Multi-factor Logistic Regression Model Research Articles

Machine Learning-Based predictive model for adolescent metabolic syndrome: Utilizing data from NHANES 2007–2016

Metabolic syndrome (Mets) in adolescents is a growing public health issue linked to obesity, hypertension, and insulin resistance, increasing risks of cardiovascular disease and mental health problems. Early detection and intervention are crucial but often hindered by complex diagnostic requirements. This study aims to develop a predictive model using NHANES data, excluding biochemical indicators, to provide a simple, cost-effective tool for large-scale, non-medical screening and early prevention of adolescent MetS. After excluding adolescents with missing diagnostic variables, the dataset included 2,459 adolescents via NHANES data from 2007–2016. We used LASSO regression and 20-fold cross-validation to screen for the variables with the greatest predictive value. The dataset was divided into training and validation sets in a 7:3 ratio, and SMOTE was used to expand the training set with a ratio of 1:1. Based on the training set, we built eight machine learning models and a multifactor logistic regression model, evaluating nine predictive models in total. After evaluating all models using the confusion matrix, calibration curves and decision curves, the LGB model had the best predictive performance, with an AUC of 0.969, a Youden index of 0.923, accuracy of 0.978, F1 score of 0.989, and Kappa value of 0.800. We further interpreted the LGB model using SHAP, the SHAP hive plot showed that the predictor variables were, in descending order of importance, BMI age sex-specific percentage, weight, upper arm circumference, thigh length, and race. Finally, we deployed it online for broader accessibility. The predictive models we developed and validated demonstrated high performance, making them suitable for large-scale, non-medical primary screening and early warning of adolescent Metabolic syndrome. The online deployment of the model allows for practical use in community and school settings, promoting early intervention and public health improvement.

Analysis of influencing factors for complications of anterior thoracolumbar tuberculosis surgery in adults.

This study analyzes the risk factors related to the complications of anterior thoracolumbar tuberculosis in adults and to provide clinical reference. A total of 98 adult patients with thoracolumbar tuberculosis undergoing anterior surgery in our hospital from February 2020 to December 2023 were selected, and the clinical data and postoperative complications were collected. The clinical characteristics were analyzed, and the risk factors related to surgical complications were analyzed by univariate analysis and multi-factor logistic regression model. A total of 54 patients had 75 postoperative complications of different degrees. Univariate analysis showed that patient age, preoperative hemoglobin (Hb) level, bone graft fusion method, intraoperative blood loss, and postoperative neurological function [Asian neurological function classification] were correlated with the occurrence of postoperative complications (P < .05). Multivariate Logistic regression analysis showed that age over 60 years old, preoperative Hb < 100 g/L, blood loss ≥ 800 mL, bone graft fusion method were independent risk factors for anterior postoperative complications of thoracolumbar tuberculosis (P < .05). The independent risk factors for surgical complications of anterior thoracolumbar tuberculosis were age over 60 years old, preoperative Hb < 100 g/L, blood loss ≥ 800 mL, titanium cage by bone graft fusion. Controlling these variable factors before operation can reduce the incidence of postoperative complications.

Prevalence of overweight and obesity among preschool children in Hainan: a cross-sectional study in China's largest free-trade zone.

Childhood obesity leads to significant health risks, emphasizing the critical need for effective preventive measures during the preschool years. However, there is a lack of comprehensive studies on overweight and obesity among preschool children in Hainan Island, China's largest free-trade zone. Our study assessed the prevalence of overweight and obesity among preschool children across Hainan Island using Chinese, World Health Organization (WHO), and International Obesity Task Force (IOTF) criteria. Additionally, the potential factors influencing overweight and obesity among preschool children in Hainan Island were further explored. We conducted a cross-sectional survey of children aged 3-6 years covering 18 cities and counties in China's largest free trade zone. The survey primarily involved anthropometric data collection and questionnaires on children's information and the sociodemographic characteristics of their parents or guardians. We recorded the height and weight of each child and calculated their body mass index (BMI). The z-score for BMI-for-age was calculated using the WHO-recommended Anthro and AnthroPlus software, and diagnoses of overweight and obesity were determined separately according to the Chinese, WHO, and IOTF criteria. The chi-squared test, t-test, or rank-sum test was applied to describe and statistically analyze the baseline characteristics of the participating children. Additionally, potential factors affecting overweight and obesity were analyzed using a multifactor binary logistic regression model. The prevalence of overweight and obesity among preschool children in Hainan Island was 11.30% based on the Chinese criteria, significantly higher than the rates of 5.80% and 5.40% observed according to the WHO and IOTF criteria, respectively (χ 2 = 12,870.368, P < 0.001). After multifactorial adjusted analyses, we found that according to the three growth criteria, having overweight fathers or mothers, family incomes of more than 100,000 Yuan, fully active eating, and higher birth weights increased the risk of overweight and obesity among preschool children in Hainan Island. The prevalence of overweight and obesity among preschool children in Hainan Island was lower compared to rates reported in other regions. Considering that the growth and development indicators for children under 7 years old in Hainan Island are generally lower than international standards, the use of Chinese standards may be more suitable for detecting overweight and obesity among preschool children in this area. Based on the risk factors identified in this study, preventive measures can be targeted in the future to reduce the risk of overweight and obesity in preschool children in Hainan Island.

