Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

OBJECTIVE: To determine the prevalence of lumbar spondylolysis (LS) and the proportion of spondylolytic spondylolisthesis (SS) in China, and to evaluate the musculoskeletal status of patients with LS and SS. METHODS: Spine Computed Tomography (CT) images were collected from community populations aged 40 and above in a nationwide multi-center project. LS was diagnosed, and SS was graded by an experienced radiologist. Bone mineral density (BMD) and paraspinal muscle parameters were quantified based on CT images. RESULTS: One hundred and seventeen patients of a total of 3,317 individuals were diagnosed with LS, corresponding to a prevalence rate of 3.53%. 63 of the 1,214 males (5.18%) and 54 of the 2,103 females (2.57%) were diagnosed with LS. SS occurred in 64/121 vertebrae (52.89%). BMD was not associated with LS ( P = 0.341). The L5 extensor paraspinal muscle density was higher in the LS group than in the non-LS group. In the LS group, patients with SS had a smaller L5 paraspinal extensor muscle cross-sectional area than those without SS ( P = 0.003). CONCLUSION The prevalence of LS in Chinese adults was 3.53%, with prevalence rates of 5.18% in males and 2.57% in females. Patients with LS have higher muscle density, whereas those with SS have smaller muscle cross-sectional areas at the L5 level.
Humans ; Male ; Female ; Middle Aged ; China/epidemiology* ; Prevalence ; Adult ; Lumbar Vertebrae/diagnostic imaging* ; Spondylolysis/diagnostic imaging* ; Aged ; Bone Density ; Tomography, X-Ray Computed ; Aged, 80 and over ; Spondylolisthesis/epidemiology* ; East Asian People

Objective To investigate the difference between the management of patients in arrhythmia ward and non-arrhythmia wards and optimize the management plan of patients with atrial fibrillation.Methods Data of 1 537 patients with atrial fibrillation admitted to the arrhythmia ward and non-arrhythmia ward in the Department of Cardiology of the Second Hospital of Tianjin Medical University from September 2019 to September 2021 were collected.Baseline data,use of oral anticoagulants,use of heart rate control drugs and antiarrhythmic drugs,and use of antiplatelet drugs were compared between the two groups.Results The mean CHA2DS2-VASc score in the non-specialized atrial fibrillation(AF)management group was higher than that in the specialized AF management group,and the difference was statistically significant[(4.76±1.71)vs.(3.46±1.87),P＜0.001].There were statistically significant differences between the two groups in terms of gender,age,comorbidities such as heart failure,hypertension,diabetes,stroke,and vascular disease(all P＜0.001).The proportion of paroxysmal and permanent AF types in the non-specialized AF management group was higher(P＜0.001).The usage rates of rate control drugs(56.0％vs.40.1％),beta-blockers(50.7％vs.36.6％),and digoxin(17.6％vs.5.2％)were significantly higher in the non-specialized AF management group compared to the specialized AF management group,all with statistical significance(all P＜0.001).The usage rates of antiarrhythmic drugs(49.8％vs.22.6％),amiodarone(26.2％vs.5.6％),dronedarone(3.1％vs.0.4％),and propafenone(2.9％vs.0.1％)were significantly higher in the specialized AF management group compared to the non-specialized AF management group,all with statistical significance(all P＜0.001),while there was no statistical difference in the usage rate of sotalol between the two groups.The proportion of patients undergoing coronary artery examination in the non-specialized AF management group(43.6％)was significantly higher than that in the specialized AF management group(25.7％),with statistical significance(P＜0.001).Conclusions The treatment of patients with atrial fibrillation varies greatly due to the management of different specialized wards.

Objective To explore the prediction of hospital indoor microbial concentration in air based on real-time indoor air environment monitoring data and machine learning algorithms.Methods Four locations in a hospital were selected as monitoring sampling points from May 23 to June 5,2022.The"internet of things"sensor was used to monitor a variety of real-time air environment data.Air microbial concentration data collected at each point were matched,and the gradient boosting decision tree(GBDT)was used to predict real-time indoor microbial concentra-tion in air.Five other common machine learning models were selected for comparison,including random forest(RF),decision tree(DT),k-nearest neighbor(KNN),linear regression(LR)and artificial neural network(ANN).The validity of the model was verified by the mean absolute error(MAE),root mean square error(RMSE)and mean absolute percentage error(MAPE).Results The MAPE value of GBDT model in the outpa-tient elevator room(point A),bronchoscopy room(point B),CT waiting area(point C),and nurses'station in the supply room(point D)were 22.49％,36.28％,29.34％,and 26.43％,respectively.The mean performance of the GBDT model was higher than that of other machine learning models at three sampling points and slightly lower than that of the ANN model at only one sampling point.The mean MAPE value of GBDT model at four sampling points was 28.64％,that is,the predicted value deviated from the actual value by 28.64％,indicating that GBDT model has good prediction results and the predicted value was within the available range.Conclusion The GBDT machine learning model based on real-time indoor air environment monitoring data can improve the prediction accuracy of in-door air microbial concentration in hospitals.

