ObjectiveTo develop and validate a diagnostic prediction model for differentiating pulmonary tuberculosis from community-acquired pneumonia based on routine blood parameters. MethodsA total of 642 patients with pulmonary tuberculosis and 503 patients with community-acquired pneumonia were retrospectively enrolled from the Seventh Hospital of Tangshan. They were randomly divided into a training set and an internal validation set at a 7∶3 ratio. Additionally， 218 patients from the 981st Hospital were independently included as an external validation set. The Boruta algorithm and recursive feature elimination were employed to select predictors from 82 blood parameters， sex， and age. A multivariate Logistic regression model was established and evaluated using receiver operating characteristic （ROC） curves， calibration curves， and decision curve analysis. ResultsThe final model incorporated eight predictors， namely uric acid， urea nitrogen， alkaline phosphatase， monoamine oxidase， alanine aminotransferase， glutathione， neutrophil percentage， and age. The model achieved areas under the curve （AUCs） of 0.800 （95%CI： 0.769-0.830）， 0.787 （95%CI： 0.738-0.836）， and 0.736 （95%CI： 0.667-0.835） in the training， internal validation， and external validation sets， respectively. The model demonstrated good calibration， and decision curve analysis showed clinical net benefit within the threshold probability range of 10%-80%. ConclusionThe developed model exhibits good discriminative ability and clinical utility， serving as an effective early screening tool for primary healthcare institutions.

Cardiac surgery patients often present with multiple comorbidities,the risk of periop-erative complications and the complexity of postoperative rehabilitation have significantly increased,posing higher demands on comprehensive perioperative management.Preoperative exercise pre-reha-bilitation,as a multidisciplinary collaborative intervention strategy,has been demonstrated to signifi-cantly improve the clinical prognosis of patients undergoing elective cardiac surgery by enhancing their cardiopulmonary function,muscle strength,and overall physiological functional reserve,thereby in-creasing the body's tolerance to surgical stress.Although phase-specific research achievements have been made domestically and internationally in the field of exercise pre-rehabilitation,its standardized implementation and clinical translation on a global scale still face numerous obstacles,necessitating systematic review and in-depth exploration.Therefore,this study aimed to conduct a systematic re-view of the intervention protocols,clinical efficacy,safety,and feasibility of preoperative exercise pre-rehabilitation in patients undergoing elective cardiac surgery,with the goal of providing theoretical evidence and practical references for optimizing perioperative management pathways and promoting the implementation of enhanced recovery after surgery concepts.

Objective To construct and evaluate an evaluation index system for the training effect of cardiac surgery specialist nurses and provide a reference for the quality evaluation of cardiac surgery specialist nurse training.Methods Based on the Kirkpatrick Model,the preliminary draft of the evaluation index system for the training effect of cardiac surgery specialist nurses was formed through literature review and semi-structured interviews.The Delphi method was used to conduct the expert consultation with 24 experts nationwide in September 2024,and the weight of each index was determined by the analytic hierarchy process.In February 2025,60 cardiac surgery nurses from 3 tertiary A hospitals in Nanjing were selected as the survey subjects,and a satisfaction questionnaire on the evaluation index system for the training effect of cardiac surgery nurses was used for the survey.Results The effective recovery rates of the 2 rounds of expert questionnaires were 96％and 100％,respectively.The expert authority coefficient was 0.913,and the Kendall harmony coefficient was 0.127-0.212 and 0.152-0.176,respectively(both P＜0.05).The final evaluation index system for the training effect of cardiac surgery specialist nurses included 4 primary indexes,14 secondary indexes and 59 tertiary indicators.The satisfaction questionnaire score of the evaluation index system for the training effect of cardiac surgery nurses was(18.75±2.21).Conclusion The evaluation index system for the training effect of cardiac surgery specialist nurses was scientific and reliable,and can guide significance for the subsequent training,assessment and evaluation of cardiac surgery specialist nurses.

