Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

BACKGROUND:How to improve the accuracy of puncture,reduce surgical damage,and improve surgical efficiency during vertebroplasty is currently one of the focuses of exploration and improvement in vertebroplasty techniques. OBJECTIVE:To explore the clinical significance of application of mixed reality technology in percutaneous vertebroplasty for spinal fractures. METHODS:Two patients with osteoporotic vertebral compression fracture in Dalian Second People's Hospital in June 2023 were selected.Before operation,128-row CT scanning of the lumbar spine was performed and the original data of digital imaging and communications in medicine(DICOM)were obtained.Visual Volume software was used to build the three-dimensional network model of vertebral compression fracture.Holographic imaging glasses were used to accurately map 3D network model images to the real world,assist the surgeon in completing preoperative simulation,explaining preoperative conditions and treatment plans,and guiding puncture and bone cement injection during surgery. RESULTS AND CONCLUSION:(1)Precise puncture was achieved with the assistance of a mixed reality technology.Postoperative imaging examination showed good bone cement filling and no obvious leakage.The postoperative symptoms of the patient were alleviated well,and they were able to move to the ground on the same day after surgery.(2)It is concluded that a mixed reality technology is helpful for preoperative surgical design and communication efficiency with patients and their families.Assisting with precise puncture during surgery,shortening surgical time,and reducing side injuries is a new and effective clinical diagnosis and treatment model,which has development potential in minimally invasive,precise,and personalized treatment of spinal surgery.

Purpose: Neoadjuvant chemotherapy is strongly recommended for advanced gastric cancer due to good local control and a high rate of R0 dissection with this strategy. Minimally invasive techniques such as laparoscopy-assisted or total laparoscopic approaches is becoming more and more acceptable in the treatment for gastric cancer. However, the safety and efficiency of total laparoscopic D2 gastrectomy (TLG) for advanced gastric cancer after neoadjuvant chemotherapy have not been well evaluated. Methods: A retrospective study in a single center from 2014 to 2016 was conducted. A total of 65 locally advanced gastric cancers were treated by laparoscopy-assisted gastrectomy (LAG) or TLG. Parameters which include operation time, blood loss, complications, hospital stay, 3-year overall survival, and 3-year disease-free survival were used for comparison. Results: The time of operation in the TLG group was shorter than in the LAG group (P = 0.013), blood loss was less (P = 0.002) and time to first flatus was shorter (P = 0.039) in the TLG group than that in the LLG group. Intraoperative and postoperative complications were comparable in both groups. No significant difference was found in 3-year overall and disease-free survival. Conclusion For patients with locally advanced gastric cancer after neoadjuvant chemotherapy, laparoscopic D2 gastrectomy can be considered as a safe and efficient alternative. A further multicenter prospective randomized controlled study is needed to elucidate the applicability of this technique for advanced gastric cancer.

Objective:To explore the predictive value of deep learning (DL)-based coronary artery calcification score (CACS) for obstructive coronary artery disease (CAD) and noncalcified plaque/mixed plaque in type 2 diabetes mellitus (T2DM).Methods:Forty hundred and twenty-four consecutive T2DM patients who accepted CACS scan and coronary CT angiography (CCTA) from December 2012 to December 2019 were included retrospectively, with clinical risk factors and plaque features collected. Plaque composition was classified as calcified, non-calcified or mixed plaque. Obstructive CAD was defined as maximum diameter stenosis≥50%. CACS was calculated with a fully automated method based on DL. Univariate and multivariate logistic regressions were applied to select statistically significant factors and the odds ratios(ORs) were measured. Receiver operating characteristic (ROC) curve was evaluated to assess the predictive performance.Results:Increased CACS was associated with a significantly higher odds of obstructive CAD in CCTA (adjusted ORs were 2.22, 6.18 and 16.98 for CACS=1-99, 100-299, 300-999 vs. CACS=0, and P values were 0.009,<0.001,<0.001 respectively). The area under ROC curve (AUC) of CACS to predict obstructive CAD was 0.764. Compared with 0, increased CACS was associated with increased risk of non-calcified/mixed plaque (adjusted ORs were 2.75, 4.76, 5.29 for CACS=1-99, 100-299, 300-999 respectively and P values were 0.001,<0.001,<0.001 respectively). The AUC of CACS to predict non-calcified/mixed plaque was 0.688. It took 1.17 min to perform automated measurement of CACS based on DL in total, which was significantly less than manual measurement of 1.73 min ( P<0.001). Conclusion:DL-based CACS can predict obstructive CAD and non-calcified plaque/mixed plaque in T2DM, which is economical and efficient, and has important value for clinical diagnosis and treatment.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is an underdiagnosed genetic heart disease worldwide. The management and prognosis of obstructive HCM (HOCM) and non-obstructive HCM (HNCM) are quite different, but it also remains challenging to discriminate these two subtypes. HCM is characterized by dysmetabolism, and myocardial amino acid (AA) metabolism is robustly changed. The present study aimed to delineate plasma AA and derivatives profiles, and identify potential biomarkers for HCM. METHODS: Plasma samples from 166 participants, including 57 cases of HOCM, 52 cases of HNCM, and 57 normal controls (NCs), who first visited the International Cooperation Center for HCM, Xijing Hospital between December 2019 and September 2020, were collected and analyzed by high-performance liquid chromatography-mass spectrometry based on targeted AA metabolomics. Three separate classification algorithms, including random forest, support vector machine, and logistic regression, were applied for the identification of specific AA and derivatives compositions for HCM and the development of screening models to discriminate HCM from NC as well as HOCM from HNCM. RESULTS: The univariate analysis showed that the serine, glycine, proline, citrulline, glutamine, cystine, creatinine, cysteine, choline, and aminoadipic acid levels in the HCM group were significantly different from those in the NC group. Four AAs and derivatives (Panel A; proline, glycine, cysteine, and choline) were screened out by multiple feature selection algorithms for discriminating HCM patients from NCs. The receiver operating characteristic (ROC) analysis in Panel A yielded an area under the ROC curve (AUC) of 0.83 (0.75-0.91) in the training set and 0.79 (0.65-0.94) in the validation set. Moreover, among 10 AAs and derivatives (arginine, phenylalanine, tyrosine, proline, alanine, asparagine, creatine, tryptophan, ornithine, and choline) with statistical significance between HOCM and HNCM, 3 AAs (Panel B; arginine, proline, and ornithine) were selected to differentiate the two subgroups. The AUC values in the training and validation sets for Panel B were 0.83 (0.74-0.93) and 0.82 (0.66-0.98), respectively. CONCLUSIONS The plasma AA and derivatives profiles were distinct between the HCM and NC groups. Based on the differential profiles, the two established screening models have potential value in assisting HCM screening and identifying whether it is obstructive.
Humans ; Amino Acids ; Cysteine ; Cardiomyopathy, Hypertrophic/diagnosis* ; Biomarkers ; Proline ; Arginine ; Ornithine ; Glycine ; Choline

