous vehicles (AV) for agro-industrial purposes is proposed. Multivariate analysis is performed at the virtual commissioning stage in order to plan early maintenance and repair activities. The paper uses the method of analyzing the operating environment for a comparative assessment of various operating scenarios. The method is based on solving a complex of optimization problems of linear programming. A formal description of virtual test scenarios is proposed. The method of multifactorial analysis is implemented in the process of virtual tests using optimal purpose system models and AV simulation. A procedure for virtual AV tests has been developed, including step-by-step modeling and multivariate analysis. The sets of input and output key parameters of the AV and analyzed scenarios are determined. It is proposed to perform two consecutive efficiency assessment tasks. The first task is to compare the effectiveness of individual AV and determine the limits of their effectiveness. The solution of the second task makes it possible to evaluate the effectiveness of AV system operation scenarios. The target values of changes in the key parameters of the AV and operating scenarios are obtained, leading to an increase in the efficiency of operation and maintenance. Conducting a multifactorial analysis of the results of virtual tests allows you to formulate requirements and recommendations for the design of AV maintenance systems.

Association between weight-adjusted waist index and risk of diabetes mellitus type 2 in United States adults and the predictive value of obesity indicators

BackgroundThe weight-adjusted waist index (WWI) is a quantitative anthropometric index that can be applied to evaluate obesity. This study examined the relationship between adult United States (US) residents’ risk of diabetes mellitus type 2 (T2DM) and WWI.MethodsThe NHANES (National Health and Nutrition Examination Survey) 2001–2018 provided the data for this investigation. This study used multifactorial logistic regression analysis, smoothed curve fitting, subgroup analysis, and interaction tests to assess the association between WWI and T2DM. Additionally, threshold effects were calculated using a two-stage linear regression model. The receiver operating characteristic(ROC) curves evaluated the diagnostic ability of the WWI and commonly used obesity indicators.Results20,477 participants were enrolled in the analysis, and patients with greater levels of WWI had a higher prevalence of T2DM. WWI and T2DM have a non-linear relationship, with a positive association found on the left side of the breakpoint (WWI = 12.35) (OR = 1.82, 95%CI:1.64–2.02), whereas, on the right side, no such relationship was found (OR = 0.9, 95%CI:0.61–1.34). For every unit rise in WWI, the probability of having T2DM increased by 67% after controlling for all other variables (OR:1.67,95%CI:1.53–1.83). Based on subgroup analyses, individuals under 40 had a higher correlation between WWI and T2DM (P < 0.001).ROC analyses showed that WWI had the best discrimination and accuracy in predicting T2DM compared to other obesity indicators (WC, BMI, and Weight).ConclusionHigher WWI values had a higher prevalence of T2DM in US individuals, especially in adults under 40. WWI has the strongest ability to predict T2DM. Therefore, the importance of WWI in the early identification of T2DM in US adults should be emphasized.

Predictive value of serum MED1 and PGC-1α for bronchopulmonary dysplasia in preterm infants

ObjectiveThis study aimed to predict the bronchopulmonary dysplasia (BPD) in preterm infants with a gestational age(GA) < 32 weeks utilizing clinical data, serum mediator complex subunit 1 (MED1), and serum peroxisome proliferator-activated receptor gamma coactivator-1alpha (PGC-1α).MethodsThis prospective observational study enrolled 70 preterm infants with GA < 32 weeks. The infants were categorized into two groups: non-BPD group(N = 35) and BPD group(N = 35), including 25 cases with mild BPD and 10 patients with moderate/severe subgroups. We performed multifactorial regression analysis to investigate the postnatal risk factors for BPD. Furthermore, we compared serum levels of biomarkers, including MED1 and PGC-1α, among infants with and without BPD at postnatal days 1, 7, 14, 28, and PMA 36 weeks. A logistic regression model was constructed to predict BPD’s likelihood using clinical risk factors and serum biomarkers.ResultsSerum levels of MED1 on the first postnatal day, PGC-1α on the 1st, 7th, and 28th days, and PMA at 36 weeks were significantly lower in the BPD group than in the non-BPD group (P < 0.05). Furthermore, the predictive model for BPD was created by combing serum levels of MED1 and PGC-1α on postnatal day 1 along with clinical risk factors such as frequent apnea, mechanical ventilation time > 7 d, and time to reach total enteral nutrition. Our predictive model had a high predictive accuracy(C statistics of 0.989) .ConclusionMED1and PGC-1α could potentially serve as valuable biomarkers, combined with clinical factors, to aid clinicians in the early diagnosis of BPD.

