The PICO model is a general model in building problems of evidence-based medicine (EBM). However, with the deepening and refinement of the medical research and the rising of qualitative research, the PICO model could not satisfy all problems. This article introduces the expansions of the PICO model and puts forward the SPIDER model according to the qualitative problem and its relationship with the PICO model, which can build the best search strategy of clinical problems in a short time.
ObjectiveTo introduce sensitivity and homogeneity tests in network meta-analysis and its implementation in R software. MethodsUsing an example, we performed sensitivity analysis by comparing the random effect model with the fixed effect model. Homogeneity analysis was performed using metaphor package and combinat package in R software. ResultsThe results of the two models were similar, and the data was steady. The results of homogeneity analysis showed that the confidential intervals in all loops were crossed over with blank value; and direct and indirect estimates of the effects in network meta-analysis were not significantly different, with good homogeneity. ConclusionNetwork meta-analysis is a kind of indirect comparison analysis method, and its sensitivity is especially important. The introduction of homogeneity makes network meta-analysis more accurate. Using R software for sensitivity and homogeneity analysis in network meta-analysis is a feasible method.
ObjectiveTo explore the main risk factors related to the incidence of epilepsy and the cause of epilepsy, so as to provide basis for decision making on epilepsy prevention. MethodsSuch databases as PubMed (1980 to 2013.1.2), EMbase (1980 to 2013.1.2) and CNKI (1987 to 2013.1.2) were electronically searched to collect case-control studies on risk factors for epilepsy. Meanwhile, relevant studies were also manually retrieved. Two reviewers independently screened studies according to the inclusion and exclusion criteria, extracted data, and assessed methodological quality. Then, meta-analysis was performed using RevMan 5.2 software. Results17 studies involving 6 641 participants (including 3 114 cases and 3 527 controls) were included. The results of meta-analysis showed that, family history of epilepsy, traumatic brain injury, febrile seizures, neonatal disease, and risk factors during pregnancy were associated with the incidence of epilepsy, with pooled OR (95%CI) values of 5.11 (3.19, 8.20), 4.14 (3.63, 4.73), 5.10 (2.64, 9.87), 3.33 (1.84, 6.05), and 3.23 (1.80, 5.78), respectively. ConclusionCurrently evidence shows that the risk factors influencing the incidence of epilepsy are family history of epilepsy, traumatic brain injury, febrile seizures, neonatal disease, and risk factors during pregnancy.
Objectives To investigate the relationship between SG13S114 and SG13S32 polymorphisms in ALOX5AP gene and risk of ischemic stroke in Chinese population. Methods We searched Web of Science, EMbase, PubMed, CNKI, CBM and WanFang Data databases to collect case-control studies on SG13S114 and SG13S32 polymorphisms of ALOX5AP gene and risk of ischemic stroke in Chinese from inception to February 2017. Two reviewers independently screened literature, extracted data, and assessed the risk of bias of included studies. Meta-analysis was then performed by Stata 12.0 software. Results A total of 20 studies were included. The results of meta-analysis showed that SG13S114 polymorphism in ALOX5AP gene was associated with risk of ischemic stroke in Chinese (A vs. T: OR=1.12, 95%CI 1.00 to 1.27, P=0.05; TA+AA vs. TT: OR=1.14, 95%CI 1.01 to 1.28, P=0.04; AA vs. TT: OR=1.33, 95%CI 1.07 to 1.65, P=0.012). However, no significant association between SG13S32 polymorphism and ischemic stroke in Chinese was found. Conclusions SG13S114 polymorphisms in ALOX5AP gene is associated with risk of ischemic stroke in Chinese, in which the A allele of ALOX5AP may be a risk factor.