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Objective@#This study aimed to determine the predictive performance of non-contrast CT (NCCT) signs for hemorrhagic growth after intracerebral hemorrhage (ICH) when stratified by onset-to-imaging time (OIT). @*Materials and Methods@#1488 supratentorial ICH within 6 h of onset were consecutively recruited from six centers between January 2018 and August 2022. NCCT signs were classified according to density (hypodensities, swirl sign, black hole sign, blend sign, fluid level, and heterogeneous density) and shape (island sign, satellite sign, and irregular shape) features. Multivariable logistic regression was used to evaluate the association between NCCT signs and three types of hemorrhagic growth: hematoma expansion (HE), intraventricular hemorrhage growth (IVHG), and revised HE (RHE). The performance of the NCCT signs was evaluated using the positive predictive value (PPV) stratified by OIT. @*Results@#Multivariable analysis showed that hypodensities were an independent predictor of HE (adjusted odds ratio [95% confidence interval] of 7.99 [4.87–13.40]), IVHG (3.64 [2.15–6.24]), and RHE (7.90 [4.93–12.90]). Similarly, OIT (for a 1-h increase) was an independent inverse predictor of HE (0.59 [0.52–0.66]), IVHG (0.72 [0.64–0.81]), and RHE (0.61 [0.54– 0.67]). Blend and island signs were independently associated with HE and RHE (10.60 [7.36–15.30] and 10.10 [7.10–14.60], respectively, for the blend sign and 2.75 [1.64–4.67] and 2.62 [1.60–4.30], respectively, for the island sign). Hypodensities demonstrated low PPVs of 0.41 (110/269) or lower for IVHG when stratified by OIT. When OIT was ≤ 2 h, the PPVs of hypodensities, blend sign, and island sign for RHE were 0.80 (215/269), 0.90 (142/157), and 0.83 (103/124), respectively. @*Conclusion@#Hypodensities, blend sign, and island sign were the best NCCT predictors of RHE when OIT was ≤ 2 h. NCCT signs may assist in earlier recognition of the risk of hemorrhagic growth and guide early intervention to prevent neurological deterioration resulting from hemorrhagic growth.
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BACKGROUND@#Chronic obstructive pulmonary diseases (COPD) affects 45%-63% of lung cancer patients worldwide. Lung cancer patients complicated with COPD have decreased cardiopulmonary function and increased perioperative risk, and their postoperative exercise endurance and lung function are significantly lower than those with conventional lung cancer. Previous studies have shown that postoperative exercise training can improve the exercise endurance of unselected lung cancer patients, but it is unclear whether lung cancer patients with COPD can also benefit from postoperative exercise training. This study intends to explore the effects of postoperative exercise training on exercise endurance, daily activity and lung function of lung cancer patients with COPD.@*METHODS@#Seventy-four patients with non-small cell lung cancer (NSCLC) complicated with COPD who underwent pneumonectomy in the lung cancer center of West China Hospital of Sichuan University from August 5, 2020 to August 25, 2021 were prospectively analyzed. They were randomly divided into exercise group and control group; The patients in the two groups received routine postoperative rehabilitation in the first week after operation, and the control group was given routine nursing from the second week. On this basis, the exercise group received postoperative exercise rehabilitation training for two weeks. Baseline evaluation was performed 3 days before operation and endpoint evaluation was performed 3 weeks after operation.@*RESULTS@#The exercise endurance, daily activity and pulmonary function test results of the two groups decreased from baseline to the end point. However, after the operation and intervention program, the maximum oxygen consumption of Cardiopulmonary Exercise Test and the walking distance of 6-Minute Walking Test in the exercise group were significantly better than those in the control group [(13.09±1.46) mL/kg/min vs (11.89±1.38) mL/kg/min, P=0.033; (297±46) m vs (243±43) m, P=0.041]. The average number of we-chat steps in the exercise group was also significantly better than that in the control group (4,381±397 vs 3,478±342, P=0.035). Forced vital capacity (FVC) and forced expiratory volume in one second (FEV1) in the exercise group were better than those in the control group, but the difference did not reach a statistically significant level [(1.76±0.19) L vs (1.60±0.28) L, P=0.084; (1.01±0.17) L vs (0.96±0.21) L, P=0.467].@*CONCLUSIONS@#Postoperative exercise rehabilitation training can improve exercise endurance and daily activity ability of patients with lung cancer complicated with COPD and promote postoperative rehabilitation.
