ObjectiveTo introduce a meta-analysis of linear or nonlinear multilevel models using SAS MIXED and SAS NLMIXED.MethodsA systematic review performed to evaluate the risk of local recurrence in patients with cervical cancer treated with radical chemoradiotherapy and adjuvant surgery published by Shim et al. was selected as an illustration. An SAS software was used to implement meta-analysis based on linear or nonlinear multi-level models, and programming codes were provided.ResultsIn the absence of covariates, the OR combined effect values of PROC MIXED based on the bivariate random effects model and PROC NLMIXED of the nonlinear mixed effects model were 0.63 (95%CI 0.46 to 0.87, P=0.005 7) and 0.60 (95%CI 0.39 to 0.81, P=0.000 3), respectively. In the case of covariates, the bivariate random effects model and the nonlinear mixed effects model provided an effect value of OR=0.65 (95%CI 0.47 to 0.91, P=0.011) and 0.59 (95%CI 0.38 to 0.80, P=0.000 3). Covariate OR effect values were 2.70 (95%CI 0.16 to 45.23, P>0.05) and 1.86 (95%CI ?0.07 to 3.79, P=0.06).ConclusionsThe meta-analysis results of the SAS NLMIXED nonlinear mixed-effects model are similar to those of the SAS MIXED linear mixed-effects model. PROC NLMIXED has powerful programming capability and nonlinear mixed-effects model has flexible modeling capabilities for sparse data. Therefore, PROC NLMIXED will play an increasingly important role in meta-analysis.
ObjectiveTo systematically review the association between chronotype and depressive symptoms among adolescents. MethodsCNKI, VIP, WanFang Data, PubMed, ScienceDirect and Web of Science databases were electronically searched to collect studies on the association between adolescent chronotype and depressive symptoms from inception to January 17th, 2022. Two reviewers independently screened literature, extracted data, and assessed the risk of bias of the included studies. Meta-analysis was then performed using Stata 16.0 software. ResultsA total of 12 studies were included. The results of meta-analysis showed that there was an association between chronotype and depressive symptoms (Fisher’s Z=?0.19, 95%CI ?0.21 to ?0.17, P<0.001). ConclusionCurrent evidence shows that evening-type chronotype may be a risk factor for depressive symptoms among adolescents. Due to the limited quality and quantity of the included studies, more high-quality studies are needed to verify the above conclusion.
【摘要】 目的 探討CT對嬰幼兒腹部巨大囊性病變的診斷價值及其鑒別診斷。 方法 搜集2003年-2009年間經手術病理證實的2歲以內患兒腹部巨大囊性病變62例，分析其病變部位、大小、形態、分隔、密度和強化、囊壁及與周圍臟器關系等要素。 結果 62例中，先天性膽總管囊腫4例，重度腎積水36例，巨輸尿管2例，囊性腎母細胞瘤4例，大網膜囊腫4例，腸系膜囊腫3例，卵巢囊腫6例，囊性畸胎瘤3例。 各種囊性病變有其一定的發病部位和特征性的CT表現。 結論 CT是嬰幼兒腹部囊性病變定位、定性診斷的重要影像學方法。【Abstract】 Objective To explore the value of CT diagnosis and differential diagnosis of the giant cystic lesions in abdomen of the infants. Methods A total of 62 infants younger than 2 years old with the giant cystic lesions in abdomen confirmed by surgery and histopathology from 2003 to 2009 were collected. The location of the lesion, range, configuration, thickness of cystic wall and septa, density, contrast enhancement, and adjacent organs were observed and analyzed. Results In 62 infants, there were congenital cyst of common bile duct in 4, giant hydronephrosis in 36, primary megaureter in 2, cystic Wilms tumor in 4, greater omentum cyst in 4, mesenteric cyst in 3, ovarian cystic in 6, and cystic teratoma in 3. Each disease had its own lesions location and features of CT images. Conclusion CT is very effective on the localized and qualitative diagnosis of the giant cystic lesions in abdomen of infants.
ObjectivesTo systematically review the safety and efficacy of aspirin in primary prevention of cardiovascular diseases.MethodsPubMed, EMbase, Web of Science, The Cochrane Library, CBM, WanFang Data, CNKI and VIP databases were electronically searched to collect randomized controlled trials (RCTs) of aspirin for primary prevention of cardiovascular diseases from inception to November 2018. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies, and then, meta-analysis was performed by RevMan 5.3 software.ResultsA total of 13 RCTs involving 164 225 participants were included. The results of meta-analysis showed that: aspirin reduced the risk of myocardial infarction (RR=0.85, 95%CI 0.75 to 0.97, P=0.01), ischemic stroke (RR=0.86, 95%CI 0.79 to 0.95, P=0.002) and risk of major adverse cardiovascular events (RR=0.90, 95%CI 0.86 to 0.94, P<0.000 1). However, all-cause mortality (RR=0.97, 95%CI 0.93 to 1.02, P=0.22) and cardiovascular mortality (RR=0.93, 95%CI 0.85 to 1.02, P=0.11) were not reduced. Additionally, it increased risk of hemorrhagic stroke (RR=1.29, 95%CI 1.02 to 1.64, P=0.03), major bleeding (RR=1.43, 95%CI 1.31 to 1.56, P<0.000 01) and gastrointestinal bleeding (RR=1.59, 95%CI 1.33 to 1.90, P<0.000 01).ConclusionCurrent evidence shows that aspirin can reduce the incidence of major adverse cardiovascular events and myocardial infarction during primary prevention of cardiovascular disease, while increase the risk of bleeding, especially gastrointestinal bleeding. Therefore, its potential benefits may be offset. Due to limited quality and quantity of the included studies, more high-quality studies are required to verify the above conclusion.
ObjectiveTo systematically evaluate risk prediction models for ventricular arrhythmia (VA) following percutaneous coronary intervention (PCI) in patients with acute myocardial infarction (AMI), aiming to provide references for the development, optimization, and application of the models. MethodsDatabases including CNKI, Wanfang, VIP, Chinese Biomedical Literature Database, PubMed, Embase, and Cochrane Library were searched for studies on VA prediction models after PCI in AMI patients from inception to September 2025. Two researchers independently screened the literature, extracted data, and assessed the quality of included studies using the prediction model risk of bias assessment tool. Meta-analysis of common predictors was performed using Stata 18.0 software, and the area under the curve (AUC) of the models was statistically analyzed using MedCalc software. ResultsA total of 12 studies were included, establishing 12 models involving 3411 patients. The incidence of VA ranged from 11.0% to 50.8%, with an overall incidence of approximately 24.5%. The AUC values of the 12 models ranged from 0.717 to 0.983, indicating good predictive performance. However, the overall risk of bias in the included studies was high. Statistical analysis yielded a pooled AUC of 0.853 [95%CI (0.807, 0.899)]. Meta-analysis results showed that Killip class, left ventricular ejection fraction, thrombolysis in myocardial infarction flow grade, number of diseased coronary vessels, troponin levels, diabetes mellitus, J-wave on electrocardiogram, and serum potassium level were independent predictive factors for VA after PCI in AMI patients (P<0.05). ConclusionThe risk prediction models for VA after PCI in AMI patients demonstrate good overall discrimination. However, existing studies generally suffer from a high risk of bias, and the calibration and external validation of the models are severely insufficient, limiting their direct clinical applicability. Future multicenter, large-sample, prospective studies are needed to optimize study design and reporting processes, aiming to develop and validate more robust prediction models suitable for clinical practice, facilitating early identification and prevention of VA after PCI in AMI patients.