AIM:To investigate the visual development of children under 6 years old in Wuhan, and provide evidence-based support for the formulation and optimization of regional policies for children's eye health care.METHODS:Suresight refractive screener was applied to rapid refractive status examination in 4 989 preschool children under 6 years old in Wuhan City, with results determined according to the manufacturer's age-specific referral criteria. All screened pre-school children completed vision screening and comprehensive ophthalmic examination.RESULTS: A total of 4 989 children under 6 years old were screened out, including 2 641 males and 2 348 females. They were divided into 6 groups according to age: 426 aged from 6-month to 1-year-old, 903 aged >1 to 2 years old, 1 078 aged >2 to 3 years old, 442 aged >3 to 4 years old, 808 aged >4 to 5 years old, and 1 332 aged >5 to 6 years old. The abnormal rate in the 6-month to 1-year-old group was 44.60%, in the >1 to 2 years old group was 26.02%, in the >2 to 3 years old group was 15.58%, in the >3 to 4 years old group was 10.86%, in the >4 to 5 years old group was 21.91%, in the >5 to 6 years old group was 23.27%, and the total refractive abnormal rate for children aged 6 mo to 6 years old was 22.61%. The refractive abnormal rate generally showed a decreasing trend with increasing age(P<0.001); the refractive abnormal rate in boys aged 6-month to 6 years old was 12.33%, and in girls was 10.28%, with no statistically significant difference in the abnormal rate between boys and girls(P>0.05); among children aged 6-month to 6 years old, the abnormal rate of single-eye myopia was 0.98%, of single-eye hyperopia was 5.41%, of single-eye astigmatism was 9.92%, of binocular myopia was 0.98%, of binocular hyperopia was 2.79%, and of binocular astigmatism was 8.14%; the prevalence of astigmatism in children aged 6-month to 1-year-old was 40.38%, in those aged >1 to 2 years old was 19.82%, in those aged >2 to 3 years old was 12.34%, in those aged >3 to 4 years old was 9.05%, in those aged >4 to 5 years old was 18.81%, and in those aged >5 to 6 years old was 16.89%; the prevalence of astigmatism in children aged 6-month to 6 years old was 18.06%. The abnormal rate of astigmatism in the four age groups ranging from 6-month to 4 years old decreased continuously with age(P<0.001). There was no statistically significant difference in the abnormal rate of astigmatism between the >4 to 5 years old group and the >5 to 6 years old group(P>0.05).CONCLUSION:Refractive error has become a common eye disease among preschool children. Through early vision screening, establishing a systematic refractive management file, and early intervention, the best treatment period can be seized to avoid missing it and causing adverse consequences.

ObjectiveTo investigate the independent predictive factors for 90-day mortality in patients with acute-on-chronic liver failure （ACLF）， to establish a risk predictive model， and to assess its predictive efficacy in comparison with MELD， MELD-Na， MELD 3.0， and COSSH-ACLF Ⅱ. MethodsA retrospective analysis was performed for the clinical data of 394 patients with ACLF who were admitted to The Affiliated Hospital of Inner Mongolia Medical University and Hohhot Second Hospital from July 2018 to July 2024， and general information and laboratory markers on admission were collected from all patients. The independent-samples t test or the Mann-Whitney U test was used for comparison of quantitative data between two groups， and the chi-square test or the adjusted chi-square test was used for comparison of qualitative data between two groups. The LASSO regression analysis was used to identify related variables， and the multivariate logistic regression analysis was used to establish a predictive model and generate a nomogram. The receiver operating characteristic （ROC） curve， the area under the ROC curve （AUC）， calibration curve， and clinical decision curve were used to assess