ABSTRACT
Objective To find out valuable association patterns hidden in the events of falls among hospitalized patients,and to provide scientific references for prevention of falls.Methods According to basic principles of data mining,totally 7 170 records of 239 cases of falls in a tertiary hospital in Zhejiang Province from 2011 to 2016 were collected.Apriori algorithm was conducted to mine association patterns,and chi-square test was used to test effectiveness for strong association patterns.Results Through the condition setting,245 association patterns were obtained,and 94 patterns were selected by chi-square test.Finally,18 strong patterns were obtained via analysis with professional knowledge.Conclusion Through data mining of falls in hospitalized patients,figuring out strong association patterns for factors of falls,can help to discover system's weaknesses,and to provide scientific and accurate references for further development of targeted preventive measures.
ABSTRACT
Objective To find out valuable association patterns hidden in the events of falls among hospitalized patients,and to provide scientific references for prevention of falls.Methods According to basic principles of data mining,totally 7 170 records of 239 cases of falls in a tertiary hospital in Zhejiang Province from 2011 to 2016 were collected.Apriori algorithm was conducted to mine association patterns,and chi-square test was used to test effectiveness for strong association patterns.Results Through the condition setting,245 association patterns were obtained,and 94 patterns were selected by chi-square test.Finally,18 strong patterns were obtained via analysis with professional knowledge.Conclusion Through data mining of falls in hospitalized patients,figuring out strong association patterns for factors of falls,can help to discover system's weaknesses,and to provide scientific and accurate references for further development of targeted preventive measures.
ABSTRACT
<p><b>OBJECTIVE</b>To investigate the combined effects between the two polymorphisms murine double minute 2 (MDM2) rs2279744 T→G and P53 rs1042522 G→C on the genetic susceptibility of breast cancer.</p><p><b>METHODS</b>A total of 600 female patients with diagnosed breast cancer were consecutively recruited from the Yuhang district, Hangzhou city during March 2001 to May 2009. In the same period as the cases were collected, 600 healthy women living in Yuhang district, Hangzhou city were selected from a nutritional survey conducted. Peripheral blood lymphocytes were obtained from the study subjects and the demographic information were collected through questionnaires. PCR-restriction fragment length polymorphism (PCR-RFLP) was used for genotyping MDM2 rs2279744 T→G and P53 rs1042522 G→C. Logistic regression analysis was used to analyze the combined effects of the two polymorphisms on breast cancer risk.</p><p><b>RESULTS</b>The frequency of MDM2 rs2279744 GG, TG and TT genotypes were 31.5% (189/600), 45.5% (273/600), 23.0% (138/600) in case group and 19.0% (114/600), 49.2% (295/600), 31.8% (191/600) in control group. The frequency of P53 rs1042522 GG, GC and CC genotypes were 23.1% (139/600), 50.2% (301/600), 26.7% (160/600) in case group and 30.5% (183/600), 51.3% (308/600), 18.2% (109/600) in control group. Logistic regression analysis showed that carriers with rs2279744 TG, GG genotypes had a significant increased risk for developing breast cancer compared with rs2279744 TT carriers (OR = 1.31, 95%CI: 0.97 - 1.73 for TG; OR = 2.24, 95%CI: 1.61 - 3.09 for GG). When comparing with rs1042522 GG carriers, carriers with rs1042522 GC, CC genotypes had a significant increased risk for developing breast cancer (OR = 1.34, 95%CI: 0.94 - 1.68 for GC; OR = 1.89, 95%CI: 1.35 - 2.68 for CC). The united analysis of this two polymorphisms showed that compared with individuals carrying rs2279744 TT and rs1042522 GG (the frequency were 4.8% (29/600) in case group and 11.5% (69/600) in control group), carries with rs2279744 TG/GG and rs1042522 GC/GG genotypes (the frequency were 95.2% (571/600) in case group and 88.5% (531/600) in control group) showed significant higher risk in the susceptibility to breast cancer (OR = 2.30, 95%CI: 1.39 - 3.82 for TG/GC + GG; OR = 2.14, 95%CI: 1.29 - 3.55 for TT + GC/CC; OR = 2.86, 95%CI: 1.80 - 4.53 for TG/GG + GC/CC). The combination of MDM2 rs2279744 T→G and P53 rs1042522 G→C contributed to a significantly higher risk of breast cancer than did any one of the variant (P = 0.046). The risk of susceptibility to breast cancer was much higher when this two polymorphisms both variant.</p><p><b>CONCLUSIONS</b>The MDM2 rs2279744 T→G and P53 rs1042522 G→C may be risk factor for breast cancer. Significant combined effects between the two polymorphisms may contribute to the genetic susceptibility to breast cancer.</p>