Objective To investigate the association of sleep disorders with the development and progression of nonalcoholic fatty liver disease(NAFLD).Methods A total of 1 868 participants from the health examination cohort and fatty liver cohort of Beijing Friendship Hospital from June 2022 to June 2023 were enrolled as subjects.Related data were collected from all subjects,including age,sex,education level,chronic medical history,and biochemical parameters,and all subjects completed Pittsburgh Sleep Quality Index(PSQI)scale independently.According to the diagnostic criteria,the subjects were divided into non-NAFLD group with 1 122 subjects and NAFLD group with 746 subjects,and according to the stage of progression,the patients in the NAFLD group were further divided into simple fatty liver group(SFL group with 624 subjects)and nonalcoholic steatohepatitis(NASH)group with 122 subjects.A one-way analysis of variance or the Kruskal-Wallis H test was used for comparison of continuous data between three groups.The chi-square test was used for comparison of categorical data between the three groups.The binary Logistic regression analysis was used to investigate the association between sleep factors and NAFLD,and the multinomial Logistic regression analysis was used to investigate the association between sleep factors and the different stages of NAFLD;two multivariate models were constructed for adjustment of potential confounding factors,i.e.,an age-sex adjustment model and a multivariate adjustment model,and the multivariate adjustment model adjusted the factors of age,sex,education level,smoking,diabetes,hypertension,body mass index(BMI),triglyceride(TG),and high-density lipoprotein cholesterol(HDL-C).Results There were significant differences in age,sex,BMI,education level,smoking,diabetes,hypertension,alanine aminotransferase,TG,and HDL-C between the non-NAFLD,SFL,and NASH groups(all P<0.05).There were also significant differences between the three groups in the total score of PSQI scale and the proportion of subjects with a score of 0—3 points for the 7 sleep components(all P<0.05).The multivariate adjustment model showed no significant association between sleep disorders and SFL,while long sleep latency(odds ratio[OR]=4.04,95%confidence interval[CI]:2.33—7.03,P<0.001),short sleep duration(OR=3.53,95%CI:1.83—6.82,P<0.001),and severe sleep disorders(OR=2.96,95%CI:1.48—5.93,P=0.002)were closely associated with the risk of NASH.Conclusion Overall sleep condition and its components of sleep disorders are not significantly associated with the simple fatty liver;however,long sleep latency,short sleep duration,and severe sleep disorders can increase the risk of NASH,which should be taken seriously in clinical practice.

Chimeric antigen receptor (CAR)-T cell therapy has achieved remarkable success in the treatment of hematological malignancies. Based on the immunomodulatory capability of CAR-T cells, efforts have turned toward exploring their potential in treating autoimmune diseases. Bibliometric analysis of 210 records from 128 academic journals published by 372 institutions in 40 countries/regions indicates a growing number of publications on CAR-T therapy for autoimmune diseases, covering a range of subtypes such as systemic lupus erythematosus, multiple sclerosis, among others. CAR-T therapy holds promise in mitigating several shortcomings, including the indiscriminate suppression of the immune system by traditional immunosuppressants, and non-sustaining therapeutic levels of monoclonal antibodies due to inherent pharmacokinetic constraints. By persisting and proliferating in vivo, CAR-T cells can offer a tailored and precise therapeutics. This paper reviewed preclinical experiments and clinical trials involving CAR-T and CAR-related therapies in various autoimmune diseases, incorporating innovations well-studied in the field of hematological tumors, aiming to explore a safe and effective therapeutic option for relapsed/refractory autoimmune diseases.

Objective To explore the clinical manifestations,endoscopic findings,histopathological changes,treatment,and prognosis of eosinophilic gastrointestinal disease(EGID)in children,with the aim of enhancing awareness among pediatricians about this condition.Methods Data of 267 children with EGID were prospectively collected from January 2019 to July 2022 at Jiangxi Children's Hospital,Hunan Children's Hospital,and Henan Children's Hospital.The age of onset,symptoms,physical signs,laboratory examination results,endoscopic findings,histopathological changes,and treatment outcomes were observed.Results Among the 267 children with EGID,the majority had mild(164 cases,61.4% )or moderate(96 cases,35.6% )clinical severity.The disease occurred at any age,with a higher prevalence observed in school-age children(178 cases).The main symptoms in infants were vomiting and hematemesis,while in toddlers,vomiting and bloody stools were prominent.Abdominal pain and vomiting were the primary symptoms in preschool and school-age children.Nearly half(49.4% )of the affected children showed elevated platelet counts on hematological examination,but there was no significant difference in platelet counts among children with mild,moderate,and severe EGID(P>0.05).Endoscopic findings in EGID children did not reveal significant specificity,and histopathological examination showed no specific structural damage.Among them,85.0% (227 cases)received acid suppression therapy,34.5% (92 cases)practiced dietary avoidance,20.9% (56 cases)received anti-allergic medication,and a small proportion(24 cases,9.0% )were treated with prednisone.Clinical symptoms were relieved in all patients after treatment,but three cases with peptic ulcers experienced recurrence after drug discontinuation.Conclusions Mild and moderate EGID are more common in children,with no specific endoscopic findings.Dietary avoidance,acid suppression therapy,and anti-allergic medication are the main treatment methods.The prognosis of EGID is generally favorable in children.[Chinese Journal of Contemporary Pediatrics,2024,26(2):139-144]

