Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.

Objective To establish the pharmacokinetic model of linezolid in neonates,and to optimize the administration regimen. Methods A prospective study was conducted among 64 neonates with sepsis who received linezolid as anti-infective therapy,and liquid chromatography-tandem mass spectrometry was used to measure the plasma concentration of the drug. Clinical data were collected,and nonlinear mixed effects modeling was used to establish a population pharmacokinetic (PPK) model. Monte Carlo simulation and evaluation was performed for the optimal administration regimen of children with different features. Results The pharmacokinetic properties of linezolid in neonates could be described by a single-compartment model with primary elimination,and the population typical values for apparent volume of distribution and clearance rate were 0.79 L and 0.34 L/h,respectively. The results of goodness of fit,visualization verification,and the Bootstrap method showed that the model was robust with reliable results of parameter estimation and prediction. Monte Carlo simulation results showed that the optimal administration regimen for linezolid in neonates was as follows:6 mg/kg,q8h,at 28 weeks of gestational age (GA);8 mg/kg,q8h,at 32 weeks of GA;9 mg/kg,q8h,at 34-37 weeks of GA;11 mg/kg,q8h,at 40 weeks of GA. Conclusions The PPK model established in this study can provide a reference for individual administration of linezolid in neonates. GA and body weight at the time of administration are significant influencing factors for the clearance rate of linezolid in neonates.

Objective To understand the whole genome sequence characteristics of a Coxsackievirus A4(CVA4)isolated from Yunnan,China in 2022,and explore the phylogenetic characteristics of CVA4.Methods The whole genome sequence of CVA4 isolate 194R3/YN/CHN/2022 was amplified and sequenced,and the phylogenetic tree of CVA4 isolate was constructed by using Mega 7.0,Geneious 9.1.4 and Simplot 3.5.1 softwares.The whole ge-nome sequence characteristics were analyzed.Results The 194R3/YN/CHN/2022 isolate was identified as CVA4,belonging to the C2 gene subtype,which was consistent with the dominant gene subtype in recent years in China.Recombination analysis showed that recombination of CVA4 virus isolate with EVA114 prototype(V13-0285),CVA16 prototype(G-10),and CVA14 prototype(G-14)at the non-structural coding regions of P2 and P3 may have occurred.Conclusion The 194R3/YN/CHN/2022 isolated from Yunnan belongs to the C2 gene subtype,which is the prevalent CVA4 in China,but with certain mutations.

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.

Background/Aims: The performance of machine learning (ML) in predicting the outcomes of patients with hepatocellular carcinoma (HCC) remains uncertain. We aimed to develop risk scores using conventional methods and ML to categorize early-stage HCC patients into distinct prognostic groups. Methods: The study retrospectively enrolled 1,411 consecutive treatment-naïve patients with the Barcelona Clinic Liver Cancer (BCLC) stage 0 to A HCC from 2012 to 2021. The patients were randomly divided into a training cohort (n=988) and validation cohort (n=423). Two risk scores (CATS-IF and CATS-INF) were developed to predict overall survival (OS) in the training cohort using the conventional methods (Cox proportional hazards model) and ML-based methods (LASSO Cox regression), respectively. They were then validated and compared in the validation cohort. Results: In the training cohort, factors for the CATS-IF score were selected by the conventional method, including age, curative treatment, single large HCC, serum creatinine and alpha-fetoprotein levels, fibrosis-4 score, lymphocyte-tomonocyte ratio, and albumin-bilirubin grade. The CATS-INF score, determined by ML-based methods, included the above factors and two additional ones (aspartate aminotransferase and prognostic nutritional index). In the validation cohort, both CATS-IF score and CATS-INF score outperformed other modern prognostic scores in predicting OS, with the CATSINF score having the lowest Akaike information criterion value. A calibration plot exhibited good correlation between predicted and observed outcomes for both scores. Conclusions Both the conventional Cox-based CATS-IF score and ML-based CATS-INF score effectively stratified patients with early-stage HCC into distinct prognostic groups, with the CATS-INF score showing slightly superior performance.

