Objective:To construct an evaluation indicator system for accessories of patient monitor,so as to provide a basis for clinical management,equipment procurement,and technical improvement for accessories of medical monitor.Methods:The initial selection indicators of corresponding accessories of three types of monitoring of medical monitors,including electrocardiogram(ECG),blood oxygen saturation(SpO2)and non-invasive blood pressure(NIBP),were determined through literature research,expert consultation,and actual investigation.The Delphi method was adopted to conduct two rounds of questionnaire consultation for experts from clinical medicine,biomedical engineering and other fields in medical institutions included Sichuan Provincial People's Hospital,The Affiliated Hospital of Southwest Medical University and Medical Institute of Chengdu Institute of Metrology Verification and Testing.The evaluation indicators were screened and optimized,and the Analytic Hierarchy Process(AHP)was used to calculate the weights of each indicator.The consistency test was conducted to verify the rationality of the evaluation indicator system.Results:The evaluation indicator system for accessories of medical monitor included three first-level indicators:clinical value,cost value,and management value.The number of second-level indicators about ECG,SpO2 and NIBP of evaluation indicator system were respectively 10,9 and 8,and the number of third-level indicators of that were respectively 20,19,and 14.In the first-level indicators,the clinical value had the highest weight,with 72.49%for ECG,70.88%for SpO2 and 70.32%for NIBP.In the second-level indicators,the accuracy(28.70%for ECG,38.13%for SpO2 and 43.03%for NIBP)and safety(27.47%for ECG,26.48%for SpO2 and 23.06%for NIBP)were the core indicators.The weights of cost value and management value were between 14.62%and 17.41%,and between 12.27%and 12.89%,respectively.Conclusion:The evaluation indicator system for accessories of medical monitor integrates multi-dimensional expert opinions and quantitative analysis,highlights the priority principle for clinical performance.It can provide theoretical support for optimizing selection about accessory for medical institutions,and improving quality of monitoring,and promoting standardized management in the industry.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Objective:To investigate the potential of praeruptorin A (PA) in alleviating inflammatory damage in sepsis through the inhibition of ferritin expression.Methods:C57BL/6 mice were intraperitoneally injected with lipopolysaccharide (LPS) to establish the model of sepsis. After 6 and 12 h of PA intervention, serum levels of inflammatory cytokines IL-6 and TNF-α were measured by ELISA. Kidney tissues were collected at 72 h for HE staining to assess inflammatory cell infiltration and tissue damage. Human neutrophils were divided into four groups: control, LPS, ferritin, and LPS+ ferritin groups. After 12 h of intervention, qRT-PCR was used to detect the expression of IL-6 and TNF-α mRNA. In order to observe the effect of PA on the expression of inflammatory cytokines and ferritin, human neutrophils were grouped into control, LPS, and LPS+ PA (2/3/4 μmol/L) groups. After 12 h of intervention, qRT-PCR was performed to measure the expression of IL-1β, IL-6, TNF-α, and ferritin mRNA; ELISA was used to quantify the levels of IL-1β, IL-6, and TNF-α in culture supernatants; Western blot was used to analyze the expression of ferritin. Molecular docking was conducted to verify interactions between PA and ferritin.Results:Significant inflammatory cell recruitment, tissue damage, and elevated serum levels of IL-6 and TNF-α ( P<0.01) were observed in mice with LPS-induced sepsis. PA significantly inhibited cytokine secretion ( P<0.01) and alleviated tissue injury in sepsis mice. In human neutrophil models, ferritin upregulated the expression of IL-6 and TNF-α mRNA ( P<0.01); LPS stimulation alone increased the expression of IL-1β, IL-6, TNF-α, and ferritin at both mRNA and protein levels ( P<0.01), while co-stimulation with PA (3/4 μmol/L) significantly reversed the aforementioned results ( P<0.01). Molecular docking confirmed there were interaction sites between PA and ferritin. Conclusion:PA inhibits the release of inflammatory cytokines and alleviates tissue damage in sepsis, and the potential mechanism may involve modulating ferritin expression to suppress inflammatory responses.

