Yinshan Mountains stands on the southern edge of the Inner Mongolia Plateau, which stretches 1 200 km from east to west and 50 to 100 km from north to south. The rich and varied topographic environment of the Yinshan Mountains has created a variety of vegetation floras, which also makes the species of medicinal plant resources in this area unevenly distributed. Therefore, studying the spatial distribution difference of medicinal plant resources among various banners, counties, and districts in the Yinshan area is of great significance to formulate the protection policy and promote the industry development of medicinal plant. This study is based on the fourth national survey of traditional Chinese medicine resources in Inner Mongolia, regarding the results of the third national survey of traditional Chinese medicine resources. The species of medicinal plant resources in the Yinshan area around 31 banners, counties and districts were counted in detail. Then, using exploratory spatial data analysis(ESDA), trend surface analysis, spatial autocorrelation, geographical detector and other geostatistical analysis methods to analyze the differences in the spatial distribution of medicinal plant resources of the Yinshan area in Inner Mongolia. After discussing and analyzing the experimental results to account for the reasons for the overall trend of change and the degree of aggregation, the author further put forward relevant constructive suggestions. The results show that the areas with the most abundant and concentrated distribution of medicinal plant resources in the Yinshan area are located in Guyang county, Shiguai District of Baotou city, Tutou right banner, and Tuoketuo county; the higher richness and concentrated distribution of medicinal plant resources is in Wulate front banner, Wulate middle banner, Wulate back banner; areas with relatively low abundance and concentrated distribution of medicinal plant resources located in Qingshan district of Baotou city, Saihan district and Yuquan district of Hohhot city; areas with the lowest abundance and concentrated distribution of medicinal plant resources are located in Xincheng district and Huimin district of Hohhot city. It can be concluded that the horizontal distribution difference of multiple ecological factors, the special wetland environment of the river, the vertical difference of elevation, the farmland and other factors have an important influence on the richness of the medicinal plant resources species.
China ; Medicine, Chinese Traditional ; Plants, Medicinal

OBJECTIVE: To study the clinical features of children with recurrent Kawasaki disease (KD). METHODS: PubMed, Web of Science, Embase, CNKI, Wanfang Med Online, and Weipu Data were searched for case-control studies on the clinical features of initial and recurrent KD. The articles were screened according to the inclusion and exclusion criteria. RevMan 5.3 software was used to perform the Meta analysis. Effect models were selected based on the results of heterogeneity test, and then pooled RESULTS: A total of 9 case-control studies were included, with 12 059 children with KD in total, among whom 206 children had recurrent KD (127 boys/61.7%; 79 girls/38.3%). The results of the Meta analysis showed that compared with the initial KD onset, the children with recurrent KD had a shorter duration of fever ( CONCLUSIONS Current evidence shows that children with recurrent KD tend to have a shorter duration of fever and a lower incidence of swelling of the hands and feet. KD recurrence is more common in boys. Current evidence does not show an increased risk of developing coronary artery lesions in children with recurrent KD.
Child ; Chronic Disease ; Coronary Vessels/pathology* ; Edema/etiology* ; Female ; Fever/etiology* ; Humans ; Male ; Mucocutaneous Lymph Node Syndrome/physiopathology* ; Recurrence

Objective:To establish autoverification rules for coagulation tests in multicenter cooperative units, in order to reduce workload for manual review of suspected results and shorten turnaround time (TAT) of test reports, while ensure the accuracy of results.Methods:A total of 14 394 blood samples were collected from fourteen hospitals during December 2019 to March 2020. These samples included: Rules Establishment Group 11 230 cases, including 1 182 cases for Delta check rules; Rules Validation Group 3 164 cases, including 487cases for Delta check; Clinical Application Trial Group 77 269 cases. Samples were analyzed for coagulation tests using Sysmex CS series automatic coagulation analyzers, and the clinical information, instrument parameters, test results, clinical diagnosis, medication history of anticoagulant and other relative results such as HCT, TG, TBIL, DBIL were summarized; on the basis of historical data, the 2.5 and 97.5 percentile of all data arranged from low to high were initially accumulated; on the basis of clinical suggestions, critical values and specific drug use as well as relative guidelines, autoverification rules and limits were established.The rules were then input into middleware, in which Stage I/Stage II validation was done. Positive coincidence, negative coincidence, false negative, false positive, autoverification pass rate, passing accuracy (coincidence of autoverification and manual verification) were calculated. Autoverification rules underwent trial application in coagulation results reports.Results:(1) The autoverification algorisms involve 33 rules regarding PT/INR, APTT, FBG, D-dimer, FDP,Delta check, reaction curve and sample abnormalities; (2)Autoverification Establishment Group showed autoverification pass rate was 68.42% (7 684/11 230), the false negative rate was 0%(0/11230), coincidence of autoverification and manual verification was 98.51%(11 063/11 230), in which positive coincidence and negative coincidence were respectively 30.09% (3 379/11 230) and 68.42%(7 684/11 230); Autoverification Validation Group showed autoverification pass rate was 60.37%(1 910/3 164), the false negative rate was 0%(0/11 230), coincidence of autoverification and manual verification was 97.79%(3 094/3 164), in which positive coincidence and negative coincidence were respectively 37.42%(1 184/3 164) and 60.37%(1 910/3 164); (3) Trialed implementation of these autoverification rules on 77 269 coagulation samples showed that the average TAT shortened by 8.5 min-83.1 min.Conclusions:This study established 33 autoverification rules in coagulation tests. Validation showedthese rules could ensure test quality while shortening TAT and lighten manual workload.

Background:Clinical outcomes of undifferentiated arthritis (UA) are diverse,and only 40 ％ of patients with UA develop rheumatoid arthritis (RA) after 3 years.Discovering predictive markers at disease onset for further intervention is critical.Therefore,our objective was to analyze the clinical outcomes of UA and ascertain the predictors for RA development.Methods:We performed a prospective,multi-center study from January 2013 to October 2016 among Chinese patients diagnosed with UA in 22 tertiary-care hospitals.Clinical and serological parameters were obtained at recruitment.Follow-up was undertaken in all patients every 12 weeks for 2 years.Predictive factors of disease progression were identified using multivariate Cox proportional hazards regression.Results:A total of 234 patients were recruited in this study,and 17 (7.3％) patients failed to follow up during the study.Among the 217 patients who completed the study,83 (38.2％) patients went into remission.UA patients who developed RA had a higher rheumatoid factor (RF)-positivity (42.9％ vs.16.8％,x2=8.228,P=0.008),anti-cyclic citrullinated peptide (CCP) antibodypositivity (66.7％ vs.10.7％,x2 =43.897,P ＜ 0.001),and double-positivity rate of RF and anti-CCP antibody (38.1％ vs.4.1％,x2 =32.131,P ＜ 0.001) than those who did not.Anti-CCP antibody but not RF was an independent predictor for RA development (hazard ratio 18.017,95％ confidence interval:5.803-55.938;P ＜ 0.001).Conclusion:As an independent predictor of RA,anti-CCP antibody should be tested at disease onset in all patients with UA.