Objective:To investigate the value and clinical significance of fasting plasma glucose (FPG) in early pregnancy (8-12 gestational weeks) as a predictor of gestational diabetes mellitus (GDM) among women with different pre-pregnancy body mass index (pre-BMI) categories.Methods:A retrospective study was conducted including 9 710 singleton pregnant women (FPG levels in early pregnancy ≤5.6 mmol/L) who underwent prenatal screening and delivery in Yuyao People's Hospital from January 2020 to December 2022. Participants were stratified based on their pre-BMI as follows: <18.5 ( n=1 406), ≥18.5 to <25.0 ( n=7 162), ≥25.0 to <30.0 ( n=978), and ≥30.0 kg/m 2 ( n=164). Within each pre-BMI category, women were further divided into four groups based on FPG levels in early pregnancy (<4.5, ≥4.5 to <4.8, ≥4.8 to <5.1, and ≥5.1 mmol/L). Univariate and multivariate logistic regression analysis were used to identify risk factors for GDM, and receiver operating characteristic (ROC) curve was applied to evaluate the efficacy of FPG in early pregnancy based on different pre-BMI in predicting GDM. Results:The overall incidence of GDM in the singleton pregnancy women with FPG levels in early pregnancy ≤5.6 mmol/L was 12.3% (1 197/9 710). For a pre-BMI of <18.5 kg/m 2, the ORs with 95% CIs for GDM within the different FPG categories (<4.5, ≥4.5 to <4.8, ≥4.8 to <5.1, and ≥5.1 mmol/L) were 0.041 (95% CI: 0.015-0.409), 1.834 (95% CI: 1.089-3.088), 6.779 (95% CI: 4.041-11.371), and 13.723 (95% CI: 5.560-33.871), respectively. For pre-BMI of ≥18.5 to <25.0 kg/m 2, the respective the ORs with 95% CIs were 0.048 (95% CI: 0.012-0.203), 2.573 (95% CI: 2.091-3.168), 9.023 (95% CI: 7.240-11.245), and 9.158 (95% CI: 6.484-12.937). For pre-BMI of ≥25.0 to <30.0 kg/m 2, the ORs with 95% CIs were 0.108 (95% CI: 0.053-0.446), 1.698 (95% CI: 1.064-2.654), 7.537 (95% CI: 5.285-13.080), and 9.994 (95% CI: 5.613-18.218). For pre-BMI of ≥30.0 kg/m 2, the ORs with 95% CIs were 0.098 (95% CI: 0.072-1.015), 2.888 (95% CI: 0.911-9.157), 13.674 (95% CI: 3.480-53.736), and 20.509 (95% CI: 6.674-63.019). The optimal cutoff value of FPG in early pregnancy for GDM prediction was 4.7 mmol/L with an area under the curve of 0.752, the risk of GDM significantly increased with FPG levels ≥4.7 mmol/L in early pregnancy across all pregnant women ( OR=17.356, 95% CI: 13.757-21.896, P<0.001). Conclusions:In the singleton pregnancy women with FPG levels in early pregnancy ≤5.6 mmol/L, FPG in early pregnancy is an independent risk factor for the occurrence of GDM; for pregnant women stratified by the same pre-BMI, the risk of developing GDM increases progressively with the rise of FPG in early pregnancy. FPG in early pregnancy has a certain value in predicting the occurrence of GDM.