Objective To explore the predictive value of CT-based fat quantification parameters for early recurrence and recur-rence-free survival(RFS)in pancreatic ductal adenocarcinoma(PDAC).Methods A retrospective analysis was conducted on the data of 192 patients with pathologically confirmed PDAC,with 12 months as the threshold for early recurrence.The volume,area,density,index and visceral to subcutaneous fat ratio(VSR)of subcutaneous and visceral fat were calculated in CT portal phase images.Univariate and multivariate Cox regression analyses were performed to identify the independent predictors of early recurrence and RFS by combining clinical characteristics.The association between fat-related parameters and recurrence patterns was evaluated.Results Compared to the non-early recurrence patients,the early recurrence patients exhibited significantly higher body mass index(BMI),visceral fat vol-ume(VFV),visceral fat area(VFA),visceral fat index(VFI),and VSR,as well as significantly lower visceral fat density(VFD)(P＜0.05).Multivariate Cox regression analysis results revealed that VSR,tumor size,alanine aminotransferase(ALT)and carbohydrate antigen 19-9(CA19-9)were independent predictors of early recurrence in PDAC(P＜0.05),while VSR,tumor size,CA19-9 and gender were independent predictors of RFS in PDAC patients(P＜0.05).There were statistically significant differences in BMI,VFA,VFI,VSR,and subcutaneous fat index(SFI)among different recurrence pat-terns(P＜0.05).Conclusion VSR is an independent predictor of early recurrence and RFS in PDAC patients.Fat quantification parameters show significant differences among various recur-rence patterns.

Objective:To investigate the correlation between peri-coronary fat attenuation index (FAI) and plaque formation in patients with myocardial bridge (MB) of the left anterior descending artery (LAD) using coronary computed tomography angiography (CCTA) and to develop an optimal predictive model to explore the potential application of FAI in the primary prevention of MB related atherosclerosis.Methods:In this retrospective study, prediction models associated with perivascular fat inflammation were developed and validated using both logistic regression and machine learning (ML) algorithm. A training dataset was collected from 253 patients who underwent ≥2 coronary computed tomography angiography (CCTA) with ≥3 months intervals from one tertiary hospital from January 2007 to April 2021 and had baseline CCTA showing no plaques in LAD MB. The median follow-up time was 3.2 years. According to the same criteria, a total of 75 LAD MB patients from four other hospitals were included to form an independent external validation dataset, with a median follow-up time of 1.8 years. Receiver operating characteristic (ROC) curve analysis with integrated discrimination improvement (IDI) and category net reclassification index (NRI) were used to compare the performance of the predictive models.Results:62 patients (24.5%) in the training dataset had proximal plaque formation in LAD MB, while 22 patients (29.3%) in the external validation dataset had plaque formation during the follow-up period. Baseline FAI within the longitudinal distance equal to 30 mm proximal to the MB entrance was an independent predictor ( OR=1.068, P=0.046). According to the model results, ROC curves were plotted. The AUC of Model 1 was 0.822, and the AUCs of Model 2 and 1 were 0.821 and 0.591 in the training dataset. After the DeLong test, the AUC of Model 1 was superior to that of Model 2 ( Z=2.839, P=0.005) and Model 1 ( Z=6.124, P<0.001). These findings were further validated in the external validation dataset, where ML-model 3 yielded the best predictive performance, outperforming the logistic regression-based Model 2 (categorical NRI=0.359, P=0.048; IDI=0.108, P=0.046). Conclusion:FAI measured within the 30 mm proximal to the entrance of MBs due to its prone to plaque development is an independent predictor for atherosclerotic plaque formation. The ML-prediction model based on a decision tree algorithm combines FAI, MB anatomical features, and patient risk factors, which is beneficial for patients undergoing routine CCTA examination to identify inflamed coronary arteries in advance and guide the clinical adoption of more targeted preventive treatment, including anti-inflammatory treatment.