Association between obesity and thyroid nodules in children and adults living in iodine-sufficient areas: analysis of cross-sectional data from Tianjin, China

ObjectiveThe main purpose of this study was to analyse the association between obesity and thyroid nodules in children and adults living in iodine-sufficient areas in China.DesignAnalysis of data from two...

The predictive value of heparin-binding protein for bacterial infections in patients with severe polytrauma.

Heparin-binding protein is an inflammatory factor with predictive value for sepsis and participates in the inflammatory response through antibacterial effects, chemotaxis, and increased vascular permeability. The role of heparin-binding protein in sepsis has been progressively demonstrated, but few studies have been conducted in the context of polytrauma combined with bacterial infections. This study aims to investigate the predictive value of heparin-binding protein for bacterial infections in patients with severe polytrauma. This is a prospective single-center study. Patients with polytrauma in the emergency intensive care unit were selected for the study, and plasma heparin-binding protein concentrations and other laboratory parameters were measured within 48 hours of admission to the hospital. A two-sample comparison and univariate logistic regression analysis investigated the relationship between heparin-binding protein and bacterial infection in polytrauma patients. A multifactor logistic regression model was constructed, and the ROC curve was plotted. Ninety-seven patients with polytrauma were included in the study, 43 with bacterial infection and 54 without infection. Heparin-binding protein was higher in the infected group than in the control group [(32.00±3.20) ng/mL vs. (18.52±1.33) ng/mL, P = 0.001]. Univariate logistic regression analysis shows that heparin-binding protein is related to bacterial infection (OR = 1.10, Z = 3.91, 95%CI:1.05~1.15, P = 0.001). Multivariate logistic regression equations showed that patients were 1.12 times more likely to have bacterial infections for each value of heparin-binding protein increase, holding neutrophils and Procalcitonin (PCT) constant. ROC analysis shows that heparin-binding protein combined with neutrophils and PCT has better predictive value for bacterial infection [AUC = 0.935, 95%CI:0.870~0.977]. Heparin-binding protein may predict bacterial infection in patients with severe polytrauma. Combining heparin-binding protein, PCT, and neutrophils may improve bacterial infection prediction.

Application of 18 F-fluorodeoxyglucose PET/computed tomography in the diagnosis of infiltrative subsolid nodules in lung adenocarcinoma.

To investigate the diagnostic value of 18 F-fluorodeoxyglucose(FDG) PET/computed tomography (CT) for infiltrative subsolid nodules at different stages of lung adenocarcinoma and to explore predictive factors for invasive adenocarcinoma, providing compelling evidence for timely intervention. A retrospective analysis was conducted on PET/CT imaging data of 170 subsolid nodules lesions confirmed postoperatively as lung adenocarcinoma or precursor glandular lesions. Lesions were categorized into preinvasive lesions including atypical adenomatous hyperplasia and adenocarcinoma in situ, microinvasive adenocarcinoma, and invasive adenocarcinoma. Compared the differences in imaging features and metabolic parameters among different groups and used a multifactor logistic regression model and receiver operating characteristic curve analysis to identify predictive factors for invasive adenocarcinoma. From preinvasive lesions through microinvasive adenocarcinoma to invasive adenocarcinoma, there was a gradual increase in nodule diameter, nodule area, and proportion of part-solid nodule. Statistical significance ( P < 0.05) was observed in the rates of spiculation and pleural indentation between preinvasive lesions versus microinvasive adenocarcinoma and invasive adenocarcinoma groups. The maximum standardized uptake value and maximum standardized uptake ratio show statistically significant differences ( P < 0.05) between the invasive adenocarcinoma group and the other groups. Logistic regression analysis indicated that nodule composition, nodule diameter, and maximum standardized uptake ratio were predictive factors for invasive adenocarcinoma ( P < 0.05). For part-solid nodules, the longest diameter of the solid component has a high diagnostic value. The imaging features of 18 F-FDG PET/CT contribute to the diagnosis of infiltrative subsolid nodules at different stages of lung adenocarcinoma, providing robust evidence for timely intervention.

The mediating role of insulin resistance in the association between inflammatory score and MAFLD: NHANES 2017-2018.

The association between inflammatory score, insulin resistance (IR), and metabolic-associated fatty liver disease (MAFLD) is inconclusive. The objective of this study was to examine the relationship between the inflammatory score and MAFLD and investigate the potential mediating effect of IR (evaluated by triglyceride-glucose index) in this association. Calculating inflammatory score was performed based on white blood cells and high-sensitivity C-reactive protein. The association between the inflammatory score and MAFLD was evaluated based on the weighted multifactor logistic regression model. Restricted cubic splines (RCS) were used to visualize the dose-response relationship between the inflammatory score and MAFLD. We also conducted a mediation analysis to assess the extent to which IR mediates this association. Among the 1090 participants, 563 were ultimately diagnosed with MAFLD. Multivariate logistic regression results indicated a close positive association between inflammatory score and MAFLD (odds ratio = 1.235, 95% confidence interval 1.069-1.427, p = .007). The RCS results indicated a linear dose-response relationship between the inflammatory score and the risk of MAFLD after adjusting for potential confounding factors. Furthermore, the mediation analysis results showed that IR partially mediated the association between the inflammatory score and MAFLD (percent mediation = 33%). Our research results indicate that the inflammatory score is positively associated with the risk of MAFLD, and IR plays a partial mediating effect in this association.