Objective To explore the efficiency of artificial intelligence and radiomics-assisted X-ray in diagnosis of lumbar osteoporotic vertebral compression fractures(OVCF).Methods The clinical data of 455 patients diagnosed as lumbar OVCF by MRI in our hospital were selected.The patients were divided into the training group(n=364)and the validation group(n=91),X-ray films were extracted,the image delineation,feature extraction and data analysis were carried out,and the artificial intelligence radiomics deep learning was applied to establish a diagnostic model for OVCF.After verifying the effectiveness of the model by receiver operating characteristic(ROC)curve,area under the curve(AUC),calibration curve,and decision curve analysis(DCA),the efficiencies of manual reading,model reading,and model-assisted manual reading of X-ray in the early diagnosis of OVCF were compared.Results The ROC curve,AUC and calibration curve proved that the model had good discrimination and calibration,and excellent diagnostic performance.DCA demonstrated that the model had a higher clinical net benefit.The diagnostic efficiency of the manual reading group:the accuracy rate was 0.89,the recall rate was 0.62.The diagnostic efficiency of the model reading group:the accuracy rate was 0.93,the recall rate was 0.86,the model diagnosis showed good predictive performance,which was significantly better than the manual reading group.The diagnostic efficiency of the model-assisted manual reading group:the accuracy rate was 0.92,the recall rate was 0.72,and the recall rate of the model-assisted manual reading group was higher than that of the manual reading group,but lower than that of the model reading group,indicating the superiority of the model diagnosis.Conclusion The diagnostic model established based on artificial intelligence and radiomics in this study has reached an ideal level of efficacy,with better diagnostic efficacy compared with manual reading,and can be used to assist X-ray in the early diagnosis of OVCF.

Objective To develop a clinical prediction model for predicting risk factors for prolonged hospital stay after anterior cervical discectomy and fusion(ACDF).Methods The clinical data of 914 patients underwent ACDF treatment for cervical spondylotic myelopathy(CSM)were retrospectively analyzed.According to the screening criteria,800 eligible patients were eventually included,and the patients were divided into the development cohort(n=560)and the validation cohort(n=240).LASSO regression was used to screen variables,and multivariate Logistic regression analysis was used to establish a prediction model.The prediction model was evaluated from three aspects:differentiation,calibration and clinical effectiveness.The performance of the model was evaluated by area under the curve(AUC)and Hosmer-Lemeshow test.Decision curve analysis(DCA)was used to evaluate the clinical effectiveness of the model.Results In this study,the five factors that were significantly associated with prolonged hospital stay were male,abnormal BMI,mild-to-moderate anemia,stage of surgery(morning,afternoon,evening),and alcohol consumption history.The AUC of the development cohort was 0.778(95%CI:0.740 to 0.816),with a cutoff value of 0.337,and that of the validation cohort was 0.748(95%CI:0.687 to 0.809),with a cutoff value of 0.169,indicating that the prediction model had good differentiation.At the same time,the Hosmer-Lemeshow test showed that the model had a good calibration degree,and the DCA proved that it was effective in clinical application.Conclusion The prediction model established in this study has excellent comprehensive performance,which can better predict the risk of prolonged hospital stay,and can guide clinical intervention as soon as possible,so as to minimize the postoperative hospital stay and reduce the cost of hospitalization.

Objective To explore the risk factors for surgical site infection(SSI)after transforaminal lumbar interbody fusion(TLIF)for the treatment of lumbar degenerative diseases.Methods A total of 1 000 patients who underwent TLIF for lumbar degenerative diseases in our hospital were included and divided into the infection group(n=23)and the non-infection group(n=977)according to whether the surgical incision was infected.General data,surgical and laboratory indicators of patients were collected,and potential risk factors of SSI were screened by univariate analysis and multivariate regression analysis,a nomogram model was established,and its predictive efficiency was validated by the receive operating characteristic(ROC)curve.Results The incidence of SSI in patients after TLIF was 2.3％.The results of univariate analysis showed that age,operative time,intraoperative blood loss,preoperative C-reactive protein(CRP),smoking,and diabetes mellitus were the significant risk factors for the occurrence of SSI.Multivariate regression analysis showed that older age,longer operation time,more intraoperative blood loss,smoking and diabetes mellitus were the independent risk factors for postoperative SSI.ROC curve showed that the nomogram model established in this study has good predictive efficiency.Conclusion Older age,longer operation time,more intraoperative blood loss,smoking,and diabetes mellitus were independent risk factors for postoperative SSI.For patients with these high risk factors,corresponding intervention measures should be taken before operation to reduce the incidence of SSI.

