Objective To investigate the sleep status in children with autism spectrum disorder (ASD) and its relationship with executive function and neurodevelopment. Methods The medical records of 346 children with ASD in the hospital from April 2023 to January 2025 were retrospectively collected. The sleep status of children was investigated by Children’ s Sleep Habits Questionnaire (CSHQ). According to the score, the children were divided into good sleep group (CSHQ score<41 points, 189 cases) and sleep disorder group (CSHQ score≥41 points, 157 cases). The general data were compared between groups of children. Chinese version of Behavior Rating Inventory of Executive Function-Preschool Version (BRIEF-P) and developmental behavior assessment scale of children aged 0-6 years (Children's psychological scale-II) were used to analyze the relationship between sleep status and executive function and neurodevelopment in children with ASD. Results The CSHQ score of 346 children was (39.08±3.24) points, including 157 cases with CSHQ score≥41 points and 189 cases with CSHQ score<41 points. The proportion of severe previous medical history and executive function score in sleep disorder group were significantly higher than those in good sleep group, and the evaluation result of developmental quotient was lower than that in good sleep group (P<0.05). Logistic regression analysis showed that executive ability and neurodevelopment were closely related to sleep status in children with ASD (P<0.05). Spearman correlation analysis showed that sleep status in children with ASD was negatively correlated with executive function (r=-0.456, P<0.05), and was positively correlated with the developmental quotient (r=0.547, P<0.05). Conclusion The incidence rate of sleep disorder is high in children with ASD, and sleep status is closely related to executive function and neurodevelopment. Clinically, it is necessary to pay attention to the sleep problems in children with ASD, and take effective intervention measures to improve the sleep quality of children and promote the training of executive function and neurodevelopment.

Myasthenia gravis is an autoimmune disorder characterized by impaired neuromuscular transmission. Thymectomy is one of the therapeutic options for acetylcholine receptor antibody-positive myasthenia gravis patients. The quality of perioperative care is directly associated with surgical safety and patient outcomes. However, there is currently a lack of specialized nursing consensus or guidelines specifically addressing the care of these patients domestically or internationally. To promote the standardization and normalization of perioperative nursing care for myasthenia gravis patients undergoing thymectomy and to ensure treatment efficacy, a panel of 57 experts from relevant fields was convened. Based on evidence-based medicine and clinical practice experience, discussions were held on various aspects including condition assessment, nutritional support, medication management, and airway care, resulting in a consensus with 18 final recommendations by using the Delphi method through two rounds of expert consultation. This consensus aims to provide a scientific reference for the perioperative nursing care of myasthenia gravis patients undergoing thymectomy.

Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

Objective To investigate the impact of intraoperative red blood cell (RBC) transfusion volume on the postoperative oxygenation index in lung transplant recipients. Methods This retrospective study analyzed the clinical data of patients who underwent lung transplantation at Wuxi People's Hospital Affiliated to Nanjing Medical University from 2021 to 2023. Patients were divided into a non-severe primary graft dysfunction (PGD) group and a severe PGD group based on whether their postoperative oxygenation index was>200 mm Hg at 0, 24, and 48 h. General patient data and intraoperative RBC transfusion volumes were compared between the two groups. A binary logistic regression model was constructed to explore the effect size (OR and its 95%CI) of RBC transfusion volume on postoperative oxygenation status at different time points (0, 24, and 48 h). The area under the receiver operating characteristic curve was calculated to evaluate the model's diagnostic performance. Results A total of 351 patients were included (260 males, 91 females), with ages ranging from 20 to 77 years. The OR for the effect of intraoperative RBC transfusion on poor oxygenation was 1.486 (95%CI 0.982 to 2.248, P=0.061) at 0 h postoperatively, 3.111 (95%CI 1.793 to 5.399, P<0.001) at 24 h, and 1.583 (95%CI 1.026 to 2.442, P=0.038) at 48 h. This indicated that as time progressed, the postoperative oxygenation status of lung transplant recipients was affected by the intraoperative transfusion volume. Furthermore, an RBC transfusion volume>975 mLhad a significant impact on patient oxygenation at 24 and 48 h postoperatively. Conclusion The volume of intraoperative RBC transfusion has a significant impact on the oxygenation status at 24 and 48 h postoperatively. Intraoperative RBC transfusion volume is associated with the occurrence of severe PGD after lung transplantation. Controlling the volume of RBC transfusion during lung transplantation may help reduce the incidence of severe PGD.