Purpose: Our study aimed to make a propensity score matching (PSM) analysis on the clinical application of gastricjejunum pouch anastomosis (GJPA) and Billroth-II anastomosis after distal gastrectomy. Methods: We collected clinical data from 249 patients who received distal gastrectomy from January 2016 to July 2020. According to the reconstruction method used, all patients were divided into the Billroth-II group and the GJPA group. Clinical data and operation complications were analyzed. Results: The clinical characteristics of the 2 groups were comparable after PSM. In the Billroth-II group, the incidence rate of delayed gastric emptying was higher than that in the GJPA group. Fewer patients suffered reflux gastritis in the GJPA group. The RGB (residue, gastritis, and bile) scores related to the severity of bile reflux into the remnant stomach, gastritis, and residue were higher in the Billroth-II group. Postoperative nutritional status and Visick classification demonstrated that postoperative subjective feelings in the GJPA group were improved significantly. Conclusion The application of GJPA in reconstruction after distal gastrectomy is safe, economical, and reliable. This reconstruction improved the quality of life of patients. It is worth popularizing widely in clinical settings.

Objective:To review the experience of closure of the left-main-bronchial stump fistula using endoscopic liner cutter staplers through the right thoracic approach and I stage or staged treatment for the left pyothorax.Methods:6 patients with the left-main-bronchial stump fistula after left pneumonectomy combined with pyothorax were treated by closing the left-main-bronchial stump using endoscopic liner cutter staplers through the right thoracic approach, and pleura was used to cover the distal and proximal incisional margin of the stump respectively. The thoracic T-tube drainage was used in the I stage or staged treatment for the left pyothorax.Results:All patients were survived without recurrence of the bronchopleural fistula. 4 patients were observed to have no recurrence of pyothorax when 1 patient had recurrence of pyothorax and was treated with intermittent T-tube drainage.1 patient operated with left-thoracic fenestration in the past was treated with drainage waiting for secondary operation.Conclusion:The right thoracic approach seemed to be a safer and more effective method than the transsternal transpericardial approach in cases with the left-main-bronchial stump fistula combined with pyothorax. The use of endoscopic liner cutter staplers reduced the risk of bleeding, infection and recurrence of fistula. The T-tube drainage in the I stage or staged treatment for the left pyothorax was considered to be an easier way for treatment.