OBJECTIVE: To investigate whether Salvianolic acid A (SAA) can restore cartilage endplate cell degeneration of intervertebral discs and to identify the mechanism via regulation of micro-RNA. METHODS: Cartilage endplate cells were isolated from lumbar intervertebral disc surgical samples and were treated with serum containing a series of concentrations of SAA (2, 5, and 10 ?M) for 24, 48, and 72 h to identify a proper dose and treatment time of SAA. The effect SAA on interlenkin-1β (IL-1β)-induced extracellular matrix degradation of cartilage endplate cells were analyzed by Alcian blue staining and assessment of the expression levels of ADAMTS-5, MMP3 and Col2a1. Further, the potential target miRNAs were preliminarily screened by micro-RNA sequencing combining qRT-PCR and Western blot, and then, the miRNAs mimics and inhibitors were used to verify the regulatory effect of SAA on potential target miRNAs. RESULTS: The 10 μM SAA treatment for 48 h significantly enhanced the viability of cartilage endplate cells, and increased Col2a1 expression and glycosaminoglycan accumulation that were repressed by IL-1β, and reduced the effect of IL-1β on ADAMTS-5, and MMP3. Screening analysis based on micro-RNA sequencing and Venny analysis identified the downstream micro-RNAs, including miR-940 and miR-576-5p. Then, the miR-940-mimic or miR-576-5p-mimic were transfected into CEPCs. Compared with the SAA group, the expression of ADAMTS-5 and MMP3 increased significantly and the expression of COL2A1 obviously decreased after overexpression of miR-940 or miR-576-5p in CEPCs. CONCLUSION Salvianolic acid A attenuated the IL-1β-induced extracellular matrix degradation of cartilage endplate cells by targeting regulate the miR-940 and the miR-576-5p.
Humans ; Apoptosis ; Cartilage/metabolism* ; Chondrocytes/metabolism* ; Interleukin-1beta/metabolism* ; Matrix Metalloproteinase 3/metabolism* ; MicroRNAs/metabolism*

Objective: To explore the influence and significance of respiratory filter on the judgment of pulmonary function and the conclusion of occupational health examination in occupational health examination. Methods: From August to November 2020, 252 occupational health examinees were randomly selected as the research objects, and the lung function was examined with the respiratory filter bite and the straight cylinder bite without filter, respectively. The lung function examination indexes and the qualification rate of lung function examination were analyzed and compared between the two groups, and the diagnostic criteria of lung function examination was corrected. Results: 252 subjects were 36 (30, 42) years old. The qualified rate of lung function examination with respiratory filter bite (28.17%, 71/252) was lower than that with straight cylinder bite (34.92%, 88/252) , the difference was statistically significant (P<0.05) . The percentage of forced vital capacity in normal predicted value (FVC%) , percentage of forced expiratory volume in the first second in normal predicted value (FEV(1)%) , and percentage of forced expiratory volume in the first second in forced vital capacity (FEV(1)/FVC%) of subjects using respiratory filter bite were lower than those using the straight cylinder bite (P<0.05) . The corrected diagnostic criteria of pulmonary function were FVC%>78%, FEV(1)%>77%, FEV(1)/FVC%>68%. There was no significant difference between the qualified rate of the respiratory filter bite lung function test calculated according to the corrected diagnostic criteria (35.71%, 90/252) and the qualified rate of the straight cylinder bite lung function test calculated according to the original diagnostic criteria (34.92%, 88/252) (P>0.05) . Conclusion: In occupational health examination, the use of respiratory filter may affect the results of pulmonary function examination. The diagnostic criteria of pulmonary function can be corrected according to different filtering effects to ensure the accuracy of the conclusions of occupational health examination.
Humans ; Adult ; Occupational Health ; Lung ; Vital Capacity ; Forced Expiratory Volume ; Respiratory Function Tests/methods*