[Modification of allergic dermatitis on the associations between early-life exposure to size-specific particulate matter and childhood allergic rhinitis].

To evaluate the modification of allergic dermatitis on the association between PM exposure and allergic rhinitis in preschool children. This cross-sectional study was based on a questionnaire conducted between June 2019 and June 2020 to caregivers of children aged 3 to 6 years in the kindergartens of 7 Chinese cities to collect information on allergic rhinitis and allergic dermatitis. A mature machine learning-based space-time extremely randomized trees model was applied to estimate early-life, prenatal, and first-year exposure of PM1, PM2.5 and PM10 at 1 km×1 km resolution. A combination of multilevel logistic regression and restricted cubic spline functions was used to quantitatively assess whether allergic dermatitis modifies the associations between size-specific PM exposure and the risk of childhood allergic rhinitis. The results showed that out of 28 408 children, 14 803 (52.1%) were boys and 13 605 (47.9%) were girls; the age of children ranged from 3.1 to 6.8 years, with a mean age of (4.9±0.9) years, of which 3 586 (12.6%) were diagnosed with allergic rhinitis. Among all children, 17 832 (62.8%) were breastfed for more than 6 months and 769 (2.7%) had parental history of atopy. A total of 21 548 children (75.9%) had a mother with an educational level of university or above and 7 338 (29.6%) had passive household cigarette smoke exposure. The adjusted ORs for childhood allergic rhinitis among the children with allergic dermatitis as per interquartile range (IQR) increase in early-life PM1(9.8 µg/m3), PM2.5 (14.9 µg/m3) and PM10 (37.7 µg/m3) were significantly higher than the corresponding ORs among the children without allergic dermatitis [OR: 1.45, 95%CI (1.26, 1.66) vs. 1.33, 95%CI (1.20, 1.47), for PM1; OR: 1.38, 95%CI (1.23, 1.56) vs. 1.32, 95%CI (1.21, 1.45), for PM2.5; OR: 1.56, 95%CI (1.31, 1.86) vs. 1.46, 95%CI (1.28, 1.67), for PM10]. The interactions between allergic dermatitis and size-specific PM exposure on childhood allergic rhinitis were statistically significant (Z value=19.4, all P for interaction<0.001). The similar patterns were observed for both prenatal and first-year size-specific PM exposure and the results of the dose-response relationship were consistent with those of the logistic regression. In conclusion, allergic dermatitis, as an important part of the allergic disease progression, may modify the association between ambient PM exposure and the risk of childhood allergic rhinitis. Children with allergic dermatitis should pay more attention to minimize outdoor air pollutants exposure to prevent the further progression of allergic diseases.

[Analysis of clinical characteristics and risk factors of chest tightness variant asthma in children].

Objective: To analyze the clinical features and risk factors of chest tightness variant asthma (CTVA) in children, so as to provide basis for the prevention and management of the disease. Methods: A cross-sectional study was conducted to analyze 178 children aged 6-17 years old who were admitted to the Department of Allergy, Capital Institute of Pediatrics Affiliated Children's Hospital from January 2021 to January 2023 due to chest tightness. The age was 8.83(7.50, 11.58) years old, with 89 males (50%) and 89 females (50%). According to the diagnosis of CTVA, 130 cases were divided into CTVA group and 48 non-CTVA cases were divided into control group. Demographic data, personal history, family history, clinical features, auxiliary examination results and other data were collected. The clinical characteristics, allergens, FeNO level and pulmonary function parameters of the two groups were analyzed. Logistic regression analysis was used to explore the risk factors of the disease. Results: The proportion of school-age children (6-11 years old) in CTVA group was higher than that of adolescent children (≥12 years old) [(113/130,86.9%) vs (26/48,54.2%),Z=21.985,P<0.01]. The proportion of CTVA combined with eczema [(74/130,56.9%) vs (19/48,39.6%), χ2=4.225,P<0.05] and rhinitis symptoms [(98/130,75.4%) vs (27/48,56.2%), χ2=6.138,P<0.05] was higher. The positive rates of mold sensitization [(52/130,40.0%) vs (11/48,22.9%), χ2=4.474,P<0.05] and multiple sensitization [(71/130,54.6%) vs (18/48,37.5%), χ2=4.108,P<0.05] in inhaled allergens were significantly higher than those of control group. The proportion of elevated FeNO (>20 ppb) in CTVA children was 20.8% (27/130), which was significantly higher than that in control group 4.2%(2/48)(χ2=7.086,P<0.01). There were no statistical differences in spirometry parameters FEV1 and FVC between CTVA group and control group (P both>0.05). FEV1/FVC, PEF, FEF25, FEF50, FEF75 and MMEF were significantly lower than those in control group (P all<0.05). Logistic regression analysis showed that rhinitis symptoms (OR=2.351, 95%CI 1.105-5.002, P=0.026), multiple sensitizations (OR=2.184, 95%CI 1.046-4.557, P=0.038), tIgE>60 kU/L(OR=3.080, 95%CI 1.239-7.654, P=0.015), FeNO>20 ppb (OR=6.734, 95%CI 1.473-30.796, P=0.014) and small airway dysfunction (OR=3.164, 95%CI 1.089-9.194, P=0.034) were risk factors for chest tightness variant asthma. FeNO combined with FEF50 has the largest area under the curve (Z=2.744, P<0.01) in diagnosing CTVA. Conclusion: CTVA is more common in school-age children than in adolescent children. Rhinitis symptoms, multiple sensitization, tIgE>60 kU/L, FeNO>20 ppb and small airway dysfunction are risk factors for chest tightness variant asthma. FeNO combined with small airway indexes can improve the diagnostic value of CTVA.

