Objective: To investigate the reciprocal causal relationships between periodontitis and hepatobiliary diseases through Mendelian randomization (MR) analyses, to provide evidence for joint prevention and clinical decision-making in patients with concurrent periodontitis and hepatobiliary diseases. Methods: Single nucleotide polymorphisms (SNPs) were extracted from the largest genome-wide association study on periodontitis (17 353 cases, 28 210 controls) and hepatobiliary diseases within the European ancestry and used as instrumental variables (IVs). The strength of the associations was examined by calculating the F-statistic. The SNPs significantly associated with the outcome were removed by scanning on Phenoscanner platform. Bidirectional causal associations between periodontitis and hepatobiliary diseases were estimated using inverse variance weighted (IVW), MR-Egger, and Weighted Median methods. The robustness of the findings was further verified through additional sensitive MR approaches, including Cochran’s Q statistic （IVW）, Rucker’s Q statistic （MR-Egger）, MR-PRESSO and Leave-one-out analysis. Further MR analyses, utilizing other available genome-wide association studies (GWAS) on hepatobiliary diseases, were conducted to validate the results. Results: The IVW method found that periodontitis had a causal impact on acalculous cholecystitis (odds ratio = 1.277, 95% CI 1.097-1.485, P=0.002), implying an increased risk of acalculous cholecystitis associated with periodontitis, while the MR-Egger regression and Weighted Median failed to observe significant causal effects of periodontitis on acalculous cholecystitis. However, no bidirectional causal associations between periodontitis and nonalcoholic fatty liver disease, cirrhosis or liver cancer were observed using IVW, MR-Egger regression and Weighted Median. The bidirectional causal relationships were deemed unlikely to be influenced by horizontal pleiotropy. Further, the validation analysis based on alternative GWAS data suggested parallel results. Conclusions The MR analyses suggest that periodontitis may elevate the risk of acalculous cholecystitis. Further investigations, including clinical studies and mechanistic explorations, are warranted to validate these findings. However, the MR analyses do not support bidirectional causal associations between periodontitis and nonalcoholic fatty liver disease, cirrhosis or liver cancer.

Objective:To examine the current diagnostic and treatment practices, as well as surgical outcomes, for individuals over the age of 60 diagnosed with acute aortic arch dissection(ATAAD)at Tianjin University Chest Hospital.This analysis evaluates the safety and feasibility of performing open surgical procedures on elderly patients affected by aortic dissection.Methods:A retrospective analysis was conducted on 509 patients diagnosed with ATAAD who were registered in the Chest Pain Center data reporting platform(https: //datacs.chinacpc.org/)at Tianjin Chest Hospital, covering the period from June 2015 to December 2021.The patients were divided into two groups: the elderly group, consisting of individuals aged 60 years or older, and the non-elderly group, comprising those under 60 years of age.Their surgical conditions and short-term outcomes were subsequently examined and compared.Results:A total of 509 patients were included, 311 cases(61.1%)were identified within the non-elderly group, with a mean age of 45.78 ± 8.96 years(range: 21-59 years).In contrast, 198 cases(38.9%)belonged to the elderly group, with a mean age of 65.61 ± 4.13 years(range: 60-81 years).A total of 416 patients(81.7%)received surgical intervention.Among those who underwent surgery, the elderly group exhibited a significantly higher proportion of females(38.1% vs.20.6%, P<0.001), and these patients had smaller body surface areas and lower body mass index values.Furthermore, a greater number of elderly patients presented with comorbid conditions such as hypertension, coronary artery disease, chronic obstructive pulmonary disease, and stroke(all P<0.05).The 30-day all-cause mortality rate, incidence of cerebral infarction, and rate of continuous renal replacement therapy(CRRT)utilization were similar in both groups(20.9% vs.18.8%、15.1% vs.10.5%、19.4% vs.18.1%, all P>0.05).However, elderly patients experienced longer postoperative recovery durations, extended periods of ventilator dependency, and a higher incidence of new-onset atrial fibrillation following surgery(all P<0.05). Conclusions:The surgical rate for elderly patients with ATAAD is low, suggesting that there is significant potential for improvement in clinical diagnosis and treatment.Advanced age should not be viewed as a contraindication for surgery; rather, appropriate case selection and personalized treatment plans can enhance the success rate of surgical interventions.

