Objective To evaluate the diagnostic value of positive serum specific antibodies to Mycoplasma pneumoniae(MP)in children with Mycoplasma pneumoniae pneumonia(MPP).Methods PubMed,Cochrane Library,Embase,Sinomed,CNKI,Wanfang and VIP databases were searched for studies on the detection of MPP based on antibodies from the establishment of the database to March 31,2023.After literature screening and data extraction,STATA 16.0 software was used for Meta-analysis.Results A total of 9 literatures and 2 148 clinical samples were included.The combined sensitivities[M(95%CI)]of particle agglutination assay(PA)and enzyme-linked immunosorbent assay(ELISA)were 50%(31～69)and 88%(85～90),and the combined specificities[M(95%CI)]were 88%(76～95)and 88%(62～97).The combined diagnostic odds ratio(DOR)[M(95%CI)]were 5.61(3.30～9.53)and 43.82(12.78～150.19),and the summary receiver operating characteristic curve(SROC)area under the curve(AUC)were 0.80 and 0.88,respectively.Conclusion Serum MP specific antibody detection can be used for diagnosis and screening of children MPP,but needs to be combined with clinical symptoms improve the accuracy of the diagnosis.

Objective:To investigate the awareness levels of doctors from various departments regarding fertility preservation to provide reference and suggestions for further improving awareness and promoting multidisciplinary development in fertility preservation.Methods:From November to December 2023, the China Alliance of Fertility Preservation initiated this survey covering 88 hospitals in 23 cities across 20 provinces in China. The survey focused on the degree of understanding of basic concepts, technological perceptions, treatment concepts, and related challenges regarding fertility preservation. Descriptive statistics and Fisher's exact test were used to analyze the difference in awareness levels across various departments.Results:There was a significant difference in the awareness of fertility preservation guidelines among physicians from different departments ( P<0.001). Reproductive center physicians had the highest level of understanding [68.3% (41/60)]. Doctors in the reproductive centers had a higher awareness rate of the five fertility preservation techniques (ovarian tissue cryopreservation, oocyte cryopreservation, sperm cryopreservation, testicular tissue cryopreservation, and embryo cryopreservation) than that in other departments (all P<0.05). Regarding treatment concepts, more reproductive center physicians believed that psychological counselling about fertility preservation before oncological treatment was necessary ( P=0.016). Hematologists had more worries and concerns about fertility preservation treatment. Additionally, 96.7% (58/60) of reproductive center physicians expressed the need to establish effective referral mechanisms within the same city, province, or across provinces. However, 55.6% (35/63) of oncologists, 64.6% (31/48) of hematologists, and 77.8% (7/9) of pediatricians considered treating primary tumors far more important than fertility preservation. Conclusion:Doctors from different departments have varying levels of understanding regarding fertility preservation. It is necessary to strengthen the dissemination and training of fertility preservation knowledge among physicians from various departments, as well as to promote a multidisciplinary treatment model to improve efficiency, to establish a comprehensive referral mechanism to improve patients' opportunities for fertility preservation.

Objective In this study,clinical data of Alzheimer's disease(AD)patients,structural magnetic resonance imaging(sMRI)data,and positron emission tomography(PET)data were used to construct an auxiliary diagnostic model with good classification effects,so as to formulate a personalized treatment plan at the early stage of the patients,which is of great significance for the prevention and treatment of AD.Methods In this study,a total of 401 study subjects containing complete sMRI images and PET images were selected from the ADNI-1(Alzheimer's disease neuroimaging initiative-1,ADNI-1)database.We used statistical parameters mapping(SPM)and voxel-based morphometric(VBM)analysis of MATLAB to perform pre-processing operations such as spatial normalization and skull stripping on sMRI images and PET images of the study subjects.With the help of the brain atlas was used to segment the brain tissue structure.After that,the segmented gray matter was extracted from the corresponding brain regions based on anatomical automatic labeling,and the feature values of all brain regions were obtained.Then the extracted brain region feature values are then subjected to fisher score,support vector machine-recursive feature elimination(SVM-RFE)and least absolute shrinkage and selection operator(LASSO),a hybrid filtered-wrapped-embedded feature selection method with three different principles,to realize the dimensionality reduction of high-dimensional image data.Finally,the PAC-Bayesian strategy boosting based multi-view learning(PB-MVBoost)model is constructed based on multi-view decision fusion for clinical,sMRI and PET data.And it is compared with the traditional machine learning models support vector machine(SVM),decision tree(DT),K-nearest neighbor(KNN),random forests(RF),adaptive boosting(AdaBoost),and extreme gradient boosting(XGBoost)which are constructed after concatenating views.It is compared with multi-view multi-kernel learning models(AverageMKL,EasyMKL)and multi-view confusion matrix boosting,which is also the same multi-view decision fusion.Results Among all the multi-view fusion models of AD-MCI,the PB-MVBoost model based on decision fusion has the best performance(accuracy=0.98,F1-score=0.97,precision=0.98,recall=0.96,MSE=0.07).Among all the multi-view fusion models of MCI-NC,the model performance of PB-MVBoost based on decision fusion was the best(accuracy=0.99,F1-score=0.98,precision=0.99,recall=0.98,MSE=0.05).Conclusion In the classification of AD-MCI and MCI-NC,the distinction and calibration degree of PB-MVBoost model were optimized,indicating that the auxiliary diagnosis model of Alzheimer's disease constructed by PB-MVBoost classifier based on decision fusion performed the best,which could improve the recognition of patients with mild cognitive impairment and then assist clinical diagnosis.