[Current situation and influencing factors of wheezing among children and adolescents aged 3-18 years in 11 cities in China from 2022 to 2023].

Objective: To explore the incidence and influencing factors of wheezing among children and adolescents aged 3-18 years in 11 cities in China from 2022 to 2023. Methods: From October 2022 to August 2023, 11 cities including Xishuangbanna in Yunnan Province, Suqian in Jiangsu Province, Chifeng and Hohhot in Inner Mongolia, Tangshan in Hebei Province, Changzhi in Shanxi Province, Yinchuan in Ningxia Province, Lanzhou and Dingxi in Gansu Province, Linyi in Shandong Province, and Tonghua in Jilin Province were selected as research sites to recruit kindergarten children and primary and secondary school adolescents in local urban areas. A total of 21 959 children and adolescents were included in this study. Demographic information, wheezing data (whether wheezing has occurred in the past and whether wheezing attacks have occurred in the past one year), personal history, family history and other information were collected through questionnaires. The multivariate logistic regression model was used to analyze the influencing factors of wheezing attacks in the past one year. Results: The mean age of 21 959 children and adolescents was (12.09±3.65) years old, and 52.3% (11 480) were boys. The incidence of wheezing history was 3.7% (816 cases), and the incidence of wheezing attacks in the past year was 2.5% (556 cases). The multivariate logistic regression model analysis results showed that compared with older age, girls, full-term natural delivery, no allergic rhinitis, no family history of allergic diseases, no passive smoking, partial diet, natural conception and childbirth, the children aged 3-18 years with young age, male, partial diet, passive smoking, family history of allergic diseases, allergic rhinitis, cesarean section, premature birth, and assisted reproduction had a higher risk of wheezing [OR (95%CI): 0.86(0.84-0.88), 1.27(1.07-1.51), 2.31(1.95-2.75), 2.09(1.76-2.47), 3.5(2.80-4.37), 4.05(3.39-4.83), 1.20(1.02-1.43), 2.26(1.66-3.09), and 1.67(1.01-2.78)]. Conclusion: From 2022 to 2023, the incidence of wheezing among children aged 3-18 years in China is not significantly higher than before, and childhood wheezing may be related to factors such as children's age, gender, dietary habits, family and personal history of allergic diseases, passive smoking, and perinatal period.

[Correlation between arousal threshold and occurrence of hypertension in patients with obstructive sleep apnea hypopnea syndrome].

Objective: To investigate the relationship between arousal threshold (ArTH) and hypertension in patients with obstructive sleep apnea hypopnea syndrome (OSA). Methods: This study recruited 648 patients diagnosed with OSA at the Sleep Center of the Second Affiliated Hospital of Soochow University from January 2020 to August 2021, including 569 males and 79 females, aged 42(35,52) years. The basic demographic information and clinical data of all patients were collected, including blood pressure measurement, and relevant questionnaire scores, and nocturnal polysomnography (PSG) parameters. A clinical predictive model based on sleep apnea hypopnea index (AHI), lowest pulse oxygen saturation (LSpaO2) and hypopnea ratio (FHypopneas) was used to access the arousal threshold of OSA patients. Patients were divided into OSA group and OSA with hypertension group according to whether they were combined with hypertension. The differences in the above indexes between the two groups were analyzed to explore the relationship between arousal threshold and hypertension in OSA patients, using a binary logistic stepwise regression analysis. Results: A total of 648 OSA patients were enrolled, including 415 in the OSA with hypertension group and 233 in the OSA group. Compared with OSA group, OSA with hypertension group had older age, higher body mass index (BMI), higher blood pressure at bedtime and at awakening, higher AHI and lower proportion of hypopnea (all P<0.05). There were no significant differences between other general data and PSG parameters (all P>0.05). The proportion of patients with low arousal threshold (AHI<30 events per hour, LSpO2>82.5%, Fhypopneas>58.3%) in OSA with hypertension group was lower, and the proportion of phenotypic patients with low arousal threshold was significantly lower (30.1% vs. 52.4% P<0.001). Binary logistic stepwise regression analysis showed that the high arousal threshold (OR=1.930, 95%CI:1.326-2.808, P=0.001) was an independent risk factor for OSA complicated with hypertension. Conclusion: The arousal threshold is associated with the development of hypertension in OSA patients, and OSA patients with a high arousal threshold have a higher risk of developing hypertension.

Association Between Urinary Phthalate Metabolites and Chronic Obstructive Pulmonary Disease: A Cross-Sectional Study.