A retrospective study of Parkinson's disease in Southwest China 2021–2024: An age-based approach

BackgroundGlobally, Parkinson's disease (PD) is one of the common neurodegenerative diseases in the elderly with increasing morbidity and disability, and its clinical pathogenesis is not clear. ObjectiveTo compare the differences in disease severity and blood biomarkers levels and their correlation between patients with early-onset Parkinson's disease (EOPD) and late-onset Parkinson's disease (LOPD). MethodsA total of 342 patients diagnosed with PD were retrospectively collected. PD patients were categorized into EOPD (24 patients) and LOPD (318 patients) according to the age of onset of the disease. The Hoehn-Yahr (HY) staging was used to assess the severity of the disease in PD patients. Subjective rating scales such as the Mini-mental State Examination (MMSE) were used to assess the motor and non-motor functions of the patients. The differences of objective blood biomarkers such as triglyceride (TG) between the two groups were investigated. The correlation between them and PD was explored by logistic analysis. ResultsPercentage of EOPD group with HY staged as intermediate to late and Scales for Outcomes in Parkinson's Disease-Autonomic (SCOPA-AUT), Movement Disorder Society-Unified Parkinson's disease Rating Scale-III (MDS-UPDRS-III), Montreal Cognitive Assessment (MoCA) score and TG, non-high-density lipoprotein-cholesterol (N-HDL-C), homocysteine (HCY), apolipoprotein B (Apo-B), free triiodothyronine (FT3), free thyroxine (FT4), high-sensitivity C-reactive protein (hs-CRP) levels were lower than those in the LOPD group (P < 0.05); and the proportion of HY staged as early stage, Hamilton Anxiety Scale (HAMA) and Fatigue severity scale (FSS) scores and the levels of vitamin B12 were higher than those in the LOPD group (P < 0.05). The results of Multifactorial Logistic regression analysis showed that N-HDL-C [OR = 1.409, 95 % CI (1.063, 1.868)], Apo-B [OR = 0.797, 95 % CI (0.638, 0.997)], Vitamin B12 [OR = 0.992, 95 % CI (0.987, 0.998)] and hs-CRP [OR = 1.124, 95 % CI (1.070, 1.182)] were independent factors affecting the severity of PD, with significant differences between groups (P < 0.05). ConclusionN-HDL-C, Apo-B, Vitamin B12, and hs-CRP levels play an important role in the progression of PD.

Analysis of risk factors for lymph node metastasis in 1096 patients with early gastric cancer and establishment of a predictive nomogram

