Clarifying the relationship and analyzing the influential factors of bronchial asthma in children with attention-deficit hyperactivity disorder

BACKGROUND Bronchial asthma is closely related to the occurrence of attention-deficit hyperactivity disorder(ADHD)in children,which can easily have adverse effects on children’s learning and social interactions.Studies have shown that childhood asthma can increase the risk of ADHD and the core symptoms of ADHD.Compared with children with ADHD alone,children with asthma and ADHD are more likely to show high levels of hyperactivity,hyperactive-impulsive and other externalizing behaviors and anxiety in clinical practice and have more symptoms of somatization and emotional internalization.AIM To explore the relationship between ADHD in children and bronchial asthma and to analyze its influencing factors.METHODS This retrospective cohort study was conducted at Dongying People's Hospital from September 2018 to August 2023.Children diagnosed with ADHD at this hospital were selected as the ADHD group,while healthy children without ADHD who underwent physical examinations during the same period served as the control group.Clinical and parental data were collected for all participating children,and multivariate logistic regression analysis was employed to identify risk factors for comorbid asthma in children with ADHD.RESULTSSignificant differences were detected between the ADHD group and the control group in terms of family history ofasthma and allergic diseases, maternal complications during pregnancy, maternal use of asthma and allergymedications during pregnancy, maternal anxiety and depression during pregnancy, and parental relationshipstatus (P < 0.05). Out of the 183 children in the ADHD group, 25 had comorbid asthma, resulting in a comorbidityrate of 13.66% (25/183), compared to the comorbidity rate of 2.91% (16/549) among the 549 children in the controlgroup. The difference in the asthma comorbidity rate between the two groups was statistically significant (P <0.05). The results of the multivariate logistic regression analysis indicated that family history of asthma and allergicdiseases, maternal complications during pregnancy, maternal use of asthma and allergy medications duringpregnancy, maternal anxiety and depression during pregnancy, and parental relationship status are independentrisk factors increasing the risk of comorbid asthma in children with ADHD (P < 0.05).CONCLUSIONChildren with ADHD were more likely to have comorbid asthma than healthy control children were. A familyhistory of asthma, adverse maternal factors during pregnancy, and parental relationship status were identified asrisk factors influencing the comorbidity of asthma in children with ADHD. Clinically, targeted interventions basedon these factors can be implemented to reduce the risk of comorbid asthma. This information is relevant for resultssections of abstracts in scientific articles.

Safety and effectiveness of lurasidone in the treatment of Chinese schizophrenia patients:An interim analysis of post-marketing surveillance

BACKGROUND Schizophrenia is a psychiatric disorder characterized by chronic or recurrent symptoms.Lurasidone was licensed in China in 2019 for the treatment of adult schizophrenia in adults with a maximum dose of 80 mg/d.However,post-market surveillance(PMS)with an adequate sample size is required for further validation of the drug’s safety profile and effectiveness.AIM To conduct PMS in real-world clinical settings and evaluate the safety and effectiveness of lurasidone in the Chinese population.METHODS A prospective,multicenter,open-label,12-wk surveillance was conducted in China's Mainland.All patients with schizophrenia from 10 sites who had begun medication with lurasidone between September 2019 and August 2022 were eligible for enrollment.Safety assessments included adverse events(AEs),adverse drug reactions(ADRs),extrapyramidal symptoms(EPS),akathisia,use of EPS drugs,weight gain,and laboratory values as metabolic parameters and the QTc interval.The effectiveness was assessed using the brief psychiatric rating scale(BPRS)from baseline to the end of treatment.RESULTS A total of 965 patients were enrolled in the full analysis set and 894 in the safety set in this interim analysis.The average daily dose was 61.7±19.08 mg(mean±SD)during the treatment.AEs and ADRs were experienced by 101 patients(11.3%)and 78 patients(8.7%),respectively,which were mostly mild.EPS occurred in 25 individuals with a 2.8%incidence,including akathisia in 20 individuals(2.2%).Moreover,59 patients received drugs for treating EPS during the treatment,with an incidence of 6.6%which dropped to 5.4%at the end of the treatment.The average weight change was 0.20±2.36 kg(P=0.01687)with 0.8%of patients showing a weight gain of≥7%at week 12 compared with that at the baseline.The mean values of metabolic parameters and the QTc interval at baseline and week 12 were within normal ranges.The mean changes in total BPRS scores were-8.9±9.76(n=959),-13.5±12.29(n=959),and-16.8±13.97(n=959)after 2/4,6/8,and 12 wk,respectively(P<0.001 for each visit compared with the baseline)using the last-observation-carried-forward method.CONCLUSION The interim analysis of the PMS of adult patients with schizophrenia demonstrate the safety and effectiveness of lurasidone in the Chinese population.No new safety or efficacy concerns were identified.

Text Mining and Analysis of Treatise on Febrile Diseases Based on Natural Language Processing

Objective:With using natural language processing (NLP) technology to analyze and process the text of "Treatise on Febrile Diseases (TFDs)"for the sake of finding important information, this paper attempts to apply NLP in the field of text mining of traditional Chinese medicine (TCM)literature. Materials and Methods:Based on the Python language, the experiment invoked the NLP toolkit such as Jieba, nltk, gensim,and sklearn library, and combined with Excel and Word software. The text of "TFDs" was sequentially cleaned, segmented, and moved the stopped words, and then implementing word frequency statistics and analysis, keyword extraction, named entity recognition (NER) and other operations, finally calculating text similarity. Results:Jieba can accurately identify the herbal name in "TFDs." Word frequency statistics based on the word segmentation found that "warm therapy" is an important treatment of "TFDs." Guizhi decoction is the main prescription,and five core decoctions are identified. Keyword extraction based on the term "frequency-inverse document frequency" algorithm is ideal.The accuracy of NER in "TFDs" is about 86%;latent semantic indexing model calculating the similarity,"Understanding of Synopsis of Golden Chamber (SGC)" is much more similar with "SGC" than with "TFDs." The results meet expectation. Conclusions:It lays a research foundation for applying NLP to the field of text mining of unstructured TCM literature. With the combination of deep learning technology,NLP as an important branch of artificial intelligence will have broader application prospective in the field of text mining in TCM literature and construction of TCM knowledge graph as well as TCM knowledge services.