Objective: To determine the association of urinary phthalate metabolites with chronic obstructive pulmonary disease (COPD), airflow obstruction, lung function and respiratory symptoms. Methods: Our study included a total of 2023 individuals aged ≥ 40 years old in the National Health and Nutrition Examination Survey (NHANES). Multivariate logistic regression was conducted to explore the correlation of eleven urinary phthalate metabolites (MCNP, MCOP, MECPP, MnBP, MCPP, MEP, MEHHP, MEHP, MiBP, MEOHP, and MBzP) with COPD, airflow obstruction and respiratory symptoms. Linear regression analyses were used to evaluate the relationship between urinary phthalate metabolites and lung function. Results: When compared to the first tertile, the third tertile of MEHHP was associated with the risk of COPD [OR: 2.779; 95% confidence interval (CI): 1.129-6.840; P = 0.026]. Stratified analysis showed that MEHHP increased the risk of COPD by 7.080 times in male participants. Both MCPP and MBzP were positively correlated with the risk of airflow obstruction. The third tertile of MBzP increased the risk of cough by 1.545 (95% CI: 1.030-2.317; P = 0.035) times. Both FEV1 and FVC were negatively associated with MEHHP, MECPP, MnBP, MEP, MiBP and MEOHP. Conclusion: Higher levels of MEHHP are associated with increased risk of COPD, and lower measures of FEV1 and FVC. MBzP is positively related to airflow obstruction and cough.

Association of Severe Vitamin D Deficiency with Hospitalization in the Previous Year in Hospitalized Exacerbated COPD Patients.

Purpose: Vitamin D deficiency (VDD, 25-hydroxyvitamin D < 20 ng/mL) has been reported associated with exacerbation of chronic obstructive pulmonary disease (COPD) but sometimes controversial. Research on severe vitamin D deficiency (SVDD, 25-hydroxyvitamin D < 10 ng/mL) in exacerbation of COPD is limited. Patients and Methods: We performed a retrospective observational study in 134 hospitalized exacerbated COPD patients. 25-hydroxyvitamin D was modeled as a continuous or dichotomized (cutoff value: 10 or 20 ng/mL) variable to evaluate the association of SVDD with hospitalization in the previous year. Receiver operator characteristic (ROC) analysis was performed to find the optimal cut-off value of 25-hydroxyvitamin D. Results: In total 23% of the patients had SVDD. SVDD was more prevalent in women, and SVDD group tended to have lower blood eosinophils counts. 25-hydroxyvitamin D level was significantly lower in patients who were hospitalized in the previous year (13.6 vs 16.7 ng/mL, P = 0.044), and the prevalence of SVDD was higher (38.0% vs 14.3%, P = 0.002). SVDD was independently associated with hospitalization in the previous year [odds ratio (OR) 4.34, 95% CI 1.61-11.72, P = 0.004] in hospitalized exacerbated COPD patients, whereas continuous 25-hydroxyvitamin D and VDD were not (P = 0.1, P = 0.9, separately). The ROC curve yielded an area under the curve of 0.60 (95% CI 0.50-0.71) with an optimal 25-hydroxyvitamin D cutoff of 10.4 ng/mL. Conclusion: SVDD probably showed a more stable association with hospitalization in the previous year in hospitalized exacerbated COPD patients. Reasons for lower eosinophil counts in SVDD group needed further exploration.

Hepatitis C risk score as a tool to identify individuals with HCV infection: a demonstration and cross-sectional epidemiological study in Egypt.

OBJECTIVES: Hepatitis C virus (HCV) infection poses a global health challenge. By the end of 2021, the WHO estimated that less than a quarter of global HCV infections had been diagnosed. There is a need for a public health tool that can facilitate the identification of people with HCV infection and link them to testing and treatment, and that can be customised for each country. METHODS: We derived and validated a risk score to identify people with HCV in Egypt and demonstrated its utility. Using data from the 2008 and 2014 Egypt Demographic and Health Surveys, two risk scores were constructed through multivariable logistic regression analysis. A range of diagnostic metrics was then calculated to evaluate the performance of these scores. RESULTS: The 2008 and 2014 risk scores exhibited similar dependencies on sex, age and type of place of residence. Both risk scores demonstrated high and similar areas under the curve of 0.77 (95% CI: 0.76 to 0.78) and 0.78 (95% CI: 0.77 to 0.80), respectively. For the 2008 risk score, sensitivity was 73.7% (95% CI: 71.5% to 75.9%), specificity was 68.5% (95% CI: 67.5% to 69.4%), positive predictive value (PPV) was 27.8% (95% CI: 26.4% to 29.2%) and negative predictive value (NPV) was 94.1% (95% CI: 93.5% to 94.6%). For the 2014 risk score, sensitivity was 64.0% (95% CI: 61.5% to 66.6%), specificity was 78.2% (95% CI: 77.5% to 78.9%), PPV was 22.2% (95% CI: 20.9% to 23.5%) and NPV was 95.7% (95% CI: 95.4% to 96.1%). Each score was validated by applying it to a different survey database than the one used to derive it. CONCLUSIONS: Implementation of HCV risk scores is an effective strategy to identify carriers of HCV infection and to link them to testing and treatment at low cost to national programmes.