Early Identification of Metabolic Syndrome in Adults of Jiaxing, China: Utilizing a Multifactor Logistic Regression Model.

The purpose of this study is to develop and validate a clinical prediction model for diagnosing Metabolic Syndrome (MetS) based on indicators associated with its occurrence. This study included a total of 26,637 individuals who underwent health examinations at the Jiaxing First Hospital Health Examination Center from January 19, 2022, to December 31, 2022. They were randomly divided into training (n = 18645) and validation (n = 7992) sets in a 7:3 ratio. Firstly, the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm was employed for variable selection. Subsequently, a multifactor Logistic regression analysis was conducted to establish the predictive model, accompanied by nomograms. Thirdly, model validation was performed using Receiver Operating Characteristic (ROC) curves, Harrell's concordance index (C-index), calibration plots, and Decision Curve Analysis (DCA), followed by internal validation. In this study, six predictive indicators were selected, including Body Mass Index, Triglycerides, Blood Pressure, High-Density Lipoprotein Cholesterol, Low-Density Lipoprotein Cholesterol, and Fasting Blood Glucose. The model demonstrated excellent predictive performance, with an AUC of 0.978 (0.976-0.980) for the training set and 0.977 (0.974-0.980) for the validation set in the nomogram. Calibration curves indicated that the model possessed good calibration ability (Training set: Emax 0.081, Eavg 0.005, P = 0.580; Validation set: Emax 0.062, Eavg 0.007, P = 0.829). Furthermore, decision curve analysis suggested that applying the nomogram for diagnosis is more beneficial when the threshold probability of MetS is less than 89%, compared to either treating-all or treating-none at all. We developed and validated a nomogram based on MetS risk factors, which can effectively predict the occurrence of MetS. The proposed nomogram demonstrates significant discriminative ability and clinical applicability. It can be utilized to identify variables and risk factors for diagnosing MetS at an early stage.

Developing a nomogram model for 3-month prognosis in patients who had an acute ischaemic stroke after intravenous thrombolysis: a multifactor logistic regression model approach

ObjectivesThis study is to establish a nomination graph model for individualised early prediction of the 3-month prognosis of patients who had an acute ischaemic stroke (AIS) receiving intravenous thrombolysis with...

P-299 The influence of ovarian endometriomas surgery or not and the iron overload in follicular fluid on the outcome of IVF-ET

Abstract Study question To investigate the influence of ovarian endometriomas(OEM) surgery or not on the outcome of in vitro fertilization and embryo transfer. Summary answer Laparoscopic surgery can not significantly improve the outcome of IVF-ET in OEM patients, but may decrease the ovarian reserve. What is known already Despite the great advantages of ovarian endometriomas surgery treatment in endometriosis-linked infertility, the impact of laparoscopic cystectomy on outcomes of infertility management with ART is controversial. Numerous mechanisms have been proposed in an effort to delineate the multifaceted pathophysiology that induces impairment of reproductive dynamics in patients with OEM. Reactive oxygen species, dysregulation of the immune system and iron overload constitute the crucial mechanisms that detrimentally affect oocyte and embryo developmental potential. Study design, size, duration This study retrospectively included 882 cycles in our reproductive center from January 2018 to December 2020, and the patients were divided into operation group (n = 386) and OEM group (n = 496) according to whether they underwent laparoscopic cystectomy before IVF-ET. Participants/materials, setting, methods The baseline data of age, infertility duration, basic FSH, AFC, and BMI were used as matching factors, and Propensity score matching was carried out according to the sample ratio of 1:1, and 327 cycles in the operation group and 327 cycles in the OEM group were finally included. Follicular fluid was collected under ultrasound guidance during oocyte retrieval. A total of 74 follicular fluid samples meeting the study conditions were collected. Main results and the role of chance (1)The clinical pregnancy rate of fresh embryo transfer cycle in the OEM group was significantly higher than that in the operation group (77.4% Vs 52.9%), and the difference was statistically significant (P = 0.039). There was no significant difference in pregnancy outcome in frozen embryo transfer cycle (P &amp;gt; 0.05). (2) The results of Multi-factor logistic regression model showed the clinical pregnancy rate of patients in the OEM group was 3.048 times than that of patients in the operation group in fresh cycle, and the difference was significant (OR 3.029 95%CI 1.017-9.018, P = 0.047), while early abortion and live birth pregnancy outcomes were not significantly affected in both groups. For the frozen embryo transfer cycle, there were no significant effects on clinical pregnancy, early abortion and live birth pregnancy outcomes in both groups. (3) There was no significant difference in follicular fluid iron concentration between OEM group and control group(11.53±3.38 Vs 12.18±4.37μg/dl, P = 0.112). The concentration of ferritin in follicle fluid in OEM group (57.38±139.90) was significantly higher than that in control group (24.88±13.76 μg/ml), the difference was statistically significant (P = 0.032). Limitations, reasons for caution The present study being of a retrospective and monocentric study, may not come to a very convincing conclusion, and some unknown biases might still exist due to possible underestimation of some confounders. Wider implications of the findings Collectively, our results indicate that laparoscopic ovarian cystectomy couldn’t significantly improve the IVF-ET outcomes in patients with OEM, but rather increased the risk of reduced ovarian reserve function. Ovarian reserve function was the main factor affecting the IVF-ET outcomes for infertile patients with OEM. Trial registration number /

