OBJECTIVE: To explore the co-morbid influencing factors of postmenopausal osteoporosis(PMOP) and dyslipidemia, and to provide evidence-based basis for clinical co-morbidity management. METHODS: Based on the 2017 to 2018 Beijing community cross-sectional survey data, PMOP patients were included and divided into the dyslipidemia group and the uncomplicated dyslipidemia group according to whether they were comorbid with dyslipidemia. Demographic characteristics, living habits and disease history were collected through questionnaires, and bone mineral density and bone metabolism biomarkers (osteocalcin, blood calcium, serum typeⅠprocollagen N-terminal prepeptide, etc.) were detected on site. Co-morbidity risk factors were analyzed using binary logistic regression. RESULTS: Three hundred and twenty patients with PMOP were included, including the comorbid group (75 patients) and the uncomplicated group (245 patients). The results showed that history of cardiovascular disease [OR=1.801, 95%CI(1.003, 3.236), P=0.049], history of cerebrovascular disease [OR=2.923, 95%CI(1.460, 5.854), P=0.002], frying and cooking methods[OR=5.388, 95%CI(1.632, 17.793), P=0.006], OST results[OR=0.910, 95%CI(0.843, 0.983), P=0.016], and blood Ca results [OR=60.249, 95%CI(1.862, 1 949.926), P=0.021] were the influencing factors of PMOP complicated with dyslipidemia. CONCLUSION Focus should be placed on the influencing factors of PMOP and dyslipidemia co-morbidities, with emphasis on multidimensional assessment, combining lifestyle interventions with bone metabolism marker monitoring to optimize co-morbidity management.
Humans ; Dyslipidemias/epidemiology* ; Female ; Middle Aged ; Osteoporosis, Postmenopausal/metabolism* ; Aged ; Cross-Sectional Studies ; Risk Factors ; Bone Density

PURPOSE: We carried out the study aiming to explore and analyze the risk factors, the distribution of pathogenic bacteria, and their antibiotic-resistance characteristics influencing the occurrence of surgical site infection (SSI), to provide valuable assistance for reducing the incidence of SSI after traumatic fracture surgery. METHODS: A retrospective case-control study enrolling 3978 participants from January 2015 to December 2019 receiving surgical treatment for traumatic fractures was conducted at Tangdu Hospital of Air Force Medical University. Baseline data, demographic characteristics, lifestyles, variables related to surgical treatment, and pathogen culture were harvested and analyzed. Univariate analyses and multivariate logistic regression analyses were used to reveal the independent risk factors of SSI. A bacterial distribution histogram and drug-sensitive heat map were drawn to describe the pathogenic characteristics. RESULTS: Included 3978 patients 138 of them developed SSI with an incidence rate of 3.47% postoperatively. By logistic regression analysis, we found that variables such as gender (males) (odds ratio (OR) = 2.012, 95% confidence interval (CI): 1.235 - 3.278, p = 0.005), diabetes mellitus (OR = 5.848, 95% CI: 3.513 - 9.736, p < 0.001), hypoproteinemia (OR = 3.400, 95% CI: 1.280 - 9.031, p = 0.014), underlying disease (OR = 5.398, 95% CI: 2.343 - 12.438, p < 0.001), hormonotherapy (OR = 11.718, 95% CI: 6.269 - 21.903, p < 0.001), open fracture (OR = 29.377, 95% CI: 9.944 - 86.784, p < 0.001), and intraoperative transfusion (OR = 2.664, 95% CI: 1.572 - 4.515, p < 0.001) were independent risk factors for SSI, while, aged over 59 years (OR = 0.132, 95% CI: 0.059 - 0.296, p < 0.001), prophylactic antibiotics use (OR = 0.082, 95% CI: 0.042 - 0.164, p < 0.001) and vacuum sealing drainage use (OR = 0.036, 95% CI: 0.010 - 0.129, p < 0.001) were protective factors. Pathogens results showed that 301 strains of 38 species of bacteria were harvested, among which 178 (59.1%) strains were Gram-positive bacteria, and 123 (40.9%) strains were Gram-negative bacteria. Staphylococcus aureus (108, 60.7%) and Enterobacter cloacae (38, 30.9%) accounted for the largest proportion. The susceptibility of Gram-positive bacteria to Vancomycin and Linezolid was almost 100%. The susceptibility of Gram-negative bacteria to Imipenem, Amikacin, and Meropenem exceeded 73%. CONCLUSION Orthopedic surgeons need to develop appropriate surgical plans based on the risk factors and protective factors associated with postoperative SSI to reduce its occurrence. Meanwhile, it is recommended to strengthen blood glucose control in the early stage of admission and for surgeons to be cautious and scientific when choosing antibiotic therapy in clinical practice.
Humans ; Surgical Wound Infection/epidemiology* ; Male ; Female ; Risk Factors ; Retrospective Studies ; Middle Aged ; Adult ; Case-Control Studies ; Fractures, Bone/surgery* ; Aged ; Drug Resistance, Bacterial ; Logistic Models ; Anti-Bacterial Agents/therapeutic use* ; Incidence ; Bacteria/drug effects*