Spatial Variation and Determinants of Inadequate Minimum Meal Frequency among Children Aged 6-23 Months in Ethiopia: Spatial and multilevel analysis using Ethiopian Mini Demographic and Health Survey (EMDHS) 2019.

Introduction: Minimum meal frequency is the number of times children eat in a day. Without adequate meal frequency, infants and young children are prone to malnutrition. There is little information on the spatial distribution and determinants of inadequate meal frequency at the national level. Therefore, we aimed to investigate the spatial distribution and determinants of inadequate meal frequency among young children in Ethiopia. Methods: The most recent Ethiopian demographic and health survey data was used. The analysis was conducted using a weighted sample of 1,610 children aged 6-23 months old. The Global Moran's I was estimated to assess the regional variation in minimum meal frequency. Further, a multivariable multilevel logistic regression model was fitted to identify factors associated with inadequate meal frequency. The AOR (adjusted odds ratio) at 95% CI (confidence interval) was computed to assess the strength and significance of the relationship between explanatory variables and the outcome variable. Factors with a p-value of <0.05 are declared statistically significant. Results: This study revealed that the prevalence of inadequate meal frequency was found to be 30.56% (95% CI: 28.33-32.88). We identified statistically significant clusters of high inadequate meal frequency, notably observed in Somalia, northern Amhara, the eastern part of southern nations and nationalities, and the southwestern Oromia regions. Child age, antenatal care (ANC) visit, marital status, and community level illiteracy were significant factors that were associated with inadequate meal frequency. Conclusion: According to the study findings, the proportion of inadequate meal frequency among young children in Ethiopia was higher and also distributed non-randomly across Ethiopian regions. As a result, policymakers and other concerned bodies should prioritize risky areas in designing intervention. Thus, special attention should be given to the Somalia region, the northern part of Amhara, the eastern part of Southern nations and nationalities, and southwestern Oromia.

Factors associated with postpartum fatigue: an exploration of the moderating role of resilience.

Background: Postpartum fatigue (PPF) can impair the physical and mental well-being of women. The aims of this study were to assess the associations between fatigue and maternal health-related variables, specifically, sleep quality, depression symptoms, and resilience, and to explore the moderating role of resilience in the relationships between sleep quality, depression symptoms, and fatigue. Methods: This cross-sectional study used data collected from mothers during the postpartum period via an online platform. PPF was assessed using the Fatigue Severity Scale, whereas sleep quality and depression symptoms were assessed using the Pittsburgh Sleep Quality Index and Edinburgh Postnatal Depression Scale, respectively. The Brief Resilience Scale was used to assess resilience. Simple and multiple binary logistic regression analyses were performed to examine the association of each independent variable with PPF and to determine the most significant predictors of PFF. The data were analyzed using SPSS, and structural equation modeling was performed using AMOS 23. A moderation analysis was performed to explore the moderating role of resilience using the Hayes PROCESS macro. Results: A total of 1,443 postpartum mothers were included in the analysis. The simple binary logistic regression analysis showed that having chronic disease (odds: 1.52; p = 0.02), mother's age (odds: 0.97; p = 0.03), mother's body mass index (BMI; odds: 1.03; p = 0.01), depression symptoms (odds: 1.09; p ≤ 0.0001), sleep quality (odds: 1.17; p ≤ 0.0001), and resilience (odds: 0.42; p ≤ 0.0001) all contributed to fatigue during postpartum. Multivariate logistic regression showed that the mother's BMI, sleep quality, depression symptoms, and resilience were significant predictors of PPF. Moderation analyses showed that resilience was not a significant moderator between the main effects of sleep quality and fatigue (interaction effect: ß = 0.01, p = 0.31, 95% CI: -0.01 to 0.04) or between the main effects of depression symptoms and fatigue during postpartum (interaction effect: ß = 0.01, p = 0.82, 95% CI: -0.01 to 0.02). Conclusion: Given the deleterious effects of PPF on maternal health outcomes, factors associated with PPF should be assessed regularly. In addition to mothers' BMI, sleep quality, and depression symptoms, resilience could also be a crucial factor in predicting fatigue severity during this critical time for mothers even though it was not a significant moderator among this sample.

A risk prediction model of gestational diabetes mellitus based on traditional and genetic factors.

