OBJECTIVE To explore the risk factors for polymyxin-and carbapenem-resistant Klebsiella pneumoni-ae(PR-CRKP)infection and establish the prediction model.METHODS The clinical data were retrospectively col-lected from the patients with CRKP infection who were treated in the First Affiliated Hospital of Xi'an Jiaotong University from Jan.2023 to Mar.2024.The enrolled patients were divided into the CRKP group and the PR-CRKP group according to the result of drug susceptibility testing for polymyxin B.Totally 203 patients who were treated from Jan.2023 to Dec.2023 were assigned as the modeling group,and 91 patients who were treated from Jan.2024 to Mar.2024 were assigned as the validation group.Multivariate logistic regression analysis was per-formed for the risk factors for PR-CRKP infection,nomogram was built up for prediction of PR-CRKP infection by R software,and the predictive efficacy of the model was evaluated by means of receiver operating characteristic(ROC)curves.RESULTS The result of univariate analysis showed that the proportions of patients who received fi-berobronchoscopy,endotracheal intubation/tracheotomy,were complicated with other carbapenem-resistant or-ganisms(CROs)infections,bloodstream infections,were treated in intensive care unit(ICU)and had the history of exposure to polymyxins and carbapenems 3 months before the admission were higher in the PR-CRKP group than in the CRKP group(P＜0.05);the length of hospital stay and duration of use of polymyxins and carbapene-ms were longer in the PR-CRKP group than in the CRKP group(P＜0.05).Multivariate logistic regression analy-sis indicated that complication with other CROs infections,history of exposure to polymyxins and carbapenems 3 months before the admission,duration of use of polymyxins and ICU stay were the risk factors for the PR-CRKP infection(P＜0.05).The area under the curve(AUC)of the predictive model was 0.898 in the modeling group,with the sensitivity 80.33％,the specificity 84.51％.ROC curve analysis showed that the AUC was 0.901 in the validation group,with the sensitivity 75.00％,the specificity 92.73％.CONCLUSION The prediction model that is established based on the result of multivariate analysis has high value in prediction of PR-CRKP infection.

OBJECTIVE: To explore the effect of light music therapy on delirium in intensive care unit (ICU) patients undergoing invasive mechanical ventilation, and provide evidence-based support for clinical prevention of delirium. METHODS: A prospective randomized controlled trial was conducted. 140 patients with invasive mechanical ventilation admitted to the department of respiratory and critical care medicine of First Affiliated Hospital of Guangxi Medical University from January 2024 to January 2025 were enrolled. The patients were divided into intervention group and control group using a random number table method. The control group received routine treatment and nursing care, while the intervention group received light music therapy three times a day for 30 minutes each time for 7 consecutive days. The confusion assessment method-ICU (CAM-ICU) was used to evaluate delirium, and the incidence of delirium within 7 days was statistically analyzed. Richmond agitation-sedation score (RASS), critical care pain observation tool (CPOT) score, mechanical ventilation duration, the length of ICU stay, and ICU stay expenses were record. RESULTS: 129 cases were ultimately included, including 64 cases in the control group and 65 cases in the intervention group. There was no statistically significant difference in baseline data between the two groups, indicating comparability. The incidence of delirium in the intervention group was significantly lower than that in the control group (27.7% vs. 51.6%, χ ² = 7.687, P = 0.006). There was no significantly difference in RASS score between the two groups before enrollment (P = 0.840). After intervention, the RASS score in the intervention group significantly decreased, from 2.00 points on the 1st day of enrollment to 0.00 points on the 7th day, while the control group only decreased from 2.00 points to 1.50 points. The decreasing trend of the intervention group was more pronounced, especially on the 3rd day (P = 0.047) and the 7th day (P =0.005), with significant differences between the groups. The time effect (F = 18.929, P < 0.001), group effect (F = 6.655, P = 0.011), and time group interaction effect (F = 7.372, P < 0.001) of the two groups of RASS score were significant, suggesting that light music therapy has better timeliness and sustainability in improving patients' sedation status. There was no significantly difference in CPOT score between the two groups before enrollment (P = 0.902). After intervention, the CPOT score in the intervention group rapidly decreased from 3.00 points before enrollment to 1.00 points on the 1st day, and continued until the 7th day, while the control group showed a slower decrease from 2.50 points to 2.00 points and only dropped to 1.00 points on the 7th day. There were significant differences on 1st day and 3rd day between two groups (both P < 0.05). The time effect (F = 28.125, P < 0.001), group effect (F = 11.580, P = 0.001), and time group interaction effect (F = 4.048, P = 0.020) of the two groups of CPOT score were significant, indicating that light music therapy has better pain control, but the interaction effect is low, indicating that the impact of the intervention on the CPOT score was mainly concentrated in the early stage (1-3 days), and the long-term effect may be influenced by other factors. Compared with the control group, the intervention group showed a significant reduction in mechanical ventilation time (days: 10.57±2.94 vs. 11.95±3.74, P = 0.021) and the length of ICU stay (days: 14.91±4.37 vs. 17.53±4.83, P = 0.002). The ICU hospitalization expenses of the intervention group was slightly lower than that of the control group [ten thousand yuan: 22.431 (12.473, 28.489) vs. 29.362 (11.996, 41.389)], but the difference was not statistically significant (P = 0.086). CONCLUSIONS Light music therapy can effectively reduce the incidence of delirium in patients undergoing invasive mechanical ventilation, improve consciousness and pain perception, shorten mechanical ventilation time and hospital stay, and has significant clinical promotion value high-quality studies.
Humans ; Delirium/prevention & control* ; Intensive Care Units ; Respiration, Artificial ; Music Therapy ; Prospective Studies ; Male ; Female ; Middle Aged ; Critical Care ; Aged