Analysis of influencing factors of HPV vaccination willingness of female sex workers in urban entertainment venues based on the IMB model in Guangxi, China

ObjectiveUnderstanding HPV vaccination willingness and its influencing factors among female sex workers (FSWs) in entertainment venues in an urban area of Guangxi, China.MethodsFrom 15 August to 15 October 2022, FSWs in entertainment venues with commercial sex trade in an urban area of Guangxi were selected as the study subjects for the questionnaire survey using the method of intentional sampling. The questionnaire based on the information-motivation-behavior (IMB) skills model was used to collect the basic characteristics, HPV and HPV vaccine-related information and cognition, motivation to vaccinate, behavioral skills and willingness to vaccinate from the research targets. A multifactor logistic regression model was used to analyze the factors influencing the research targets' willingness to receive HPV vaccination.ResultsOf the 921 research targets, 712 (77.31%) were willing to receive HPV vaccination. The higher the level of knowledge regarding HPV and HPV vaccine-related information, the higher the motivation for HPV vaccination. In addition, the higher the behavioral skills score, the higher the willingness of FSWs in entertainment venues to receive HPV vaccination (P<0.001). FSWs in entertainment venues with lower venue grades [OR(95% CI)=0.693 (0.539, 0.891), P=0.004] were more reluctant to receive HPV vaccination. Those who favored the effectiveness of the vaccine in preventing the disease [OR(95% CI)=2.144 (1.449, 3.174), P<0.001] and those who had heard of HPV vaccine [OR(95% CI)=2.105 (1.451, 3.054), P<0.001], were able to perceive the benefits of HPV vaccination [OR(95% CI)=1.134 (1.045, 1.230), P=0.002]. These individuals acquired greater behavioral skills i.e., self-decision making for HPV vaccination [OR(95% CI)=1.130 (1.008, 1.267), P=0.036] and self-efficacy [OR(95% CI)=1.135 (1.081, 1.191), P<0.001] and they were more willing to receive HPV vaccine.ConclusionsThere was a relatively high HPV vaccination willingness among FSWs in entertainment venues in an urban area of Guangxi, China. Attention should be focused on introducing the benefits of primary prevention measures such as the HPV vaccine for individuals and behavioral skills for HPV vaccination in order to increase their willingness to be vaccinated thus increasing their HPV vaccination rate.

Development and validation of a nomogram for predicting in-hospital mortality of patients with cervical spine fractures without spinal cord injury

BackgroundThe incidence of cervical spine fractures is increasing every day, causing a huge burden on society. This study aimed to develop and verify a nomogram to predict the in-hospital mortality of patients with cervical spine fractures without spinal cord injury. This could help clinicians understand the clinical outcome of such patients at an early stage and make appropriate decisions to improve their prognosis.MethodsThis study included 394 patients with cervical spine fractures from the Medical Information Mart for Intensive Care III database, and 40 clinical indicators of each patient on the first day of admission to the intensive care unit were collected. The independent risk factors were screened using the Least Absolute Shrinkage and Selection Operator regression analysis method, a multi-factor logistic regression model was established, nomograms were developed, and internal validation was performed. A receiver operating characteristic (ROC) curve was drawn, and the area under the ROC curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were calculated to evaluate the discrimination of the model. Moreover, the consistency between the actual probability and predicted probability was reflected using the calibration curve and Hosmer–Lemeshow (HL) test. A decision curve analysis (DCA) was performed, and the nomogram was compared with the scoring system commonly used in clinical practice to evaluate the clinical net benefit.ResultsThe nomogram indicators included the systolic blood pressure, oxygen saturation, respiratory rate, bicarbonate, and simplified acute physiology score (SAPS) II. The results showed that our model had satisfactory predictive ability, with an AUC of 0.907 (95% confidence interval [CI] = 0.853–0.961) and 0.856 (95% CI = 0.746–0.967) in the training set and validation set, respectively. Compared with the SAPS-II system, the NRI values of the training and validation sets of our model were 0.543 (95% CI = 0.147–0.940) and 0.784 (95% CI = 0.282–1.286), respectively. The IDI values of the training and validation sets were 0.064 (95% CI = 0.004–0.123; P = 0.037) and 0.103 (95% CI = 0.002–0.203; P = 0.046), respectively. The calibration plot and HL test results confirmed that our model prediction results showed good agreement with the actual results, where the HL test values of the training and validation sets were P = 0.8 and P = 0.95, respectively. The DCA curve revealed that our model had better clinical net benefit than the SAPS-II system.ConclusionWe explored the in-hospital mortality of patients with cervical spine fractures without spinal cord injury and constructed a nomogram to predict their prognosis. This could help doctors assess the patient’s status and implement interventions to improve prognosis accordingly.