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. The introduction of the foundation model has revolutionized the application of AI in medical treatment and facilitated its integration into clinical practice. This review emphasizes the clinical application of AI in PCa by discussing recent advancements from both pathological and imaging perspectives. Furthermore, it explores the current challenges faced by AI in clinical applications while also considering future developments, aiming to provide a valuable point of reference for the integration of AI and clinical applications.
Humans ; Prostatic Neoplasms/diagnosis* ; Male ; Artificial Intelligence ; Deep Learning ; Prognosis

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

OBJECTIVES: To explore the risk factors of feeding intolerance (FI) in critically ill children receiving enteral nutrition (EN) and to construct a prediction nomogram model for FI. METHODS: A retrospective study was conducted to collect data from critically ill children admitted to the Pediatric Intensive Care Unit of Xiangya Hospital, Central South University, between January 2015 and October 2020. The children were randomly divided into a training set (346 cases) and a validation set (147 cases). The training set was further divided into a tolerance group (216 cases) and an intolerance group (130 cases). Multivariate logistic regression analysis was used to screen for risk factors for FI in critically ill children receiving EN. A nomogram was constructed using R language, which was then validated on the validation set. The model's discrimination, calibration, and clinical net benefit were evaluated using receiver operating characteristic curves, calibration curves, and decision curves. RESULTS: Duration of bed rest, shock, gastrointestinal decompression, use of non-steroidal anti-inflammatory drugs, and combined parenteral nutrition were identified as independent risk factors for FI in critically ill children receiving EN (P<0.05). Based on these factors, a nomogram prediction model for FI in critically ill children receiving EN was developed. The area under the receiver operating characteristic curve for the training set and validation set was 0.934 (95%CI: 0.906-0.963) and 0.852 (95%CI: 0.787-0.917), respectively, indicating good discrimination of the model. The Hosmer-Lemeshow goodness-of-fit test showed that the model had a good fit (χ 2=12.559, P=0.128). Calibration curve and decision curve analyses suggested that the model has high predictive efficacy and clinical application value. CONCLUSIONS Duration of bed rest, shock, gastrointestinal decompression, use of non-steroidal anti-inflammatory drugs, and combined parenteral nutrition are independent risk factors for FI in critically ill children receiving EN. The nomogram model developed based on these factors exhibits high predictive efficacy and clinical application value.
Humans ; Critical Illness ; Enteral Nutrition/adverse effects* ; Male ; Risk Factors ; Female ; Child, Preschool ; Infant ; Nomograms ; Retrospective Studies ; Child ; Logistic Models

OBJECTIVES: To study the impact of family socioeconomic status on children's reading fluency and the chain mediation effect of family reading environment and children's living and learning styles in this relationship. METHODS: A total of 473 children from grades 2 to 6 in two primary schools in Nanjing were selected through stratified random sampling. The children's reading fluency was assessed, and a questionnaire was used to collect information on family socioeconomic status, family reading environment, and children's living and learning styles. The mediation model was established using the Process macro in SPSS, and the Bootstrap method was employed to test the significance of the mediation effects. RESULTS: Family socioeconomic status, family reading environment, and children's living and learning styles were significantly positively correlated with reading fluency (P<0.001). The family reading environment and children's living and learning styles mediated the relationship between family socioeconomic status and children's reading fluency. Specifically, the independent mediation effect of family reading environment accounted for 11.02% of the total effect, while the independent mediation effect of children's living and learning styles accounted for 10.79%. The chain mediation effect of family reading environment and children's living and learning styles accounted for 7.41% of the total effect. CONCLUSIONS Family socioeconomic status can affect children's reading fluency through three pathways: family reading environment, children's living and learning styles, and the chain mediation effect of family reading environment and children's living and learning styles.
Humans ; Child ; Male ; Female ; Reading ; Learning ; Social Class ; Family

