1.Observation in effect of different follow-up types on discharged patients with indwelling D-J stents
Xiangfeng QUAN ; Ji JING ; Suqing LU ; Yuqin LI ; Xuelin WEN ; Dongyuan TANG ; Linling WU ; Ruilian WU
Chinese Journal of Practical Nursing 2011;27(5):17-19
Objective To explore the effect of health education through different postoperative follow-up method, including telephone、Email and QQ, on patients with indwelling D-J stents. Methods 319patients with indwelling D-J stents were divided into the control group(88 cases), the telephone group(89 cases), the Email group (70 cases) and the QQ group (72 cases). M1 patients received rourine health education during hospitalization and before discharge, the latter three groups received follow-up by telephone、Email and QQ after discharge respectively. The rehabilitation effect was observed in the four groups. Results The complication rates of the telephone group, the Email group and the QQ group was significantly less and the mastering of knowledge about prevention and handling of complication was better than the control group during the follow-up. Conclusions Different types of follow-up can be selected by patients according to their actual status. Decreasing complication rate, favorable social benefit and approval of the patients family members will be seen due to involvement of the patients family in health education.
2.Correlation between Genetic Variants and Polymorphism of Caveolin and Sudden Unexplained Death.
Fang Yu WU ; Xin Hua TANG ; Lian Lei GAI ; Xiao Ping KONG ; Bo HAO ; Er Wen HUANG ; He SHI ; Li Hui SHENG ; Li QUAN ; Shui Ping LIU ; Bin LUO
Journal of Forensic Medicine 2017;33(2):114-119
OBJECTIVES:
To explore the genetic variation sites of caveolin (CAV) and their correlation with sudden unexplained death (SUD).
METHODS:
The blood samples were collected from SUD group (71 cases), coronary artery disease (CAD) group (62 cases) and control group (60 cases), respectively. The genome DNA were extracted and sequencing was performed directly by amplifying gene coding region and exon-intron splicing region of CAV1 and CAV3 using PCR. The type of heritable variation of CVA was confirmed and statistical analysis was performed.
RESULTS:
A total of 4 variation sites that maybe significative were identified in SUD group, and two were newfound which were CAV1: c.45C>T (T15T) and CAV1:c.512G>A (R171H), and two were SNP loci which were CAV1:c.246C>T (rs35242077) and CAV3:c.99C>T (rs1008642) and had significant difference (P<0.05) in allele and genotype frequencies between SUD and control groups. Forementioned variation sites were not found in CAD group.
CONCLUSIONS
The variants of CAV1 and CAV3 may be correlated with a part of SUD group.
Caveolins/genetics*
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Coronary Artery Disease
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Death, Sudden/etiology*
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Exons
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Genotype
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Humans
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Male
;
Polymerase Chain Reaction
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Polymorphism, Single Nucleotide
3.Class-imbalance Prediction and High-dimensional Risk Factor Identification of Adverse Reactions of Traditional Chinese Medicine with Centralized Monitoring in Real-world Hospitals
Feibiao XIE ; Yehui PENG ; Wei YANG ; Jinfa TANG ; Juan LIU ; Weixia LI ; Hui ZHANG ; Dongyuan WU ; Yali WU ; Yuanming LENG ; Xinghua XIANG
Chinese Journal of Experimental Traditional Medical Formulae 2023;29(14):114-122
ObjectiveTo achieve high-dimensional prediction of class imbalanced of adverse drug reaction(ADR) of traditional Chinese medicine(TCM) and to classify and identify risk factors affecting the occurrence of ADR based on the post-marketing safety data of TCM monitored centrally in real world hospitals. MethodThe ensemble clustering resampling combined with regularized Group Lasso regression was used to perform high-dimensional balancing of ADR class-imbalanced data, and then to integrate the balanced datasets to achieve ADR prediction and the risk factor identification by category. ResultA practical example study of the proposed method on a monitoring data of TCM injection performed that the accuracy of the ADR prediction, the prediction sensitivity, the prediction specificity and the area under receiver operating characteristic curve(AUC) were all above 0.8 on the test set. Meanwhile, 40 risk factors affecting the occurrence of ADR were screened out from total 600 high-dimensional variables. And the effect of risk factors on the occurrence of ADR was identified by classification weighting. The important risk factors were classified as follows:past history, medication information, name of combined drugs, disease status, number of combined drugs and personal data. ConclusionIn the real world data of rare ADR with a large amount of clinical variables, this paper realized accurate ADR prediction on high-dimensional and class imbalanced condition, and classified and identified the key risk factors and their clinical significance of categories, so as to provide risk early warning for clinical rational drug use and combined drug use, as well as scientific basis for reevaluation of safety of post-marketing TCM.