Objective:To evaluate the efficacy of preoperative prediction of regional lymph node (RLN) metastasis in renal cell carcinoma (RCC) using a machine learning model based on habitat imaging radiomics from renal MRI.Methods:This cross-sectional study retrospectively analyzed 220 patients with RCC who underwent nephrectomy and RLN dissection at four medical centers of Chinese PLA General Hospital from January 2010 to August 2023. The cohort included 65 patients with RLN metastasis and 155 without. A stratified random sampling method was used to divide 175 patients from the first medical center into a training set ( n=140) and an internal test set ( n=35) in an 8∶2 ratio, while 45 patients from the third, fourth, and fifth medical centers constituted the external test set. The primary RCC lesions were categorized into 15 habitat subregions based on corticomedullary-phase enhancement and T 2WI signal intensity on MRI, and the volume fractions of different subregions were analyzed. In the training cohort, radiomics features derived from the habitat subregions were used to construct a radiomics model employing various machine learning algorithms, including extremely random trees (ET), gradient boosting decision trees (GBDT), random forest (RF), and support vector machine (SVM). The optimal model was selected and combined with RLN short-axis diameter to develop a combined model. The efficacy of each model in predicting RLN metastasis was evaluated using the receiver operating characteristic (ROC) curve. Results:The volume fraction of hyper-enhanced hyper-intense regions in the non-metastatic group was significantly higher than that in the metastatic group (0.05±0.09 vs. 0.02±0.03; t=3.00, P=0.003). Among the machine learning models constructed using 15 optimal habitat radiomics features, the SVM model demonstrated the best performance, with area under the ROC curve (AUC) values of 0.85 (95% CI 0.72-0.98) in the internal test set and 0.82 (95% CI 0.67-0.98) in the external test set, surpassing those of the ET, GBDT, and RF models. The combined model, integrating the SVM model with RLN short-axis diameter, achieved AUC values of 0.94 (95% CI 0.85-1.00) in the internal test set and 0.89 (95% CI 0.78-1.00) in the external test set, with RLN short-axis diameter contributing AUC values of 0.81 (95% CI 0.66-0.96) and 0.81 (95% CI 0.68-0.94), respectively. The diagnostic sensitivity of the combined model was 91.7% in the internal test set and 85.7% in the external test set, with specificities of 78.3% and 67.7%, respectively. Conclusion:The combined model based on MRI habitat imaging radiomics and RLN short-axis diameter demonstrates excellent preoperative assessment capability for RLN metastasis in RCC.

Objective:To examine the current diagnostic and treatment practices, as well as surgical outcomes, for individuals over the age of 60 diagnosed with acute aortic arch dissection(ATAAD)at Tianjin University Chest Hospital.This analysis evaluates the safety and feasibility of performing open surgical procedures on elderly patients affected by aortic dissection.Methods:A retrospective analysis was conducted on 509 patients diagnosed with ATAAD who were registered in the Chest Pain Center data reporting platform(https: //datacs.chinacpc.org/)at Tianjin Chest Hospital, covering the period from June 2015 to December 2021.The patients were divided into two groups: the elderly group, consisting of individuals aged 60 years or older, and the non-elderly group, comprising those under 60 years of age.Their surgical conditions and short-term outcomes were subsequently examined and compared.Results:A total of 509 patients were included, 311 cases(61.1%)were identified within the non-elderly group, with a mean age of 45.78 ± 8.96 years(range: 21-59 years).In contrast, 198 cases(38.9%)belonged to the elderly group, with a mean age of 65.61 ± 4.13 years(range: 60-81 years).A total of 416 patients(81.7%)received surgical intervention.Among those who underwent surgery, the elderly group exhibited a significantly higher proportion of females(38.1% vs.20.6%, P<0.001), and these patients had smaller body surface areas and lower body mass index values.Furthermore, a greater number of elderly patients presented with comorbid conditions such as hypertension, coronary artery disease, chronic obstructive pulmonary disease, and stroke(all P<0.05).The 30-day all-cause mortality rate, incidence of cerebral infarction, and rate of continuous renal replacement therapy(CRRT)utilization were similar in both groups(20.9% vs.18.8%、15.1% vs.10.5%、19.4% vs.18.1%, all P>0.05).However, elderly patients experienced longer postoperative recovery durations, extended periods of ventilator dependency, and a higher incidence of new-onset atrial fibrillation following surgery(all P<0.05). Conclusions:The surgical rate for elderly patients with ATAAD is low, suggesting that there is significant potential for improvement in clinical diagnosis and treatment.Advanced age should not be viewed as a contraindication for surgery; rather, appropriate case selection and personalized treatment plans can enhance the success rate of surgical interventions.