Objective:To explore the value of pre-treatment contrast-enhanced computed tomography (CT)-based texture analysis in predicting response to non-small cell lung cancer (NSCLC) immunotherapy.Methods:From January to July 2018, a total of 51 lesions from 42 patients with advanced non-small cell lung cancer receiving immunotherapy at Shanghai Chest Hospital were selected in this retrospective study. Pre-treatment contrast-enhanced CT-based texture features were extracted by MaZda software. Ten optimal texture features were chosen based on three different methods: Fisher coefficient, mutual information measure (MI) and minimization of classification error probability combined average correlation coefficients(POE+ ACC), respectively. According to the efficacy of the first immunotherapy, 51 lesions were divided into non-progressive disease (non-PD, n=26) and progressive disease (PD, n=25). The differences were tested in each texture feature set between the two groups. The immunotherapy effects of target lesions were analyzed by principal component analysis(PCA), linear discriminant analysis (LDA) and nonlinear discriminant analysis (NDA). The sensitivity, specificity, accuracy, positive-predictive value (PPV) and negative-predictive value (NPV) were calculated. The area under the curve (AUC) was used to quantify the predictive accuracy of the three analysis models for each texture feature set and compare them with the actual classification results. Results:In all of three texture feature sets, the texture parameter differences of Perc.50%, Perc.90%, "S(5, 5)SumEntrp" and "S(4, 4)SumEntrp" were higher in PD group than those in non-PD group (all P<0.05). The classification result of texture feature set chosen by POE+ ACC and analyzed by NDA was identified as the best model (AUC=0.802, 95% CI: 0.674-0.930), and its sensitivity, specificity, accuracy, PPV and NPV were 72%, 88.5%, 80.4%, 85.7%, 76.7%, respectively. Conclusion:Pre-treatment contrast-enhanced CT-based texture characteristics of NSCLC may function as non-invasive biomarkers for the evaluation of response to immunotherapy.

Objective:To explore the value of pre-treatment contrast-enhanced computed tomography (CT)-based texture analysis in predicting response to non-small cell lung cancer (NSCLC) immunotherapy.Methods:From January to July 2018, a total of 51 lesions from 42 patients with advanced non-small cell lung cancer receiving immunotherapy at Shanghai Chest Hospital were selected in this retrospective study. Pre-treatment contrast-enhanced CT-based texture features were extracted by MaZda software. Ten optimal texture features were chosen based on three different methods: Fisher coefficient, mutual information measure (MI) and minimization of classification error probability combined average correlation coefficients(POE+ ACC), respectively. According to the efficacy of the first immunotherapy, 51 lesions were divided into non-progressive disease (non-PD, n=26) and progressive disease (PD, n=25). The differences were tested in each texture feature set between the two groups. The immunotherapy effects of target lesions were analyzed by principal component analysis(PCA), linear discriminant analysis (LDA) and nonlinear discriminant analysis (NDA). The sensitivity, specificity, accuracy, positive-predictive value (PPV) and negative-predictive value (NPV) were calculated. The area under the curve (AUC) was used to quantify the predictive accuracy of the three analysis models for each texture feature set and compare them with the actual classification results. Results:In all of three texture feature sets, the texture parameter differences of Perc.50%, Perc.90%, "S(5, 5)SumEntrp" and "S(4, 4)SumEntrp" were higher in PD group than those in non-PD group (all P<0.05). The classification result of texture feature set chosen by POE+ ACC and analyzed by NDA was identified as the best model (AUC=0.802, 95% CI: 0.674-0.930), and its sensitivity, specificity, accuracy, PPV and NPV were 72%, 88.5%, 80.4%, 85.7%, 76.7%, respectively. Conclusion:Pre-treatment contrast-enhanced CT-based texture characteristics of NSCLC may function as non-invasive biomarkers for the evaluation of response to immunotherapy.

Objective:To investigate the value of pericoronary adipose tissue histogram parameters based on coronary CT angiography (CTA) images for the differentiation of acute coronary syndrome and stable coronary artery disease.Methods:The clinical data and CTA images of 93 patients with coronary CTA examination in Suzhou Kowloon Hospital from 2013 to 2018 were analyzed retrospectively. There were 39 patients with acute coronary syndrome (acute coronary syndrome group) and 54 patients with stable coronary artery disease (stable coronary artery disease group). A region of interest (ROI) was drawn around the stenosis of the coronary arteries, with CT attenuation ranging from-190 to -30 HU to exclude non-adipose tissue. The CT attenuation of ROI excluding non-adipose were measured and histogram analysis was performed. The obtained parameters included the mean value, median value and the 5th, 10th, 45th, 55th, 70th and 95th percentiles. The differences in histogram parameters between the two groups were compared, and then the value of each parameter in differentiating acute coronary syndrome and stable coronary artery disease was evaluated based on receiver operating characteristic (ROC) analysis. The stepwise regression of multivariate logistic regression analysis was used to identify the useful features and establish the final prediction model. The ROC curve of the final model was calculated and its value was analyzed.Results:The mean, median and the 5th, 10th, 45th, 55th,70th and 95th percentile differences between the acute coronary syndrome group and the stable coronary artery disease group were statistically significant (all P<0.05). The ROC curve for the median and the 95th percentile had the same area under curve (AUC) of 0.73. The sensitivity, specificity and AUC of the diagnostic model established by multiple logistic regression were 82.1%, 89.1% and 0.90 respectively. Conclusion:CT attenuation histogram of pericoronary adipose tissue is of high value in differentiating acute coronary syndrome from stable coronary artery disease.