Objective To explore the value of biparametric magnetic resonance imaging(bp-MRI)radiomics models in noninvasive prediction of high-risk prostate cancer.Methods A total of 320 patients with pathologically confirmed prostate cancer were retro-spectively selected,and all patients underwent bp-MRI before pathology,including T2WI and diffusion weighted imaging(DWI).Appar-ent diffusion coefficient(ADC)maps were extracted from DWI.All patients were divided into high-risk(Gleason score≥8)and medium-low risk(Gleason score ≤7)groups based on the Gleason score.Using 3D Slicer software,the entire prostate gland was outlined.Python software was used to calculate parameters,and the minimum redundancy maximum correlation and sequence back-ward elimination algorithms were used to extract and select radiomics features and to build a model.Three radiomics(T2 WI,DWI,ADC)models were constructed and verified by logistic regression(LR).The performance of the model was evaluated by area under the curve(AUC)of receiver operating characteristic(ROC)curve,specificity(SP),sensitivity(SE),and accuracy(ACC).An indi-vidual prediction model was established via the clinical data of 224 patients and bp-MRI features,and validated via the data of 96 patients.Results A total of 1 165 radiomics features were extracted.After feature screening,2,4 and 6 radiomics features were screened out to construct T2WI model,DWI model and ADC model for predicting high-risk prostate cancer.All radiomics models had significant predictive performance in identifying medium-low risk and high-risk groups(P＜0.05).The DWI model had the highest predictive value,and the AUC,ACC,SE,and SP in the training group were 0.814,0.756,0.838,and 0.744,respectively.The AUC,ACC,SE,and SP in the verification group were 0.840,0.756,0.848,and 0.784,respectively.Conclusion Radiomics based on bp-MRI can better identify medium-low risk and high-risk prostate cancer before surgery.

OBJECTIVE To evaluate the effectiveness， safety， economy， innovation， suitability and accessibility of recombinant Mycobacterium tuberculosis fusion protein （EC）， and to provide evidence for selecting skin detection methods for tuberculosis infection diagnosis and auxiliary diagnosis of tuberculosis. METHODS The effectiveness and safety of EC compared with purified protein derivative of tuberculin （TB-PPD） were analyzed by the method of systematic review. Cost minimization analysis， cost-effectiveness analysis and cost-utility analysis were used to evaluate the short-term economy of EC compared with TB-PPD， and cost-utility analysis was used to evaluate the long-term economy. The evaluation dimensions of innovation， suitability and accessibility were determined by systematic review and improved Delphi expert consultation， and the comprehensive score of EC and TB-PPD in each dimension were calculated by the weight of each indicator. RESULTS The scores of effectiveness， safety， economy， innovation and suitability of EC were all higher than those of TB-PPD. The affordability scores of the two drugs were consistent， while the availability score of EC was lower than those of TB-PPD. After considering dimensions and index weight， the scores of effectiveness， safety， economy， innovation， suitability， accessibility and the comprehensive score of EC were all higher than those of TB-PPD. CONCLUSIONS Compared with TB-PPD， EC performs better in all dimensions of effectiveness， safety， economy， innovation， suitability and accessibility. However， it is worth noting that EC should further improve its availability in the dimension of accessibility.

OBJECTIVE: To investigate the consistency and diagnostic performance of magnetic resonance imaging (MRI) for detecting microvascular invasion (MVI) of hepatocellular carcinoma (HCC) and the validity of deep learning attention mechanisms and clinical features for MVI grade prediction. METHODS: This retrospective study was conducted among 158 patients with HCC treated in Shunde Hospital Affiliated to Southern Medical University between January, 2017 and February, 2020. The imaging data and clinical data of the patients were collected to establish single sequence deep learning models and fusion models based on the EfficientNetB0 and attention modules. The imaging data included conventional MRI sequences (T₁WI, T₂WI, and DWI), enhanced MRI sequences (AP, PP, EP, and HBP) and synthesized MRI sequences (T1mapping-pre and T1mapping-20 min), and the high-risk areas of MVI were visualized using deep learning visualization techniques. RESULTS: The fusion model based on T1mapping-20min sequence and clinical features outperformed other fusion models with an accuracy of 0.8376, a sensitivity of 0.8378, a specificity of 0.8702, and an AUC of 0.8501 for detecting MVI. The deep fusion models were also capable of displaying the high-risk areas of MVI. CONCLUSION The fusion models based on multiple MRI sequences can effectively detect MVI in patients with HCC, demonstrating the validity of deep learning algorithm that combines attention mechanism and clinical features for MVI grade prediction.
Humans ; Carcinoma, Hepatocellular ; Retrospective Studies ; Liver Neoplasms ; Magnetic Resonance Imaging ; Algorithms