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

This study was aimed at exploring novel auxiliary diagnostic biomarkers for brucellosis and their potential miR-NA-mRNA regulatory networks.High-throughput sequencing was used to compare miRNA expression differences in serum ex-osomes between patients with brucellosis and healthy controls.Subsequently,RT-qPCR was used to validate the expression of significantly upregulated exosomal miRNAs.The diagnostic value of these miRNAs was assessed with ROC curves,and bioin-formatics analyses were performed to investigate the potential roles of the miRNAs in brucellosis infection.The ROC curve a-nalysis indicated that the area under the curve for exosomal hsa-miR-11400(P＜0.05),hsa-miR-199a-5p(P＜0.05),and hsa-miR-148a-5p(P＜0.05)was 0.79,0.81,and 0.74,respectively.A total of 465 differentially expressed miRNAs and their tar-get genes were predicted,including 25 immune-related target genes,most of which were closely associated with cancer-related proteoglycans,NF-kappa B signaling pathways,and IL-17 signaling pathways.The constructed differentially expressed gene network indicated that the immune genes PLXNA2,IL17RA,PRKCA,CD22,ACVR1B,and CBL might be regulated by hsa-miR-199a-5p and hsa-miR-148a-5p.These findings suggest that exosomal miRNAs might serve as auxiliary diagnostic indicators for brucellosis.Our exosomal miRNA-mRNA regulatory network provides new insights into the pathogenesis and treatment of brucellosis.

Objective To investigate the perioperative management of antithrombotic drugs in patients undergoing non-cardiac surgery.Methods Patients on long-term antithrombotic drugs who underwent non-cardiac surgery in our hospital were included.Through interviews with patients and physicians,perioperative antithrombotic medication regimens were reviewed and compared with the"Multidisciplinary Expert Consensus on Perioperative Management of Antithrombotic Therapy"to evaluate compliance with consensus and analyze influencing factors.Results A total of 372 patients were included in the analysis.Among them,355 patients were on long-term antiplatelet therapy alone,and 17 were on long-term oral anticoagulantion.364(97.8％)discontinued antithrombotic medications prior to surgery.109 patients(29.3％)received low molecular weight heparin(LMWH)bridging therapy.Among the 355 patients on antiplatelet therapy,108(30.4％)had discontinuation durations consistent with the consensus recommendations,while 186(52.4％)discontinued medications for longer periods.Postoperatively,the average hospital stay for antiplatelet therapy patients was 6.64 days,with only 37(10.4％)resuming therapy during hospitalization.The average hospital stay for patients on anticoagulants was 9.94 days,with only 2(11.8％)resuming therapy during hospitalization.Regarding perioperative risk assessment,only 40(10.8％)of patients underwent additional internal medical evaluation for thromboembolic risk after medication discontinuation,with the remainder assessed soly by surgeons.Coronary heart disease was an independent risk factor associated with internal medical evaluation(OR 2.851,95％CI 1.160-7.011,P=0.022).For bleeding risk assessment,surgeons evaluations aligned with the consensus in 68.0％of cases,but surgeons tended to underestimate risk compared to the consensus.Conclusions In this single-center study,perioperative antithrombotic management showed low compliance with expert consensus,characterized by prolonged preoperative medication discontinuation,high rates of LMWH bridging,and low postoperative in-hospital resumption of therapy.A robust multidisciplinary collaboration system should be established to enhance comprehensive patient assessment.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]