Background: and Purpose Intravenous tenecteplase (TNK) efficacy has not been well demonstrated in acute ischemic stroke (AIS) beyond 4.5 hours after onset. This study aimed to determine the effect of intravenous TNK for AIS within 4.5 to 24 hours of onset. Methods: In this pilot trial, eligible AIS patients with diffusion-weighted imaging (DWI)-fluid attenuated inversion recovery (FLAIR) mismatch were randomly allocated to intravenous TNK (0.25 mg/kg) or standard care within 4.5–24 hours of onset. The primary endpoint was excellent functional outcome at 90 days (modified Rankin Scale [mRS] score of 0–1). The primary safety endpoint was symptomatic intracranial hemorrhage (sICH). Results: Of the randomly assigned 80 patients, the primary endpoint occurred in 52.5% (21/40) of TNK group and 50.0% (20/40) of control group, with no significant difference (unadjusted odds ratio, 1.11; 95% confidence interval 0.46–2.66; P=0.82). More early neurological improvement occurred in TNK group than in control group (11 vs. 3, P=0.03), but no significant differences were found in other secondary endpoints, such as mRS 0–2 at 90 days, shift analysis of mRS at 90 days, and change in National Institutes of Health Stroke Scale score at 24 hours and 7 days. There were no cases of sICH in this trial; however, asymptomatic intracranial hemorrhage occurred in 3 of the 40 patients (7.5%) in the TNK group. Conclusion This phase 2, randomized, multicenter study suggests that intravenous TNK within 4.5–24 hours of onset may be safe and feasible in AIS patients with a DWI-FLAIR mismatch.

OBJECTIVE: To investigate the factors related to renal impairment in patients with diabetic kidney disease (DKD) from the perspective of integrated Chinese and Western medicine. METHODS: Totally 492 patients with DKD in 8 Chinese hospitals from October 2017 to July 2019 were included. According to Kidney Disease Improving Global Outcomes (KDIGO) staging guidelines, patients were divided into a chronic kidney disease (CKD) 1-3 group and a CKD 4-5 group. Clinical data were collected, and logistic regression was used to analyze the factors related to different CKD stages in DKD patients. RESULTS: Demographically, male was a factor related to increased CKD staging in patients with DKD (OR=3.100, P=0.002). In clinical characteristics, course of diabetes >60 months (OR=3.562, P=0.010), anemia (OR=4.176, P<0.001), hyperuricemia (OR=3.352, P<0.001), massive albuminuria (OR=4.058, P=0.002), atherosclerosis (OR=2.153, P=0.007) and blood deficiency syndrome (OR=1.945, P=0.020) were factors related to increased CKD staging in patients with DKD. CONCLUSIONS Male, course of diabetes >60 months, anemia, hyperuricemia, massive proteinuria, atherosclerosis, and blood deficiency syndrome might indicate more severe degree of renal function damage in patients with DKD. (Registration No. NCT03865914).
Humans ; Male ; Diabetes Mellitus, Type 2 ; Diabetic Nephropathies ; Hyperuricemia ; Kidney ; Proteinuria ; Renal Insufficiency, Chronic/complications*