BACKGROUND: Gestational diabetes mellitus (GDM) is a prevalent pregnancy complication during pregnancy. We aimed to evaluate a risk prediction model of GDM based on traditional and genetic factors. METHODS: A total of 2744 eligible pregnant women were included. Face-to-face questionnaire surveys were conducted to gather general data. Serum test results were collected from the laboratory information system. Independent risk factors for GDM were identified using univariate and multivariate logistic regression analyses. A GDM risk prediction model was constructed and evaluated with the Hosmer-Lemeshow goodness-of-fit test, goodness-of-fit calibration plot, receiver operating characteristic curve and area under the curve. RESULTS: Among traditional factors, age ≥30 years, family history, GDM history, impaired glucose tolerance history, systolic blood pressure ≥116.22 mmHg, diastolic blood pressure ≥74.52 mmHg, fasting plasma glucose ≥5.0 mmol/L, 1-hour postprandial blood glucose ≥8.8 mmol/L, 2-h postprandial blood glucose ≥7.9 mmol/L, total cholesterol ≥4.50 mmol/L, low-density lipoprotein ≥2.09 mmol/L and insulin ≥11.5 mIU/L were independent risk factors for GDM. Among genetic factors, 11 single nucleotide polymorphisms (SNPs) (rs2779116, rs5215, rs11605924, rs7072268, rs7172432, rs10811661, rs2191349, rs10830963, rs174550, rs13266634 and rs11071657) were identified as potential predictors of the risk of postpartum DM among women with GDM history, collectively accounting for 3.6% of the genetic risk. CONCLUSIONS: Both genetic and traditional factors contribute to the risk of GDM in women, operating through diverse mechanisms. Strengthening the risk prediction of SNPs for postpartum DM among women with GDM history is crucial for maternal and child health protection.

We aimed to evaluate a risk prediction model of gestational diabetes mellitus (GDM) based on traditional and genetic factors. A total of 2744 eligible pregnant women were included. Face-to-face questionnaire surveys were conducted to collect general data. Among traditional factors, age ≥30 years old, family history, GDM history, impaired glucose tolerance history, systolic blood pressure ≥116.22 mmHg, diastolic blood pressure ≥74.52 mmHg, fasting plasma glucose ≥5.0 mmol/L, 1-hour postprandial blood glucose ≥8.8 mmol/L, 2-h postprandial blood glucose ≥7.9 mmol/L, total cholesterol ≥4.50 mmol/L, low-density lipoprotein ≥2.09 mmol/L and insulin ≥11.5 mIU/L were independent risk factors for GDM. Among genetic factors, 11 single nucleotide polymorphisms were identified as potential predictors of the risk of postpartum DM among women with GDM history, collectively accounting for 3.6% of the genetic risk. Both genetic and traditional factors increase the risk of GDM in women.

Development and validation of an intraoperative hypothermia nomograph model for patients undergoing video-assisted thoracoscopic lobectomy: a retrospective study.

This study aimed to develop and internally validate a nomogram model for assessing the risk of intraoperative hypothermia in patients undergoing video-assisted thoracoscopic (VATS) lobectomy. This study is a retrospective study. A total of 530 patients who undergoing VATS lobectomy from January 2022 to December 2023 in a tertiary hospital in Wuhan were selected. Patients were divided into hypothermia group (n = 346) and non-hypothermia group (n = 184) according to whether hypothermia occurred during the operation. Lasso regression was used to screen the independent variables. Logistic regression was used to analyze the risk factors of hypothermia during operation, and a nomogram model was established. Bootstrap method was used to internally verify the nomogram model. Receiver operating characteristic (ROC) curve was used to evaluate the discrimination of the model. Calibration curve and Hosmer Lemeshow test were used to evaluate the accuracy of the model. Decision curve analysis (DCA) was used to evaluate the clinical utility of the model. Intraoperative hypothermia occurred in 346 of 530 patients undergoing VATS lobectomy (65.28%). Logistic regression analysis showed that age, serum total bilirubin, inhaled desflurane, anesthesia duration, intraoperative infusion volume, intraoperative blood loss and body mass index were risk factors for intraoperative hypothermia in patients undergoing VATS lobectomy (P < 0.05). The area under ROC curve was 0.757, 95% CI (0.714-0.799). The optimal cutoff value was 0.635, the sensitivity was 0.717, and the specificity was 0.658. These results suggested that the model was well discriminated. Calibration curve has shown that the actual values are generally in agreement with the predicted values. Hosmer-Lemeshow test showed that χ2 = 5.588, P = 0.693, indicating that the model has a good accuracy. The DCA results confirmed that the model had high clinical utility. The nomogram model constructed in this study showed good discrimination, accuracy and clinical utility in predicting patients with intraoperative hypothermia, which can provide reference for medical staff to screen high-risk of intraoperative hypothermia in patients undergoing VATS lobectomy.

Risk factors and predictive models for frozen shoulder.

This study aims to explore the risk factors associated with frozen shoulder (FS) and develop a predictive model for diagnosing FS, in order to facilitate early detection of the condition. A total of 103 patients diagnosed with FS and admitted to the Department of Joint Surgery at Suining Central Hospital between October 2021 and October 2023 were consecutively included in the study. Additionally, 309 individuals without shoulder joint diseases, matched for age and gender, who visited the department during the same time, were included as the control group.The complete recording of clinical data for all patients was followed by the utilization of statistical tests such as the Mann-Whitney U test, sample t test, and chi-square test to compare different groups. Additionally, multivariate binary logistic regression analysis was employed to identify risk factors associated with the occurrence of FS in patients, leading to the establishment of a prediction model and derivation of a simplified equation. The diagnostic effectiveness of individual indicators and prediction models was assessed through the use of receiver operating characteristic (ROC) curve analysis. In the sample of 103 individuals, 35 were identified as male and 68 as female, with an average age range of 40-70 years (mean age: 54.20 ± 6.82 years). The analysis conducted between different groups revealed that individuals with a low body mass index (BMI), in conjunction with other factors such as diabetes, cervical spondylosis, atherosclerosis, and hyperlipidemia, were more susceptible to developing FS. Logistic regression analysis further indicated that low BMI, diabetes, cervical spondylosis, and hyperlipidemia were significant risk factors for the occurrence of FS. These variables were subsequently incorporated into a predictive model, resulting in the creation of a simplified equation.The ROC curve demonstrated that the combined indicators in the predictive model exhibited superior diagnostic efficacy compared to single indicators, as evidenced by an area under the curve of 0.787, sensitivity of 62.1%, and specificity of 82.2%. Low BMI, diabetes, cervical spondylosis, and hyperlipidemia are significant risk factors associated with the occurrence of FS. Moreover, the utilization of a prediction model has demonstrated superior capability in forecasting the likelihood of FS compared to relying solely on individual indicators. This finding holds potential in offering valuable insights for the early diagnosis of FS.

