Objective:To analyze the clinical characteristics of children hospitalized with acute lower respiratory tract infections (ALRTI) caused by respiratory syncytial virus (RSV) in Kunming area in 2023.Methods:The clinical data of children with RSV-ALRTI admitted to Kunming Children's Hospital from January to December 2023 were retrospectively analyzed.According to the severity of the disease and whether the children developed severe pneumonia,they were divided into common group and severe group.The general data,clinical manifestations,laboratory indexes,imaging results,treatment and outcomes of the children between the two groups were compared.Multinomial Logistic regression analysis was used to study the risk factors for severe RSV-ALRTI.Results:A total of 696 children with RSV-ALRTI were included,including 432 males (62.1%) and 264 females (37.9%),with a median age of 1.30 (0.40,3.38) years.The onset of RSV-ALRTI occured throughout the year,with a peak incidence in May to August (60.6%).One hundred and seventy-one of 696 samples were tested RSV gene sequence,and two genotypes of RSV A-ON1(60.8%) and RSV B-BA9(39.2%) were detected.Among the 696 children,480 (69.0%) were in the common group and 216 (31.0%) were in the severe group.The age of the children in the severe group was lower than that of the common group,and the proportions of age <1 year,preterm birth,congenital diseases (congenital anomalies of airway development,congenital heart disease),combined Mycoplasma pneumoniae infections,and combined bacterial infections were higher than those of the common group ( P<0.05).There was no statistically significant differences in fever and cough symptoms between the two groups ( P>0.05),but the proportions of children in the severe group with wheezing,shortness of breath,dyspnea,vomiting,and diarrhea were significantly higher than those in the common group ( P<0.05),and the proportions of moist rales and wheezing heard by lung auscultation were significantly higher than those in the common group ( P<0.05).The levels of leukocytes,neutrophils,neutrophil percentage,platelets,procalcitonin,lactate dehydrogenase,alanine aminotransferase,aspartate aminotransferase,creatine kinase isoenzyme,and ferritin in the severe group were higher than those in the common group,while the levels of hemoglobin,lymphocyte percentage,albumin,creatinine,IgG,IgM,IgA,interleukin 6,D-dimer,and fibrin were lower than those in the common group ( P<0.05).The proportions of pulmonary consolidation and pleural effusion in the severe group were higher than those in the common group,and the severe group was more likely to have bilateral pulmonary consolidation ( P<0.05).Both groups of children were given interferon aerosol inhalation for antiviral treatment,and actively symptomatic and supportive treatment.One case in the severe group died during hospitalization,and the remaining 695 cases were cured and discharged.The proportions of children in the severe group using antibiotics,dual antibiotics,intravenous hormones,intravenous immunoglobulin,complications,transfer to PICU,use of invasive mechanical ventilation,length of hospital stay,and treatment costs were significantly higher than those in the common group ( P<0.001).Multinomial Logistic regression analysis showed that low age ( OR=0.878,95% CI 0.800~0.963, P=0.006),congenital diseases (congenital anomalies of airway development,congenital heart disease) ( OR=2.892,95% CI 1.977~4.233, P<0.001),and co-infection with bacteria ( OR=1.846,95% CI 1.268~2.686, P=0.001) were risk factors for the development of severe pneumonia in RSV-infected children. Conclusions:In 2023,RSV-ALRTI in children in Kunming area had an incidence throughout the year,and the peak age group of incidence was predominantly <1 year old,and the main genotype of infection was RSV A-ON1.Children with RSV-ALRTI who are young,suffering from congenital diseases (congenital anomalies of airway development,congenital heart disease) and complicated with bacterial infection are more likely to develop into severe diseases,and should be paid close attention and active intervention to reduce the incidence of critical illness.

OBJECTIVE To construct and evaluate nomogram prediction model for refractory chemotherapy-induced nausea and vomiting （CINV）. METHODS The data of malignant tumor patients who received chemotherapy at the Third People’s Hospital of Zhengzhou from January 2017 to December 2023 were collected. These patients were categorized into the occurrence group and the non-occurrence group according to the occurrence of refractory CINV. Multivariate Logistic regression analysis was employed to screen predictive factors for refractory CINV and constructing a nomogram prediction model. Model performance was assessed via receiver operating characteristic curve analysis. Model calibration was evaluated using Bootstrap resampling. Decision curve analysis （DCA） was used to determine the clinical net benefit of three strategies under different risk thresholds. Clinical impact curves were utilized to assess the clinical value of the model at different risk thresholds. Shapley additive explanations （SHAP） analysis was performed to evaluate individual factor contributions to the predictive model. RESULTS A total of 388 patients were included， with 219 experiencing refractory CINV. Multivariate Logistic regression identified 11 predictive factors for refractory CINV， including gastrointestinal disease history， anticipated nausea and vomiting， chemotherapy-induced emetic risk classification， and electrolyte levels， etc. The model’s area under the curve was 0.80 [95% confidence interval （0.76， 0.84）]， with a mean error of 0.036. DCA demonstrated the prediction model had higher clinical net benefit when the risk threshold was between 0.05 and 0.85. SHAP analysis revealed the top three predictive factors as gastrointestinal disease history （0.924）， chemotherapy- induced emetic risk classification （0.866）， and electrolyte levels （0.581）. CONCLUSIONS Eleven factors， including gastrointestinal disease history， anticipated nausea and vomiting， chemotherapy-induced emetic risk classification， and electrolyte levels， are identified as predictors of refractory CINV. The model based on these factors has good predictive ability， which can be used to predict the risk of refractory CINV.