Development and Validation of a Nomogram Model for Individualizing the Risk of Osteopenia in Abdominal Obesity

Objective: This study was aimed to create and validate a risk prediction model for the incidence of osteopenia in individuals with abdominal obesity.Methods: Survey data from the National Health and Nutrition Examination Survey (NHANES) database for the years 2013–2014 and 2017–2018 was selected and included those with waist circumferences ≥102 m in men and ≥88 cm in women, which were defined as abdominal obesity. A multifactor logistic regression model was constructed using LASSO regression analysis to identify the best predictor variables, followed by the creation of a nomogram model. The model was then verified and evaluated using the consistency index (C-index), area under the receiver operating characteristic (ROC) curve (AUC), calibration curve, and decision curve analysis (DCA).Results Screening based on LASSO regression analysis revealed that sex, age, race, body mass index (BMI), alkaline phosphatase (ALP) and Triglycerides (TG) were significant predictors of osteopenia development in individuals with abdominal obesity (P < 0.05). These six variables were included in the nomogram. In the training and validation sets, the C indices were 0.714 (95 % CI: 0.689–0.738) and 0.701 (95 % CI: 0.662–0.739), respectively, with corresponding AUCs of 0.714 and 0.701. The nomogram model exhibited good consistency with actual observations, as demonstrated by the calibration curve. The DCA nomogram showed that early intervention for at-risk populations has a net positive impact.Conclusion: Sex, age, race, BMI, ALP and TG are predictive factors for osteopenia in individuals with abdominal obesity. The constructed nomogram model can be utilized to predict the clinical risk of osteopenia in the population with abdominal obesity.

Machine learning-based prediction of composite risk of cardiovascular events in patients with stable angina pectoris combined with coronary heart disease: development and validation of a clinical prediction model for Chinese patients.

Objective: To develop a risk score model for the occurrence of composite cardiovascular events (CVE) in patients with stable angina pectoris (SA) combined with coronary heart disease (CHD) by comparing the modeling effects of various machine learning (ML) algorithms. Methods: In this prospective study, 690 patients with SA combined with CHD attending the Department of Integrative Cardiology, China-Japan Friendship Hospital, from October 2020 to October 2021 were included. The data set was randomly divided into a training group and a testing group in a 7:3 ratio in the per-protocol set (PPS). Model variables were screened using the least absolute shrinkage selection operator (LASSO) regression, univariate analysis, and multifactor logistic regression. Then, nine ML algorithms are integrated to build the model and compare the model effects. Individualized risk assessment was performed using the SHapley Additive exPlanation (SHAP) and nomograms, respectively. The model discrimination was evaluated by receiver operating characteristic curve (ROC), the calibration ability of the model was evaluated by calibration plot, and the clinical applicability of the model was evaluated by decision curve analysis (DCA). This study was approved by the Clinical Research Ethics Committee of China-Japan Friendship Hospital (2020-114-K73). Results: 690 patients were eligible to finish the complete follow-up in the PPS. After LASSO screening and multifactorial logistic regression analysis, physical activity level, taking antiplatelets, Traditional Chinese medicine treatment, Gensini score, Seattle Angina Questionnaire (SAQ)-exercise capacity score, and SAQ-anginal stability score were found to be predictors of the occurrence of CVE. The above predictors are modeled, and a comprehensive comparison of the modeling effectiveness of multiple ML algorithms is performed. The results show that the Light Gradient Boosting Machine (LightGBM) model is the best model, with an area under the curve (AUC) of 0.95 (95% CI = 0.91-1.00) for the test set, Accuracy: 0.90, Sensitivity: 0.87, and Specificity: 0.96. Interpretation of the model using SHAP highlighted the Gensini score as the most important predictor. Based on the multifactorial logistic regression modeling, a nomogram, and online calculators have been developed for clinical applications. Conclusion: We developed the LightGBM optimization model and the multifactor logistic regression model, respectively. The model is interpreted using SHAP and nomogram. This provides an option for early prediction of CVE in patients with SA combined with CHD.

Contributing Factors for the Increased Inter-arm Systolic Blood Pressure Difference in Different Age Groups