Using machine-learning models to predict extubation failure in neonates with bronchopulmonary dysplasia.

AIM: To develop a decision-support tool for predicting extubation failure (EF) in neonates with bronchopulmonary dysplasia (BPD) using a set of machine-learning algorithms. METHODS: A dataset of 284 BPD neonates on mechanical ventilation was used to develop predictive models via machine-learning algorithms, including extreme gradient boosting (XGBoost), random forest, support vector machine, naïve Bayes, logistic regression, and k-nearest neighbor. The top three models were assessed by the area under the receiver operating characteristic curve (AUC), and their performance was tested by decision curve analysis (DCA). Confusion matrix was used to show the high performance of the best model. The importance matrix plot and SHapley Additive exPlanations values were calculated to evaluate the feature importance and visualize the results. The nomogram and clinical impact curves were used to validate the final model. RESULTS: According to the AUC values and DCA results, the XGboost model performed best (AUC = 0.873, sensitivity = 0.896, specificity = 0.838). The nomogram and clinical impact curve verified that the XGBoost model possessed a significant predictive value. The following were predictive factors for EF: pO2, hemoglobin, mechanical ventilation (MV) rate, pH, Apgar score at 5 min, FiO2, C-reactive protein, Apgar score at 1 min, red blood cell count, PIP, gestational age, highest FiO2 at the first 24 h, heart rate, birth weight, pCO2. Further, pO2, hemoglobin, and MV rate were the three most important factors for predicting EF. CONCLUSIONS: The present study indicated that the XGBoost model was significant in predicting EF in BPD neonates with mechanical ventilation, which is helpful in determining the right extubation time among neonates with BPD to reduce the occurrence of complications.

Predicting risk of the subsequent early pregnancy loss in women with recurrent pregnancy loss based on preconception data.

BACKGROUND: For women who have experienced recurrent pregnancy loss (RPL), it is crucial not only to treat them but also to evaluate the risk of recurrence. The study aimed to develop a risk predictive model to predict the subsequent early pregnancy loss (EPL) in women with RPL based on preconception data. METHODS: A prospective, dynamic population cohort study was carried out at the Second Hospital of Lanzhou University. From September 2019 to December 2022, a total of 1050 non-pregnant women with RPL were participated. By December 2023, 605 women had subsequent pregnancy outcomes and were randomly divided into training and validation group by 3:1 ratio. In the training group, univariable screening was performed on RPL patients with subsequent EPL outcome. The least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were utilized to select variables, respectively. Subsequent EPL prediction model was constructed using generalize linear model (GLM), gradient boosting machine (GBM), random forest (RF), and deep learning (DP). The variables selected by LASSO regression and multivariate logistic regression were then established and compared using the best prediction model. The AUC, calibration curve, and decision curve (DCA) were performed to assess the prediction performances of the best model. The best model was validated using the validation group. Finally, a nomogram was established based on the best predictive features. RESULTS: In the training group, the GBM model achieved the best performance with the highest AUC (0.805). The AUC between the variables screened by the LASSO regression (16-variables) and logistic regression (9-variables) models showed no significant difference (AUC: 0.805 vs. 0.777, P = 0.1498). Meanwhile, the 9-variable model displayed a well discrimination performance in the validation group, with an AUC value of 0.781 (95%CI 0.702, 0.843). The DCA showed the model performed well and was feasible for making beneficial clinical decisions. Calibration curves revealed the goodness of fit between the predicted values by the model and the actual values, the Hosmer-Lemeshow test was 7.427, and P = 0.505. CONCLUSIONS: Predicting subsequent EPL in RPL patients using the GBM model has important clinical implications. Future prospective studies are needed to verify the clinical applicability. TRIAL REGISTRATION: This study was registered in the Chinese Clinical Trial Registry with the registration number of ChiCTR2000039414 (27/10/2020).

Occupational health disorders among physical education teachers compared to classroom and subject specialist teachers.