Objective:To explore the effect of setting up an internal-cross disciplinary team (ICDT) in the intensive care unit (ICU) on a new model of overall treatment for patients with chronic critical illness (CCI).Methods:A 60-year-old male patient with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) admitted to ICU in the Second Affiliated Hospital of Fujian Medical University was introduced. The role of ICDT composed of physicians, nurses, respiratory therapists, physiotherapists, clinical dietitians and patients' family members in ventilator withdrawal and super-early rehabilitation was analyzed in this case.Results:The patient was diagnosed as AECOPD, type Ⅱ aspiration penumonia respiratory failure, septic shock. The ICDT in ICU carried out early rehabilitation treatment for the patient on the basis of traditional infection control and supportive treatment. Under the care of the ICDT, peripheral blood white blood cell count (WBC), neutrophil count (NEU), procalcitonin (PCT), arterial partial pressure of carbon dioxide (PaCO 2), maximum inspiratory pressure (MIP), maximum expiratory pressure (MEP), right excursion of diaphragm, sputum viscosity, tidal volume (VT) and respiratory rate (RR) were improved. Subsequently, the ventilator mode was gradually changed and the ventilator parameters were down-regulated. The ventilator was successfully weaned on the 10th day of treatment. After weaning, the patient's bedside pulmonary function indicators improved, and he was transferred out of ICU on the 15th day of treatment and discharged on the 20th day. The mental state of the patients was good and the quality of life was greatly improved in CCI outpatient follow-up. Conclusions:ICDT cooperation is very important for monitoring and treatment of CCI patients, which is beneficial to the super-early rehabilitation and prognosis improvement of critically ill patients.

Objective:To explore any changes with age in the center of plantar pressure among normal people after walking.Methods:Fifty healthy subjects were divided into a young group and an elderly group, each of 25. Gait descriptors were collected for each subject using a model AL-600 gait and balance training and evaluation apparatus. The gait descriptors were the center of pressure displacement (COPD), and the COPD in the medial-lateral (COPD-X) and anterior-posterior (COPD-Y) directions before and after 10 and 15 minutes of walking.Results:The average COPD, COPD-X and COPD-Y of the elderly group increased after both 10 and 15 minutes of walking, but among the young group increases were observed only after 15 minutes. The average COPD, COPD-X and COPD-Y of the elderly group were always significantly larger than the young group′s averages.Conclusions:Gait stability among the elderly decreases after as little as 10 minutes of walking, but among the young decreases are observed only after 15 minutes.

Antipyretic-analgesics are currently one of the most prescribed drugs in children.The clinical application of antipyretic-analgesics for children in our country still have irrational phenomenon, which affects the therapeutic effect and even poses hidden dangers to the safety of children.In this paper, suggestions were put forward from the indications, dosage form/route, dosage suitability, pathophysiological characteristics of children with individual differences and drug interactions in the symptomatic treatment of febrile children, so as to provide reference for the general pharmacists when conducting prescription review.

Objective:To document the blood indexes of middle-aged and elderly intracerebral hemorrhage (ICH) patients complicated with deep vein thrombosis (DVT).Methods:A retrospective analysis was conducted of 77 hospitalized ICH patients using venous color Doppler ultrasonography within 3 days of admission. According to the results, they were divided into a DVT group (18 cases) and a non-DVT group (59 cases). The blood routine, biochemistry, coagulation, and D-dimer examinations were conducted on the 2nd day after admission. T-tests and rank sum tests tested the significance of any differences between the groups in average white blood cell counts, neutrophil percentages, platelets, albumin, globulin, fasting blood glucose, urea nitrogen, creatinine, uric acid, electrolytes, fibrinogen or D-dimer.Results:The average levels of albumin, uric acid and calcium in the DVT group were significantly lower than in the non-DVT group. The average levels of fasting blood glucose and D-dimer were significantly higher.Conclusions:Decreased serum uric acid, calcium and albumin levels, together with increased fasting blood glucose and D-dimer are related to the occurrence of DVT in ICH patients. To reduce the risk of DVT it is important to maintain normal levels of serum uric acid, calcium and albumin and to limit D-dimer and fasting blood glucose.