OBJECTIVES: This study aimed to use machine learning algorithms to build a prediction model of the first permanent molar caries of 9-year-old children in Suzhou and screen out risk factors. METHODS: Random stratified whole group sampling was applied to randomly select 9-year-old students from 38 primary schools in 14 townships and streets in Wuzhong District for oral examination and questionnaire survey. Multifactor Logistics regression was used to analyze the risk factors of tooth decay. The data set was randomly divided into training sets and verification sets according to 8∶2, and R 4.3.1 was used to build five machine learning algorithms: random forest, decision tree, extreme gradient boosting (XGBoost), Logistics regression, and lightweight gradient enhancement (LightGBM). The predictive effect of these five models was evaluated using the area under the characteristic curve (AUC). The marginal contribution of quantitative characteristics to the caries prediction model was determined through Shapley additive explanations (SHAP). RESULTS: This study included 7 225 samples that met the standard. The caries rate of the first permanent molar was 54.96%. Multifactor Logistic regression analysis showed that sweet drinks, dessert and candy, snack frequency, and snacks before going to bed after brushing teeth were correlated with the occurrence of first permanent molar caries (P<0.05). The AUC values of decision tree, Logistic regression, LightGBM, random forest, and XGBoost were 75.5%, 83.9%, 88.6%, 88.9%, and 90.1%, respectively. Compared with the variables after single heat coding, the SHAP value of high-frequency sweets (such as dessert candy ≥2 times a day, mother's sugary diet ≥2 times a day) and bad oral hygiene habits (such as frequent snacks before going to bed after brushing teeth and irregular brushing teeth) exhibited the highest positive. CONCLUSIONS XGBoost algorithm has a good prediction effect for first permanent molar caries in 9-year-old children. High-frequency sweet factors and bad oral hygiene habits have a strong positive impact on the risk of first permanent molar caries and are key drivers that can be used in the formulation of targeted interventions.
Humans ; Dental Caries/epidemiology* ; Child ; Machine Learning ; China/epidemiology* ; Molar ; Risk Factors ; Female ; Logistic Models ; Male ; Decision Trees ; Algorithms

