Objective:To analyze the etiological characteristics of Clostridium ramosum DZS3717106 isolated from the blood of a patient with septic shock secondary to perianal abscess and the immunological characteristics of the patient. Methods:The isolate was subjected to morphological observation, mass spectrometry, antibiotic susceptibility testing, and 16S rRNA sequencing. Biochemical and cytological test results of the patient were collected. Flow cytometry was used to detect T cell subsets. Impacts of the virulence factors of the isolate on the host immune system were evaluated.Results:DZS3717106 was an anaerobic Clostridium with pleomorphic rod-shaped cells and spores. It was sensitive to penicillin G, piperacillin/tazobactam, and metronidazole, but resistant to clindamycin. It carried various virulence and resistance genes. The patient was immunocompromised with abnormal IL-6, IL-8, and IL-10 levels. Conclusions:Septic shock caused by Clostridium ramosum is rare, and more research is needed on the causes and epidemiology. DZS3717106 infection triggers over-activated inflammatory response in the patient, which may be closely related to the occurrence and development of septic shock.

Objective:To analyze the risk factors for clinically relevant delayed gastric emptying (CR-DGE) following laparoscopic pancreaticoduodenectomy (LPD) and to develop a model to predict the postoperative CR-DGE after LPD using the machine-learning approach with multi-model comparison.Methods:Clinical data of 278 patients with tumors located in the pancreatic head and periampullary region undergoing LPD at People’s Hospital of Zhengzhou University from January 2019 to December 2023 were retrospectively analyzed, including 167 males and 111 females, aged 59 (53, 66) years. According to the occurrence of DGE, patients were divided into the CR-DGE group ( n=94) and the non-CR-DGE group ( n=184). Main clinical characteristics were compared between the groups, including pancreatic duct diameter, intraoperative blood loss and operative time. The perioperative indicators were selected using the least absolute shrinkage and selection operator (LASSO) algorithm. Following variable selection, 278 patients were allocated into a training set ( n=222) and a validation set ( n=56) in an 8∶2 ratio. Eight machine learning models were selected to model the training set: random forest, adaptive boosting, light gradient boosting, multilayer perceptron, support vector machine, K-nearest neighbor algorithm, decision tree and complementary set plain bayes. The area under the curve (AUC) of receiver operating characteristic curve of the validation set was utilized to identify the optimal model. The predictive performance of the optimal model was evaluated using calibration plots and decision curve analysis (DCA). The contribution of each feature to the prediction is assessed using Shapley additive explanation (SHAP). Results:Univariate analysis showed statistically significant differences between the CR-DGE and non-CR-DGE groups in terms of age [66(62, 69) years vs. 56(51, 60), years], diabetes [42.6%(40/94) vs. 11.4%(21/184)], level of fibrinogen [3.43(2.74, 4.18) g/L vs. 3.84(3.19, 4.68) g/L], pancreatic duct diameter [2.00(1.50, 2.70) mm vs. 3.40(1.60, 5.00) mm], intraoperative blood loss [300(200, 600) ml vs. 200(150, 300) ml], operative time [472(430, 502) min vs. 430(365, 475) min], clinically relevant postoperative pancreatic fistula [34.0%(32/94) vs. 3.8%(7/184)], abdominal fluid accumulation [46.8%(44/94) vs. 12.5%(23/184)], postoperative hemorrhage [20.2%(19/94) vs. 3.3%(6/184)], abdominal infection [28.7%(27/94) vs. 11.4% (21/184)] and duration of postoperative gastrointestinal decompression [4.00 (2.00, 6.00) d vs. 3.00 (2.00, 5.00) d] (all P<0.05). The eleven variables selected via LASSO were incorporated into each of the eight machine learning models. Results demonstrated that the random forest model achieved the highest performance in the validation set, with an AUC of 0.894 (95% CI: 0.800-0.985), accuracy of 0.820 and sensitivity of 0.606. Calibration plots and DCA confirmed the robustness of the random forest model. SHAP analysis indicated that age, pancreatic duct diameter and preoperative aspartate aminotransferase were important predictors in the random forest model. Conclusion:The random forest model developed in this study demonstrated a good predictive performance for CR-DGE after LPD and may assist in the early identification of high-risk patients in clinical practice.