Objective:To search for and screen evidence related to perioperative nutrition management in cardiac surgery patients and summarize the best available evidence.Methods:Computerized searches were conducted in BMJ Best Practice, UpToDate, Guidelines International Network, National Institute for Health and Care Excellence website, National Guideline Clearinghouse, Scottish Intercollegiate Guideline Network, Registered Nurses' Association of Ontario, Canadian Medical Association Clinical Practice Guidelines Library, Medlive, Joanna Briggs Institute (JBI) Evidence-Based Health Care Centre Database, Cochrane Library, American College of Physicians Journal Club, PubMed, Web of Science, Embase, China National Knowledge Infrastructure, China Biology Medicine disc, Wanfang Data, VIP and other database and professional association websites for literature related to perioperative nutrition management in cardiac surgery patients. The search time limit is from the establishment of the database to April 30, 2024. Two researchers independently screened the literature based on quality standards, performed quality assessments, and extracted and synthesized the evidence.Results:A total of 17 articles were included, including four clinical decisions, five guidelines, five expert consensuses, two systematic reviews, and one randomized controlled trial. The final best evidence was summarized into 35 key recommendations across eight areas: multidisciplinary team formation, nutritional assessment and monitoring, dietary management, caloric requirements, nutrient intake, preoperative nutritional support therapy, postoperative nutritional support therapy, and health education.Conclusions:The best evidence summarized in this study for perioperative nutrition management in cardiac surgery patients is scientifically rigorous and comprehensive. It provides evidence-based support and decision-making guidance for clinical healthcare providers in managing perioperative nutrition for cardiac surgery patients.

Objective:To investigate the correlation between peri-coronary fat attenuation index (FAI) and plaque formation in patients with myocardial bridge (MB) of the left anterior descending artery (LAD) using coronary computed tomography angiography (CCTA) and to develop an optimal predictive model to explore the potential application of FAI in the primary prevention of MB related atherosclerosis.Methods:In this retrospective study, prediction models associated with perivascular fat inflammation were developed and validated using both logistic regression and machine learning (ML) algorithm. A training dataset was collected from 253 patients who underwent ≥2 coronary computed tomography angiography (CCTA) with ≥3 months intervals from one tertiary hospital from January 2007 to April 2021 and had baseline CCTA showing no plaques in LAD MB. The median follow-up time was 3.2 years. According to the same criteria, a total of 75 LAD MB patients from four other hospitals were included to form an independent external validation dataset, with a median follow-up time of 1.8 years. Receiver operating characteristic (ROC) curve analysis with integrated discrimination improvement (IDI) and category net reclassification index (NRI) were used to compare the performance of the predictive models.Results:62 patients (24.5%) in the training dataset had proximal plaque formation in LAD MB, while 22 patients (29.3%) in the external validation dataset had plaque formation during the follow-up period. Baseline FAI within the longitudinal distance equal to 30 mm proximal to the MB entrance was an independent predictor ( OR=1.068, P=0.046). According to the model results, ROC curves were plotted. The AUC of Model 1 was 0.822, and the AUCs of Model 2 and 1 were 0.821 and 0.591 in the training dataset. After the DeLong test, the AUC of Model 1 was superior to that of Model 2 ( Z=2.839, P=0.005) and Model 1 ( Z=6.124, P<0.001). These findings were further validated in the external validation dataset, where ML-model 3 yielded the best predictive performance, outperforming the logistic regression-based Model 2 (categorical NRI=0.359, P=0.048; IDI=0.108, P=0.046). Conclusion:FAI measured within the 30 mm proximal to the entrance of MBs due to its prone to plaque development is an independent predictor for atherosclerotic plaque formation. The ML-prediction model based on a decision tree algorithm combines FAI, MB anatomical features, and patient risk factors, which is beneficial for patients undergoing routine CCTA examination to identify inflamed coronary arteries in advance and guide the clinical adoption of more targeted preventive treatment, including anti-inflammatory treatment.