Objective: To compare the impact of different prognostic scores in patients with acute-on-chronic liver failure (ACLF) in order to provide treatment guidance for liver transplantation. Methods: The information on inpatients with ACLF admitted at Beijing You'an Hospital Affiliated to Capital Medical University and the First Affiliated Hospital of Zhejiang University School of Medicine from January 2015 to October 2022 was collected retrospectively. ACLF patients were divided into liver transplantation and non-liver transplantation groups, and the two groups prognostic conditions were followed-up. Propensity score matching was carried out between the two groups on the basis of liver disease (non-cirrhosis, compensated cirrhosis, and decompensated cirrhosis), the model for end-stage liver disease incorporating serum sodium (MELD-Na), and ACLF classification as matching factors. The prognostic condition of the two groups after matching was compared. The difference in 1-year survival rate between the two groups was analyzed under different ACLF grades and MELD-Na scores. The independent sample t-test or rank sum test was used for inter-group comparison, and the χ (2) test was used for the comparison of count data between groups. Results: In total, 865 ACLF inpatients were collected over the study period. Of these, 291 had liver transplantation and 574 did not. The overall survival rates at 28, 90, and 360 days were 78%, 66%, and 62%, respectively. There were 270 cases of matched ACLF post-liver transplantation and 270 cases without ACLF, in accordance with a ratio of 1:1. At 28, 90, and 360 days, patients with non-liver transplantation had significantly lower survival rates (68%, 53%, and 49%) than patients with liver transplantation (87%, 87%, and 78%, respectively; P < 0.001). Patients were classified into four groups according to the ACLF classification criteria. Kaplan-Meier survival analysis showed that the survival rates of liver transplantation and non-liver transplantation patients in ACLF grade 0 were 77.2% and 69.4%, respectively, with no statistically significant difference (P = 0.168). The survival rate with an ACLF 1-3 grade was significantly higher in liver transplantation patients than that of non-liver transplantation patients (P < 0.05). Patients with ACLF grades 1, 2, and 3 had higher 1-year survival rates compared to non-liver transplant patients by 50.6%, 43.6%, and 61.7%, respectively. Patients were divided into four groups according to the MELD-Na score. Among the patients with a MELD-Na score of < 25, the 1-year survival rates for liver transplantation and non-liver transplantation were 78.2% and 74.0%, respectively, and the difference was not statistically significant (P = 0.149). However, among patients with MELD-Na scores of 25-30, 30-35, and≥35, the survival rate was significantly higher in liver transplantation than that of non-liver transplantation, and the 1-year survival rate increased by 36.4%, 54.9%, and 62.5%, respectively (P < 0.001). Further analysis of the prognosis of patients with different ACLF grades and MELD-Na scores showed that ACLF grades 0 or 1 and MELD-Na score of < 30 had no statistically significant difference in the 1-year survival rate between liver transplantation and non-liver transplantation (P > 0.05), but in patients with MELD-Na score≥30, the 1-year survival rate of liver transplantation was higher than that of non-liver transplantation patients (P < 0.05). In the ACLF grade 0 and MELD-Na score of≥30 group, the 1-year survival rates of liver transplantation and non-liver transplantation patients were 77.8% and 25.0% respectively (P < 0.05); while in the ACLF grade 1 and MELD-Na score of≥30 group, the 1-year survival rates of liver transplantation and non-liver transplantation patients were 100% and 20.0%, respectively (P < 0.01). Among patients with ACLF grade 2, the 1-year survival rate with MELD-Na score of < 25 in patients with liver transplantation was 73.9% and 61.6%, respectively, and the difference was not statistically significant (P > 0.05); while in the liver transplantation patients group with MELD-Na score of ≥25, the 1-year survival rate was 79.5%, 80.8%, and 75%, respectively, which was significantly higher than that of non-liver transplantation patients (36.6%, 27.6%, 15.0%) (P < 0.001). Among patients with ACLF grade 3, regardless of the MELD-Na score, the 1-year survival rate was significantly higher in liver transplantation patients than that of non-liver transplantation patients (P < 0.01). Additionally, among patients with non-liver transplantation with an ACLF grade 0~1 and a MELD-Na score of < 30 at admission, 99.4% survived 1 year and still had an ACLF grade 0-1 at discharge, while 70% of deaths progressed to ACLF grade 2-3. Conclusion: Both the MELD-Na score and the EASL-CLIF C ACLF classification are capable of guiding liver transplantation; however, no single model possesses a consistent and precise prediction ability. Therefore, the combined application of the two models is necessary for comprehensive and dynamic evaluation, but the clinical application is relatively complex. A simplified prognostic model and a risk assessment model will be required in the future to improve patient prognosis as well as the effectiveness and efficiency of liver transplantation.
Humans ; Acute-On-Chronic Liver Failure ; Prognosis ; Retrospective Studies ; End Stage Liver Disease ; Severity of Illness Index

The micronucleomics test can comprehensively display a variety of harmful endpoints, such as DNA damage and repair, chromosome breakage or loss and cell growth inhibition, with fast, simple and economical feature. Micronucleomics is not only widely used in the comprehensive assessment of the types and modes of genetic action of exogenous chemicals (such as drugs, food additives, cosmetics, environmental pollutants, etc.), but also plays an important role in the screening and risk assessment of cancer population at high risk. However, the traditional micronucleomics image counting method has the characteristics of time-consuming, low accuracy, and high cost, which cannot meet the current analysis requirements of large-scale, multi-index, rapidity, high precision and visualization. In recent years, with the rapid development of the era of precision medicine based on big data, visualized analysis of new micronucleomics based on machine learning and detection strategies based on deep learning have shown a good application prospect. This review, based on the application value of micronucleomics, systematically compares the traditional and new artificial intelligence counting of micronucleus images, and discusses the future direction of micronucleus image detection.
Artificial Intelligence ; Big Data ; Humans ; Machine Learning ; Precision Medicine

Animals ; Chloroquine/pharmacology* ; Longevity ; Rats