Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

ObjectiveTo analyze the distribution characteristics of traditional Chinese medicine （TCM） syndrome elements in different risk populations of heart failure complicated with type 2 diabetes. MethodsClinical data of 675 type 2 diabetes patients were retrospectively collected. Lasso-multivariate Logistic regression was used to construct a clinical prediction nomogram model. Based on this， 441 non-heart failure patients were divided into a low-risk group （325 cases） and a high-risk group （116 cases） according to the median risk score of heart failure complicated with type 2 diabetes. TCM diagnostic information （four diagnostic methods） was collected for both groups， and factor analysis was applied to summarize the distribution of TCM syndrome elements in different risk populations. ResultsLasso-multivariate Logistic regression analysis identified age， disease duration， coronary heart disease， old myocardial infarction， arrhythmia， absolute neutrophil count， activated partial thromboplastin time， and α-hydroxybutyrate dehydrogenase as independent risk factors for heart failure complicated with type 2 diabetes. These were used as final predictive factors to construct the nomogram model. Model validation results showed that the area under the curve （AUC） of the receiver operating characteristic （ROC） curve for the modeling group and validation group were 0.934 and 0.935， respectively. The Hosmer-Lemeshow test （modeling group P = 0.996， validation group P = 0.121） indicated good model discrimination. Decision curve analysis showed that the curves for All and None crossed in the upper right corner， indicating high clinical utility. The low-risk and high-risk groups each obtained 14 common factors. Preliminary analysis revealed that the main disease elements in the low-risk group were qi deficiency （175 cases， 53.85%）， dampness （118 cases， 36.31%）， and heat （118 cases， 36.31%）， with the primary locations in the spleen （125 cases， 38.46%） and lungs （99 cases， 30.46%）. In the high-risk group， the main disease elements were yang deficiency （73 cases， 62.93%）， blood stasis （68 cases， 58.62%）， and heat （49 cases， 42.24%）， with the primary locations in the kidney （84 cases， 72.41%） and heart （70 cases， 60.34%）. ConclusionThe overall disease characteristics in different risk populations of type 2 diabetes patients with heart failure are a combination of deficiency and excess， with deficiency being predominant. Deficiency and heat are present throughout. The low-risk population mainly shows qi deficiency with dampness and heat， related to the spleen and lungs. The high-risk population shows yang deficiency with blood stasis and heat， related to the kidneys and heart.

Objective: To develop a simple digital chylous plasma device and validate its ability to accurately, standardly, and non-destructively determine chylous plasma in blood banks and clinical transfusions in hospitals. Methods: A digital chylous plasma assessment device was designed and manufactured. This device was used to measure the chylous degrees of chylous plasma samples before freezing, after freeze-thawing, before viral inactivation, and after viral inactivation. The measured chylosity index values were categorized according to the requirements specified in Appendix A of the Chinese national standard GB 18469-2001 "Quality Requirements for Whole Blood and Blood Components". This process established a digital standard for chylous plasma, enabling the identification of severe, moderate and mild chylous plasma, and non-chylous plasma. Results: The initial simple product of the digital chylous assessment device was successfully designed and manufactured. There was no significant difference in the degree of chylous plasma between pre-freezing 468.11±217.73 lux and post-thawing 538.91±273.39 lux of chylous plasma (P>0.05), or between pre-viral inactivation 858.33±387.79 lux and post-viral inactivation 928.33±166.51 lux of chylous plasma (P>0.05). The median of chylous degree values for plasma chylous index grades 0 to 6 were 45 lux, 250 lux, 620 lux, 835 lux, 1 130 lux, 1 390 lux, and 1 700 lux, respectively. The defined cutoff values/ranges for the chylous degree values corresponding to plasma chylous index grade 0 to 6 were ≤125 lux, 126-465 lux, 466-740 lux, 741-1 000 lux, 1 001-1 233 lux, 1 234-1 560 lux, and ≥1 561 lux. Conclusion: This study successfully developed the initial product of the digital chylous device and established digital standards for classifying chylous plasma. The device demonstrates the potential to meet the needs for assessment of chylous plasma in both blood banks and clinical transfusions in hospitals, thereby promoting the development and application of standardized, non-destructive chylous plasma assessment technology.