Objective:To construct an evaluation index system for the effectiveness of ideological and political education in the curriculum of professional master's degree nursing programs, providing an evaluation tool for objectively assessing the teaching quality of ideological and political education in these programs.Methods:The initial draft of the index system was designed based on a review of domestic and international literature. From October 2022 to January 2023, 15 experts were selected using convenience sampling for three rounds of Delphi expert consultation, and the analytic hierarchy process was used to determine the weight of the indicators.Results:The positive response rate from the 15 experts in all three rounds of consultation was 100% (15/15), and the expert authority coefficient was 0.813. The Kendall's coefficient of concordance for the overall indicators in the third round was 0.116 ( P<0.01). The constructed evaluation index system includes 5 first-level indicators (goal and concept, faculty, course resources, teaching implementation, teaching effectiveness), 12 second-level indicators, and 49 third-level indicators. Conclusions:The evaluation index system for the effectiveness of ideological and political education in the curriculum of professional master's degree nursing programs demonstrates good scientific validity and reliability. It can provide objective and quantitative evaluation criteria for the development of ideological and political education in these programs.

Objective A randomized controlled trial was conducted on colonoscopy inpatient and outpatients to compare the efficacy and safety of water exchange(WE)colonoscopy and CO2 convention insufflation colonoscopy in elderly patients.Methods 340 patients underwent fully sedated colonoscopy were randomly divided into two groups according to colonoscopy with either WE colonoscopy group(WE group)and CO2 insufflation colonoscopy group(CO2 group).The two groups were compared in terms of Boston bowel preparation scale(BBPS),withdrawal time,cecal intubation time,cecal intubation success rate,abdominal compression,willingness to repeat,polypdetectionrate(PDR),adenoma detection rate(ADR),and safety.Results The cecal intubation success rate was significantly higher in WE group(100.0%)compared with CO2 group(96.5%),the difference was statistically significant(P=0.013).The average cecal intubation time of WE group was(10.50±1.79)min,which was longer than that of CO2 group(7.55±1.50)min,and the difference was statistically significant(P<0.01).Comparison of withdrawal time and BBPS between the two groups,the differences were not statistically significant(P>0.05).The abdominal pressure rate was lower in WE group(5.9%)compared with CO2 group(13.5%),the difference was statistically significant(P=0.017).The rate of willingness to re-examination in the WE group was 98.2%,which was significantly higher than the 93.5%in the CO2 group.The PDR in WE group(80.6%)was higher than that in CO2 group(70.6%),the ADR in WE group(67.1%)was higher than that in CO2 group(50.6%),the differences were statistically significant(P<0.05).Multivariate Logistic regression analysis showed that WE group was an effective factor in improving ADR(O＾R=2.027,P<0.01).The overall adverse events were less than 3%,with no difference between the two groups(P=1.000).Conclusion The use of WE colonoscopy has a better improved efficacy in elderly patients,and safety should be ensured by individualized assessment of the patient's co-morbidities,bowel preparation tolerance,and willingness prior to the procedure.

