ObjectiveTo systematically review the research status of risk prediction models for gestational diabetes mellitus (GDM). MethodsThe CNKI, WanFang Data, VIP, CBM, PubMed, JBI EBP, Ovid MEDLINE, Embase, Web of Science and Cochrane Library databases were electronically searched to collect relevant literature on risk prediction models for GDM from inception to October 2022. Two researchers independently screened the literature, extracted data, and assessed the risk of bias of the included studies, and then qualitative description was performed. ResultsA total of 19 studies were included, involving 19 risk prediction models. The evaluation results showed that, in terms of the risk of bias, 18 studies were high risk, and 1 study was unclear. In terms of applicability, 14 studies were high risk, 2 studies were low risk, and 3 studies were unclear. The area under the receiver operating characteristic curve of the included models was 0.69 to 0.88. The most common predictors included age, weight, pre-pregnancy BMI, history of diabetes, family history of diabetes, and race. ConclusionThe overall performance of the risk prediction model for gestational diabetes mellitus is good, but the risk of bias of the model is high, and the clinical applicability of the model needs to be further verified.
ObjectiveTo systematically review the effect of self-management intervention on the prevention and management of lymphedema in breast cancer patients. MethodsCochrane Library, Embase, PubMed, Web of Science, CINAHL, PsycINFO, SinoMed, CNKI, WanFang Data and VIP databases were electronically searched to collect studies on self-management intervention on the prevention and management of lymphedema in breast cancer patients, from database inception to June 16. Two reviewers independently screened the literature, extracted data and assessed the risk of biasof the included studies. Meta-analysis was performed using RevMan 5.4 software. ResultsA total of 37 references were included, comprising 25 randomized controlled trials (RCTs), 12 controlled clinical trials (CCTs), and a total of 3 697 patients. There were 26 studies in the meta-analysis, and the results of the meta-analysis showed that, compared with the control group, patients in the intervention group exhibited better performance in lymphedema management-related behaviors SMD=2.65, 95%CI(1.53 to 3.78), P<0.01, symptoms related to lymphedema SMD=−2.01, 95%CI (−3.66 to −0.37), P<0.05, occurrence of lymphedema RR=0.37, 95%CI (0.32 to 0.45), P<0.01, upper limb function SMD=−1.88, 95%CI (−2.83 to −0.92), P<0.01, quality of life SMD=2.79, 95%CI (2.05 to 3.54), P<0.01, and the difference was statistically significant. The intervention mainly included information support, material support, emotional support and decision support. ConclusionThere are currently a variety of self-management interventions, but they mainly focus on information support. Self-management interventions can improve the self-management behavior of breast cancer patients with lymphedema and reduce the impact of lymphedema on patients.