Objective:To explore the multiple mediating roles of intrinsic motivation and proactive behavior in the influence mechanism of perceived overqualification on the information literacy of Operating Room nurses engaged in organ transplantation.Methods:On November 2023, 308 Operating Room nurses engaged in organ transplantation from 12 hospitals in China were selected for the survey using convenience sampling method. General information questionnaire, Information Literacy Self-Rating Scale for Clinical Nurses, the 9-item Scale of Perceived Over Qualification, Intrinsic Motivation Scale, and Proactive Behavior Scale were used to investigate and to construct the chain mediating model.Results:A total of 308 questionnaires were collected and 294 questionnaires were valid, with a valid recovery rate of 95.45%. The total scores of information literacy, perceived overqualification, intrinsic motivation and proactive behavior of 294 Operating Room nurses engaged in organ transplantation were (133.95±19.07), (23.71±7.82), (76.47±13.38) and (38.01±6.31) respectively. The indirect effect of perceived overqualification of Operating Room nurses engaged in organ transplantation on information literacy existed, with a total indirect effect value of -0.348. The specific indirect effect of intrinsic motivation was 40.80% of the total indirect effect, the specific indirect effect of proactive behavior was 31.03% of the total indirect effect, and the chain mediating effect of intrinsic motivation and proactive behavior was 28.16% of the total indirect effect.Conclusions:Multiple mediating roles of intrinsic motivation and proactive behavior in the influence mechanisms of perceived overqualification on the information literacy of Operating Room nurses involved in organ transplantation are established. Managers can improve the information literacy of Operating Room nurses engaged in organ transplantation by reducing their perceived overqualification and stimulating intrinsic motivation and proactive behavior.

Objective To investigate the perioperative management of antithrombotic drugs in patients undergoing non-cardiac surgery.Methods Patients on long-term antithrombotic drugs who underwent non-cardiac surgery in our hospital were included.Through interviews with patients and physicians,perioperative antithrombotic medication regimens were reviewed and compared with the"Multidisciplinary Expert Consensus on Perioperative Management of Antithrombotic Therapy"to evaluate compliance with consensus and analyze influencing factors.Results A total of 372 patients were included in the analysis.Among them,355 patients were on long-term antiplatelet therapy alone,and 17 were on long-term oral anticoagulantion.364(97.8％)discontinued antithrombotic medications prior to surgery.109 patients(29.3％)received low molecular weight heparin(LMWH)bridging therapy.Among the 355 patients on antiplatelet therapy,108(30.4％)had discontinuation durations consistent with the consensus recommendations,while 186(52.4％)discontinued medications for longer periods.Postoperatively,the average hospital stay for antiplatelet therapy patients was 6.64 days,with only 37(10.4％)resuming therapy during hospitalization.The average hospital stay for patients on anticoagulants was 9.94 days,with only 2(11.8％)resuming therapy during hospitalization.Regarding perioperative risk assessment,only 40(10.8％)of patients underwent additional internal medical evaluation for thromboembolic risk after medication discontinuation,with the remainder assessed soly by surgeons.Coronary heart disease was an independent risk factor associated with internal medical evaluation(OR 2.851,95％CI 1.160-7.011,P=0.022).For bleeding risk assessment,surgeons evaluations aligned with the consensus in 68.0％of cases,but surgeons tended to underestimate risk compared to the consensus.Conclusions In this single-center study,perioperative antithrombotic management showed low compliance with expert consensus,characterized by prolonged preoperative medication discontinuation,high rates of LMWH bridging,and low postoperative in-hospital resumption of therapy.A robust multidisciplinary collaboration system should be established to enhance comprehensive patient assessment.