Abstract OBJECTIVE To explore the contributing factors for the increased inter-arm systolic blood pressure difference (IASBPD) in young, middle-aged, and elderly people. METHODS A total of 51,428 workers in Kailuan who underwent arteriosclerosis detection of extremities during physical examination from 2010 to 2020 were selected as the subjects. The subjects were divided into 3 groups according to the age segment proposed by the World Health Organization: young, middle-aged, and elderly group. Each age group was subsequently divided into 2 groups according to whether the IASBPD was increased: IASBPD 15 mm Hg and IASBPD &amp;gt;15 mm Hg group. The detection rate of IASBPD &amp;gt;15 mm Hg in each age group was calculated, and the contributing factors of IASBPD &amp;gt;15 mm Hg in different age groups were analyzed via multifactor logistic regression model. RESULTS The detection rate of IASBPD &amp;gt;15 mm Hg was 15.65% in all the subjects, and it was 12.90%, 15.28%, and 20.69% in the young, middle-aged, and elderly groups, respectively (χ2 = 343.83, P &amp;lt; 0.01). In all the young, middle-aged, and elderly groups, the risk factors for IASBPD &amp;gt;15 mm Hg included decreased ankle–brachial index (ABI), elevated body mass index (overweight and obesity), male, elevated brachial–ankle pulse wave velocity (baPWV), and hypertension. Furthermore, elevated high sensitive C-reactive protein (hsCRP) was a risk factor for increased IASBPD in young people (odds ratio [OR] = l.02, 95% confidence interval [CI] 1.00–1.04). And elevated low-density lipoprotein cholesterol (LDL-C) was a risk factor (OR = 1.09, 95% CI 1.03–1.15) for increased IASBPD in middle-aged people, and the high level of education was a protective factor (OR = 0.86, 95% CI 0.79–0.94). Diabetes (OR = 1.29, 95% CI 1.16–1.42) and old age (OR = 1.01, 95% CI 1.01–1.02) were risk factors for increased IASBPD in the elderly people, and high level of education (OR = 0.84, 95% CI 0.74–0.95) and elevated high-density lipoprotein cholesterol (HDL-C) (OR = 0.82, 95% CI 0.72–0.93) were protective factors. CONCLUSIONS The detection rate of IASBPD &amp;gt;15 mm Hg increases with the increase of age in the young, middle-aged, and elderly groups. Decreased ABI, elevated overweight obesity, male, elevated baPWV, and hypertension are common risk factors for increases IASBPD in 3 age groups. Furthermore, elevated hsCRP, elevated LDL-C, diabetes mellitus, and old age are risk factors for increased IASBPD in young, middle-aged, and elderly group, respectively.

Власний досвід застосування нейромережевого аналізу в прогнозуванні довготермінового виживання пацієнтів із хронічною серцевою недостатністю

The aim – predicting the risk of fatal outcome within 3 years in patients with CHF and reduced left ventricular ejection fraction (LVEF) with neural network.Materials and methods. The retrospective analysis of 490 medical histories of patients who were hospitalized in the heart failure department between 2011 and 2018 years with CHF II–IV functional class according to NYHA with LVEF ≤ 40 % on the background of coronary heart disease was conducted. Patients with clinical signs of heart failure II NYHA functional class – 455 (92.8 %) patients and with clinical signs of CHF III NYHA functional class – 35 (7.2 %) patients. The analysis was conducted for 490 patients: 228 (46.5 %) patients had a fatal event within three years, 262 (53.5 %) patients survived three years. Results and discussion. Factor features was selected for building a neural network. The information about 8 factor characteristics (ACE inhibitor (X1), atrium fibrillation (X2), renal dysfunction (X3), age (X4), arterial pressure (X5), (X6), LV diastolic volume index ( X7), LV myocardial mass index (X8)) was used for building of neural network models. Three-layer Multiplayer Perceptron (MLP) model with one hidden layer (logistic activation function) was built in the final. This neural network is a type of multi-layer neural network (multi-network perceptron). Each neuron of this system uses a nonlinear activation function. The sensitivity and specificity of this neural network model was evaluated. The education of this neural network did by the method of backpropagation. The quality of the classification of this model was evaluated with the test set of cases. The area under the curve of the operating characteristics of the neural MLP model for predicting the risk of a fatal event exceeds that area of the 9-factor logistic regression model (p&lt;0.001).Conclusions. The use of neural network analysis increase the accuracy of predicting a fatal outcome for a 3-year period compared to a multifactor logistic regression model. According to the construction of the neural network MLP model, a strong connection of the risk of a fatal event over the course of 3 years with the presence of atrium fibrillation, renal dysfunction, age, LV diastolic volume index, LV myocardial mass index and ACE inhibitor in the treatment was revealed. The quality of the neural network MLP model is high (area under the curve AUC=0.842). Youden Index (Ycrit=0.3049), the sensitivity of the MLP model is 76.8 % (95 % CI 70.7–82.1 %), the specificity of the model is 81.3 % (95 % CI 76.0–85.8 %), predictive significance +PV – 78.1 % (95 % CI 73.3–82.3 %), predictive significance –PV – 80.1 % (95 % CI 75.9–83.7 %). The accuracy of predicting the risk of a fatal outcome within 3 years for the neural network MLP model is higher than for the 9-factor logistic regression model (р&lt;0.001).

The influence of health literacy and knowledge about smoking hazards on the intention to quit smoking and its intensity: an empirical study based on the data of China's health literacy investigation.