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical burden and standardize the healthcare. In this study, the CDSS was built under a hierarchical-label interpretable classification framework, trained by a state-of-the-art transformer-based model, and validated in a multi-center style. METHODS: We conducted stratified sampling on a previously established dataset containing 302,965 electronic colonoscopy reports with pathology, identified 2041 patients' records representative of overall features, and randomly divided into the training and testing sets (7:3). A total of five main labels and 22 sublabels were applied to annotate each record on a network platform, and the data were trained respectively by three pre-training models on Chinese corpus website, including bidirectional encoder representations from transformers (BERT)-base-Chinese (BC), the BERT-wwm-ext-Chinese (BWEC), and ernie-3.0-base-zh (E3BZ). The performance of trained models was subsequently compared with a randomly initialized model, and the preferred model was selected. Model fine-tuning was applied to further enhance the capacity. The system was validated in five other hospitals with 3177 consecutive colonoscopy cases. RESULTS: The E3BZ pre-trained model exhibited the best performance, with a 90.18% accuracy and a 69.14% Macro-F1 score overall. The model achieved 100% accuracy in identifying cancer cases and 99.16% for normal cases. In external validation, the model exhibited favorable consistency and good performance among five hospitals. CONCLUSIONS The novel CDSS possesses high-level semantic recognition of colonoscopy reports, provides appropriate recommendations, and holds the potential to be a powerful tool for physicians and patients. The hierarchical multi-label strategy and pre-training method should be amendable to manage more medical text in the future.
Humans ; Colonoscopy/methods* ; Deep Learning ; Decision Support Systems, Clinical ; Female ; Male

The triple energizer is the pathway for the transportation and metabolism of qi,blood and body fluid in the body,and the xuanfu(sweat pores)is the way for the ascending,descending,exiting,and entering of qi movement in the muscular striae and the exterior.Professor Li Huilin believes that the pathogenesis of acne is usually due to the dysfunction of triple energizer and the stagnation of depressed yang-heat,which result into the abnormal opening and closing of the xuanfu and the accumulation of heat-toxin in the muscular striae.For the treatment of acne with traditional Chinese medicine,it is necessary to pay attention to the regulation of triple energizer-xuanfu.The treatment should be based on unblocking therapy,and the therapeutic principle of unblocking triple energizer and opening xuanfu should be taken into account.In clinical practice,it is necessary to identify the syndromes of upper energizer,middle energizer and lower energizer.The syndrome of the upper energizer is often due to fire-heat,which results from the wind-heat in lung meridian or the exuberance of heart fire.The upper-energizer syndrome can be treated by the therapy of relieving and clearing the pathogens with light and mild drugs,expelling fire-heat to open sweat pores,and through the modified use of Mahuang Lianqiao Chixiaodou Decoction,Ma Xing Shi Gan Decoction,or Puji Xiaodu Decoction.The syndrome of the middle energizer is usually due to the qi stagnation,which results from intense stomach-heat,damp-heat in the spleen and stomach,liver depression and qi stagnation,or spleen deficiency with dampness accumulation.The middle-energizer syndrome can be treated by the therapy of regulating qi movement to relieve stagnation and open sweat pores,and through the modified use of Qingwei san,Sanren Decoction,Huanglian Wendan Decoction,Chaihu Shugan Powder,or Heqi Powder.The syndrome of the lower energizer is often due to healthy-qi deficiency,which results from yin deficiency of liver and kidney,or deficiency-cold in lower energizer.The lower-energizer syndrome can be treated by the therapy of cultivating the vital essence and consolidating vital base,supplementing deficiency to open sweat pores,and through the modified use of Liuwei Dihuang Pills or Yanghe Decoction.