Objective: To investigate the risk factors for lymph node metastasis in patients with early gastric cancer and establish a model for prediction of risk. Methods: The cohort of this retrospective observational study comprised 1096 patients who had undergone radical gastric cancer surgery combined with standard D1 lymphadenectomy and been diagnosed with early gastric cancer by postoperative pathology in Zhongshan Hospital affiliated with Fudan University from January 2016 to July 2022. The patients were allocated to groups with and without lymph node metastases. Clinicopathological characteristics were compared between the two groups and multi-factor logistic regression analysis used to identify independent risk factors for lymph node metastasis in patients with early gastric cancer. Indications for endoscopic resection in the Japanese Gastric Cancer Association (JGCA) guideline were also incorporated into construction of the model. The patient cohort was divided into training and validation sets in a 6:4 ratio. The identified independent risk factors were used to construct a predictive nomogram. Receiver operating characteristic curves were plotted separately and the difference between them in predictive efficacy was compared using the area under the curve (AUC). Results: A total of 1,096 patients with early gastric cancer were included, with 750 males and 346 females. Their average age was (61.4±10.9) years old, and the mean tumor diameter was (23.8±11.4) mm. Among them, 188 patients (17.2%) had positive lymph node metastasis, with 109 cases in N1 stage, 42 cases in N2 stage, and 37 cases in N3 stage. Additionally, 462 patients were in T1a stage, while 634 patients were in T1b stage. Univariate analysis showed that tumor diameter, location, Lauren classification, gross morphology, histological type, intravascular invasion, ulceration, differentiation type and tumor T stage were associated with lymph node metastasis after radical gastrectomy for early gastric cancer (all P<0.05). Multifactorial analysis showed that the presence of intravascular invasion (OR=14.822, 95%CI: 9.323-23.572, P<0.001), undifferentiated type (OR=3.095, 95%CI: 1.649-5.811, P<0.001), tumor T1b (OR=1.798, 95%CI: 1.053-3.079, P=0.032), and tumor diameter ≥2 cm (OR=1.229, 95%CI: 1.031-1.469, P=0.022) were independent risk factors for lymph node metastasis. The baseline data of the training set and validation set were consistent in terms of balance (all P>0.05). We used the above variables to establish a predictive nomogram for lymph node metastasis in patients with early gastric cancer. The AUC values obtained from the validation of the model in the training and validation sets were 0.880 (95%CI: 0.849-0.911) and 0.881 (95%CI: 0.841-0.921), respectively, and were significantly better than the predictive efficacy based on the JGCA guideline (AUC=0.777, 95%CI: 0.746-0.809, P<0.001). Conclusions: Patients with early gastric cancer and intravascular invasion, undifferentiated tumors, tumor T1b, and diameter ≥2 cm are at higher risk of postoperative lymph node metastasis than other patients. The predictive model developed in this study more accurately predicts lymph node metastasis in patients with early gastric cancer than previously proposed methods.

Multi-factor coupling analysis of electric field distribution in electrochemical machining with electrolyte suction tool

Electrochemical machining (ECM) technology holds significant potential for applications in high accuracy engineering and manufacturing. To confine the electrolyte region during ECM and mitigate the effects of reaction products and heat generation, an electrolyte suction tool has been proposed. However, the complex electric field distribution on the anode surface during the application of pulse voltage, limits the further utilization of ECM with suction tool. A multi-physics simulation model is established to calculate the region of electrolyte confinement by the suction tool, current density distribution within the electrolyte region, and material removal. The model considers the combined effects of polarization and double layer, and all key parameters are calibrated through classical electrochemical testing experiments rather than fitted based on the predicted results. This study elucidates the transient response of current density on the anode surface during the application of pulse voltage. The simulation accuracy is validated by comparing experimental and simulated current waveforms, as well as material removal profiles under different pulse parameters and electrode shapes. This research is of great significance for improving surface precision and controllability of complex structures in ECM with suction tool, promoting its further application in the field of precision machining.

Innovative regression model-based decision support tool for optimizing radiotherapy techniques in thoracic esophageal cancer.

Modern radiotherapy exemplified by intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT), has transformed esophageal cancer treatment. Facing challenges in treating thoracic esophageal cancer near vital organs, this study introduces a regression model-based decision support tool for the optimal selection of radiotherapy techniques. We enrolled 106 patients diagnosed with locally advanced thoracic esophageal cancer in this study and designed individualized IMRT and VMAT radiotherapy plans for each patient. Detailed dosimetric analysis was performed to evaluate the differences in dose distribution between the two radiotherapy techniques across various thoracic regions. Single-factor and multifactorial logistic regression analyses were employed to establish predictive models (P1 and P2) and factors such as TLV/PTV ratio. These models were used to predict the compliance and potential advantages of IMRT and VMAT plans. External validation was performed in a validation group of 30 patients. Using predictive models, we developed a data-driven decision support tool. For upper thoracic cases, VMAT plans were recommended; for middle/lower thoracic cases, the tool guided VMAT/IMRT choices based on TLV/PTV ratio. Models P1 and P2 assessed IMRT and VMAT compliance. In validation, the tool showed high specificity (90.91%) and sensitivity (78.95%), differentiating IMRT and VMAT plans. Balanced performance in compliance assessment demonstrated tool reliability. In summary, our regression model-based decision support tool provides practical guidance for selecting optimal radiotherapy techniques for thoracic esophageal cancer patients. Despite a limited sample size, the tool demonstrates potential clinical benefits, alleviating manual planning burdens and ensuring precise, individualized treatment decisions for patients.