OBJECTIVE To investigate the risk factors for carbapenem-resistant gram-negative bacteria(GNB)bloodstream infection(BSI)in patients with hematological malignancies(HMs)and their prognosis,and to devel-op a nomogram prediction model.METHODS A total of 316 patients with HMs and GNB-BSI admitted to the First Affiliated Hospital of Xi'an Jiaotong University from Jan.2017 to Dec.2022 were selected as the training set,and 106 patients admitted from Jan.2023 to Oct.2024 were selected as the validation set.Variables were selected by lasso regression and multifactor logistic regression,and a nomogram model was constructed.The prediction model was internally validated by the receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis(DCA),respectively.RESULTS Granulocytopenia for ≥7 days(OR=14.525),use of cephalosporins/β-lactamase inhibitors within 30 days before BSI(OR=3.510),exposure history of carbapenem antibacterial drug(OR=4.840)and albumin＜30 g/L(OR=2.697)were risk factors for CR-GNB BSI in patients with HMs(P＜0.05).Septic shock(OR=6.934),central venous catheterization(OR=5.586),inappropriate empirical antibac-terial drug therapy(OR=4.744),CR-GNB infection(OR=2.916)and albumin＜30 g/L(OR=3.324)were risk factors for 30-day mortality in patients with HMs and GNB-BSI(P＜0.05).Based on these indicators,two nomogram models were constructed.The areas under the ROC curve(AUC)for the internal validation set were 0.775 and 0.849,respectively.The calibration curves demonstrated high predictive performance for the pre-diction models(P=0.998 and 0.660,respectively),and DCA showed high clinical application value for both models.CONCLUSION The nomogram prediction model constructed in this study based on multifactor analy-sis not only demonstrates good predictive value but also exhibits significant clinical efficacy,aiding in the early i-dentification of high-risk patients for targeted therapy.

OBJECTIVE To investigate the risk factors for carbapenem-resistant gram-negative bacteria(GNB)bloodstream infection(BSI)in patients with hematological malignancies(HMs)and their prognosis,and to devel-op a nomogram prediction model.METHODS A total of 316 patients with HMs and GNB-BSI admitted to the First Affiliated Hospital of Xi'an Jiaotong University from Jan.2017 to Dec.2022 were selected as the training set,and 106 patients admitted from Jan.2023 to Oct.2024 were selected as the validation set.Variables were selected by lasso regression and multifactor logistic regression,and a nomogram model was constructed.The prediction model was internally validated by the receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis(DCA),respectively.RESULTS Granulocytopenia for ≥7 days(OR=14.525),use of cephalosporins/β-lactamase inhibitors within 30 days before BSI(OR=3.510),exposure history of carbapenem antibacterial drug(OR=4.840)and albumin＜30 g/L(OR=2.697)were risk factors for CR-GNB BSI in patients with HMs(P＜0.05).Septic shock(OR=6.934),central venous catheterization(OR=5.586),inappropriate empirical antibac-terial drug therapy(OR=4.744),CR-GNB infection(OR=2.916)and albumin＜30 g/L(OR=3.324)were risk factors for 30-day mortality in patients with HMs and GNB-BSI(P＜0.05).Based on these indicators,two nomogram models were constructed.The areas under the ROC curve(AUC)for the internal validation set were 0.775 and 0.849,respectively.The calibration curves demonstrated high predictive performance for the pre-diction models(P=0.998 and 0.660,respectively),and DCA showed high clinical application value for both models.CONCLUSION The nomogram prediction model constructed in this study based on multifactor analy-sis not only demonstrates good predictive value but also exhibits significant clinical efficacy,aiding in the early i-dentification of high-risk patients for targeted therapy.