During the course of their work, teachers may be subjected to conditions that cause different health problems. This study examines occupational health disorders in a representative sample of 858 teachers (528 female; age 44.0 ± 9.67 years) divided into three groups of teachers with specific occupational requirements: specialist physical education teachers (specialist PETs), classroom teachers, and specialist teachers. The number of health disorders in the last 12 months was recorded using the Chronic Health Disorders Questionnaire. The differences between the different types of teachers, controlled for sex and age, were analyzed using binary logistic regression. The results showed that 89% of teachers experienced colds as the most frequently reported health problem, followed by 58% for lower back problems, 57% for headaches, 51% for hoarseness, and 43% for neck problems. A binary logistic regression showed that specialist PETs were the group with the highest health risk. They were about twice as likely to have musculoskeletal or hearing disorders than the other two groups of teachers. They were also significantly more likely to suffer from hoarseness. Understanding these different health challenges is critical to developing targeted interventions and robust support systems. These interventions should include initiatives aimed at raising awareness of health risk factors, implementing injury interventions and vocal cord hygiene programs, making ergonomic adjustments, and promoting awareness of self-care (both mental and physical). Given that the teaching profession is currently struggling with an aging workforce and a shortage of teachers, addressing these challenges is critical to the continued well-being of the teaching professionals.

[An analysis of related factors in thrombocytopenia combined with cirrhosis: a cross-sectional study of 2 517 cases].

Objective: To explore the related factors of thrombocytopenia (TCP) occurrence in patients with cirrhosis. Methods: A cross-sectional study was conducted. Inpatients with an initial diagnosis of cirrhosis at Peking University First Hospital from January 1, 2010 to December 31, 2020 were included. Clinical data such as demographic characteristics, etiology of cirrhosis, complications of cirrhosis, laboratory indicators, Child-Pugh grade, invasive procedures, and mortality during hospitalization were collected. A logistic regression model was used to explore the related factors of TCP occurrence in patients with cirrhosis. Categorical variables were compared by the χ(2) test. The inter-group comparison was performed using continuous variables, a t-test, one-way analysis of variance (ANOVA), or a nonparametric test. Results: There were a total of 2 592 cases of cirrhosis. 75 cases with incomplete clinical data were excluded. 2 517 cases were included for analysis. The median age was 58 (50, 67) years. Males accounted for 64%. 1 435 cases (57.0%) developed TCP, and 434 cases (17.2%) had grade 3-4 TCP. Gender, primary biliary cholangitis (PBC), primary sclerosing cholangitis (PSC), and concomitant esophagogastric varices (EGV) were the major factors associated with TCP. Females were more prone to combine with TCP (OR=1.32, 95%CI: 1.12-1.56, P=0.001). Patients combined with EGV (OR=3.09, 95%CI: 2.63-3.65, P<0.001) were more prone to develop TCP, which was associated with the increased incidence of hypersplenism (P<0.001). Patients with PBC (OR=0.64, 95%CI: 0.50-0.82, P<0.001) and PSC (OR=0.23, 95%CI: 0.06-0.65, P=0.010) were less prone to develop TCP, which was due to the shorter prothrombin time and better coagulation function of PBC patients (P<0.001), and the lower proportion of hypersplenism in combined PSC patients (P=0.004). Patients with TCP and grade 3-4 TCP had a higher rate of hemostatic procedures (P<0.05), but a lower rate of liver biopsy (P<0.05). Patients with grade 3-4 TCP had a higher nosocomial mortality rate compared to those without (P=0.004). Conclusion: TCP is common in patients with cirrhosis. However, TCP occurrence is higher in female patients with EGV and lower in patients combined with PBC and PSC. TCP affects invasive procedures and is associated with adverse outcomes.

Development and validation of a scoring system to predict the mortality of hospitalized patients with SARS-CoV-2 Omicron: a nationwide, multicentre study.

BACKGROUND: The Omicron variant broke out in China at the end of 2022, causing a considerable number of severe cases and even deaths. The study aimed to identify risk factors for death in patients hospitalized with SARS-CoV-2 Omicron infection and to establish a scoring system for predicting mortality. METHODS: 1817 patients were enrolled at eight hospitals in China from December 2022 to May 2023, including 815 patients in the training group and 1002 patients in the validation group. Forty-six clinical and laboratory features were screened using LASSO regression and multivariable logistic regression. RESULTS: In the training set, 730 patients were discharged and 85 patients died. In the validation set, 918 patients were discharged and 84 patients died. LASSO regression identified age, levels of interleukin (IL) -6, blood urea nitrogen (BUN), lactate dehydrogenase (LDH), and D-dimer; neutrophil count, neutrophil-to-lymphocyte ratio (NLR) as associated with mortality. Multivariable logistic regression analysis showed that older age, IL-6, BUN, LDH and D-dimer were significant independent risk factors. Based on these variables, a scoring system was developed with a sensitivity of 83.6% and a specificity of 83.5% in the training group, and a sensitivity of 79.8% and a sensitivity of 83.0% in the validation group. CONCLUSIONS: A scoring system based on age, IL-6, BUN, LDH and D-dime can help clinicians identify patients with poor prognosis early.

Effect modification by statin use status on the association between fine particulate matter (PM2.5) and cardiovascular mortality.

