Objective:To analyze the predictive value of the prognostic nutritional index combined with inflammatory indicators for clinical outcomes in patients with ischemic stroke, providing a basis for targeted therapeutic interventions and nursing care for patients at potential risk of poor outcomes.Methods:This retrospective cohort study recruited 424 ischemic stroke patients admitted to the Stroke Center of the First Hospital of Jilin University from June 2021 to May 2024 by the convenience sampling method. Collect the general demographic data, routine laboratory examination results within 24 hours of admission, as well as the National Institutes of Health Stroke Scale (NIHSS) scores at admission and discharge of the patients. Based on 3-month functional outcomes, patients were divided into a favorable prognosis group and a poor prognosis group. Univariate analysis, least absolute shrinkage and selection operator regression, and binary Logistic regression were employed to screen predictive variables and develop a nomogram model. Internal validation was performed using the Bootstrap method. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve were drew to evaluate the predictive performance of the model.Results:The favorable prognosis group comprised 256 patients, including 57 females and 199 males, with an age of 61(54, 68) years. The poor prognosis group included 168 patients, with 55 females and 113 males, and an age of 66(58, 72) years. Binary Logistic regression identified age, sex, hyperlipidemia, NIHSS score at discharge, prognostic nutritional index, systemic inflammatory response index, and systemic immune-inflammation index as independent predictors of prognosis in ischemic stroke patients ( χ2 values were 4.52-56.18, all P<0.05). The prediction model demonstrated the area under the curve of ROC of 0.806 (95% CI 0.764-0.849), with an optimal cutoff value of 0.406, achieving specificity of 78% and sensitivity of 68%. The Hosmer-Lemeshow test yielded a non-significant P>0.05, and the calibration curve showed good agreement between predicted and observed outcomes, with a mean absolute error of 0.012. Decision curve analysis confirmed the clinical utility of the model across a wide range of threshold probabilities. Conclusions:The integrated prognostic model combining the prognostic nutritional index and inflammatory indicators demonstrated favorable discriminative ability, robust calibration, and substantial clinical utility. This risk stratification tool shows high applicability for predicting ischemic stroke outcomes, facilitating early identification of high-risk patients with poor prognosis and guiding personalized intervention strategies.

As a new technology in the smart hospital construction project,Building Information Modeling(BIM)can re-alize the visualization of the project engineering by constructing a three-dimensional model.Compared with the traditional Comput-er Aided Design(CAD)two-dimensional mapping,it has stronger simulation,collaboration and optimization functions.Taking the construction project of the second phase of the scientific research and teaching building of a national regional medical center as an example,this article deeply compared the application value and management effectiveness of CAD two-dimensional mapping and BIM three-dimensional model in the project construction process,with the aim of providing certain references and guidance for the comprehensive construction of smart hospitals and the construction of smart project engineering.

Objective:To analyze the predictive value of the prognostic nutritional index combined with inflammatory indicators for clinical outcomes in patients with ischemic stroke, providing a basis for targeted therapeutic interventions and nursing care for patients at potential risk of poor outcomes.Methods:This retrospective cohort study recruited 424 ischemic stroke patients admitted to the Stroke Center of the First Hospital of Jilin University from June 2021 to May 2024 by the convenience sampling method. Collect the general demographic data, routine laboratory examination results within 24 hours of admission, as well as the National Institutes of Health Stroke Scale (NIHSS) scores at admission and discharge of the patients. Based on 3-month functional outcomes, patients were divided into a favorable prognosis group and a poor prognosis group. Univariate analysis, least absolute shrinkage and selection operator regression, and binary Logistic regression were employed to screen predictive variables and develop a nomogram model. Internal validation was performed using the Bootstrap method. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve were drew to evaluate the predictive performance of the model.Results:The favorable prognosis group comprised 256 patients, including 57 females and 199 males, with an age of 61(54, 68) years. The poor prognosis group included 168 patients, with 55 females and 113 males, and an age of 66(58, 72) years. Binary Logistic regression identified age, sex, hyperlipidemia, NIHSS score at discharge, prognostic nutritional index, systemic inflammatory response index, and systemic immune-inflammation index as independent predictors of prognosis in ischemic stroke patients ( χ2 values were 4.52-56.18, all P<0.05). The prediction model demonstrated the area under the curve of ROC of 0.806 (95% CI 0.764-0.849), with an optimal cutoff value of 0.406, achieving specificity of 78% and sensitivity of 68%. The Hosmer-Lemeshow test yielded a non-significant P>0.05, and the calibration curve showed good agreement between predicted and observed outcomes, with a mean absolute error of 0.012. Decision curve analysis confirmed the clinical utility of the model across a wide range of threshold probabilities. Conclusions:The integrated prognostic model combining the prognostic nutritional index and inflammatory indicators demonstrated favorable discriminative ability, robust calibration, and substantial clinical utility. This risk stratification tool shows high applicability for predicting ischemic stroke outcomes, facilitating early identification of high-risk patients with poor prognosis and guiding personalized intervention strategies.