OBJECTIVE: To analyze the clinical features and prognosis of patients with Castleman's disease (CD) and improve the diagnosis and treatment of CD. METHODS: Clinical data of patients diagnosed with CD by pathological biopsy in Gansu Provincial Hospital from January 2009 to November 2020 were retrospectively analyzed. According to clinical classification, the patients were divided into two groups: UCD (unicentric CD) group (n=20) and MCD (multicentric CD) group (n=9). The clinical manifestations, laboratory examination, treatment regimens, pathological examination and follow-up data were statistically analyzed. RESULTS: There were no significant differences in average age and gender ratio between UCD group and MCD group. In UCD patients, 80.0% were hyaline vascular type, and 20.0% were plasma cell type. In MCD patients, 33.3% were hyaline vascular type, 55.6% were plasma cell type, and 11.1% were mixed type. There was significant difference in pathological classification between the two groups (P=0.039). The UCD patients usually presented asymptomatic single lymph node enlargement with mild clinical symptoms, while the MCD patients were characterized by multiple superficial and deep lymph node enlargement throughout the body. The incidences of asthenia, splenomegaly, serous effusion in MCD group were higher than those in UCD group (P<0.05). Meanwhile, the incidences of anemia, hypoproteinemia, increased ESR, elevated serum globulin and elevated β₂-microglobulin were significantly higher than those in UCD group too (P<0.05). There was no significant difference in the incidences of abnormal WBC, PLT and elevated LDH between the two groups (P>0.05). Among 20 patients with UCD, 13 cases reached complete remission (CR), 1 case achieved partial remission (PR). Among 9 patients with MCD, 3 cases received CR and 4 cases received PR. CONCLUSION Patients with CD requires pathological examination for diagnosis. Patients with UCD show mild clinical symptoms, good surgical treatment effect and good prognosis. Patients with MCD have diversified clinical manifestations and relatively poor prognosis, and these patients require comprehensive treatment.
Humans ; Castleman Disease/therapy* ; Retrospective Studies ; Prognosis ; Splenomegaly ; Anemia

OBJECTIVES: To investigate the risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture and establish a nomogram model for predicting the risk of neonatal asphyxia. METHODS: A retrospective study was conducted with 613 cases of neonatal asphyxia treated in 20 cooperative hospitals in Enshi Tujia and Miao Autonomous Prefecture from January to December 2019 as the asphyxia group, and 988 randomly selected non-asphyxia neonates born and admitted to the neonatology department of these hospitals during the same period as the control group. Univariate and multivariate analyses were used to identify risk factors for neonatal asphyxia. R software (4.2.2) was used to establish a nomogram model. Receiver operator characteristic curve, calibration curve, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the model for predicting the risk of neonatal asphyxia, respectively. RESULTS: Multivariate logistic regression analysis showed that minority (Tujia), male sex, premature birth, congenital malformations, abnormal fetal position, intrauterine distress, maternal occupation as a farmer, education level below high school, fewer than 9 prenatal check-ups, threatened abortion, abnormal umbilical cord, abnormal amniotic fluid, placenta previa, abruptio placentae, emergency caesarean section, and assisted delivery were independent risk factors for neonatal asphyxia (P<0.05). The area under the curve of the model for predicting the risk of neonatal asphyxia based on these risk factors was 0.748 (95%CI: 0.723-0.772). The calibration curve indicated high accuracy of the model for predicting the risk of neonatal asphyxia. The decision curve analysis showed that the model could provide a higher net benefit for neonates at risk of asphyxia. CONCLUSIONS The risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture are multifactorial, and the nomogram model based on these factors has good value in predicting the risk of neonatal asphyxia, which can help clinicians identify neonates at high risk of asphyxia early, and reduce the incidence of neonatal asphyxia.
Infant, Newborn ; Humans ; Male ; Pregnancy ; Female ; Nomograms ; Retrospective Studies ; Cesarean Section ; Risk Factors ; Asphyxia Neonatorum/etiology*

Humans ; Multiple Myeloma/genetics* ; Neoplasm, Residual/diagnosis* ; Flow Cytometry ; High-Throughput Nucleotide Sequencing