Objective To analyze the clinical characteristics and risk factors of noninfectious fever after endovascular repair of aortic dilatation diseases, and to explore management strategies. Methods A retrospective analysis was conducted on the clinical data of patients who underwent endovascular aortic repair for aortic dilatation diseases from January 2021 to October 2023. Based on inclusion and exclusion criteria, the enrolled patients were divided into a febrile group and an afebrile group according to the presence of postoperative fever. Clinical data, including demographics and surgical details, were compared between the two groups. Multivariate logistic regression analysis was performed on indicators with P≤0.05 in the univariate analysis, and receiver operating characteristic (ROC) curves were generated to analyze the predictive value of risk factors for postoperative noninfectious fever. Results A total of 305 patients were included in the final analysis. Postoperative noninfectious fever occurred in 75.08% (229/305) of the patients, with 98.25% of cases occurring within the first two postoperative days. The febrile group (n=229) had a median age of 65.0 (IQR: 53.0, 73.0) years with 83.4% males, while the afebrile group (n=76) had a median age of 71.0 (IQR: 65.0, 76.7) years with 84.2% males. Univariate analysis showed that the age, prevalence of coronary heart disease, preoperative statin use, and prevalence of aortic aneurysm were significantly lower in the febrile group compared to the afebrile group. Logistic regression analysis indicated that age, surgical site, disease type, preoperative elevated body temperature, and stent type were significantly associated with noninfectious fever, while preoperative statin use was negatively correlated. ROC curve analysis demonstrated that age, surgical site, preoperative elevated body temperature, and stent type had significant predictive value for postoperative noninfectious fever (P<0.01). Conclusion Noninfectious fever is highly prevalent following aortic repair. The relationship between fever and infection should be comprehensively evaluated based on risk factors and changes in the patient's condition to promote the rational use of antibiotics.

Objective To explore whether there is a causal relationship between intestinal flora and esophageal cancer. Methods Summary statistics of intestinal flora and esophageal cancer were obtained from the Genome-wide Association Studies (GWAS) database. Five methods, including inverse variance weighted (IVW), weighted median estimation, Mendelian randomization (MR)-Egger regression, single mode, and weighted mode, were used for analysis, with IVW as the main analysis method. Sensitivity analysis was used to evaluate the reliability of MR results. Results In the IVW method, Oxalobacteraceae [OR=1.001, 95%CI (1.000, 1.002), P=0.023], Faecalibacterium [OR=1.001, 95%CI (1.000, 1.002), P=0.028], Senegalimassilia [OR=1.002, 95%CI (1.000, 1.003), P=0.006] and Veillonella [OR=1.001, 95%CI (1.000, 1.002), P=0.018] were positively correlated with esophageal cancer, while Burkholderiales [OR=0.999, 95%CI (0.998, 1.000), P=0.002], Eubacterium oxidoreducens [OR=0.998, 95%CI (0.997, 0.999), P=0.038], Romboutsia [OR=0.999, 95%CI (0.998, 1.000), P=0.048] and Turicibacter [OR=0.998, 95%CI (0.997, 0.999), P=0.013] were negatively correlated with esophageal cancer. Sensitivity analysis showed no evidence of heterogeneity, horizontal pleiotropy and reverse causality. Conclusion Oxalobacteraceae, Faecalibacterium, Senegalimassilia and Veillonella increase the risk of esophageal cancer, while Burkholderiales, Eubacterium oxidoreducens, Romboutsia and Turicibacter decrease the risk of esophageal cancer. Further studies are needed to explore how these bacteria affect the progression of esophageal cancer.