Objective:To investigate the influence of contrast-enhanced computed tomography(CECT)on dose calculation in magnetic resonance imaging(MRI)-guided online adaptive radiotherapy(oART)based on the electron density(ED)assignment method for rectal cancer.Methods:A retrospective analysis was conducted on the medical data of 15 patients with locally advanced rectal cancer at middle-low segments,who admitted to the Chinese PLA General Hospital between December 2023 and April 2025.All patients underwent both plain computed tomography(PCT)and CECT scans during location.The average HU and ED value of all organs that were extracted from PCT and CECT images in the treatment plan system were obtained,and the influences of contrast agent of intake on image characteristics of the structure of each organ(small intestine,femoral head,bladder)were analyzed.PCT was used as referred image to design reference plan(Pref).The synthetic CT(sCT)was simulated and generated on the basis of PCT and CECT,respectively.The beam flow field that was same with Pref was used to recalculate dose on sCT,and then,the online plan(PPCT)based on PCT,and the online plan(PCECT)based on CECT were obtained,respectively,which can simulate the online dose calculation of MRI-guided online adaptive radiotherapy(oART).The Pref was used as reference to compare dosimetric parameters for target region and organ at risk(OAR)through dose volume histogram(DVH)and planed evaluation indicators.Additionally,three dimension(3D)slicer software was used to perform γ analysis for the results of dose distribution,and explore the differences among PPCT,PCECT and Pref on dose distribution.Results:In terms of image characteristics,the HU values of soft-tissue organs(intestine,bladder,spinal cord,soft tissue)and planning target volume(PTV)in CECT were higher than those in PCT,and the differences of them were statistically significant(Zintestines=-2.188,Zbladder=-3.196,tspinal cord=-3.767,tsoft tissue=-10.083,tPTV=-4.693,P<0.05),while its influence was less on bone tissue.The statistical results of ED were consistent with those of HU.Regarding to dosimetric parameters,there was no statistically significant difference in target coverage rate between PPCT and Pref(P>0.05),and the D50%of the PPCT[(2724.25±19.91)cGy]was higher than that of the Pref[(2718.99±21.13)cGy],and the difference was statistically significant(t=-3.679,P=0.002).However,the target coverage rate of PCECT was 94.65(94.04,95.27)%,and the difference of that between PCECT and Pref was statistically significant(Z=-2.158,P=0.031).For OAR,the differences of Dmax value of the small intestine,and the V20 of the left femoral head between PPCT and Pref were significant(Z=-2.556,-2.529,P<0.05).The differences of the Dmax of small intestine,and the D50%of bladder between PCECT and Pref were significant(t=-4.821,2.171,P<0.05).The comparative γ passed rates of PPCT,PCECT and Pref under the standards of 3 mm/3%and 2 mm/2%were all above 95%,and the differences were not significant(P>0.05).Conclusions:The influence of CECT on dose calculation in MRI-guided oART based on ED assignment method for rectal cancer is relatively small,which can be directly used in the design of reference plan,but the maximum dose of radiation-sensitive organs such as the small intestine should be paid attention.

As a new technology in the smart hospital construction project,Building Information Modeling(BIM)can re-alize the visualization of the project engineering by constructing a three-dimensional model.Compared with the traditional Comput-er Aided Design(CAD)two-dimensional mapping,it has stronger simulation,collaboration and optimization functions.Taking the construction project of the second phase of the scientific research and teaching building of a national regional medical center as an example,this article deeply compared the application value and management effectiveness of CAD two-dimensional mapping and BIM three-dimensional model in the project construction process,with the aim of providing certain references and guidance for the comprehensive construction of smart hospitals and the construction of smart project engineering.