Objective:To investigate the level of beliefs about medication in young patients with newly treated pulmonary tuberculosis and analyze its influencing factors.Methods:This was a cross-sectional study. Using the convenient sampling method, a total of 320 young newly treated pulmonary tuberculosis patients who visited the designated tuberculosis hospitals in Kashgar Prefecture and Hotan Prefecture of Xinjiang Uygur Autonomous Region from January 2022 to April 2023 were selected as the research objects. The investigation was carried out with the General Information Questionnaire, Beliefs about Medicines Questionaire Specific (BMQ-S), 8-Item Morisky Medication Adherence Scale (MMAS-8), Brief Illness Perception Questionnaire (BIPQ) and Tuberculosis-related Stigma Scale (TSS). Multiple linear regression was used to analyze the influencing factors of medication beliefs in young patients with newly treated tuberculosis.Results:A total of 320 questionnaires were distributed in this study, and 302 valid questionnaires were collected, with an effective response rate of 94.38% (302/320). The total score of BMQ-S of 302 young patients with newly treated tuberculosis was -1.00 (-2.00, 1.00), MMAS-8 score was 5.38 (4.75, 5.75), BIPQ score was 37.00 (24.00, 44.00) and TSS score was 48.00 (44.00, 52.00). The results of multiple linear regression analysis showed that comorbidities, medication adherence, disease perception and stigma were the influencing factors of medication beliefs in young newly treated pulmonary tuberculosis patients ( P<0.01) . Conclusions:The medication belief level of young patients with newly treated pulmonary tuberculosis needs to be improved. Medical staff should correct the negative cognition of the patient's disease, emphasize the benefits of drug treatment and enhance the patients' beliefs in the necessity of medication.

Objective:To explore the mediating effect of medication self-efficacy between perceived social support and compliance behavior in young patients with newly treated pulmonary tuberculosis under the Southern Xinjiang Model.Methods:A cross-sectional survey was conducted in Kashgar Tuberculosis Prevention and Control Institute Hospital and Tuberculosis Specialist Hospital of Hetian from January 2022 to April 2023. A total of 302 young patients with initial treatment of pulmonary tuberculosis in were selected as the research objects by convenience sampling method. The General Information Questionnaire, the Tuberculosis Compliance Behavior Rating Scale, Perceived Social Support Scale and Self-efficacy for Appropriate Medication Use scale were used to investigate, and the correlation analysis and mediating effect analysis were carried out.Results:The total scores of compliance behavior, self-efficacy and perceived social support were (119.09 ± 13.49), (23.48 ± 6.25) and (55.67 ± 11.33) respectively. All dimensions of medication self-efficacy and perceived social support were positively correlated with compliance behavior ( r values were 0.555 - 0.943, all P<0.01), and medication self-efficacy was positively correlated with perceived social support ( r = 0.981, P<0.01). Medication self-efficacy played a partial mediating effect between perceived social support and compliance behavior, accounting for 74.46% of the total effect. Conclusions:The medication self-efficacy of young patients with newly treated pulmonary tuberculosis is the mediating variable between perceived social support and compliance behavior. Medical staff should focus on and carefully evaluate the medication self-efficacy and perceived social support of patients, so as to give supportive intervention in time, so as to change or even reverse the non-compliance behavior and improve the compliance level of patients.