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Humans , Carcinoma, Non-Small-Cell Lung/surgery , Exercise , Forced Expiratory Volume , Lung Neoplasms/surgery , Pulmonary Disease, Chronic Obstructive/complicationsABSTRACT
ObjectivesThis study aims to develop a machine learning approach for automated severity assessment of COVID-19 patients based on clinical and imaging data. Materials and MethodsClinical data--demographics, signs, symptoms, comorbidities and blood test results--and chest CT scans of 346 patients from two hospitals in the Hubei province, China, were used to develop machine learning models for automated severity assessment of diagnosed COVID-19 cases. We compared the predictive power of clinical and imaging data by testing multiple machine learning models, and further explored the use of four oversampling methods to address the imbalance distribution issue. Features with the highest predictive power were identified using the SHAP framework. ResultsTargeting differentiation between mild and severe cases, logistic regression models achieved the best performance on clinical features (AUC:0.848, sensitivity:0.455, specificity:0.906), imaging features (AUC:0.926, sensitivity:0.818, specificity:0.901) and the combined features (AUC:0.950, sensitivity:0.764, specificity:0.919). The SMOTE oversampling method further improved the performance of the combined features to AUC of 0.960 (sensitivity:0.845, specificity:0.929). DiscussionImaging features had the strongest impact on the model output, while a combination of clinical and imaging features yielded the best performance overall. The identified predictive features were consistent with findings from previous studies. Oversampling yielded mixed results, although it achieved the best performance in our study. ConclusionsThis study indicates that clinical and imaging features can be used for automated severity assessment of COVID-19 patients and have the potential to assist with triaging COVID-19 patients and prioritizing care for patients at higher risk of severe cases.
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Automatic severity assessment and progression prediction can facilitate admission, triage, and referral of COVID-19 patients. This study aims to explore the potential use of lung lesion features in the management of COVID-19, based on the assumption that lesion features may carry important diagnostic and prognostic information for quantifying infection severity and forecasting disease progression. A novel LesionEncoder framework is proposed to detect lesions in chest CT scans and to encode lesion features for automatic severity assessment and progression prediction. The LesionEncoder framework consists of a U-Net module for detecting lesions and extracting features from individual CT slices, and a recurrent neural network (RNN) module for learning the relationship between feature vectors and collectively classifying the sequence of feature vectors. Chest CT scans of two cohorts of COVID-19 patients from two hospitals in China were used for training and testing the proposed framework. When applied to assessing severity, this framework outperformed baseline methods achieving a sensitivity of 0.818, specificity of 0.952, accuracy of 0.940, and AUC of 0.903. It also outperformed the other tested methods in disease progression prediction with a sensitivity of 0.667, specificity of 0.838, accuracy of 0.829, and AUC of 0.736. The LesionEncoder framework demonstrates a strong potential for clinical application in current COVID-19 management, particularly in automatic severity assessment of COVID-19 patients. This framework also has a potential for other lesion-focused medical image analyses.
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Coronavirus disease 2019 (COVID-19) has spread globally, and medical resources become insufficient in many regions. Fast diagnosis of COVID-19, and finding high-risk patients with worse prognosis for early prevention and medical resources optimization is important. Here, we proposed a fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis by routinely used computed tomography. We retrospectively collected 5372 patients with computed tomography images from 7 cities or provinces. Firstly, 4106 patients with computed tomography images and gene information were used to pre-train the DL system, making it learn lung features. Afterwards, 1266 patients (924 with COVID-19, and 471 had follow-up for 5+ days; 342 with other pneumonia) from 6 cities or provinces were enrolled to train and externally validate the performance of the deep learning system. In the 4 external validation sets, the deep learning system achieved good performance in identifying COVID-19 from other pneumonia (AUC=0.87 and 0.88) and viral pneumonia (AUC=0.86). Moreover, the deep learning system succeeded to stratify patients into high-risk and low-risk groups whose hospital-stay time have significant difference (p=0.013 and 0.014). Without human-assistance, the deep learning system automatically focused on abnormal areas that showed consistent characteristics with reported radiological findings. Deep learning provides a convenient tool for fast screening COVID-19 and finding potential high-risk patients, which may be helpful for medical resource optimization and early prevention before patients show severe symptoms. Take-home messageFully automatic deep learning system provides a convenient method for COVID-19 diagnostic and prognostic analysis, which can help COVID-19 screening and finding potential high-risk patients with worse prognosis.