Objective:To investigate the influence of contrast-enhanced computed tomography(CECT)on dose calculation in magnetic resonance imaging(MRI)-guided online adaptive radiotherapy(oART)based on the electron density(ED)assignment method for rectal cancer.Methods:A retrospective analysis was conducted on the medical data of 15 patients with locally advanced rectal cancer at middle-low segments,who admitted to the Chinese PLA General Hospital between December 2023 and April 2025.All patients underwent both plain computed tomography(PCT)and CECT scans during location.The average HU and ED value of all organs that were extracted from PCT and CECT images in the treatment plan system were obtained,and the influences of contrast agent of intake on image characteristics of the structure of each organ(small intestine,femoral head,bladder)were analyzed.PCT was used as referred image to design reference plan(Pref).The synthetic CT(sCT)was simulated and generated on the basis of PCT and CECT,respectively.The beam flow field that was same with Pref was used to recalculate dose on sCT,and then,the online plan(PPCT)based on PCT,and the online plan(PCECT)based on CECT were obtained,respectively,which can simulate the online dose calculation of MRI-guided online adaptive radiotherapy(oART).The Pref was used as reference to compare dosimetric parameters for target region and organ at risk(OAR)through dose volume histogram(DVH)and planed evaluation indicators.Additionally,three dimension(3D)slicer software was used to perform γ analysis for the results of dose distribution,and explore the differences among PPCT,PCECT and Pref on dose distribution.Results:In terms of image characteristics,the HU values of soft-tissue organs(intestine,bladder,spinal cord,soft tissue)and planning target volume(PTV)in CECT were higher than those in PCT,and the differences of them were statistically significant(Zintestines=-2.188,Zbladder=-3.196,tspinal cord=-3.767,tsoft tissue=-10.083,tPTV=-4.693,P<0.05),while its influence was less on bone tissue.The statistical results of ED were consistent with those of HU.Regarding to dosimetric parameters,there was no statistically significant difference in target coverage rate between PPCT and Pref(P>0.05),and the D50%of the PPCT[(2724.25±19.91)cGy]was higher than that of the Pref[(2718.99±21.13)cGy],and the difference was statistically significant(t=-3.679,P=0.002).However,the target coverage rate of PCECT was 94.65(94.04,95.27)%,and the difference of that between PCECT and Pref was statistically significant(Z=-2.158,P=0.031).For OAR,the differences of Dmax value of the small intestine,and the V20 of the left femoral head between PPCT and Pref were significant(Z=-2.556,-2.529,P<0.05).The differences of the Dmax of small intestine,and the D50%of bladder between PCECT and Pref were significant(t=-4.821,2.171,P<0.05).The comparative γ passed rates of PPCT,PCECT and Pref under the standards of 3 mm/3%and 2 mm/2%were all above 95%,and the differences were not significant(P>0.05).Conclusions:The influence of CECT on dose calculation in MRI-guided oART based on ED assignment method for rectal cancer is relatively small,which can be directly used in the design of reference plan,but the maximum dose of radiation-sensitive organs such as the small intestine should be paid attention.

Objective:To evaluate the effects of different intervention measures on duration of mechanical ventilation and the length of intensive care unit (ICU) stay in critically ill patients using network Meta-analysis.Methods:Randomized controlled trial (RCT) on the effects of different intervention measures on duration of mechanical ventilation and the length of ICU stay in critically ill patients were systematically searched in PubMed, Embase, China Biomedical Literature Database, CNKI, and other databases. The search time limit was from the establishment of the database to November 2023. Literature screening, quality assessment, and data extraction were independently conducted by two researchers. Network Meta-analysis was employed to assess the effects of each intervention on duration of mechanical ventilation and the length of ICU stay, and funnel plots were generated.Results:A total of 37 RCTs were included, involving 3?977 severe patients, 2?041 in the intervention group and 1?936 in the control group. Thirteen types of interventions were analyzed, including usual care (UC), early activity (EA), early comprehensive rehabilitation (ECR), early pulmonary rehabilitation (EPR), cluster intervention strategy (CS), sedation, analgesia and cluster nursing (SACN), music therapy (MT), neuromuscular electrical stimulation (NMES), modified education and visitation (MV), virtual reality (VR), auricular point sticking (APS), acupoint acupuncture (AA), and concerted intervention (COR). Network Meta-analysis showed that MV significantly better than COR [standardized mean difference ( SMD) = -2.35, 95% confidence interval (95% CI) was -4.30 to -0.39], EPR ( SMD = -2.59, 95% CI was -4.81 to -0.37), and UC ( SMD = -4.10, 95% CI was -5.71 to -2.49) in improving duration of mechanical ventilation in critically ill patients. COR was significantly better than UC in shortened length of ICU stay ( SMD = -5.72, 95% CI was -10.07 to -1.37). The efficacy ranking results showed that for duration of mechanical ventilation, the surface under the cumulative ranking curve (SUCRA) was highest for MV (85.4%) and EA (85.4%), followed by AA (74.9%), NMES (63.1%), ECR (51.7%), CS (48.8%), SACN (34.3%), COR (29.4%), EPR (26.1%), and UC (0.7%). For the length of ICU stay, COR had the highest SUCRA (82.3%), followed by APS (79.7%), MV (77.7%), EPR (68.0%), NMES (57.6%), CS (54.4%), ECR (51.1%), SACN (41.9%), MT (39.8%), EA (39.3%), AA (33.0%), VR (15.4%), and UC (9.8%). The funnel plot results of ICU stay showed that the publication bias between studies were relatively small. Conclusions:MV and COR appear to be effective interventions for reducing mechanical ventilation time and ICU stay in critically ill patients. However, due to the number and quality of included studies, these findings require confirmation through additional high-quality research.