Objective: To analyze the association between intraoperative blood transfusion and adverse perinatal outcomes(a composite of maternal death, hepatic encephalopathy, etc) in patients with acute fatty liver of pregnancy (AFLP), identify independent risk factors for these outcomes, and develop and validate a risk prediction model for early identification of high-risk patients. Methods: Clinical data of 56 AFLP patients admitted to our hospital from January 2008 to January 2025 were retrospectively analyzed. The chi-square test was used to compare the incidence of adverse perinatal outcomes between the transfusion group and the non-transfusion group. Univariate and multivariate Firth-penalized logistic regression analyses were performed to identify independent predictors of adverse outcomes. Based on the identified independent risk factors, a combined prediction model was developed. Internal validation was performed using the Bootstrap method (1 000 resamplings) to assess the model′s generalizability. Model performance was evaluated using receiver operating characteristic(ROC) curves and calibration curves. Finally, a nomogram for predicting adverse perinatal outcomes in AFLP was constructed. Results: Overall, 57.1%(32/56) of the patients received blood product transfusion during the termination of pregnancy. Multivariate Firth-penalized logistic regression analysis showed that, given the limited sample size, intraoperative blood transfusion had no independent statistical effect on adverse outcomes (OR=0.812, 95%CI:0.133-3.698, P=0.797). Mediation analysis also revealed no significant indirect effect. The independent risk factors were decreased preoperative fibrinogen (OR=14.062, 95%CI:2.389-126.656, P=0.003), pregnancy with infection (OR= 4.536, 95%CI:1.143-22.107, P=0.031), and cesarean section (OR=8.691, 95%CI:1.321-90.081, P=0.023). The combined prediction model achieved an AUC of 0.881 (95% CI:0.793-0.969, P<0.001), indicating good discrimination. At the optimal cut-off value, the sensitivity was 65.6%, specificity 95.8%, positive predictive value 95.5%, and negative predictive value 67.6%. Internal validation by the Bootstrap method showed that the predictive model had good discrimination and no obvious overfitting. The calibration curve demonstrated that the model′s predicted risk was consistent with the actual observed risk. Based on this, an AFLP perinatal adverse outcome nomogram model was constructed. Conclusion: Under the limited sample size of this study, no independent statistical effect of intraoperative blood product infusion on adverse perinatal outcomes in AFLP patients was detected. A multivariate Firth-penalized logistic regression model incorporating decreased preoperative fibrinogen, pregnancy with infection, and cesarean delivery demonstrated good discrimination and calibration. The derived nomogram may serve as an exploratory tool for early risk stratification and proactive intervention.

[摘 要] 目的：探讨m6A调控因子在宫颈癌预后评估、免疫微环境特征及治疗反应中的作用，构建基于m6A调控因子的预后风险模型，并分析其与免疫浸润、药物敏感性及细胞间通信的关系。方法：基于TCGA和GEO数据库中宫颈鳞癌及腺癌（CESC）转录组数据，分析22个m6A调控因子的表达与突变情况；采用LASSO‑Cox回归构建m6A相关预后风险模型，并依据风险评分将患者分为高、低风险组。利用CIBERSORT和ESTIMATE算法评估两组免疫细胞浸润及微环境特征；通过oncoPredict预测抗肿瘤药物敏感性。整合单细胞转录组数据（E-MTAB-12305），采用CellChat分析细胞间通信网络。结果：共鉴定出12个在宫颈癌中差异表达的m6A调控因子。高风险组患者总生存期缩短（P < 0.05），免疫评分降低，且对紫杉醇、氟尿嘧啶、多柔比星等抗肿瘤药物敏感性较差（IC50较高）。单细胞分析显示宫颈癌组织中细胞间通信网络发生改变，其中T细胞与内皮/上皮细胞间的相互作用可能主要由CCL5‑ACKR1和MIF‑（CD74 + CXCR4）配体‑受体介导。在临床样本中，对关键的m6A调控因子进行mRNA和蛋白水平的验证，结果显示部分调控因子在宫颈癌组织中的表达水平高于正常宫颈组织（P < 0.05）。结论：m6A调控因子特征可有效预测宫颈癌患者预后，其风险评分与肿瘤免疫浸润、药物敏感性及细胞通信密切相关，为宫颈癌的预后分层及个体化治疗提供了新的分子依据。