Objective:To evaluate the efficacy of preoperative prediction of regional lymph node (RLN) metastasis in renal cell carcinoma (RCC) using a machine learning model based on habitat imaging radiomics from renal MRI.Methods:This cross-sectional study retrospectively analyzed 220 patients with RCC who underwent nephrectomy and RLN dissection at four medical centers of Chinese PLA General Hospital from January 2010 to August 2023. The cohort included 65 patients with RLN metastasis and 155 without. A stratified random sampling method was used to divide 175 patients from the first medical center into a training set ( n=140) and an internal test set ( n=35) in an 8∶2 ratio, while 45 patients from the third, fourth, and fifth medical centers constituted the external test set. The primary RCC lesions were categorized into 15 habitat subregions based on corticomedullary-phase enhancement and T 2WI signal intensity on MRI, and the volume fractions of different subregions were analyzed. In the training cohort, radiomics features derived from the habitat subregions were used to construct a radiomics model employing various machine learning algorithms, including extremely random trees (ET), gradient boosting decision trees (GBDT), random forest (RF), and support vector machine (SVM). The optimal model was selected and combined with RLN short-axis diameter to develop a combined model. The efficacy of each model in predicting RLN metastasis was evaluated using the receiver operating characteristic (ROC) curve. Results:The volume fraction of hyper-enhanced hyper-intense regions in the non-metastatic group was significantly higher than that in the metastatic group (0.05±0.09 vs. 0.02±0.03; t=3.00, P=0.003). Among the machine learning models constructed using 15 optimal habitat radiomics features, the SVM model demonstrated the best performance, with area under the ROC curve (AUC) values of 0.85 (95% CI 0.72-0.98) in the internal test set and 0.82 (95% CI 0.67-0.98) in the external test set, surpassing those of the ET, GBDT, and RF models. The combined model, integrating the SVM model with RLN short-axis diameter, achieved AUC values of 0.94 (95% CI 0.85-1.00) in the internal test set and 0.89 (95% CI 0.78-1.00) in the external test set, with RLN short-axis diameter contributing AUC values of 0.81 (95% CI 0.66-0.96) and 0.81 (95% CI 0.68-0.94), respectively. The diagnostic sensitivity of the combined model was 91.7% in the internal test set and 85.7% in the external test set, with specificities of 78.3% and 67.7%, respectively. Conclusion:The combined model based on MRI habitat imaging radiomics and RLN short-axis diameter demonstrates excellent preoperative assessment capability for RLN metastasis in RCC.

Objective:Using different machine learning methods to construct and screen the best prediction model for predicting the risk of death within 30 days after surgery in patients with acute type A aortic dissection.Methods:Five hundred and twenty-one patients with acute type A aortic dissection who underwent surgery between 2015 and 2022 were included, after collecting their perioperative date and screening them, 329 patients were retained. two different groups of predictor variables were generated by using Lasso regression and principal component analysis, after that, logistic regression, support vector machine algorithm, random forest algorithm, gradient boosting algorithm, and super learning algorithm were used to develop prediction models for the risk of death within 30 days after surgery. Finally, we compare the models and select the best one. Results:The AUC values for all models rangrd from 0.791-0.959. The model using Lasso regression to determine the predictor variables and built by the super learning algorithm had the best prediction with an AUC value of 0.959. Conclusion:The super learning algorithm better than other algorithms in predicting death within 30 days after acute type A aortic dissection.