Objective To explore the predictive value of CT-based fat quantification parameters for early recurrence and recur-rence-free survival(RFS)in pancreatic ductal adenocarcinoma(PDAC).Methods A retrospective analysis was conducted on the data of 192 patients with pathologically confirmed PDAC,with 12 months as the threshold for early recurrence.The volume,area,density,index and visceral to subcutaneous fat ratio(VSR)of subcutaneous and visceral fat were calculated in CT portal phase images.Univariate and multivariate Cox regression analyses were performed to identify the independent predictors of early recurrence and RFS by combining clinical characteristics.The association between fat-related parameters and recurrence patterns was evaluated.Results Compared to the non-early recurrence patients,the early recurrence patients exhibited significantly higher body mass index(BMI),visceral fat vol-ume(VFV),visceral fat area(VFA),visceral fat index(VFI),and VSR,as well as significantly lower visceral fat density(VFD)(P＜0.05).Multivariate Cox regression analysis results revealed that VSR,tumor size,alanine aminotransferase(ALT)and carbohydrate antigen 19-9(CA19-9)were independent predictors of early recurrence in PDAC(P＜0.05),while VSR,tumor size,CA19-9 and gender were independent predictors of RFS in PDAC patients(P＜0.05).There were statistically significant differences in BMI,VFA,VFI,VSR,and subcutaneous fat index(SFI)among different recurrence pat-terns(P＜0.05).Conclusion VSR is an independent predictor of early recurrence and RFS in PDAC patients.Fat quantification parameters show significant differences among various recur-rence patterns.

Objective To construct and evaluate an evaluation index system for the training effect of cardiac surgery specialist nurses and provide a reference for the quality evaluation of cardiac surgery specialist nurse training.Methods Based on the Kirkpatrick Model,the preliminary draft of the evaluation index system for the training effect of cardiac surgery specialist nurses was formed through literature review and semi-structured interviews.The Delphi method was used to conduct the expert consultation with 24 experts nationwide in September 2024,and the weight of each index was determined by the analytic hierarchy process.In February 2025,60 cardiac surgery nurses from 3 tertiary A hospitals in Nanjing were selected as the survey subjects,and a satisfaction questionnaire on the evaluation index system for the training effect of cardiac surgery nurses was used for the survey.Results The effective recovery rates of the 2 rounds of expert questionnaires were 96％and 100％,respectively.The expert authority coefficient was 0.913,and the Kendall harmony coefficient was 0.127-0.212 and 0.152-0.176,respectively(both P＜0.05).The final evaluation index system for the training effect of cardiac surgery specialist nurses included 4 primary indexes,14 secondary indexes and 59 tertiary indicators.The satisfaction questionnaire score of the evaluation index system for the training effect of cardiac surgery nurses was(18.75±2.21).Conclusion The evaluation index system for the training effect of cardiac surgery specialist nurses was scientific and reliable,and can guide significance for the subsequent training,assessment and evaluation of cardiac surgery specialist nurses.

Objective:To search for and screen evidence related to perioperative nutrition management in cardiac surgery patients and summarize the best available evidence.Methods:Computerized searches were conducted in BMJ Best Practice, UpToDate, Guidelines International Network, National Institute for Health and Care Excellence website, National Guideline Clearinghouse, Scottish Intercollegiate Guideline Network, Registered Nurses' Association of Ontario, Canadian Medical Association Clinical Practice Guidelines Library, Medlive, Joanna Briggs Institute (JBI) Evidence-Based Health Care Centre Database, Cochrane Library, American College of Physicians Journal Club, PubMed, Web of Science, Embase, China National Knowledge Infrastructure, China Biology Medicine disc, Wanfang Data, VIP and other database and professional association websites for literature related to perioperative nutrition management in cardiac surgery patients. The search time limit is from the establishment of the database to April 30, 2024. Two researchers independently screened the literature based on quality standards, performed quality assessments, and extracted and synthesized the evidence.Results:A total of 17 articles were included, including four clinical decisions, five guidelines, five expert consensuses, two systematic reviews, and one randomized controlled trial. The final best evidence was summarized into 35 key recommendations across eight areas: multidisciplinary team formation, nutritional assessment and monitoring, dietary management, caloric requirements, nutrient intake, preoperative nutritional support therapy, postoperative nutritional support therapy, and health education.Conclusions:The best evidence summarized in this study for perioperative nutrition management in cardiac surgery patients is scientifically rigorous and comprehensive. It provides evidence-based support and decision-making guidance for clinical healthcare providers in managing perioperative nutrition for cardiac surgery patients.