OBJECTIVE: To study the clinical and laboratory characteristics of monoclonal gammopathy anemia and explore the risk factors associated with anemia in monoclonal gammopathy. METHODS: A retrospective analysis was conducted on 5 539 patients who underwent immunofixation electrophoresis at the First Affiliated Hospital of Chengdu Medical College from January 2016 to February 2024. A total of 351 newly diagnosed M protein positive patients were selected as the study subjects, including 270 in the anemia group and 81 in the non-anemia group. Laboratory test results were compared between the two groups, and logistic regression models were used to analyze the risk factors for anemia. ROC curve analysis was performed to evaluate the predictive value of risk factors for anemia in monoclonal gammopathy. RESULTS: The proportion of non-anemic patients was 23.1% (81/351), with a median age of 67(60-75) years; the proportion of anemic patients was 76.9% (270/351), with a median age of 70(63-75) years. The total protein, globulin, urea, creatinine, uric acid, β₂-microglobulin, and ceruloplasmin levels in the anemia group were higher than those in the non-anemia group ( P < 0.05), while albumin, neutrophil count, lymphocyte count, monocyte count, complement C3, complement C4, haptoglobin, and transferrin levels were lower in the non-anemia group ( P < 0.05). After adjustment, multivariate logistic regression analysis shows that elevated GLB, increased β₂-MG, decreased ANC, and reduced complement C3 were independent risk factors for anemia in monoclonal gammopathy ( P < 0.05). ROC curve analysis demonstrates that GLB, β₂-MG, ANC, and complement C3 had good predictive value for anemia associated with monoclonal gammopathy. CONCLUSION Elevated GLB, increased β₂-MG, decreased ANC, and reduced complement C3 are independent risk factors for anemia in monoclonal gammopathy (P < 0.05). The combined assessment of these four factors has good predictive value for anemia in monoclonal gammopathy.
Humans ; Retrospective Studies ; Anemia/complications* ; Aged ; Middle Aged ; Paraproteinemias/diagnosis* ; Risk Factors ; Male ; Female ; Logistic Models ; ROC Curve ; Complement C3

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

Objective:To investigate the risk of falls in patients with Parkinson's disease and establish and validate a prediction model.Methods:We selected 372 patients with Parkinson's disease at Sichuan Nanchong Mental Health Centre from January 2022 to Septem-ber 2023.The patients were divided in a 7:3 ratio into model group(260 cases)and validation group(112 cases).According to previ-ous literature and suspected factors found in clinical practice,we collected general information(sex,age,etc.)and disease-related factors(the duration of Parkinson's disease,the type of medications taken,etc.)that may be associated with falls in patients with Parkinson's disease.In the model group,between patients with and those without falls within 1 year as reported by the patients or their family members,potential predictors for falls were determined through comparison of general information and disease-related factors,least absolute shrinkage and selection operator(LASSO)regression,and multivariable logistic regression.Based on the significant factors,a nomogram model was established and validated.Results:In the model group,81(31.15%)of the 260 patients experienced falls.According to the LASSO regression and multivariable logistic regression results,alcohol consumption,the type of medications,the score of the Unified Parkinson's Disease Rating Scale part Ⅲ(UPDRS-Ⅲ),the Berg Balance Scale score,the presence of arthritis,and the presence of osteoporosis were independent factors influenc-ing falls in patients with Parkinson's disease.The area under curve(AUC)of the receiver operator characteristic curve(ROC)for pre-dicting the risk of falls in patients with Parkinson's disease was 0.896(95%CI=0.856-0.935)in the model group and 0.883(95%CI=0.840-0.926)in the validation group.The calibration curve analysis results showed that the prediction curves of the model and valida-tion groups closely fitted the standard curves.The decision curve analysis results indicated that when the probability threshold for pre-dicting the fall risk in Parkinson's disease using the nomogram was 0.10-0.90,the net benefit rate of the patients was greater than 0.Conclusion:The risk of falls in patients with Parkinson's disease are mainly influenced by factors such as alcohol consumption and the type of medications.The nomogram model established in this study can be used to predict the fall risk in patients with Parkinson's disease.