Objective:To investigate the impact of the interval period between biopsy and MR examination on tumor detection and extraprostatic extension (EPE) assessment for prostate cancer (PCa) using multi-parametric MRI (mpMRI).Methods:The study was cross-sectional and retrospectively included 130 patients with PCa who underwent RP and preoperative systematic biopsies followed by mpMRI between January 2021 and December 2022 in the First Medical Center of Chinese PLA General Hospital. Patients were divided into 3 groups according to interval following biopsy (group A,<3 weeks, 31 cases; group B, 3-6 weeks, 67 cases; group C,>6 weeks, 32 cases). The percentages of hemorrhage volume in the total prostate were drawn on T 1WI and calculated. The junior, senior and expert radiologists independently localized the index lesions and calculated the accuracy for tumor detection, in addition to assessing the probabilities of EPE according to EPE grade. The correlation between the hemorrhage extent and interval was analyzed using the Spearman correlation coefficient. The accuracy for tumor detection was compared using χ2 test among groups. The diagnostic performance of the radiologists for EPE prediction was assessed using the receiver operating characteristic curve, and the differences between the corresponding area under the curve (AUC) were compared using the DeLong test. Results:The percentage of hemorrhage was correlated with the interval between biopsy and MR examination ( r=-0.325, P<0.001). The detection accuracy of junior radiologist was 83.9% (26/31), 76.1% (51/67), and 78.1% (25/32) in group A, B and C, respectively; no differences were observed in the detection accuracy among three groups ( χ2=0.76, P=0.685). The detection accuracy of senior radiologist was 83.9% (26/31), 80.6% (54/67), and 71.9% (23/32) in 3 groups with no differences ( χ2=1.53, P=0.464). The detection accuracy of expert radiologist was 80.6% (25/31), 77.6% (52/67), and 93.8% (30/32) with no differences ( χ2=3.95, P=0.139). The AUC (95% CI) for predicting EPE were 0.830 (0.652-0.940), 0.704 (0.580-0.809), 0.800 (0.621-0.920) in the group A, B and C for junior radiologist; 0.876 (0.708-0.966), 0.768 (0.659-0.863), 0.896 (0.736-0.975) for senior radiologist; and 0.866 (0.695-0.961), 0.813 (0.699-0.895), 0.852 (0.682-0.952) for expert radiologist, respectively. No differences were observed among the subgroups in each radiologist ( P>0.05). Conclusion:The interval period does not significantly affect the detection accuracy and EPE assessment of PCa using mpMRI. There is probably no necessity for prolonged intervals following systematic biopsy to preserve the clarity of MRI interpretation for PCa.

Objective To summarize the results and clinical experience of transcatheter valve-in-valve implantation using domestic self-expanding valve in patients with aortic degenerated bio-prosthesis. Methods From January 2019 to April 2023, the patients who underwent transcatheter valve-in-valve surgery in the Department of Cardiac Surgery of Tianjin Chest Hospital due to surgical bio-prosthesis failure were included. Characteristics of valves, perioperative complications, and hemodynamic manifestations during the early postoperative and follow-up period were analyzed. Results A total of 24 patients were enrolled, including 14 males and 10 females with an average age of 68.17±7.72 years, and the average interval between the two operations was 10.48±4.09 years. All patients were successfully discharged without complications such as coronary artery obstruction and pacemaker implantation, and the average transvalvular pressure gradient was 16.39±6.52 mm Hg before discharge. During the median follow-up time of 16 months, the left ventricular diastolic inner diameter and ejection fraction were continuously improved. Conclusion Transcatheter valve-in-valve using domestic self-expanding valves is safe and feasible to treat aortic bioprosthetic valve failure. Sound patient selection and surgical strategies are critical to achieve good hemodynamics.