the performance of the model. ResultsA total of 394 patients with ACLF were included in this study， with 136 patients in the training set， 58 in the internal validation set， and 200 in the external validation set. The cohort had a mean age of 52.9±11.7 years， among whom male patients accounted for 72.84% （287/394）， the patients with HBV infection accounted for 22.33% （88/394）， the patients with alcohol-related causes accounted for 45.94% （181/394）， and the patients with other causes （including drug-induced and autoimmune diseases） accounted for 31.73% （125/394）. The overall 90-day mortality rate was 27.41% （108/394）. The multivariate logistic regression analysis showed that diabetes （odds ratio ［OR］= 5.831， 95% confidence interval ［CI］： 1.587 — 21.424， P=0.008）， cystatin C （Cys-C） （OR=2.984， 95%CI： 1.501 — 5.933， P=0.002）， and spontaneous peritonitis （SBP） （OR=5.692， 95%CI： 2.150 — 15.071， P<0.001） were independent risk factors， and a nomogram was generated based on these factors. This model had an AUC of 0.836 in the training set， 0.881 in the internal validation set， and 0.878 in the external validation set， showing a good discriminatory ability. The calibration curve showed a good degree of fitting， with a relatively high net clinical benefit. The subgroup analysis based on etiology showed that the model had an AUC of 0.850 in the patients with HBV infection， 0.858 in the patients with alcohol-induced ACLF， and 0.908 in the patients with other etiologies， indicating that the model had a good discriminatory ability across the populations with different etiologies. Compared with traditional scores， the model （AUC=0.836） had a significantly better predictive value than MELD （AUC=0.619， Z=3.197， P=0.001）， MELD-Na （AUC=0.651， Z=2.998， P=0.003）， MELD 3.0 （AUC=0.601， Z=3.682， P<0.001）， and COSSH-ACLF Ⅱ （AUC=0.719， Z=2.396， P=0.017） alone. ConclusionDiabetes， SBP， and Cys-C are independent risk factors for 90-day mortality in patients with ACLF. Compared with MELD， MELD-Na， MELD 3.0， and COSSH-ACLF Ⅱ scores， this model has a higher predictive value for 90-day prognosis in patients with ACLF and is suitable for patients with ACLF caused by various etiologies.

Objective To compare the radiation doses to adult patients from two types of computed tomography (CT) scanners at a hospital in Shanghai City, analyze the radiation dose to patients and impact factors, and provide data for reducing radiation dose in CT examinations. Methods Radiation parameters and radiation doses to adult patients from two types of CT scanners were investigated. Adult patients aged 15-<40 years and 40-70 years who underwent head, chest, abdomen, and lumbar spine CT examinations were randomly selected to collect their scanning data. Effective doses for different scanning regions and age groups were estimated using conversion formulas and compared. Results The CT scanning data of 160 adult patients from each type of CT scanners were collected. For scanner A, the 75th percentiles of volume CT dose index (CTDI_vol) of the head, chest, abdomen, and lumbar spine were 45, 4, 7, and 6 mGy; the 75th percentiles of dose-length product (DLP) were 726, 143, 373, and 179 mGy·cm; the 75th percentiles of effective dose were 1.5, 2.0, 5.6, and 2.7 mSv. For scanner B, the 75th percentiles of CTDI_vol of the head, chest, abdomen, and lumbar spine were 54, 6, 9, and 15 mGy; the 75th percentiles of DLP were 755, 215, 502, and 428 mGy·cm; the 75th percentiles of effective dose were 1.6, 3.0, 7.4, and 6.4 mSv. Conclusion The 75th percentiles of the CTDI_vol and DLP of all scanning regions were lower than the diagnostic reference levels for both types of scanners. Except for head DLP, scanner A demonstrated significantly lower CTDI_vol and DLP values than scanner B across all regions. The 75th percentiles of effective dose for head, chest, and abdomen examinations on both scanners did not exceed the corresponding values reported for patients in Hangzhou City.