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T-box transcription factor gene (TBX) interferes with the origin and development of organs, and TBX5 is expressed highest in normal cardiac and pulmonary tissues. Lack of TBX5 may lead to thoracic malformation and abnormal diaphragmatic development, in which ectopic expression and overexpression may induce the apoptosis of cell and inhibit the development of cell. Previous studies demonstrated the potential role of TBX5 in the development and progression of esophageal adenocarcinoma, gastric cancer, colon cancer and breast cancer. We reviewed the association between the expression of TBX2 subfamily and the prognosis, and explore the research progress of TBX5 in regulating the development and progression of lung cancer. Even though the relationshihp the development of lung cancer and TBX5 are not clear, TBX5 could significantly inhibit in vivo tumor growth, and the level of TBX5 was negatively correlated with lung cancer progression. Therefore, the gene expression levels and methylation extent of TBX could be a potential biomarker to reveal the proliferation and metastasis of lung cancer, as well as a therapeutic target for lung cancer. .
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Objective To investigate the radiographic characteristics of posterosuperior fracture fragment of the injured vertebral body and its effects on the results of surgical treatment in thoracolumbar burst fractures.Methods A total of 45 patients with acute thoracolumbar burst treated by either anterior or posterior surgery from January 2014 to December 2015 were analyzed by retrospective casecontrol study.There were 24 males and 21 females with a mean age of 33.6 years (range,23-52 years).Fractured segments included T12 in six cases,L1 in 15,L2 in 14,L3 in 5,and L4 in 5.Based on AO classification,there were ten cases of A3 fractures and 35 cases of Ag fractures,among which four cases of A4 were combined with B2 injuries.Eleven patients underwent anterior surgery and 34 patients posterior surgery.The operation time and intraoperative blood loss were recorded.The following parameters were also measured pre-and post-operatively,namely the displacement and inversion angle of posterosuperior fracture fragment,Cobb angle,anteroposterior diameter (APD) of spinal canal,and American spinal injury association (ASIA) neurological scale.Results All patients were followed up for 11-24 months (mean,17 months).There were no complications except for one case of implant loosening at three months after anterior surgery.The average operation time was 138.3 minutes and intraoperative blood loss was 293.7 ml in anterior surgery while the average operation time was 77.5 minutes and intraoperative blood loss was 54.7 ml in posterior surgery (P < 0.05).Compared with postoperative situation,the canal APD was increased by 55.5% in anterior surgery and the corresponding increase was 14.9% in posterior surgery (P < 0.01).There was no significant difference between two groups in Cobb angle correction.Compared with situation before surgery,the postoperative ASIA grading was improved in 73% of the patients in anterior surgery and while it was enhanced in 24% of the patients in posterior surgery (P < 0.05).On the aspect of spinal canal decompression,anterior surgery had obvious decompression effects.The canal APD of anterior surgery was 94.4%,which was larger than 88.5% in posterior surgery,although the difference was not significant.Notably,when the fragment displacement was ≤ 8 mm,posterior surgery could achieve 97.4% APD which was comparable with that of anterior surgery.In contrast,when the fragment displacement was > 8 mm,the APD was much smaller in posterior surgery with only 78.5% (P < 0.05).Similarly,when the fragment inversion was ≤25° or > 25°,the APD was significantly different in anterior surgery and posterior surgery (95.4% vs.80.8%) (P < 0.05).Conclusions Although posterior surgery for thoracolumbar burst fractures is easy to perform and has short operation time and little intraoperative blood loss,it cannot always guarantee adequate decompression of spinal canal.When the posterosuperior fragment displacement is > 8 mm or when its inversion is > 25°,stand-alone posterior indirect reduction technique is likely to lead to inadequacy of canal restoration.In this case,anterior surgery should be considered in order to achieve more complete canal decompression.Therefore,this radiographic characteristic of the posterosuperior fragment could serve as an approach reference for thoracolumbar burst fractures.