Objective To construct a regional collaborative cloud-based treatment model treatment model for patients with severe road traffic injuries,and to preliminarily evaluate the differences in nursing timeliness indicators and outcomes.Methods The regional collaborative cloud-based treatment platform includes 4 ports,including public security traffic police,pre-hospital emergency center,regional trauma center triage,and regional trauma center resuscitation unit.This forms a standardized real-time interactive treatment process between regional medical services and police for patients with severe road traffic injuries.Using a concurrent control study design,241 patients with severe road traffic injuries admitted to the emergency department of a regional trauma center in Zhejiang Province from May 2022 to May 2024 were selected as the study subjects.Among them,120 patients treated with the regional real-time collaborative cloud-based treatment model were designated as an experimental group,while 121 patients treated with the original trauma care process were designated as a control group.The differences in timeliness indicators and outcomes between the 2 groups were compared.Results The study included 241 patients with severe trauma.After the application of the regional collaborative cloud-based treatment model,the time from the scene of the accident to the hospital,the proportion of information early waming,completion time of pre-examination and triage,waiting time of the trauma team,the time of the first CT,the length of multidisciplinary consultation,and the time for completing hospitalization procedures in the experimental group were shorter than those in the control group(P＜0.05),the proportion of information early waming in the experimental group was 100％(120/120),and the proportion of information early waming in the control group was 52.1％(63/121).The difference between the two groups was statistically significant(P＜0.001).The survival rate of the experimental group was 90.8％(109/120),and that of the control group was 86.0％(104/121).There was no significant difference between the two groups(x2=1.399,P=0.237).Conclusion The regional collaborative cloud-based treatment model improves the timeliness and standardization of the treatment of patients with severe road traffic injury,which has certain reference significance and promotion value.

This report summarizes the emergency care and nursing interventions for a Parkinson's disease patient with severe hypothermia complicated by ventricular arrhythmia.Key nursing points included continuous core temperature monitoring with goal-directed,phased,progressive rewarming;proactive identification and rapid response to arrhythmias;precise fluid management and skin protection to dynamically optimize blood perfusion and pressure redistribution;vigilant prevention and early intervention of hypothermia-related complications.With multidisciplinary treatment and meticulous nursing care,the patient was successfully discharged after 17 days of hospitalization with a favorable recovery.At the three-month follow-up after discharge,the patient had recovered well with no recurrence of similar episodes.

Objective To investigate the predictive value of edema metabolic and hematoma dynamics changes on motor and cog-nitive recovery outcomes in patients with intracerebral hemorrhage(ICH).Methods The CT data of ICH patients were collected to evaluate hematoma volume changes from admission to day 3.On day 3,multivoxel magnetic resonance spectroscopy(MRS)was per-formed with region of interest located in the edema region and contralateral normal tissue.Motor and cognitive function recovery was assessed using the simplified F-M scale and the Montreal cognitive assessment(MoCA)on day 3 and at the 3-month follow-up,respec-tively.Overall clinical outcomes were assessed using the Glasgow outcome scale(GOS),and all patients were divided into good and poor outcome groups.Clinical data and metabolic differences in the edema region between the two groups were compared,respec-tively.Logistic regression analysis and receiver operating characteristic(ROC)curves were used to identify and evaluate independent prognostic factors.Subgroup analysis were performed via stratification of hematoma location.Results The logistic regression analy-sis indicated that intraventricular extension,hematoma changes,and the ratio of N-acetyl aspartate(NAA)around the hematoma to contralateral normal brain parenchyma NAA(rNAA)were inde-pendent prognostic factors for poor outcomes(P＜0.05).The area under the curve(AUC)for each factor and the combined model were 0.69,0.73,0.79,and 0.82,respectively.In patients with ICH in the basal ganglia region,△F-M was negatively correlated with hematoma changes and positively correlated with rNAA value(P＜0.001).In patients with ICH in the thalamic and lobar regions,△MoCA was not significantly correlated with hematoma changes(P＞0.05),but was positively correlated with rNAA value(P＜0.001).Conclusion The rNAA holds predictive value for motor and cognitive recovery outcomes following standard treatment.