Objective To develop a machine learning model integrating preoperative chest CT radiomic features with clinical data for predicting 5-year postoperative recurrence risk in stage Ⅰ non-small cell lung cancer(NSCLC)patients undergoing surgical resection.Methods A total of 217 patients with pathologically confirmed stage Ⅰ NSCLC(selected from 778 initially screened cases based on our inclusion and exclusion criteria)treated in Army Medical Center of PLA between January 2014 and December 2019 were retrospectively enrolled,including 53 recurrence cases and 164 non-recurrence cases within 5-year follow-up.They were randomly divided into a training set(n=173)and a validation set(n=44)in a ratio of 8:2.Radiomic models were established based on extracted features from tumor-dominant regions of interest(ROI)on CT images,while clinical models were developed using demographic characteristics and preoperative laboratory examinations.A combined model was further constructed by integrating both feature sets,and model performance was compared to identify the optimal predictive model.Results This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model.Among 6 machine learning algorithms,the adaptive boosting(Adaboost)model demonstrated the best overall predictive performance,with an area under the curve(AUC)of 0.866(95%CI:0.808～0.923;accuracy:0.832,specificity:0.884)in the training set and of 0.806(95%CI:0.630～0.983;accuracy:0.795,specificity:0.971)in the validation set.Univariate and multivariate logistic regression analyses identified 4 clinical features for clinical model construction.The clinical model achieved an AUC value of 0.874(95%CI:0.821～0.928;accuracy:0.827,specificity:0.891)in the training set and 0.813(95%CI:0.677～0.948;accuracy:0.636,specificity:0.600)in the validation set.By integrating the 7 radiomic features and 4 clinical features using a feature-level fusion strategy,the combined model exhibited further improved predictive performance,with an AUC value of 0.953(95%CI:0.924～0.983;accuracy:0.884,specificity:0.860)and 0.852(95%CI:0.729～0.976;accuracy:0.682,specificity:0.629),respectively in the training set and the validation set.Conclusion The combined model integrating preoperative CT radiomic features with clinical risk factors may provide an evidence-based framework for evaluating 5-year postoperative recurrence risk in stage Ⅰ NSCLC patients.

Objective A randomized controlled trial was conducted on colonoscopy inpatient and outpatients to compare the efficacy and safety of water exchange(WE)colonoscopy and CO2 convention insufflation colonoscopy in elderly patients.Methods 340 patients underwent fully sedated colonoscopy were randomly divided into two groups according to colonoscopy with either WE colonoscopy group(WE group)and CO2 insufflation colonoscopy group(CO2 group).The two groups were compared in terms of Boston bowel preparation scale(BBPS),withdrawal time,cecal intubation time,cecal intubation success rate,abdominal compression,willingness to repeat,polypdetectionrate(PDR),adenoma detection rate(ADR),and safety.Results The cecal intubation success rate was significantly higher in WE group(100.0%)compared with CO2 group(96.5%),the difference was statistically significant(P=0.013).The average cecal intubation time of WE group was(10.50±1.79)min,which was longer than that of CO2 group(7.55±1.50)min,and the difference was statistically significant(P<0.01).Comparison of withdrawal time and BBPS between the two groups,the differences were not statistically significant(P>0.05).The abdominal pressure rate was lower in WE group(5.9%)compared with CO2 group(13.5%),the difference was statistically significant(P=0.017).The rate of willingness to re-examination in the WE group was 98.2%,which was significantly higher than the 93.5%in the CO2 group.The PDR in WE group(80.6%)was higher than that in CO2 group(70.6%),the ADR in WE group(67.1%)was higher than that in CO2 group(50.6%),the differences were statistically significant(P<0.05).Multivariate Logistic regression analysis showed that WE group was an effective factor in improving ADR(O＾R=2.027,P<0.01).The overall adverse events were less than 3%,with no difference between the two groups(P=1.000).Conclusion The use of WE colonoscopy has a better improved efficacy in elderly patients,and safety should be ensured by individualized assessment of the patient's co-morbidities,bowel preparation tolerance,and willingness prior to the procedure.