Objective To investigate the efficacy of low-dose inhaled nitric oxide (iNO) in the treatment of severe hypoxemia after Sun’s operation. Methods The clinical data of patients undergoing Sun’s operation for acute Type A aortic dissection in our hospital from January 2020 to June 2022 were retrospectively analyzed. Patients who received conventional treatment before November 2021 were enrolled as a control group. After November 2021, iNO was used in our hospital, and the patients who received iNO as an iNO group. The preoperative clinical baseline data, perioperative clinical data and oxygenation index were compared between the two groups. Results A total of 54 patients were included in the control group, including 45 males and 9 females, with an average age of 53.0±10.9 years. A total of 27 patients were included in the iNO group, including 21 males and 6 females, with an average age of 52.0±10.6 years. The preoperative body mass index of the two groups was greater than 25 kg/m2, white blood cell count, C-reactive protein were significantly higher than normal level, but there was no statistical difference between the groups (P＞0.05). There were no statistical differences in intraoperative data between the two groups (P＞0.05). The iNO group had significantly shorter duration of mechanical ventilation, postoperative ICU stay, and postoperative hospital stay than the control group (P<0.001). After 12 h of iNO treatment, hypoxic condition improved obviously, oxygenation indices in 12 h, 24 h, 36 h,48 h, 60 h and 72 h in the iNO group were significantly higher than those in the control group (P<0.05). Conclusion The treatment of severe hypoxemia after Sun’s surgery with low-dose of iNO is safe and effective, can significantly improve oxygenation function, and has significant advantages in shortening ventilator use time, postoperative ICU stay and postoperative hospital stay, but it is not significant in changing postoperative mortality.

Objective　To assess the diagnostic efficacy of the cell-free Mycobacterium tuberculosis DNA testing (CF-TB) in tuberculous pleurisy. Methods　A total of 71 patients diagnosed with tuberculous pleurisy and 35 patients with non-tuberculous pleurisy were selected from the Fifth People's Hospital of Wuxi between January to December 2022. The standard pleural puncture was conducted to collect pleural effusion, which was then utilized for Mycobacterium tuberculosis culture, GeneXpert Mycobacterium tuberculosis/rifampicin resistance (GeneXpert MTB/RIF), CF-TB, and adenosine deaminase (ADA) testing. Blood samples were subjected to tuberculosis infection T-cell spotting test (T-SPOT.TB) assay. The receiver operator characteristic curve (ROC) was applied to obtain the optimal cut-off value for pleural fluid CF-TB and to compare the diagnostic performance of CF-TB with other methods. Data analysis was conducted using SPSS 22.0 software, with statistical significance defined as P<0.05. Results　The ROC curve analysis determined that the optimal cycle threshold (Ct) value for diagnosing tuberculous pleurisy using CF-TB in pleural fluid was 38.489, with a sensitivity of 91.5% and specificity of 97.1%. In comparison, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of T-SPOT.TB and pleural fluid ADA in diagnosing tuberculous pleurisy were 86.0%, 71.4%, 86.0%, 71.4%, 81.1%, and 55.0%, 91.4%, 92.9%, 50.8%, 67.0%, respectively, all of which were lower than the diagnostic efficiency of CF-TB. Furthermore, the specificity of pleural fluid CF-TB in diagnosing tuberculous pleurisy (97.1%) was not significantly different from GeneXpert MTB/RIF (100%) and Mycobacterium tuberculosis culture (100%), but its sensitivity (91.5%) was significantly higher than both GeneXpert MTB/RIF (19.7%) and Mycobacterium tuberculosis culture (28.2%), with a statistically significant difference (P<0.001). Conclusions　Compared to the conventional gold standard for diagnosing tuberculous pleurisy, CF-TB exhibits a higher sensitivity and its specificity is superior to that of tuberculosis immunological test. Consequently, CF-TB can serve as a valuable complement to other traditional detection methods in aiding the diagnosis of tuberculous pleurisy.