Objective: To analyze the short-term effect of individual atmospheric PM_2.5 exposure on the diversity, enterotype, and community structure of gut microbiome in healthy elderly people in Jinan, Shandong province. Methods: The present panel study recruited 76 healthy elderly people aged 60-69 years old in Dianliu Street, Lixia District, Jinan, Shandong Province, and followed them up five times from September 2018 to January 2019. The relevant information was collected by questionnaire, physical examination, precise monitoring of individual PM_2.5 exposure, fecal sample collection and gut microbiome 16S rDNA sequencing. The Dirichlet multinomial mixtures (DMM) model was used to analyze the enterotype. Linear mixed effect model and generalized linear mixed effect model were used to analyze the effect of PM_2.5 exposure on gut microbiome α diversity indices (Shannon, Simpson, Chao1, and ACE indices), enterotype and abundance of core species. Results: Each of the 76 subjects participated in at least two follow-up visits, resulting in a total of 352 person-visits. The age of 76 subjects was (65.0±2.8) years old with BMI (25.0±2.4) kg/m². There were 38 males accounting for 50% of the subjects. People with an educational level of primary school or below accounted for 10.5% of the 76 subjects, and those with secondary school and junior college or above accounting for 71.1% and 18.4%. The individual PM_2.5 exposure concentration of 76 subjects during the study period was (58.7±53.7) μg/m³. DMM model showed that the subjects could be divided into four enterotypes, which were mainly driven by Bacteroides, Faecalibacterium, Lachnospiraceae, Prevotellaceae, and Ruminococcaceae. Linear mixed effects model showed that different lag periods of PM_2.5 exposure were significantly associated with a lower gut α diversity index (FDR<0.05 after correction). Further analysis showed that PM_2.5 exposure was significantly associated with changes in the abundances of Firmicutes (Megamonas, Blautia, Streptococcus, etc.) and Bacteroidetes (Alistipes) (FDR<0.05 after correction). Conclusion: Short-term PM_2.5 exposure is significantly associated with a decrease in gut microbiome diversity and changes in the abundance of several species of Firmicutes and Bacteroidetes in the elderly. It is necessary to further explore the underlying mechanisms between PM_2.5 exposure and the gut microbiome, so as to provide a scientific basis for promoting the intestinal health of the elderly.
Aged ; Humans ; Male ; Middle Aged ; Feces/microbiology* ; Gastrointestinal Microbiome ; Particulate Matter ; RNA, Ribosomal, 16S/genetics* ; Female

Objective:To analyze the incidence and prognosis of epilepsy in frontotemporal lobe glioma.Methods:The clinical data of 208 patients with frontotemporal lobe gliomas in Sanbo Brain Hospital Capital Medical University from 2019 to 2021 were analyzed retrospectively. According to the 2016 World Health Organization (WHO) classification of tumors of the central nervous system, the incidence of epilepsy, Modified Rankin Scale (MRS) score, and Engel Outcome Scale of patients with different grades of tumors were calculated.Results:Among all the patients with frontotemporal lobe gliomas, there was more males than females, and it was more common in the 40 -59 age group. The incidence of epilepsy associated with WHO grade Ⅰand Ⅱ glioma was 100.0% (33/33) and 60.9% (14/23), respectively, while that of WHO grade Ⅳ glioma was 19.0%(19/100). The average follow-up time was (22 ± 9) months. During the follow-up period, the incidence of WHO grade Ⅰ, Ⅱ and Ⅲ glioma-related epilepsy decreased significantly. There was no significant difference in the incidence of glioma-related epilepsy between the total and subtotal resection groups ( P>0.05). There was no statistical correlation between the side of tumor occurrence and the occurrence of epilepsy ( P>0.05), also between the gene phenotype and the occurrence of epilepsy ( P>0.05). There was no significant difference in the Engel Outcome Scale among different grades of gliomas ( P>0.05). The prognosis of patients with Engel Outcome Scale Class 1 was significantly better than that of other grades. Conclusions:The incidence of glioma-related epilepsy is negatively correlated with tumor grade. Age and sex are risk factors for glioma-related epilepsy. The incidence of postoperative epilepsy in patients with low grade glioma is significantly lower than that in patients with high grade glioma, and the prognosis is better. However, there is no significant difference in the Engel Outcome Scale among different grades of gliomas.