Objective In this study,clinical data of Alzheimer's disease(AD)patients,structural magnetic resonance imaging(sMRI)data,and positron emission tomography(PET)data were used to construct an auxiliary diagnostic model with good classification effects,so as to formulate a personalized treatment plan at the early stage of the patients,which is of great significance for the prevention and treatment of AD.Methods In this study,a total of 401 study subjects containing complete sMRI images and PET images were selected from the ADNI-1(Alzheimer's disease neuroimaging initiative-1,ADNI-1)database.We used statistical parameters mapping(SPM)and voxel-based morphometric(VBM)analysis of MATLAB to perform pre-processing operations such as spatial normalization and skull stripping on sMRI images and PET images of the study subjects.With the help of the brain atlas was used to segment the brain tissue structure.After that,the segmented gray matter was extracted from the corresponding brain regions based on anatomical automatic labeling,and the feature values of all brain regions were obtained.Then the extracted brain region feature values are then subjected to fisher score,support vector machine-recursive feature elimination(SVM-RFE)and least absolute shrinkage and selection operator(LASSO),a hybrid filtered-wrapped-embedded feature selection method with three different principles,to realize the dimensionality reduction of high-dimensional image data.Finally,the PAC-Bayesian strategy boosting based multi-view learning(PB-MVBoost)model is constructed based on multi-view decision fusion for clinical,sMRI and PET data.And it is compared with the traditional machine learning models support vector machine(SVM),decision tree(DT),K-nearest neighbor(KNN),random forests(RF),adaptive boosting(AdaBoost),and extreme gradient boosting(XGBoost)which are constructed after concatenating views.It is compared with multi-view multi-kernel learning models(AverageMKL,EasyMKL)and multi-view confusion matrix boosting,which is also the same multi-view decision fusion.Results Among all the multi-view fusion models of AD-MCI,the PB-MVBoost model based on decision fusion has the best performance(accuracy=0.98,F1-score=0.97,precision=0.98,recall=0.96,MSE=0.07).Among all the multi-view fusion models of MCI-NC,the model performance of PB-MVBoost based on decision fusion was the best(accuracy=0.99,F1-score=0.98,precision=0.99,recall=0.98,MSE=0.05).Conclusion In the classification of AD-MCI and MCI-NC,the distinction and calibration degree of PB-MVBoost model were optimized,indicating that the auxiliary diagnosis model of Alzheimer's disease constructed by PB-MVBoost classifier based on decision fusion performed the best,which could improve the recognition of patients with mild cognitive impairment and then assist clinical diagnosis.

Sepsis-associated encephalopathy (SAE) is one of the complications of sepsis, causes cognitive dysfunction ranging from mild attention deficits to progression into coma, which severely impairs patients' ability to live and mental health, and increases the long-term disability and mortality rates. Although the clinical attention to SAE has been increasing in recent years, effective interventions to improve cognitive dysfunction in sepsis survivors are still in the preclinical stage. The pathogenesis of SAE is numerous and complex, and mitochondrial dysfunction, as one of the key pathogenic mechanisms, plays a role in the cognitive development process through oxidative stress imbalance, energy metabolism disorders, and activation of apoptosis signaling pathway. The present review systematically integrates the recent studies on mitochondrial dysfunction in the development of cognitive disorders. This review systematically integrates the cutting-edge research results in recent years, discusses the mitochondrial structural disruption, mitochondrial kinetic abnormalities, respiratory chain dysfunction, and comprehensively comprehends the research progress of mitochondria-targeted antioxidant, mitochondrial autophagy activator, mitochondrial biosynthesis modifier and other novel intervention strategies in improving cognitive function of SAE patients, with the aim of providing theoretical basis for the breakthrough of the current status of clinical treatment of SAE and the targeting of mitochondria for treatment. The aim is to provide theoretical basis for breaking through the status of SAE clinical treatment and targeting mitochondrial therapy.
Humans ; Sepsis-Associated Encephalopathy/metabolism* ; Mitochondria/metabolism* ; Sepsis/complications* ; Oxidative Stress ; Cognitive Dysfunction ; Autophagy

Objective:To explore the incidence of delirium in patients of advanced age hospitalized in internal medicine departments and analyze its influencing factors.Methods:A retrospective analysis was conducted on the medical records of 586 patients of advanced age hospitalized in internal medicine departments at the Beijing University of Chinese Medicine Third Affiliated Hospital from May 2023 to May 2024. Patients were divided into a delirium group and a non-delirium group based on whether delirium occurred. Univariate analysis and binary Logistic regression analysis were used to explore the factors influencing delirium in patients of advanced age hospitalized in internal medicine departments.Results:Among 586 patients of advanced age hospitalized in internal medicine departments, the incidence of delirium was 21.2% (124/586). Binary Logistic regression analysis showed that age, activities of daily living (Barthel Index), folate deficiency, sleep disorders, and indwelling catheters were factors influencing delirium in patients of advanced age hospitalized in internal medicine departments ( P<0.05) . Conclusions:The incidence of delirium is high among patients of advanced age hospitalized in internal medicine departments. Healthcare professionals should pay particular attention to elderly patients with advanced age, limited activities of daily living, folate deficiency, sleep disorders, and indwelling catheters, and should implement targeted preventive strategies as early as possible.