BACKGROUND: Numerous studies have linked fine particulate matter (PM2.5) to increased cardiovascular mortality. Less is known how the PM2.5-cardiovascular mortality association varies by use of cardiovascular medications. This study sought to quantify effect modification by statin use status on the associations between long-term exposure to PM2.5 and mortality from any cardiovascular cause, coronary heart disease (CHD), and stroke. METHODS: In this nested case-control study, we followed 1.2 million community-dwelling adults aged ≥66 years who lived in Ontario, Canada from 2000 through 2018. Cases were patients who died from the three causes. Each case was individually matched to up to 30 randomly selected controls using incidence density sampling. Conditional logistic regression models were used to estimate odds ratios (ORs) for the associations between PM2.5 and mortality. We evaluated the presence of effect modification considering both multiplicative (ratio of ORs) and additive scales (the relative excess risk due to interaction, RERI). RESULTS: Exposure to PM2.5 increased the risks for cardiovascular, CHD, and stroke mortality. For all three causes of death, compared with statin users, stronger PM2.5-mortality associations were observed among non-users [e.g. for cardiovascular mortality corresponding to each interquartile range increase in PM2.5, OR = 1.042 (95% CI, 1.032-1.053) vs OR = 1.009 (95% CI, 0.996-1.022) in users, ratio of ORs = 1.033 (95% CI, 1.019-1.047), RERI = 0.039 (95% CI, 0.025-0.050)]. Among users, partially adherent users exhibited a higher risk of PM2.5-associated mortality than fully adherent users. CONCLUSIONS: The associations of chronic exposure to PM2.5 with cardiovascular and CHD mortality were stronger among statin non-users compared to users.

Mid-upper arm circumference predicts the risk of gestational diabetes in early pregnancy.

BACKGROUND: The present work aimed to assess the value of mid-upper arm circumference (MUAC) at 8 to 12 weeks in predicting the occurrence of gestational diabetes mellitus (GDM). METHODS: According to eligibility criteria, 328 women with singleton pregnancies who underwent routine antenatal check-ups at Qinhuangdao Maternal and Child Health Hospital from September 2017 to September 2020 were included. The patients were divided into the gestational diabetes mellitus (GDM) and non-GDM groups according to oral glucose tolerance test (OGTT) data from gestation weeks 24 to 28. Clinical data were compared between the two groups. Logistic regression analysis was performed to determine factors independently predicting GDM. Receiver operating characteristic (ROC) curve analysis was employed to analyze the value of MUAC in predicting the occurrence of GDM. The optimal cut-off points were calculated. RESULTS: In logistic regression analysis, pre-pregnancy weight, waist circumference, MUAC, UA, TG, and HDL-C independently predicted the occurrence of GDM (P < 0.05). MUAC retained statistical significance upon adjustment for various confounders (OR = 8.851, 95%CI: 3.907-20.048; P < 0.001). ROC curve analysis revealed good diagnostic potential for MUAC in GDM (AUC = 0.742, 95%CI: 0.684-0.800, P < 0.001), with a cut-off of 28.5 cm, sensitivity and specificity were 61% and 77%, respectively. CONCLUSION: Pregnant women with MUAC >28.5 cm are prone to develop GDM during pregnancy, indicating that MUAC as an important predictive factor of GDM in early pregnancy.

Prevalence of and factors associated with female child marriage in Indonesia.

Statistics from the 2018 National Social and Economic Survey revealed that one out of nine young females in Indonesia have been in female child marriage, and the prevalence remains high. Considering the serious consequences of female child marriage and that Sustainable Development Goal 5 on gender equality has targeted the elimination of female child marriage by 2030, a study concerning the prevalence and determinants of female child marriage needs to be conducted in Indonesia. In this paper, we examined the prevalence of and factors associated with female child marriage in Indonesia using binary logistic regression. We examined data from the Indonesia Demographic and Health Survey conducted in 2017. A sample of 9,333 young females aged 15-20 years was included in the study. Our analysis involved descriptive and binary logistic regression analysis. The results are presented in percentages and odds ratios (OR), with their respective confidence intervals. Our findings indicate that health insurance and sex of household head did not significantly influence female child marriage. The prevalence of female child marriage in Indonesia was quite high, reaching about 12.53%. Females with no education [OR = 76.448; (CI = 29.73-196.70)], not working [OR = 1.662; (CI = 1.41-1.94)], those with the poorest wealth index [OR = 3.215; (CI = 2.336-4.425)], those living in the east of Indonesia [OR = 1.451; (CI = 1.132-1.862)], and those living in rural areas [OR = 0.718; (CI = 0.609-0.844)] had the higher odds of experiencing female child marriage. Meanwhile, females with a secondary education level [OR = 16.296; (CI = 11.098-23.930)], those with a rich wealth index [OR = 1.940; (CI = 1.404-2.681)], and those living in the middle of Indonesia [OR = 1.263; (CI = 1.074-1.487)] were less likely to experience female child marriage. Educational background was the most significant factor influencing the high prevalence of female child marriage in Indonesia. Female empowerment through education as well as poverty alleviation were factors that could be strengthened to ensure that female child marriage is reduced or eliminated in Indonesia. Equality of access to information and better quality of education also need to be prioritized.