Objective:To investigate the biological effects of acute high-dose radon exposure on mice.Methods:BALB/c male mice aged 6 to 8 weeks were exposed once in an HD-3 ecological radon chamber with an average radon concentration of 7 × 10 5 Bq/m 3 for 10 h. Mice were weighed, their lung tissues and blood samples were collected at 1, 2 and 3 months after exposure. Control groups were set up at the three time points with four mice in each group. For these mice, the lung tissue pathology was observed using hematoxylin-eosin (HE) staining method, routine blood tests were conducted using a hematology analyzer and the levels of superoxide dismutase (SOD) and malondialdehyde (MDA) in the serum and lung tissues were measured using corresponding assay kits. Results:The HE staining result revealed that compared to the control groups, the experimental groups exhibited thickening of alveolar walls and increased infiltration of granulocyte, whose degrees, however, reduced over time and displayed no significant difference at 3 months after exposure. There was no significant difference in body weight or blood routine between the experimental and control groups. The detection result revealed decreased SOD levels in the lung tissues at 2 months after exposure, which were (11.34 ± 1.03) U/mgprot and (9.75 ± 0.71) U/mgprot, respectively for the control and experimental groups ( t = 2.54, P < 0.05). The MDA levels in lung tissue increased at 1 month after exposure, which were(2.30 ± 0.24) and (2.77 ± 0.29) nmol/mgprot, respectively for the control and experimental groups ( t = 2.49, P < 0.05). At 3 months after exposure, the SOD and MDA levels differed insignificantly between the control and experimental groups ( P > 0.05). Conclusions:After acute high-dose radon exposure, the mice suffered damage to the lung tissue, with changes in their oxidative stress indicators being detected. However, these effects gradually diminished at 3 months after exposure. Additionally, acute high-dose radon exposure did not give rise to significant changes in the body weight or routine blood result of the mice.

Nowadays, the new healthcare industry is closely integrated with the new-generation information techniques such as mobile Internet, Internet of things, cloud computing, and big data, which proposes higher requirements for the teaching objectives and contents of the optional course of medical informatics for non-informatics students in medical colleges and universities. Based on the actual teaching demands and the training objectives of clinical medical students, the teaching contents of the optional course of medical informatics were scientifically optimized and allocated. With "small datasets and basic application of electronic medical records/electronic health records" in medical informatics education as the main contents, numeric data, text data, and image data were modularized in medical information processing, and the methods of flipped classroom and case-driven teaching were adopted. The commonly used methods in machine learning (such as regression, classification, and clustering methods) were introduced and applied in task-based case studies, and the comprehensive algorithm case report was used for course assessment and evaluation. The teaching practice has shown that the above exploration not only stimulated the interest in the optional course of medical informatics among students, but also effectively implemented the "five early" mode of early prediction, early adjustment, early identification, early diagnosis, and early treatment among medical students.

To study an automatic plan(AP) method for radiotherapy after breast-conserving surgery based on TiGRT system and and compare with manual plan (MP). The dosimetry parameters of 10 patients and the evaluation of scoring table were analyzed, it was found that the targets dose of AP were better than that of MP, but there was no statistical difference except for CI, The V5, V20 and V30 of affected lungs and whole lungs in AP were lower than all that in MP, the Dmean of hearts was slightly higher than that of MP, but the difference was not statistically significant, the MU of AP was increase by 16.1% compared with MP, the score of AP evaluation was increase by 6.1% compared with MP. So the AP could be programmed and automated while ensuring the quality of the plan, and can be used to design the plans for radiotherapy after breast-conserving surgery.
Breast Neoplasms/surgery* ; Female ; Humans ; Mastectomy, Segmental ; Organs at Risk ; Radiotherapy Dosage ; Radiotherapy Planning, Computer-Assisted ; Radiotherapy, Intensity-Modulated