Objective:To study the value of Logistic regression model and XGBoost model in predicting upper limb lymphedema after radical mastectomy.Methods:A total of 150 patients with breast cancer admitted to the Department of Breast Surgery of the Affiliated Hospital of Jining Medical College from Jan. 2023 to Jan. 2024 were collected as the study objects, all of whom underwent surgical treatment. The subjects were divided into the occurrence group (30 cases) and the non-occurrence group (120 cases) according to whether upper limb lymphedema occurred after operation. The clinical data of the patients in the study were collected, and the risk prediction models of upper limb lymphedema after radical mastectomy were constructed based on Logistic regression analysis and XGBoost method, respectively, and the predictive value of the two models was compared.Results:Among the 150 patients, 30 patients developed upper limb lymphedema after surgery, with an incidence of 20.00% (30/150) . The age, body mass index (BMI) level, clinical stage (stage III) , number of excised lymph nodes ≥ 10, postoperative non functional exercise, postoperative adjuvant radiotherapy, and proportion of hypertension in the incidence group were higher than those in the non incidence group ( t=3.21, 5.21, χ 2=30.68, 16.24, 12.40, 11.11, 8.58, P<0.05) . Logistic regression analysis showed that BMI, clinical stage (stage III) , number of lymph nodes removed ≥10, postoperative non-functional exercise, postoperative adjuvant radiotherapy and hypertension were all risk factors for upper limb lymphedema after radical mastectomy ( P<0.05) . ROC curve showed that the area under the curve (AUC) of multivariate Logistic regression and XGBoost model predicting upper limb lymphedema after radical mastectomy was 0.886 (95% CI: 0.843-0.941) and 0.874 (95% CI: 0.829-0.935) , respectively. There was no significant difference in AUC between the two models ( Z=1.34, P=0.462) . The Calibration curves of multivariate Logistic regression and XGBoost model were tested by Hosmer-Lemeshow, but there was no significant difference ( χ 2=0.83, P=0.516; χ 2=0.71, P=0.637) . Both models fit well. Conclusions:Multiple Logistic regression and XGBoost model were equally effective in predicting upper limb lymphedema after radical mastectomy. BMI, clinical stage (stage III) , number of lymph nodes removed ≥10, postoperative non-functional exercise, postoperative adjuvant radiotherapy, and hypertension are all important factors affecting upper limb lymphedema after radical mastectomy.

Objective To analyze the performances of electronic portal imaging device (EPID) in mechanical and dosimetry responses,and to investigate the feasibility of adopting EPID as a daily quality assurance (QA) equipment. Methods The EPID of Trilogy linear accelerator was tested for mechanical position repeatability and dose linear response. Then,a group of special fields were edited manually for simulations of field translation and symmetry deviations,and the sensitivities of EPID and MyQA Daily to field translation and symmetry deviations were evaluated,and moreover,the linear correlation between the set value and the measured value was analyzed. Finally,daily QA was conducted with EPID and MyQA Daily for 30 consecutive days,and the measurement results and time consumption were analyzed. Results The maximum deviation of EPID position repeatability was 0.4 mm,and the dose response was linearly correlated (R2>0.999). The symmetry deviation test results showed that both of EPID and MyQA Daily were capable to effectively detect the 0.2％ offset in symmetry,and a linear correlation was demonstrated between the set value and the measured results (R2>0.995). In translation test,the linear correlation of EPID was more explicit than that of MyQA Daily (R2=0.992 vs R2=0.976). In daily QA,all the measured results of EPID and MyQA Daily were within the clinic acceptance tolerance. Moreover,the mean value of Y-directional symmetry and flatness measured by EPID was approximately 1.00％ larger than MyQA Daily. The average time required by EPID was 50 s less than MyQA Daily[(129.97±4.16) s vs (184.53±4.23) s]. Conclusion EPID can be served as a reliable and efficient daily QA equipment for linear accelerator. However,it is not capable to be used as a criterion for evaluating linear accelerator performance.