Background Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals characterized by environmental persistence and have been ubiquitously detected in pregnant women. Although existing evidence suggests that PFAS may exert endocrine-disrupting effects, evidence remains limited regarding the associations of individual legacy and emerging PFAS congeners, as well as PFAS mixtures, with fetal hormonal homeostasis. Objective Based on the Jiashan Birth Cohort in China, to investigate the associations between maternal plasma concentrations of legacy and emerging PFAS in the second trimester and levels of multiple hormones in fetal cord blood. Methods A total of 336 women in the second trimester from the Jiashan Birth Cohort were enrolled. Concentrations of 53 legacy and emerging PFAS were measured in maternal plasma, and levels of eight key hormones were determined in fetal cord blood. Multiple linear regression, restricted cubic spline, and Bayesian kernel machine regression models were used to examine the linear, nonlinear, and joint associations of individual PFAS and PFAS mixtures with fetal cord blood hormone levels. Results Maternal plasma concentrations of perfluorononanoic acid, perfluorohexane sulfonic acid, perfluorooctanesulfonic acid, and 8:2 chlorinated perfluoroether sulfonic acid were positively associated with cord blood levels of insulin-like growth factor 1 (IGF1), with β values of 0.040, 0.050, 0.040, and 0.030, respectively (all P<0.05). In contrast, perfluoroheptanoic acid was negatively associated with prolactin levels (β=−0.060, P<0.01). Restricted cubic spline models revealed a nonlinear dose–response relationship between perfluorobutane sulfonic acid and growth hormone (likelihood ratio test P=0.045), with a positive association in the intermediate concentration interval (β=0.261, P=0.010) that turned negative at higher concentrations (β=−0.425, P=0.048), as well as a nonlinear trend between 6:2 fluorotelomer sulfonic acid and prolactin (likelihood ratio test P=0.074). Bayesian kernel machine regression analysis indicated a negative trend between PFAS mixture exposure and cord blood prolactin levels. Conclusion Maternal PFAS exposure in the second trimester is associated with higher insulin-like growth factor 1 levels and lower prolactin levels in fetal cord blood. Prolactin appears to be consistently associated with both individual PFAS congeners and PFAS mixtures. These findings suggest that maternal PFAS exposure may affect fetal endocrine homeostasis by disrupting the hypothalamic-pituitary-prolactin regulatory axis.

ObjectiveTo investigate the association between sarcopenia and short-term prognosis in patients with acute-on-chronic liver failure （ACLF）， to assess the value of Model for End-Stage Liver Disease （MELD）， MELD combined with serum sodium concentration （MELD-Na）， MELD 3.0， and Chinese Group on the Study of Severe Hepatitis B （COSSH）-ACLF Ⅱ score in predicting the 90-day prognosis of ACLF patients， and to analyze the predictive gain of sarcopenia over traditional prognostic scoring models. MethodsA retrospective study was conducted among 219 patients with ACLF who were hospitalized in The Affiliated Hospital of Inner Mongolia Medical University， No. 2 Hospital of Hohhot， Hohhot First Hospital， and Inner Mongolia People’s Hospital from July 2018 to July 2024. L3 skeletal muscle index （L3-SMI） was measured and calculated based on abdominal computed tomography images， and sarcopenia was diagnosed based on L3-SMI. According to 90-day prognosis， the patients with ACLF were divided into survival group with 124 patients and death group with 95 patients. The chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups； the independent samples t-test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups. The multivariate Cox regression analysis （stepwise backward approach） was used to identify independent risk factors for 90-day mortality in ACLF patients. The Kaplan-Meier method was used for survival analysis， and the Log-rank test was used for comparison between groups. The receiver operating characteristic curve was plotted to evaluate the predictive performance of each model， and the DeLong test， bootstrap internal validation， net reclassification improvement （NRI）， and integrated discrimination improvement （IDI） were used to assess the predictive gain of sarcopenia. ResultsThe multivariate Cox regression analysis showed that presence of sarcopenia （hazard ratio ［HR］=3.385， 95% confidence interval ［CI］： 1.722 — 6.657， P<0.05）， older age （HR=1.036， 95%CI： 1.017 — 1.056， P<0.05）， elevated alkaline phosphatase （HR=1.006， 95%CI： 1.004 — 1.009， P<0.05）， elevated total bilirubin （HR=1.003， 95%CI： 1.001 — 1.005， P<0.05）， elevated potassium （HR=1.581， 95%CI： 1.160 — 2.155， P<0.05）， elevated serum creatinine （HR=1.015， 95%CI： 1.007 — 1.024， P<0.05）， and prolonged prothrombin time （HR=1.035， 95%CI： 1.015 — 1.055， P<0.05） were independent risk factors for 90-day mortality in ACLF patients， while elevated albumin （HR=0.885， 95%CI： 0.837 — 0.935， P<0.05） was an independent protective factor against 90-day mortality. MELD， MELD-Na， MELD 3.0， and COSSH-ACLF Ⅱ scores had an area under the ROC curve （AUC） of 0.569， 0.570， 0.632， and 0.659， respectively， for predicting the 90-day prognosis of ACLF patients， suggesting that these scores had unsatisfactory performance； after they were respectively combined with sarcopenia， the AUC was increased to 0.702， 0.687， 0.723， and 0.728， respectively. The DeLong test， NRI， and IDI analyses showed the combined models had significantly better predictive performance （all P<0.05）. ConclusionSarcopenia is an independent risk factor for 90-day mortality in patients with ACLF. Traditional scoring models have limited predictive performance for 90-day prognosis in ACLF patients， and the combination with sarcopenia significantly improves predictive value， suggesting that sarcopenia can be used as an important supplementary indicator for prognostic evaluation of ACLF in clinical practice.