Objective To investigate the acupoint selection patterns for treating diabetic cardiac autonomic neuropathy(DCAN)using data mining techniques,providing evidence for clinical practice.Methods Literature on acupuncture treatment for DCAN was retrieved from CNKI,Wanfang,VIP,and PubMed.The publication dates of the included literature ranged from the inception of each database to April 2024.Descriptive analysis,association rule analysis,and cluster analysis were performed on acupoint prescriptions,with the selection patterns of meridians and acupoints were summarized.Results A total of 27 articles were included,involving 18 acupoints.The top 10 high-frequency acupoints were Neiguan(PC6),Xinshu(BL15),Pishu(BL20),Zusanli(ST36),Sanyinjiao(SP6),Shenmen(HT7),Taixi(KI3),Lingtai(GV10),Shendao(GV11),and Shenshu(BL23).The primary meridians selected were the bladder meridian of foot-taiyang and the pericardium meridian of hand-jueyin.Specific acupoint categories predominantly included back-shu points and five transport points.Association rule and cluster analyses identified core acupoint combinations centered on Xinshu,Neiguan,Pishu,and Zusanli.Conclusion The core acupoint combination for treating DCAN with acupuncture comprises Xinshu,Neiguan,Pishu,and Zusanli.

Objective To explore the medication rules of Professor Li Huilin in treating Hashimoto's thyroiditis(HT)complicated with hypothyroidism using data mining techniques based on the R language.Methods Prescription data of the patients with HT complicated with hypothyroidism treated by Professor Li Huilin in outpatient clinics from March 2023 to March 2024 were collected.A database was established using Microsoft Excel 2021,and R language was employed to analyze the frequency,efficacy,properties and flavors,and meridian tropism of the medicinals from Chinese herbal prescriptions.Additionally,correlation analysis,association rule analysis,and cluster analysis were performed on the medicines from Chinese herbal prescriptions.Results A total of 57 Chinese herbal prescriptions involving 125 medicinals with 782 medication frequencies were included.The top 10 frequently-used medicinals were Glycyrrhizae Radix et Rhizoma Praeparata cum Melle(Zhigancao),Angelicae Sinensis Radix(Danggui),Atractylodis Macrocephalae Rhizoma(Baizhu),Astragali Radix(Huangqi),Bupleuri Radix(Chaihu),Cinnamomi Ramulus(Guizhi),Leonuri Herba(Yimucao),Paeoniae Radix Alba(Baishao),Poria(Fuling),and Fici Simplicissimae Radix(Wuzhimaotao).Most of the medicinals had therapeutic action of tonifying deficiency.The analysis of properties and flavors showed that the majority of medicinals were mild or warm in nature,and sweet in flavor.The top three meridians having the tropism of medicinals were the liver,lung,and spleen meridians.Correlation analysis identified five strongly-correlated herbal combinations.Association rule mining revealed a core herbal combination consisting of seven medicinals of Zhigancao,Huangqi,Danggui,Chaihu,Codonopsis Radix(Dangshen),Baizhu,and Cyperi Rhizoma(Xiangfu).Cluster analysis of medicinals with a frequency of≥5 yielded five groups of herbal combination.Conclusion For the treatment of HT complicated with hypothyroidism,Professor Li Huilin follows the principle of addressing the root cause of the disease,and focuses on strengthening the spleen and replenishing qi.Moreover,attention is given to soothing the liver and regulating qi,harmonizing qi and blood simultaneously,and treating symptoms and root cause simultaneously.

Objective: To assess the presence of vector-borne pathogens [including Zika virus (ZIKV), dengue virus (DENV), chikungunya virus (CHIKV), and Plasmodium (PLAS)] among voluntary blood donors in Wenshan Zhuang and Miao Autonomous Prefecture (referred to as Wenshan), so as to provide a basis for formulating blood safety-related strategies. Methods: Blood samples from voluntary blood donors in Wenshan from June to August 2022 to 2024 were selected. Real-time fluorescent quantitative reverse transcription polymerase chain reaction (RT-qPCR) was used to test 20 426 samples for ZIKV RNA, DENV RNA, and CHIKV RNA; and 19 765 samples were tested for PLAS DNA. Results: All 20 426 samples tested for ZIKV RNA, DENV RNA, and CHIKV RNA were negative; similarly, all 19 765 samples tested for PLAS DNA were negative. Conclusion: The risk of ZIKV, DENV, CHIKV, and PLAS infection among voluntary blood donors in Wenshan is relatively low. Routine surveillance for these pathogens as endemic diseases is not currently warranted. It is recommended to adjust the screening strategy based on the dynamic situation of local epidemiology control and prevention.