This study explored the relationship between smokers' health literacy, knowledge of smoking hazards, and their intention to quit. Based on data from the 2019 Health Literacy and Tobacco Use Surveillance among residents of a city in Zhejiang Province, 1120 male smokers were screened. Differential tests were used to analyze whether smokers with varying levels of health literacy and knowledge about smoking hazards differed in their intention to quit smoking and the intensity of their intention. A multi-factor logistic regression model was constructed to explore the extent of these differences. Only 24.8% of smokers had higher health literacy. Among smokers, those with an intention to quit had a higher health literacy level compared to those without such intention (32.7% vs. 17.0%, p < 0.001). Health literacy levels did not differ significantly between groups with different intensity of intention to quit (34.2% vs. 31.9% vs. 30.1%, p = 0.435). About 48.7% of the smokers a higher level of knowledge about smoking hazards. It was more prevalent in the intent to quit group compared to the no intent to quit group (54.0% vs. 43.4%, p < 0.001), and the low intent to quit group had lower knowledge compared to the moderate and high intent to quit groups (49.1% vs. 56.6% vs. 63.4%, p = 0.011). After adjusting for other influences, smokers with lower health literacy were less likely to have intention to quit (OR = 0.659, p = 0.016). And the association between knowledge about smoking hazards and whether smokers have the intention to quit is no longer significant, but it significantly affects the intensity of the intention to quit among smokers who already have the intention (OR = 0.623, p = 0.005). General health literacy may play a role in facilitating smokers' progression from the stage of no intent to quit to one of intent to quit, but a more specific understanding of the harms of smoking may be needed to increase the strength of intent to quit.

A Single-Center Large Cohort of Chronic Neutropenia Patients and a Model for Estimation of Congenital Neutropenias

Chronic neutropenia (CrN) is defined as neutropenia lasting longer than 3 months and has various underlying etiologies, including congenital neutropenia (CN). We aimed to determine the underlying etiologies of patients with CrN and define the characteristics at diagnosis suggestive for CN as a final diagnosis. The study included 197 pediatric and adolescent patients who were diagnosed with CrN between 2010 and 2022 in a single-center. Patients with transient neutropenia, splenomegaly, alloimmune, secondary autoimmune, myelodysplastic syndrome and hematological malignancies, other bone marrow failure syndromes such as Fanconi anemia, and aplastic anemia due to CrN were excluded from the study. The patients included in the study were sub-classified into 5 groups according to their final diagnosis. Group 1, patients with CN (n=64, %32.5) included all genetically verified CrN patients. Group 2, patients with primary autoimmune neutropenia (pIN) group (n=10, %5.1) with anti-granulocyte antibody (AGA) positivity. Group 3, patients with unclassified chronic idiopathic neutropenia (UCIN) (n=73, %37.1). Group 3 included patients who had a clinical severity resembling immune neutropenia, but whose AGA testing was either negative or not available; but the CrN resolved during follow-up. Group 4, included the patients with unclassified chronic benign neutropenia (UCBN) (n=34, %17.3) and included the patients with ongoing neutropenia, who do not have a history of serious infections, no underlying genetic cause for neutropenia, no AGA positivity. Group 5, unspecified congenital neutropenia (UCN) group (n=16, %8,1), was defined as the group of patients whose genetic tests did not detect a mutation in genes related to CN, but history reveales severe infections and a possible CN as an underlying cause. Genetic testing of patients varies from single gene evaluation with Sanger sequencing analysis to Whole Exome Sequencing (WES). The median age at diagnosis of neutropenia of the patients included in the study was 12 (0-168) months 53.8% of the patients were male (n=106). There was consanguinity between parents in 34.5% and at least 1 family member was diagnosed with neutropenia in the in 18.8%. Among the patients in Group 1, HAX-1 mutation was detected in 19 (29.7%) patients and it was found to be the most common genetic defect causing CN. Other common genetic disorders include ELANE mutations (18.8%), Shwachman Diamond Syndrome (10.9%), Hermansky Pudlak Syndrome (7.8%) and glycogen storage type 1 b (6.3%). G6PC3 deficiency, VPS45 deficiency, Barth syndrome and Kabuki syndrome in 2 each (3.1%), ADA2 deficiency, Cohen Syndrome, Poikiloderma with neutropenia, Prolidase deficiency, CLPB deficiency, Majeed syndrome, GINS4 deficiency, reticular dysgenesis, germline RUNX1 mutation were detected in 1 patient. There are 3 patients with acute myeloid leukemia and all of them died before hematopoietic stem cell transplantation (HSCT). Two of these patients were diagnosed with SDS, and one had ELANE mutation. One patient with the HAX-1 mutation developed non-Hodgkin lymphoma and was treated with HSCT and is still alive. There were 7 patients (3.6%) who underwent HSCT. 9 patients (4.6%) died. Except for 3 patients who died from AML and 1 who died after HSCT; 1 patient with Barth syndrome deceased related to associated dilated cardiomyopathy, Another patient with G6PC3 mutation died after complications of cardiac surgery due to associated cardiac anomaly and 3 patients (2 VPS45, 1 CLPB) died due to infections. Patients in Group1 and Group 2+Group3 were compared, in order to answer the question of “Can we create a model that predicts CN?”. Many parameters were compared and a multivariate model was created with statistically significant risk factors. CN was seen 6,3 times more in those with parental consanguinity, 8,9 times in those with a family history of neutropenia, 4,8 times in those with more than 2 hospitalizations due to infection, and 4,1 times more in those with recurrent oral involvement (p&amp;lt;0.05). Patients diagnosed with CN were estimated based on the results of the multifactor logistic regression model. The rate of correct identification of the patients by the model is 88.9%. In conclusion, our study is one of the largest single-center studies and suggests a novel classification of CrN patients.