Objective:To observe factors influencing the risk of urinary tract infection (UTI) after cerebral hemorrhage (ICH).Methods:A total of 77 ICH patients undergoing rehabilitation between August 2015 and August 2017 were studied. Among them, 24 were diagnosed with a UTI according to clinical manifestations and urine routine tests and urine culture. They formed the UTI group. The other 53 were the non-UTI group. Complete clinical evaluations were available for all 77, and those data were used to identify risk factors for UTI using univariate and multivariate logistic regression analysis.Results:The univariate analysis showed that age, side of paralysis, consciousness dysfunction, Brunnstrom staging of the lower extremity, tracheotomy, indwelling catheter, lung infection, white blood cell count, neutrophil percentage, serum natrium, uric acid, D-dimer level and fibrinogen were all significant predictors of UTI. The multivariate analysis identified age, right side hemiplegia and D-dimer level as useful predictors.Conclusions:Advanced age and a high D-dimer level are independent risk factors for UTI after ICH, while hemiplegia on the right side is a protective factor.

Currently, pediatric tuberculosis is still a serious infectious disease endangering pediatric health, and anti-tuberculosis (TB) therapy is the major treatment for this disease.The course of anti-TB treatment in children is generally long and requires multi-drug combination, which significantly increases the risk of adverse drug reactions(ADRs). Therefore, it is important for pediatricians to have an intimate knowledge of ADRs and countermeasures.The common ADRs in children include anti-TB drug-induced liver injury, skin adverse reactions, gastrointestinal reactions, drug fever, and post-bulbous neuritis.For children with mild and tolerable ADRs, symptomatic treatment should be performed and anti-TB treatment continued.If the adverse reaction is serious or cannot be tolerated, the drug should be stopped in time.If ADRs are complex, serious or rare, multidisciplinary discussion should be conducted to make the best clinical decision.

Objective:To compare the accuracy and generalized robustness of three predictive models of knowledge-based treatment strategies for radiotherapy for optimized model selection.Methods:The clinical radiotherapy plans of 45 prostate cancer (PC) cases and 25 nasopharyngeal cancer (NPC) cases were collected, and analyzed using three models (Z, L and S model), proposed by Zhu et al, Appenzoller et al and Shiraishi et al, respectively, to predict the dose-volume histogram (DVH) of bladder and rectum on PC cases and that of left and right parotid on NPC cases. The prediction error was measured by the difference of area under the predicted DVH and the clinical DVH curves (|V (pre_DVH)-V (clin_DVH)|), where a smaller prediction error implies a greater prediction accuracy. The accuracies of these three models were compared on the single organ at risk (OAR), and the generalized robustness of models was evaluated and compared by calculating the standard deviation of the prediction accuracy on different OAR. Results:For bladder and rectum, the prediction error of L model (0.114 and 0.163, respectively) was significantly higher than those values of Z and S models (≤0.071, P<0.05); for left parotid gland, the predicted error of S model (0.033) did not present significant difference from those values of Z and L models (≤0.025, P>0.05); for right parotid gland, S model (0.033) demonstrated significantly higher prediction error than those of Z and L models (≤0.028, P<0.05). Regarding different OAR, S model showed a lower standard deviation of prediction accuracy when comparing to Z and L models (0.016, 0.018 and 0.060, respectively). Conclusions:In the prediction of DVH in bladder and rectum of PC, Z and S models were more accurate than L model. In contrast, Z and L models demonstrated higher accuracy than S model in the prediction of left and right parotid glands of NPC. In respect to different OAR, the generalized robustness of S model was superior than the other two models.