Correlation between coronary artery tortuosity and poor prognosis in patients with septal hypertrophic cardiomyopathy

Objective: To investigate the incidence of coronary artery tortuosity and its correlation with poor prognosis in patients with septal hypertrophic cardiomyopathy (HCM). Methods: This was a retrospective cohort study. Patients with septal HCM who were hospitalized in Fuwai Central China Cardiovascular Hospital and Zhengzhou University People's Hospital between December 1, 2017 and June 10, 2021 were selected. Non-HCM patients were matched by gender, age, and hypertension as control group. Septal HCM was divided into two groups based on the presence or absence of coronary artery tortuosity. Clinical baseline data and coronary angiography findings were compared using a multifactorial logistic analysis of the risk factors for coronary artery tortuosity. Patients were followed up until July 1, 2022, with the primary outcome being the composite endpoint of malignant arrhythmia, ischemic stroke and all-cause death. Incidence densities were compared between the coronary artery tortuosity and non-coronary artery tortuosity groups of septal HCM patients. The Cox risk-ratio model was used to analyze risk factors for primary outcomes in septal HCM patients. Results: There were 156 patients in the septal HCM group and 156 patients in the control group, both aged (57.0±11.4) years, and 75 (48.1%) were female. The incidence of coronary artery tortuosity was significantly higher in the septal HCM group than in the control group (63.5% vs. 36.5%, P<0.01), and the coronary artery tortuosity score was also higher in the septal HCM group than in the control group (P<0.01). Multiple logistic regression analysis showed that septal HCM was a risk factor for coronary artery tortuosity (OR=3.27, 95%CI: 2.02-5.29, P<0.01). In the septal HCM patients, after (2.5±1.2) years of follow-up, the incidence density of primary outcome was significantly higher in the coronary artery tortuosity group than in the non-coronary artery tortuosity group (P=0.02), while each on-point in coronary artery tortuosity score increased the risk of primary outcome by 53% for septal HCM patients (HR=1.53, 95%CI: 1.26-1.86, P<0.01). Conclusions: Patients with septal HCM are more prone to suffer coronary artery tortuosity and suffer from it to a greater extent. Coronary artery tortuosity is an important risk factor for adverse events in patients with septal HCM.

Impact of preoperative inflammatory indices and postoperative pneumonia on postoperative atrial fibrillation in patients with non-small cell lung cancer: a retrospective study

BackgroundThis study aimed to evaluate the impact of preoperative inflammatory indices and postoperative pneumonia (POP) on postoperative atrial fibrillation (POAF) in non–small cell lung cancer (NSCLC) patients.MethodsAll consecutive patients who underwent pulmonary resection at our hospital (January 2016-October 2019) were enrolled. Preoperative inflammatory indices, demographic data, surgical details, and postoperative conditions were analyzed. Univariate and multivariate analyses of risk factors associated with POAF were also conducted.ResultsAmong the 382 patients included in the study, 32 (8.38%) developed POAF. Compared to non-POAF patients, POAF patients had greater incidence of POP (P = 0.09). Approximately 31 patients (96.9%) developed atrial fibrillation within three days after surgery. The POAF group had a significantly greater mean age (68.94 years) than did the non-POAF group (63 years) (P = 0.002). Additionally, compared to non-POAF patients, POAF patients exhibited an increased number of resected mediastinal lymph nodes (P < 0.001) and mediastinal lymph node stations (P < 0.001).The POAF group also had a greater intraoperative blood volume (P = 0.006), longer surgical duration (P = 0.022), and greater drainage volume (P = 0.003). IA/B stage (P < 0.001) and IIIA/B stage(P < 0.001), and lobectomy resection (P = 0.008) and wedge resection (P = 0.023) were also associated with POAF. Compared to those in the non-POAF group, the POAF group had longer postoperative hospital stays (10.54 days vs. 9 days; P = 0.001) and longer drainage times (7 days vs. 5 days; P = 0.004). Multivariate analysis revealed age, POP, and stage IIIA/B as independent influencing factors of POAF in NSCLC patients.ConclusionPreoperative inflammatory indices were not significantly associated with POAF, but age, POP, and stage IIIA/B were identified as independent influencing factors. Advanced-stage NSCLC patients may have a greater susceptibility to POAF than early-stage patients, although further validation is needed. Additionally, POAF was linked to a longer postoperative hospital stay.