Objective:This study investigated the awareness and consumption of Trogia venenata among populations in regions affected by Yunnan unexplained sudden death (YUSD). The findings aim to support etiological research on YUSD and contribute to the formulation of preventive measures against Trogia venenata poisoning. Methods:This study was a case-control study. From 2018 to 2021, surveys were conducted in 90 villages across 25 counties within YUSD-affected areas in Yunnan Province. Households with YUSD cases were designated as case households, whereas households without YUSD cases served as controls, ande were selected through convenience sampling at a 3:1 ratio. An enhanced questionnaire was designed to collect information on the consumption of Trogia venenata, and symptoms following consumption. Frequency data were presented as percentages, and group comparisons were conducted using χ 2 tests or Fisher’s exact tests. Results:A total of 711 questionnaires were collected (response rate: 100%), comprising 175 case households and 536 control households. Trogia venenata was present in 80.82% of the villages surveyed. Among the 711 households, 15.89% reported consuming Trogia venenata, primarily through stir-frying (53.10%), followed by boiling (29.20%), boiling and stir-frying (15.93%), and steaming (1.77%). Most households (94.69%) consumed fresh fruiting bodies, with 69.02% consuming them fewer than three times annually. The consumption rates were higher among the case households than among the control households. Of the 113 households with a history of Trogia venenata consumption, 35.40% reported symptoms such as nausea, vomiting, and limb soreness. The proportions of affected families in each group were compared according to their source, cooking method, fruiting body status and consumption frequency. The proportion of affected families with high consumption frequency (≥3 times/year) was higher than that with low consumption frequency (<3 times/year). Among 421 YUSD cases, 63 cases (14.96%) had a history of Trogia venenata consumption before death, with 43 cases showing symptoms within the longest known latency period (14 d) for poisoning by this mushroom. Conclusions:Trogia venenata is prevalent in 80.82% of YUSD-affected regions, with 16.67% of the population reporting its consumption, predominantly as fresh fruiting bodies prepared by stir-frying or boiling. Confirmed Trogia venenata consumption was identified in 14.96% of YUSD cases, suggesting that mushroom poisoning is a significant risk factor for YUSD. Ongoing health education and interventions are critical for mitigating the risk of Trogia venenata poisoning.

Objective To investigate the association between obstructive sleep apnea hypopnea syndrome （OSAHS） and white matter lesions （WMLs）. Methods A total of 91 patients who attended Department of Neurology and Department of Epilepsy and Sleep Disorders in The Second Affiliated Hospital of Harbin Medical University from June 2019 to December 2020 and met the diagnostic criteria for WMLs were enrolled as WMLs group， and 61 patients without WMLs were enrolled as control group. All subjects underwent brain MRI and PSG examinations， and related data were collected， including demographic data， past history， personal history， laboratory examination， and imaging findings. Results The WMLs group had a prevalence rate of OSAHS of 92.3% and an AHI of （32.85±19.86） events/hour on PSG， which were significantly higher than those in the control group （P<0.05）. The Spearman rank correlation analysis showed a strong positive correlation between WMLs severity and OSAHS severity（r=0.602 52，P<0.0001）. Conclusion The WMLs group is more susceptible to OSAHS than the control group， and the severity of WMLs is positively correlated with the severity of OSAHS.