Objective To investigate the Gram-positive coccus resistance in nationwide's tertiary hospitals and understand the trend of antimicrobial resistance.Methods All the clinical isolates were collected from 19 hospitals and the minimal inhibitory concentrations(MICs)were tested using agar/broth dilution method recommended.Results A total of 1 974 pathogenic Gram-positive coccus from 19 tertiary hospitals in 19 cities nationwide over the period from July 2021 to June 2022 were studied.Based on the MIC results,the prevalence of methicillin resistant Stapylococcus aureus(MRSA)and methicillin resistant Stapylococcus epidermidis(MRSE)were 36.4％and 79.9％respectively.No vancomycin insensitivity Staphylococcus was detected.Staphylococcus aureus were 100％susceptibility to linezolid and teicoplanin.Antibiotic resistance rate of Enterococcus faecalis and Enterococcus faecium to ampicillin were 3.1％and 92.9％.The detectation rate of vancomycin resistant Enterococcus(VRE)was 1.6％.Nonsusceptibility rate of Enterococcus faecalis to linezolid was 32.2％,two consecutive monitoring rises and nonsusceptibility rate of Enterococcus faecium(12.5％)was also significantly increased.The prevalence of penicillin non-susceptible Streptococcus pneumoniae(PNSSP)was 0.8％based on non-meningitis and parenteral administration criterion,decrease of nearly 30 percentage points from the previous surveillance.While for cases of oral penicillin,the rate was 71.8％,showing similar to last time.The results indicated that the number of strains with higher MIC value of penicillin(MIC ≥4 mg·L-1)decreased significantly.There were no significant differences of resistance rates of Stapylococcus aureus,Stapylococcus epidermidis,Enterococcus faecalis,Enterococcus faecium and Streptococcus pneumoniae among various groups such as different department,age,or specimen source.Conclusion VRE detection ratio stablized at a relatively low level.The number of Streptococcus pneumoniae with higher MIC value of penicillin decreased significantly compared with the previous monitoring.The increase of linezolidin-insensitive Enterococcus was noteworthy.

Objective To investigate the Gram-negative bacteria resistance in nationwide's tertiary hospitals and understand the trend of antimicrobial resistance.Method All the clinical isolates were collected from 19 hospitals and the minimal inhibitory concentrations(MICs)were tested using agar/broth dilution method recommended.Results A total of 4 066 pathogenic isolates from 19 tertiary hospitals in 19 cities nationwide over the period from July 2021 to June 2022 were studied.Based on the MIC results,Escherichia coli and Klebsiella pneumoniae showed extended spectrum β-lactamase(ESBLs)phenotype rates of 55.0％and 21.0％,respectively,ESBLs phenotype rate of Klebsiella pneumoniae keep going down.The ratios of carbapenems resistance Klebsiella pneumoniae increased by 5 percentage points compared with the previous monitoring.Carbapenems,moxalactam,sitafloxacin,β-lactam combination agents,fosfomycin trometamol,and amikacin displayed desirable antibacterial activity against Enterbacterales,susceptibal rates were above 75％.In addition,tigacycline,omacycline,colistin and fluoxefin maintained good antibacterial activity against their respective effective bacteria/species,and the bacterial sensitivity rates by more than 80％.Resistance rates of Pseudomonas aeruginosa and Acinetobacter baumannnii to imipenem were 26.3％and 72.1％and multidrug-resistant(MDR)detection rates were 41.1％and 77.3％,extensively drug-resistant(XDR)were 12.0％and 71.8％,respectively.Comparison of drug resistance rates from different wards,ages and specimen sources indicated that the proportion of resistance in Klebsiella pneumoniae and Acinetobacter baumannii isolated from intensive care unit(ICU)were significantly higher than non-ICU.Carbapenem resistance rates of Klebsiella pneumoniae isolated from ICU were more than 35％.Resistance rates of Haemophilus influenzae isolated in children to β-lactam,macrolide,clindamycin and ESBLs detection rate in Klebsiella pneumoniae isolated from children were more than those from adults and the old people,so bacterial resistance in children is an important problem in China.Conclusion ESBLs detection rate of Escherichia coli increased slightly after years of continuous decline.The proportion of carbapenem resistant Pseudomonas aeruginosa was stable,but the resistance rate of Klebsiella pneumoniae and Acinetobacter baumannii to carbapenems was still increased,which should be paid more attention.