Плацентарні фактори у вагітних з ізольованими вадами серця в плода

The placenta, as a unique and transient organ in humans, ensures the development and protection of the fetus, the expression of angiogenic and antiangiogenic factors and their receptors. The integrity of the fetoplacental endothelial barrier is critical for the development of fetal organs, especially the cardiovascular system. Placental growth factor (PLGF) regulates the morphologic and functional development of the uteroplacental vasculature and can vary with gestational age and in various pathologic conditions of the pregnant woman. Since there is a differential expression of PLGF and soluble form of fms-like tyrosine kinase (sFlt-1) at different gestational ages and their competitive interaction, it is advisable to study their level in the blood of a pregnant woman as indicators of regulation of the placental vascular system in pathological conditions of the woman and fetus. Purpose - to determine the levels of placental factors, namely PLGF and sFlt-1, in the serum of pregnant women with isolated congenital heart disease (CHD) in the fetus to increase the effectiveness of diagnostics and the ability to predict heart diseases. Materials and methods. The work was based on a prospective clinical study of a hospital sample, using the case-control study method, with the evaluation of some clinical and laboratory data in 30 pregnant women with isolated fetal CHD (study group) and 60 pregnant women with a healthy fetus (control group). In order to minimize the influence of various risk factors for fetal heart disease, the criteria for selecting pregnant women with non-syndromic forms of CHD and the control group were defined. Clinical, laboratory and statistical methods were used in the study. The level of angiogenesis indicators in blood serum of pregnant women of both groups was determined by enzyme-linked immunosorbent assay in units of pg/ml in the third trimester of pregnancy. The statistical analysis was carried out using the R software package. ROC analysis and AUC (area under the ROC curve) were used for quantitative interpretation. Differences with p&lt;0.05 were considered statistically significant. Results. According to the results of the study, the age of the women in the study group ranged from 17 to 39 years with a mean of 28.36±5.12, and the age of the women in the control group was 29.63±5.39 (p=0.239). The mean gestational age of women in the study group at enrollment was 28.26±8.45 weeks. The mean PLGF level was 93.73±77.32 pg/mL in the study group and 198.63±168.27 pg/mL in the control group (p=0.002). The average level of sFlt-1 in the blood serum of the women in the study group was 9779.44±5407.53 pg/ml, while in the pregnant women in the control group it was 3124.6±1624.53 (p&lt;0.001). The sFlt/PlGF ratio was 180.9±151.1 in the study group and 15.76±14.7 in the control group (p&lt;0.001). Conclusions. The obtained results in the form of a decrease of the placental growth factor in the blood of pregnant women with congenital heart defects in the fetus and an increase of the antiangiogenic factor in this group in the III trimester compared to a healthy fetus indicate a violation of angiogenesis in the fetoplacental system. Analysis of data on the age of pregnant women of both groups did not reveal a statistically significant difference between them. Due to the usage of multifactor logistic regression model, was created the CHD “risk calculator” which, using the placental factors of the pregnant woman, calculates the probability of the occurrence of a heart defect in fetus. The study was conducted in accordance with the tenets of the Declaration of Helsinki. The local ethics committee approved the study protocol for all participants. Informed consent was obtained from patients. No conflict of interests was declared by the author.

Nonlinear relationship between dietary calcium and magnesium intake and peripheral neuropathy in the general population of the United States.

Calcium and magnesium are essential minerals that have significant roles in nerve function and regulation. There may be a correlation between dietary calcium and magnesium intake and peripheral neuropathy. However, this relationship remains unclear and requires further study. Data from 7,726 participants in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2004 were analyzed in this study. The relationship between total dietary calcium and magnesium intake, as well as each quantile, and peripheral neuropathy was analyzed using a multifactor logistic regression model. To illustrate the dose-response relationship between calcium and magnesium intake and peripheral neuropathy, we utilized a restricted cubic spline (RCS) plot. Our analysis found a positive correlation between dietary intake of calcium and magnesium and peripheral neuropathy (calcium: OR 1.000, 95% CI 1.000-1.000; magnesium: OR 1.001, 95% CI 1.00-1.002). Participants in the first and third quantiles of dietary calcium intake had a significantly higher incidence of peripheral neuropathy than those in the second quantile (OR 1.333, 95% CI 1.034-1.719, OR 1.497, 95% CI 1.155-1.941). Those in the first and third quantiles of dietary magnesium intake also had a significantly higher incidence of peripheral neuropathy than those in the second quantile (OR 1.275, 95% CI 1.064-1.528, OR 1.525, 95% CI 1.231-1.890). The restricted cubic spline analysis revealed a U-shaped nonlinear relationship between dietary intake of calcium and magnesium and peripheral neuropathy. The study found a U-shaped non-linear relationship between dietary calcium and magnesium intake levels and peripheral neuropathy, indicating that both excessive and insufficient intake of calcium and magnesium can increase the incidence of peripheral neuropathy.