Objective:To analyze the etiological characteristics of Clostridium ramosum DZS3717106 isolated from the blood of a patient with septic shock secondary to perianal abscess and the immunological characteristics of the patient. Methods:The isolate was subjected to morphological observation, mass spectrometry, antibiotic susceptibility testing, and 16S rRNA sequencing. Biochemical and cytological test results of the patient were collected. Flow cytometry was used to detect T cell subsets. Impacts of the virulence factors of the isolate on the host immune system were evaluated.Results:DZS3717106 was an anaerobic Clostridium with pleomorphic rod-shaped cells and spores. It was sensitive to penicillin G, piperacillin/tazobactam, and metronidazole, but resistant to clindamycin. It carried various virulence and resistance genes. The patient was immunocompromised with abnormal IL-6, IL-8, and IL-10 levels. Conclusions:Septic shock caused by Clostridium ramosum is rare, and more research is needed on the causes and epidemiology. DZS3717106 infection triggers over-activated inflammatory response in the patient, which may be closely related to the occurrence and development of septic shock.

Objective:To analyze the risk factors for clinically relevant delayed gastric emptying (CR-DGE) following laparoscopic pancreaticoduodenectomy (LPD) and to develop a model to predict the postoperative CR-DGE after LPD using the machine-learning approach with multi-model comparison.Methods:Clinical data of 278 patients with tumors located in the pancreatic head and periampullary region undergoing LPD at People’s Hospital of Zhengzhou University from January 2019 to December 2023 were retrospectively analyzed, including 167 males and 111 females, aged 59 (53, 66) years. According to the occurrence of DGE, patients were divided into the CR-DGE group ( n=94) and the non-CR-DGE group ( n=184). Main clinical characteristics were compared between the groups, including pancreatic duct diameter, intraoperative blood loss and operative time. The perioperative indicators were selected using the least absolute shrinkage and selection operator (LASSO) algorithm. Following variable selection, 278 patients were allocated into a training set ( n=222) and a validation set ( n=56) in an 8∶2 ratio. Eight machine learning models were selected to model the training set: random forest, adaptive boosting, light gradient boosting, multilayer perceptron, support vector machine, K-nearest neighbor algorithm, decision tree and complementary set plain bayes. The area under the curve (AUC) of receiver operating characteristic curve of the validation set was utilized to identify the optimal model. The predictive performance of the optimal model was evaluated using calibration plots and decision curve analysis (DCA). The contribution of each feature to the prediction is assessed using Shapley additive explanation (SHAP). Results:Univariate analysis showed statistically significant differences between the CR-DGE and non-CR-DGE groups in terms of age [66(62, 69) years vs. 56(51, 60), years], diabetes [42.6%(40/94) vs. 11.4%(21/184)], level of fibrinogen [3.43(2.74, 4.18) g/L vs. 3.84(3.19, 4.68) g/L], pancreatic duct diameter [2.00(1.50, 2.70) mm vs. 3.40(1.60, 5.00) mm], intraoperative blood loss [300(200, 600) ml vs. 200(150, 300) ml], operative time [472(430, 502) min vs. 430(365, 475) min], clinically relevant postoperative pancreatic fistula [34.0%(32/94) vs. 3.8%(7/184)], abdominal fluid accumulation [46.8%(44/94) vs. 12.5%(23/184)], postoperative hemorrhage [20.2%(19/94) vs. 3.3%(6/184)], abdominal infection [28.7%(27/94) vs. 11.4% (21/184)] and duration of postoperative gastrointestinal decompression [4.00 (2.00, 6.00) d vs. 3.00 (2.00, 5.00) d] (all P<0.05). The eleven variables selected via LASSO were incorporated into each of the eight machine learning models. Results demonstrated that the random forest model achieved the highest performance in the validation set, with an AUC of 0.894 (95% CI: 0.800-0.985), accuracy of 0.820 and sensitivity of 0.606. Calibration plots and DCA confirmed the robustness of the random forest model. SHAP analysis indicated that age, pancreatic duct diameter and preoperative aspartate aminotransferase were important predictors in the random forest model. Conclusion:The random forest model developed in this study demonstrated a good predictive performance for CR-DGE after LPD and may assist in the early identification of high-risk patients in clinical practice.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