Objective To quantitatively assess the association of short-term exposure to polycyclic aromatic hydrocarbons (PAHs) in ambient fine particulate matter (PM2.5) with residents mortality. Methods A time-stratified case-crossover study was conducted from 2020 to 2022 among 10606 non-accidental residents by using the Guangzhou Cause of Death Surveillance System in Conghua District, Guangzhou. Exposure levels of PAHs in PM_2.5 and meteorological data during the study period were obtained from the Center for Disease Control and Prevention in Conghua District and the China Meteorological Administration Land Data Assimilation System (CLDAS-V2.0), respectively. Conditional Poisson regression model was used to estimate the exposure-response association between PAHs and the mortality risk. Results Fluoranthene, chrysene, benzo[k]fluoranthene, benzo[a]pyrene, and indeno[1,2,3-cd]pyrene were significantly associated with an increased risk of mortality. For every one interquartile range increase in exposure levels, the non-accidental mortality risks increased by 8.33% (95% CI: 1.80%, 15.27%), 4.67% (95% CI: 1.86%, 7.57%), 6.07% (95% CI: 2.08%, 10.21%), 4.62% (95% CI: 1.85%, 7.47%), and 4.70% (95% CI: 0.53%, 9.03%), respectively. The estimated non accidental deaths attributable to exposure to fluoranthene, chrysene, benzo[k]fluorine, benzo[a]pyrene and indine[1,2,3-cd]pyrene were 5.91%, 6.08%, 6.51%, 6.46%, and 4.21%, respectively. Conclusions Short-term exposure to PAHs in PM_2.5, including fluoranthene, chrysene, benzo[k]fluoranthene, benzo[a]pyrene and indine[1,2,3-cd]pyrene, was significantly associated with an increased risk of mortality among residents.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Objective:To evaluate the clinical value of an obstetric intelligent assistant in predicting postpartum hemorrhage (PPH) after vaginal delivery.Methods:This retrospective cohort study included 4 832 women who delivered vaginally at ≥26 weeks of gestation at the Third Affiliated Hospital, Guangzhou Medical University between May 2023 and April 2025. Participants were categorized into PPH (382 cases, blood loss ≥500 ml within 24 h after delivery) and non-PPH groups (4 450 cases). Using traditional statistical methods combined with machine learning approaches, including support vector machines and extreme gradient boosting, supplemented with deep learning techniques, we developed a novel artificial neural network model—the obstetric intelligent assistant. This model provides a refined classification of PPH occurrence and estimated blood loss volume. The obstetric intelligent assistant integrates 70 antenatal and intrapartum risk factors through hospital information system interfacing to generate visualized risk probability outputs. Predictive performance was compared between the obstetric intelligent assistant and four conventional prediction tools (Chinese Labor Room Traffic Light System; Association of Women's Health, Obstetric and Neonatal Nurses; American College of Obstetrics and Gynecology Safe Motherhood Initiative; and California Maternal Quality Care Collaborative prediction tools) using receiver operating characteristic curve.Results:(1) For antenatal prediction, the obstetric intelligent assistant achieved an area under the curve of 0.826 (95% CI: 0.774-0.838), with sensitivity of 0.794 and specificity of 0.712, while the four conventional prediction tools showed area under the curve ranging from 0.569 to 0.586. (2) For intrapartum prediction, the obstetric intelligent assistant achieved an area under the curve of 0.786 (95% CI: 0.751-0.820), with sensitivity of 0.837 and specificity of 0.762, whereas the conventional tools showed area under the curve between 0.600 and 0.613. Conclusion:The obstetric intelligent assistant demonstrates superior performance in predicting PPH compared to conventional prediction tools.