Objective:To study the value of Logistic regression model and XGBoost model in predicting upper limb lymphedema after radical mastectomy.Methods:A total of 150 patients with breast cancer admitted to the Department of Breast Surgery of the Affiliated Hospital of Jining Medical College from Jan. 2023 to Jan. 2024 were collected as the study objects, all of whom underwent surgical treatment. The subjects were divided into the occurrence group (30 cases) and the non-occurrence group (120 cases) according to whether upper limb lymphedema occurred after operation. The clinical data of the patients in the study were collected, and the risk prediction models of upper limb lymphedema after radical mastectomy were constructed based on Logistic regression analysis and XGBoost method, respectively, and the predictive value of the two models was compared.Results:Among the 150 patients, 30 patients developed upper limb lymphedema after surgery, with an incidence of 20.00% (30/150) . The age, body mass index (BMI) level, clinical stage (stage III) , number of excised lymph nodes ≥ 10, postoperative non functional exercise, postoperative adjuvant radiotherapy, and proportion of hypertension in the incidence group were higher than those in the non incidence group ( t=3.21, 5.21, χ 2=30.68, 16.24, 12.40, 11.11, 8.58, P<0.05) . Logistic regression analysis showed that BMI, clinical stage (stage III) , number of lymph nodes removed ≥10, postoperative non-functional exercise, postoperative adjuvant radiotherapy and hypertension were all risk factors for upper limb lymphedema after radical mastectomy ( P<0.05) . ROC curve showed that the area under the curve (AUC) of multivariate Logistic regression and XGBoost model predicting upper limb lymphedema after radical mastectomy was 0.886 (95% CI: 0.843-0.941) and 0.874 (95% CI: 0.829-0.935) , respectively. There was no significant difference in AUC between the two models ( Z=1.34, P=0.462) . The Calibration curves of multivariate Logistic regression and XGBoost model were tested by Hosmer-Lemeshow, but there was no significant difference ( χ 2=0.83, P=0.516; χ 2=0.71, P=0.637) . Both models fit well. Conclusions:Multiple Logistic regression and XGBoost model were equally effective in predicting upper limb lymphedema after radical mastectomy. BMI, clinical stage (stage III) , number of lymph nodes removed ≥10, postoperative non-functional exercise, postoperative adjuvant radiotherapy, and hypertension are all important factors affecting upper limb lymphedema after radical mastectomy.

Objective To investigate the predictive value of edema metabolic and hematoma dynamics changes on motor and cog-nitive recovery outcomes in patients with intracerebral hemorrhage(ICH).Methods The CT data of ICH patients were collected to evaluate hematoma volume changes from admission to day 3.On day 3,multivoxel magnetic resonance spectroscopy(MRS)was per-formed with region of interest located in the edema region and contralateral normal tissue.Motor and cognitive function recovery was assessed using the simplified F-M scale and the Montreal cognitive assessment(MoCA)on day 3 and at the 3-month follow-up,respec-tively.Overall clinical outcomes were assessed using the Glasgow outcome scale(GOS),and all patients were divided into good and poor outcome groups.Clinical data and metabolic differences in the edema region between the two groups were compared,respec-tively.Logistic regression analysis and receiver operating characteristic(ROC)curves were used to identify and evaluate independent prognostic factors.Subgroup analysis were performed via stratification of hematoma location.Results The logistic regression analy-sis indicated that intraventricular extension,hematoma changes,and the ratio of N-acetyl aspartate(NAA)around the hematoma to contralateral normal brain parenchyma NAA(rNAA)were inde-pendent prognostic factors for poor outcomes(P＜0.05).The area under the curve(AUC)for each factor and the combined model were 0.69,0.73,0.79,and 0.82,respectively.In patients with ICH in the basal ganglia region,△F-M was negatively correlated with hematoma changes and positively correlated with rNAA value(P＜0.001).In patients with ICH in the thalamic and lobar regions,△MoCA was not significantly correlated with hematoma changes(P＞0.05),but was positively correlated with rNAA value(P＜0.001).Conclusion The rNAA holds predictive value for motor and cognitive recovery outcomes following standard treatment.