Based on the"You Gu Wu Yun"theory in traditional Chinese medicine(TCM),this paper believes that"Gu"in"You Gu Wu Yun"is extended to"state"from the perspective of"TCM state".In order to avoid the adverse reactions of TCM,the macro,meso,and micro three views should be used together,and macro,meso,and micro parameters should be integrated.We should also carefully identify the physiological characteristics,pathological characteristics,constitution,syndrome,and disease of human body by combining qualitative and quantitative method,highlighting the relationship between the prescription and the"state".The correspondence between prescription and the"state"will reduce the risk of adverse reactions of TCM.In this paper,we hope to focus on the guiding role of the"You Gu Wu Yun"theory in TCM research,to give full play to the characteristics and advantages of TCM,and to dialectically treat the role of TCM.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

The correspondence between prescription and syndrome is the advantage and characteristic of traditional Chinese medicine(TCM)treatment.However,the pathogenesis of clinical diseases is complex and the condition is changeable,and the clinical application is difficult to achieve the maximum effect under the existing cognition of the correspondence between prescription and syndrome.In this paper,the five categories of physiological characteristics,pathological characteristics,constitution,syndrome,and disease of the longitudinal classification of"TCM state"are introduced into the correspondence of prescription and syndrome.Under the vertical perspective of"TCM state",the theoretical connotation of the correspondence between prescription and syndrome is interpreted as"correspondence between prescription and state",namely correspondence of"prescription-physiological characteristics",correspondence of"prescription-pathological characteristics",correspondence of"prescription-constitution",correspondence of"prescription-syndrome",and correspondence of"prescription-disease".It is hoped to accurately grasp the corresponding connotation of the correspondence between prescription and syndrome,in order to deepen the clinical thinking mode of TCM.

Humans ; Asthma/drug therapy* ; Biological Therapy

Objective: To assess the efficacy and safety of polymyxin B in neutropenic patients with hematologic disorders who had refractory gram-negative bacterial bloodstream infection. Methods: From August 2021 to July 2022, we retrospectively analyzed neutropenic patients with refractory gram-negative bacterial bloodstream infection who were treated with polymyxin B in the Department of Hematology of the First Affiliated Hospital of the Soochow University between August 2021 to July 2022. The cumulative response rate was then computed. Results: The study included 27 neutropenic patients with refractory gram-negative bacterial bloodstream infections. Polymyxin B therapy was effective in 22 of 27 patients. The median time between the onset of fever and the delivery of polymyxin B was 3 days [interquartile range (IQR) : 2-5]. The median duration of polymyxin B treatment was 7 days (IQR: 5-11). Polymyxin B therapy had a median antipyretic time of 37 h (IQR: 32-70). The incidence of acute renal dysfunction was 14.8% (four out of 27 cases), all classified as "injury" according to RIFLE criteria. The incidence of hyperpigmentation was 59.3%. Conclusion: Polymyxin B is a viable treatment option for granulocytopenia patients with refractory gram-negative bacterial bloodstream infections.
Humans ; Polymyxin B/adverse effects* ; Retrospective Studies ; Gram-Negative Bacterial Infections/complications* ; Fever/drug therapy* ; Sepsis/drug therapy* ; Anti-Bacterial Agents/therapeutic use* ; Bacteremia/complications*