Objective:To develop and validate a 30-day readmission risk prediction model for patients with chronic obstructive pulmonary disease (COPD) using multiple machine learning algorithms.Methods:Convenience sampling was used to select 1 450 COPD patients hospitalized at Tianjin Medical University General Hospital from January 2017 to December 2023 as study subjects. Twenty-nine variables associated with readmission were included. LASSO was used to screen for primary characteristic variables associated with 30-day readmission. The 1 450 patients were divided into a training set ( n=870) and a test set ( n=580) in a 6∶4 ratio. Ten machine learning methods, including random forest, AdaBoost, extreme radient Boosting (XGB), decision tree and so on, were used for model training and testing to identify the optimal prediction model. The optimal model and SHAP were employed to analyze key features and rank characteristic importance. Results:Among 1 450 COPD patients, the 30-day readmission rate was 24.48% (355/1 450). There were no significant differences in the general information between patients in test set and training set ( P>0.05). LASSO regression analysis identified seven variables with the highest predictive value, namely regular weekly exercise, hospital stay, mean arterial pressure, forced expiratory volume in one second/forced vital capacity (FEV1/FVC), C-reactive protein, body mass index, and medication adherence. Machine learning showed that in the training set, XGB had the highest area under the receiver operating characteristic curve ( AUC), sensitivity, and F1 score of 0.943, 0.926, and 0.930, respectively. In the test set, the AUC and accuracy of XGB were 0.882 and 0.858, respectively, and XGB's various scores showed that it had good generalization and predictive performance. XGB analysis showed that medication adherence, FEV1/FVC, and regular weekly exercise were negatively correlated with the 30-day readmission risk, while body mass index, C-reactive protein, mean arterial pressure, and hospital stay were positively correlated. The characteristics ranked in order of importance were medication adherence, body mass index, C-reactive protein, mean arterial pressure, FEV1/FVC, hospital stay and regular weekly exercise. Conclusions:The XGB model has strong predictive performance and good generalization ability, which can effectively predict the 30-day readmission risk of COPD patients, assist in clinical identification of high-risk patients, implement nursing interventions, and reduce readmission rates.

OBJECTIVE To explore the implementation and standardized management of infection control core ele-ments in grass-roots medical institutions within county-level medical communities.METHODS From Mar.2024 to Apr.2024,the current status of implementation of infection control core elements in the grass-roots medical institu-tions within county-level medical communities was investigated by means of questionnaire survey and qualita-tive interview,and the implementation strategies were further explored.RESULTS The infection management or-ganizational system and functions of the two county-level medical institutions within the county medical communi-ties were completed,there is no independent hospital infection management department in the primary medical in-stitutions.The infection management personnel in the 16 grass-roots medical institutions were part-time person-nel,the personnel with the educational background below junior college accounted for 84.21％,the personnel with the professional background of nursing accounted for 100.00％,the personnel with less than 5 years of working experience accounted for 78.95％,none of them had an on-the-job training certificate.The monitoring programs of the county-level medical institutions within the county medical communities were completed,there was no infec-tion management monitoring information platform in the grass-roots medical institutions.The infection cases,hand hygiene,environmental health and occupational exposures were monitored by people.The grass-roots medi-cal institutions had the highest requirements for various professional trainings and increase of training contents of prevention and control of public health infectious diseases(100.00％).The county-level medical institutions had inadequate capabilities of professional examination of medical equipment replacement and construction of medi-cal architecture.CONCLUSION It is necessary for the country and local levels of governments to attach great importance to the implementation of the infection control core elements in the grass-roots medical institutions within the county-lev-el medical communities,establish the county-level regional information platform,formulate the corresponding surveil-lance indexes and homogenized management systems,complete the cultivation of talents,and offer financial support.

Objective:To investigate the regulatory role of the tumor suppressor gene ARID1A(AT-rich interaction domain 1A)in the proliferation of lung adenocarcinoma(LUAD)cells and its molecular mechanism associated with the protein kinase B(AKT)signaling pathway.Methods:Stable ARID1A-overexpressing A549/H1299 cell models were constructed via lentiviral transfection,with transfection efficiency validated by RT-PCR and Western blot.Cell viability was assessed using the CCK-8 assay,proliferation rate was evaluated using EdU staining,and migration capacity was analyzed by scratch assay.Cell death was evaluated through Calcein/PI live/dead staining and trypan blue exclusion.The phosphorylation level of AKT(p-AKT/AKT ratio)was detected by Western blot.The role of AKT in proliferation regulation was further validated by treating overexpressing cells with the AKT inhibitor MK-2206(1 μmol/L).Results:ARID1A overexpression significantly inhibited the proliferation and migration of A549/H1299 cells while upregulating p-AKT levels.MK-2206 treatment abolished the inhibitory effects of ARID1A overexpression on proliferation.Cell death assays demonstrated no significant impact of ARID1A overexpression on LUAD cell mortality.Conclusion:ARID1A specifically suppresses LUAD cell proliferation and migration by activating the AKT signaling pathway,suggesting that targeting AKT may provide a potential therapeutic strategy for LUAD patients with ARID1A deficiency.