Objective To analyze the risk factors of plastic bronchitis (PB) in children with severe mycoplasma pneumoniae pneumonia (SMPP) and construct a Nomogram model. Methods A total of 195 children with SMPP from April 2022 to April 2025 were selected and divided into the PB group and the non-PB group according to the occurrence of PB. Their clinical data were compared. Binary logistic regression was used to analyze the risk factors of PB in SMPP, and ROC was used to analyze the predictive ability of the model. The Nomogram prediction model was established using R-4.4.3 software, and the calibration curve and clinical decision curve were plotted for analysis. Results PB occurred in 66 cases (33.85%) (P < 0.05). The duration of fever, PIV, SII, D-D, LDH, and pleural effusion were independent risk factors for PB in SMPP (OR=6.997, 1.016, 1.008, 70.202, 1.025, 32.323, P < 0.05). Based on this, the PB prediction model for SMPP occurrence established had a good goodness of fit (P > 0.05), and the area under the ROC curve was 0.888 (95%CI : 0.878-0.898). The average absolute error of Bootstrap repeated sampling 1000 times was 0.021, and the model C-index was 0.889 (95%CI: 0.888-0.991). The predicted probability of the model has a good consistency with the actual probability, with good accuracy, and the Brier score is 0.035 (95%CI: 0.015-0.054). Good clinical benefits can be achieved when the threshold probability is between 0.01 and 0.99. Conclusion The Nomogram model of PB in children with SMPP constructed based on factors such as fever duration, PIV, SII, D-D, LDH, and pleural effusion has good discrimination and accuracy, and can provide a reference for the prevention of PB.

Objective: To explore the correlation and lag effects of environmental factors on pediatric respiratory disease visits at hospital, so as to provide scientific basis for disease prediction and optimizing clinical diagnosis and treatment. Methods: Data from 503 889 pediatric respiratory disease outpatient and emergency visits a central hospital in Minhang District of Shanghai between 2017 and 2019, along with concurrent meteorological data were collected. A distributed lag non-linear models (DLNM) was constructed to explore the specific relationship between pediatric respiratory disease consultations and various environmental factors and to quantify the cumulative lag effects of environmental factors on respiratory disease consultations. Results: Among the environmental factors, temperature, fine particulate matter (PM 2.5 ), inhalable particulate matter (PM 10 ), nitrogen dioxide (NO 2), and sulfur dioxide (SO 2) were associated with pediatric respiratory disease visits. After adjusting for temperature, PM 2.5 and PM 10 concentrations did not show significant immediate or lag effects. The relative risk (RR) of pediatric respiratory disease visits increased with rising NO 2 concentrations. When NO 2 concentration ≥55 μg/m 3, significant immediate and lagged effects (lag 3, 5, and 7 days) were observed. The RR values were 1.05, 1.13, 1.17, and 1.21( P <0.05). The RR values showed an inverted “U” shaped relationship with SO 2 concentrations. When SO 2 concentration ≥5 μg/m 3, significant lagged effects (lag 3, 5, and 7 days) were observed. The RR values were 1.03 , 1.03, and 1.04 ( P <0.05). Conclusion High concentrations of NO 2 and SO 2 increase the risk of pediatric respiratory disease visits, with observable lag effects.