OBJECTIVE To explore the risk factors for polymyxin-and carbapenem-resistant Klebsiella pneumoni-ae(PR-CRKP)infection and establish the prediction model.METHODS The clinical data were retrospectively col-lected from the patients with CRKP infection who were treated in the First Affiliated Hospital of Xi'an Jiaotong University from Jan.2023 to Mar.2024.The enrolled patients were divided into the CRKP group and the PR-CRKP group according to the result of drug susceptibility testing for polymyxin B.Totally 203 patients who were treated from Jan.2023 to Dec.2023 were assigned as the modeling group,and 91 patients who were treated from Jan.2024 to Mar.2024 were assigned as the validation group.Multivariate logistic regression analysis was per-formed for the risk factors for PR-CRKP infection,nomogram was built up for prediction of PR-CRKP infection by R software,and the predictive efficacy of the model was evaluated by means of receiver operating characteristic(ROC)curves.RESULTS The result of univariate analysis showed that the proportions of patients who received fi-berobronchoscopy,endotracheal intubation/tracheotomy,were complicated with other carbapenem-resistant or-ganisms(CROs)infections,bloodstream infections,were treated in intensive care unit(ICU)and had the history of exposure to polymyxins and carbapenems 3 months before the admission were higher in the PR-CRKP group than in the CRKP group(P＜0.05);the length of hospital stay and duration of use of polymyxins and carbapene-ms were longer in the PR-CRKP group than in the CRKP group(P＜0.05).Multivariate logistic regression analy-sis indicated that complication with other CROs infections,history of exposure to polymyxins and carbapenems 3 months before the admission,duration of use of polymyxins and ICU stay were the risk factors for the PR-CRKP infection(P＜0.05).The area under the curve(AUC)of the predictive model was 0.898 in the modeling group,with the sensitivity 80.33％,the specificity 84.51％.ROC curve analysis showed that the AUC was 0.901 in the validation group,with the sensitivity 75.00％,the specificity 92.73％.CONCLUSION The prediction model that is established based on the result of multivariate analysis has high value in prediction of PR-CRKP infection.

Objective To investigate the distribution and antimicrobial resistance of clinical isolates in the First Affiliated Hospital of Xi'an Jiaotong University in 2022 for rational use of antibiotics in clinical practice.Methods Nonduplicate clinical isolates were collected from January 1,2022 to December 31,2022.Antimicrobial susceptibility testing was carried out using Kirby-Bauer method and automated systems.The data were analyzed using WHONET 5.6 software and interpreted according to the Clinical and Laboratory Standards Institute(CLSI)breakpoints(2021 Edition).Results Of the 8 638 clinical isolates,gram negative bacteria and gram positive bacteria accounted for 60.8％(5 253/8 638)and 39.2％(3 385/8 638),respectively.The prevalence of methicillin-resistant strains was 33.0％in S.aureus(MRSA),75.8％in S.epidermidis(MRSE),and 51.9％in other coagulase-negative Staphylococcus(MRCNS).No staphylococcal strains were found resistant to vancomycin.The prevalence of vancomycin-resistant E.faecium was 0.6％,and no vancomycin-resistant E.faecalis was found.E.faecalis strains showed higher resistance rate to linezolid(5.2％)than E.faecium(0.7％).The prevalence of carbapenem-resistant Enterobacterales(CRE)was 7.9％,specifically 12.1％for carbapenem-resistant K.pneumoniae(CRKP)and 1.6％for carbapenem-resistant E.coli(CREC).The prevalence of carbapenem-resistant P.aeruginosa(CRPA)and carbapenem-resistant A.baumannii(CRAB)was 30.9％and 77.0％,respectively.Conclusions Clinical microbiology laboratories should strengthen the collection and testing of clinical specimens from the sites of infection in order to improve pathogenic diagnosis and antimicrobial resistance surveillance.This is conducive to the rational use of antibiotics and reduce the further spread of multidrug-resistant bacteria.