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Objective To investigate the clinical characteristics, location, treatment and prognosis of periosteal osteosarcoma. Methods The data of 1 patient with periosteal osteosarcoma was retrospectively analyzed, and the 35 cases reported in CNKI database in recent years were analyzed. Results The patient of periosteal osteosarcoma was female and 16 years old. Periosteal osteosarcoma occurred in the tibia. The patient was treated with extensional resection, and had no recurrence and metastasis 3 months after operation. Among the 35 patients reported in the literature, the age of onset ranged from 14 to 35, the female was slightly more than the male (19 cases vs. 16 cases), and the lesion site was mainly in the tibia and femur. The 35 patients underwent surgical treatment, and 4 cases had metastasis;6 cases were treated by surgery combined with chemotherapy. Conclusions Female patients with periosteal osteosarcoma were slightly more than male, and the lesion site is mainly in the tibia and femur. The chemotherapy effect is not exact, and extensional resection is the most effective treatment method. The transfer site and the characteristics are not exact.
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Objective To compare the difference of the Cif gene expression and the inflammation markers (such as WBC and CRP et al)between mucoid and non-mucoid Pseudonmonasaeruginosa,combining with the clinical data.Methods Real-time RT-PCR was used to determine the expression level of Cif in Pseudonmonas aeruginosa and clinical data were collected to discuss the relationship among the number of WBC,the level of CRP and the Cif gene expression.Results The expression level of Cif gene in mucoid Pseudonmonas aeruginosa had a significantly higher than the non-mucoid Pseudonmonas aerugi-nosa,which was statistically significant (t=2.09,P0.05).The data also showed that the cystic fibrosis transmembrane conductance regulator in-hibitory factor (Cif)gene expression level had little correlation with the number of WBC (a=0.095,R2=0.029).Conclusion The expression of Cif gene may works for the biofilm formation of mucoid Pseudonmonas aeruginosa,which maybe a new virulence factor to Pseudonmonas aeruginosa.
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<p><b>BACKGROUND AND OBJECTIVE</b>Atelectasis is a common complication after thoracotomy, and it may threaten patients' life if it was not treated correctly and properly. The aim of this article is to explore and discuss the prevention and treatment for atelectasis during the perioperative period, and also to explore new methods for reducing the perioperative mortality due to atelectasis after thoracotomy.</p><p><b>METHODS</b>We retrospectively reviewed the medical records of 374 lung cancer patients who underwent thoracotomy in our department between Jan 2007 and Nov 2009.</p><p><b>RESULTS</b>Atelectasis occurred in 14 patients among all the 374 lung cancer patients who underwent thoracotomy. All the atelectasis returned to reexpansion after treatment.</p><p><b>CONCLUSION</b>The incidence of atelectasis in these series is relatively low compared with the reports in literatures. Good perioperative preparation and perioperative treatment can remarkably decrease the incidence and mortality of atelectasis after thoracotomy in the treatment of lung cancer.</p>
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Female , Humans , Male , Middle Aged , Lung Neoplasms , General Surgery , Pulmonary Atelectasis , Retrospective Studies , Thoracotomy , MethodsABSTRACT
MYB proteins are a superfamily of transcription factors that play regulatory roles in developmental processes and defense responses in plants. We identified 198 genes in the MYB superfamily from an analysis of the complete Arabidopsis genome sequence, among them, 126 are R2R3-MYB, 5 are R1R2R3-MYB, 64 are MYB-related, and 3 atypical MYB genes. Here we report the expression profiles of 163 genes in the Arabidopsis MYB superfamily whose full-length open reading frames have been isolated. This analysis indicated that the expression for most of the Arabidopsis MYB genes were responsive to one or multiple types of hormone and stress treatments. A phylogenetic comparison of the members of this superfamily in Arabidopsis and rice suggested that the Arabidopsis MYB superfamily underwent a rapid expansion after its divergence from monocots but before its divergence from other dicots. It is likely that the MYB-related family was more ancient than the R2R3-MYB gene family, or had evolved more rapidly. Therefore, the MYB gene superfamily represents an excellent system for investigating the evolution of large and complex gene families in higher plants. Our comprehensive analysis of this largest transcription factor superfamily of Arabidopsis and rice may help elucidate the possible biological roles of the MYB genes in various aspects of flowering plants.