Objective To explore the risk factors for intracranial infection in patients after neurosurgery,con-struct and validate a Nomogram prediction model.Methods Data of 978 patients who underwent neurosurgery in a hospital in Nanjing from January 1,2019 to December 31,2022 were retrospectively analyzed.Independent risk fac-tors were screened through logistic univariate and multivariate analyses.Modeling variables were screened through Lasso regression.A Nomogram model was constructed and internally validated by logistic regression.Effectiveness of the model was evaluated with receiver operating characteristic(ROC)curve,calibration curve and decision curve.Results Among 978 patients underwent neurosurgery,293 had postoperative intracranial infection,with an inci-dence of healthcare-associated infection of 29.96％.There was no significant difference in age,gender,proportion of coronary heart disease,cerebral infarction,diabetes and hypertension between the infected group and the non-in-fected group(all P＞0.05).Multivariate logistic analysis showed that postoperative intracranial hypertension,fe-ver,increased neutrophil percentage in blood routine examination,turbid cerebrospinal fluid,positive Pan's test,decreased glucose concentration,abnormal ratio of cerebrospinal fluid/serum glucose,positive microbial culture,absence of indwelling external ventricular drainage tubes,presence of indwelling lumbar cistern drainage tubes,use of immunosuppressive agents,and long duration of surgery were independent risk factors for postoperative intracra-nial infection in patients who underwent neurosurgery(all P＜0.05).Fifteen variables were screened out through Lasso regression.Fourteen variables were finally included for modeling after collinear screening,missing data impu-tation(random forest method)and checking pairwise interaction items.A Nomogram prediction model was con-structed,with the area under ROC curve,sensitivity,specificity,and accuracy of 0.885,0.578,0.896,and 0.704,respectively.Internal validation of the model was conducted.The modeling and validation groups presented similar effects.The calibration curve and decision curve also indicated that the model had good predictive efficacy.Conclusion The constructed Nomogram prediction model for postoperative intracranial infection after neurosurgery is scientific,and the prediction indicators are easy to obtain.The model presents with high stability,reliability,and application value,thus can provide reference for the assessment of postoperative intracranial infection after neuro-surgery.

Objective: To analyze the clinical characteristics, treatment response, and prognosis of newly diagnosed symptomatic multiple myeloma (MM) patients with systemic light chain amyloidosis (AL) . Methods: The clinical data of 160 patients with newly diagnosed MM treated at the First Affiliated Hospital of Soochow University from January 1, 2017 to October 31, 2018, were retrospectively analyzed. According to the histopathological biopsy results of bone marrow, skin, and other tissues, the patients were divided into two groups according to whether amyloidosis was combined or not, namely, the MM+AL group and the MM group. The clinical characteristics and treatment responses of the two groups were compared. Results: Among the 160 patients with newly diagnosed MM, there were 42 cases in the MM+AL group and 118 cases in the MM group. In terms of clinical features, the involved light chain and non-involved light chain (dFLC) in the MM+AL group was significantly higher than that in the MM group (P=0.039) . After induction treatment, the MM+AL group had a higher overall response rate (85.7%vs 79.7%, P<0.05) and higher excellent partial response (76.2%vs 55.1%, P<0.05) . After a median follow-up of 26 (0.25-41) months, there was no significant difference in the progression free survival and overall survival (OS) between the two groups (P>0.05) . The OS of patients in autologous hematopoietic stem cell transplantation group was better than that in non transplantation group (P<0.05) .The prognosis of patients with cardiac involvement in the MM+AL group was significantly worse than that in the MM group and MM+AL group without cardiac involvement (P<0.001) , with a median OS of only 13 months. Conclusion: The differential diagnosis between the MM+AL and MM groups requires histopathology, particularly for patients with significantly increased dFLC. The overall remission rate of patients in MM+AL group after 4 courses of induction chemotherapy was higher than that in MM group. The prognosis of patients with cardiac involvement in MM+AL group was poor.
Amyloidosis/diagnosis* ; Humans ; Immunoglobulin Light Chains ; Immunoglobulin Light-chain Amyloidosis/therapy* ; Multiple Myeloma/therapy* ; Prognosis ; Retrospective Studies

Objective: To introduce and compare four analysis methods of multiple parallel mediation model, including pure regression method, method based on inverse probability weighting, extended natural effect model method and weight-based imputation strategies. Methods: For the multiple parallel mediation model, the simulation experiments of three scenarios were carried out to compare the performance of different methods in estimating direct and indirect effects in different situations. Dataset from UK Biobank was then analyzed by using the four methods. Results: The estimation biases of the regression method and the inverse probability weighting method were relatively small, followed by the extended natural effect model method, and the estimation results of the weight-based imputation strategies were quite different from the other three methods. Conclusions: Different multiple parallel mediation analysis methods have different application situations and their own advantages and disadvantages. The regression method is more suitable for continuous mediator, and the inverse probability weighting method is more suitable for binary mediator. The extended natural effect model method has better performances when the residuals of two parallel mediators are positively correlated and the correlation degree is small. The weight-based imputation strategies might not be appropriate for parallel mediation analysis. Therefore, appropriate methods should be selected according to the specific situation in practice.
Bias ; Computer Simulation ; Humans ; Mediation Analysis ; Models, Statistical ; Probability ; Regression Analysis ; Research Design

Cannula ; Catheters ; Drainage ; Duodenal Diseases ; Humans ; Intestinal Fistula/surgery*