Objective To investigate the diagnostic value of serum anti-Müllerian hormone combined with sex hormones for polycystic ovary syndrome ( PCOS).Methods The serum levels of anti-Müllerian hormone ( AMH), testosterone ( T), luteinizing hormone ( LH), follicle-stimulating hormone (FSH) and the estradiol ( E2) were measured by electrochemiluminescence method in 82 patients with PCOS and 60 controls. The sensitivities, specificities and the areas under the receiver operating characteristic curves ( ROC-AUC) of the indicators and their combination for diagnosis of PCOS were compared by chi-square test and Z test separately.The correlations of serum AMH levels with age and sex hormones levels were analyzed separately by Spearman correlation analysis .Results The levels of serum AMH, T, LH and LH/FSH ratio in patients with PCOS were obviously higher than those in controls (62.19 pmol/L vs 27.63 pmol/L, 1.39 nmol/L vs 0.88 nmol/L, 12.72 IU/L vs 6.44 IU/L, 2.17 vs 1.17, U＝592.00, 1 096.00, 1 233.50, 1 134.00, all P＜0.01).The sensitivity of AMH (80.5%, 66/82) for diagnosis of PCOS was higher than that of LH (62.2%, 51/82) and LH/FSH ratio (54.9%, 45/82, χ2＝5.6, 13.79, all P＜0.05), but no significant difference was found when comparing with T (72%, 59/82, χ2＝1.71, P＞0.05 ) .The sensitivity of AMH ( 80.5%, 66/82 ) increased when combined with T (89.0%, 73/82), LH (87.8%, 72/82) and T+LH (95.10%, 78/82, χ2＝5.14, 4.17, 10.08, all P＜0.05), but no significant change by the combination of AMH +LH/FSH (85.4%, 70/82, χ2＝2.25, P＞0.05) .The specificity of AMH (80%, 48/60) for diagnosis of PCOS was no significant difference compared with that of T (71.7%, 43/60), LH (85%, 51/60), and LH/FSH ratio (91.7%, 55/60) (χ2＝3.20, 0.36, 2.77, all P＞0.05) .Also no increase when combined with T (71.7%, 43/60), LH (73.3%, 44/60), LH/FSH (75%, 45/60) and T +LH (66.7%, 40/60, χ2＝3.20, 2.25, 1.33, 3.38, all P＞0.05).The ROC-AUC of multiple indicators for diagnosis of PCOS were compared , AMH (0.880) was higher than T, LH and LH/FSH ratio (0.778, 0.760, 0.778, Z＝2.12, 2.46, 2.12, all P＜0.05), but no significant differences were found comparing with AMH and the combination of AMH +T, AMH+LH, AMH+LH/FSH and AMH+T+LH (0.892, 0.897, 0.898, 0.902, Z＝0.31, 0.45, 0.48, 0.59, all P＞0.05).Serum AMH levels were positively correlated with T , LH levels and LH/FSH ratio (r＝0.258, 0.241, 0.290, all P＜0.05), but not correlated with age in PCOS group (r＝-0.178, P＞0.05).In the control group, AMH levels had no correlations with T, LH levels and LH/FSH ratio (r＝0.025, 0.104, 0.111, P＞0.05), while negatively correlated with age (r＝-0.307, P＜0.05).The cutoff value of AMH for diagnosis of PCOS decreased with age .Conclusions The sensitivity of AMH for diagnosis of PCOS was higher than that of LH and LH /FSH ratio, and the sensitivity could be further improved by the combination with T or /and LH without reducing the specificity .Age-stratified cut-off values of AMH were better for accurate diagnosis of PCOS.

DCC Receptor ; chemistry ; metabolism ; Fibronectin Type III Domain ; Humans ; Models, Molecular

Objective: To investigate the relationship between the status of epidermal growth factor receptor (EGFR) mutations and brain metastases in patients with lung adenocarcinoma. Methods: From August 2010 to May 2015, a total of 1 063 lung adenocarcinoma patients with identified status of EGFR mutations in Shanxi Cancer Hospital were enrolled, of which 456 patients had EGFR mutations. Multivariate Logistic regression model was used to analyze the correlation between EGFR mutation status and brain metastases in patients with lung adenocarcinoma. Results: In 125 patients with brain metastases before initial treatment, 65 patients had EGFR mutations, including 36 patients with deletion mutations in exon 19. The frequency of EGFR 19 exon mutation was 28.8% (36/125). Among 456 patients with EGFR mutations, 65(14.3%) patients were with brain metastases, in which 36(55.0%) had deletion mutations in exon 19. The multivariate analysis showed that age, Eastern Cooperative Oncology Group (ECOG) score, EGFR mutations and N staging were associated with brain metastases(P<0.05). Further subgroup multivariate analyses showed that age, ECOG score, mutation status in exon 19 and N staging were associated with brain metastases (P<0.05). Conclusions EGFR mutation status is related to brain metastases. Mutations in EGFR exon 19 is an independent risk factor for brain metastases.